Wilmott: Recent Episodes
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Volume 2024, Issue 134. Pages 1-72
Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here.
In this issue:* D. Tudball, “Contents,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
Contents
@article{WILM:WILM12080,title = {{Contents}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12080},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12080},abstract = {Contents}}
* D. Tudball, “Jump for Joy,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
Principal Component Analysis is used to construct “microstructure modes” that describe the most common flow/return patterns and allow one to separate them into bid-ask symmetric and bid-ask anti-symmetric.
@article{WILM:WILM12081,title = {{Jump for Joy}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12081},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12081},abstract = {Principal Component Analysis is used to construct “microstructure modes” that describe the most common flow/return patterns and allow one to separate them into bid-ask symmetric and bid-ask anti-symmetric.}}
* D. Tudball, “News,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
News
@article{WILM:WILM12082,title = {{News}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12082},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12082},abstract = {News}}
* A. Brown, “Beat the Major: The Long Walk,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
Optimizing your chances of defeating a master of the macabre
@article{WILM:WILM12083,title = {{Beat the Major: The Long Walk}},author = {Brown, Aaron},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12083},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12083},abstract = {Optimizing your chances of defeating a master of the macabre}}
* R. Poulsen, “For Bettor or Worse,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
There’s nothing fishy about digging on Poisson, or is there?
@article{WILM:WILM12084,title = {{For Bettor or Worse}},author = {Poulsen, Rolf},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12084},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12084},abstract = {There’s nothing fishy about digging on Poisson, or is there?}}
* U. Wystup, “Click-and-Trade Structured Products for Wealth Management,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
This issue we speak to Milind Kulkarni, founder of FinIQ, who pioneered technology for making structured products accessible beyond large institutional users
@article{WILM:WILM12085,title = {{Click-and-Trade Structured Products for Wealth Management}},author = {Wystup, Uwe},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12085},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12085},abstract = {This issue we speak to Milind Kulkarni, founder of FinIQ, who pioneered technology for making structured products accessible beyond large institutional users}}
* L. Ballabio, “The QuantLib Ecosystem,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
Listing a number of satellite projects and ports in other languages which spawned from QuantLib
@article{WILM:WILM12086,title = {{The QuantLib Ecosystem}},author = {Ballabio, Luigi},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12086},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12086},abstract = {Listing a number of satellite projects and ports in other languages which spawned from QuantLib}}
* L. Ballotta, “The Calibration Conundrum,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
Even after solving calibration issues like non-convexity, a suitable minimization algorithm is needed, raising questions about the algorithms we hope to lead us to the promised land: the optimal parameter set of our chosen model.
@article{WILM:WILM12087,title = {{The Calibration Conundrum}},author = {Ballotta, Laura},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12087},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12087},abstract = {Even after solving calibration issues like non-convexity, a suitable minimization algorithm is needed, raising questions about the algorithms we hope to lead us to the promised land: the optimal parameter set of our chosen model.}}
* P. Mani, “Simpson’s Paradox: Conceptual Foundational Implications in Real-Life Decision-Making in Quantitative Investment and Trading,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
Pankaj Mani writes that a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined raises foundational issues in concluding the significance of statistical relationships among different variables reliably in real-world decision-making for trading, investing, risk management.
@article{WILM:WILM12088,title = {{Simpson’s Paradox: Conceptual Foundational Implications in Real-Life Decision-Making in Quantitative Investment and Trading}},author = {Mani, Pankaj},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12088},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12088},abstract = {Pankaj Mani writes that a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined raises foundational issues in concluding the significance of statistical relationships among different variables reliably in real-world decision-making for trading, investing, risk management.}}
* D. Bloch, E. Liao, and A. Bloch, “Detecting And Predicting Price Jumps With Consecutive Signature Distance,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
In order to estimate the hidden states of dynamical systems, Jump Models cluster financial observations along time series and impose a cost on jumping from one cluster to another. While these models can detect abrupt changes in the underlying time series, they suffer from two major drawbacks when it comes to detecting price jumps: (1) they cannot detect two (or more) consecutive jumps; (2) they cannot dissociate high volatility from jumps. To remedy these drawbacks, Bloch and Liao consider two seemingly unrelated problems: (1) Detecting and predicting price jumps by identifying whether a new observation results in a price jump relative to previous observations; (2) Anomaly detection of segments of a time series, that is, fixed size segments of a time series are treated as a normal corpus, and search for outliers. It is observed that while these problems are clearly different, the former can be reformulated in terms of the latter and they can therefore associate jump indicators to data-driven metrics for anomaly detection. Bloch and Liao propose a three-step process: (1) jump detection: the variance norm is combined with path signatures to come up with a data-driven jump indicator; (2) training: Bloch and Liao use this Variance Norm Jump Indicator as an input feature for Jump Models; (3) prediction: the authors use new incoming data to predict its hidden state. This approach aims at enhancing the model’s accuracy and predictive capabilities by leveraging the strengths of variance norm on detecting data points after the jump as outliers from previous distribution. Bloch and Liao conducted an extensive analysis on simulated data, examining the structure, benefits and limitations of the approach, and found that they could retrieve the true hidden states with high accuracy without using future information.
@article{WILM:WILM12089,title = {{Detecting And Predicting Price Jumps With Consecutive Signature Distance}},author = {Bloch, D and Liao, E and Bloch, A},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12089},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12089},abstract = {In order to estimate the hidden states of dynamical systems, Jump Models cluster financial observations along time series and impose a cost on jumping from one cluster to another. While these models can detect abrupt changes in the underlying time series, they suffer from two major drawbacks when it comes to detecting price jumps: (1) they cannot detect two (or more) consecutive jumps; (2) they cannot dissociate high volatility from jumps. To remedy these drawbacks, Bloch and Liao consider two seemingly unrelated problems: (1) Detecting and predicting price jumps by identifying whether a new observation results in a price jump relative to previous observations; (2) Anomaly detection of segments of a time series, that is, fixed size segments of a time series are treated as a normal corpus, and search for outliers. It is observed that while these problems are clearly different, the former can be reformulated in terms of the latter and they can therefore associate jump indicators to data-driven metrics for anomaly detection. Bloch and Liao propose a three-step process: (1) jump detection: the variance norm is combined with path signatures to come up with a data-driven jump indicator; (2) training: Bloch and Liao use this Variance Norm Jump Indicator as an input feature for Jump Models; (3) prediction: the authors use new incoming data to predict its hidden state. This approach aims at enhancing the model’s accuracy and predictive capabilities by leveraging the strengths of variance norm on detecting data points after the jump as outliers from previous distribution. Bloch and Liao conducted an extensive analysis on simulated data, examining the structure, benefits and limitations of the approach, and found that they could retrieve the true hidden states with high accuracy without using future information.}}
* J. Kienitz, “Exciting Times are Ahead – Gaussian Views and Yield Curve Extrapolation,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
In the insurance industry, products having a much longer time to maturity and yield values for up to 100 years need to be modeled. Jörg Kienitz and Leenesh Moodliyar propose to apply Gaussian Process Regression (GPR) for the extrapolation. The method is compared to two market standard methods — the Nelson-Siegel-Svensson (NSS) and the Smith-Wilson (SW) methods
@article{WILM:WILM12090,title = {{Exciting Times are Ahead - Gaussian Views and Yield Curve Extrapolation}},author = {Kienitz, Jorg},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12090},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12090},abstract = {In the insurance industry, products having a much longer time to maturity and yield values for up to 100 years need to be modeled. Jörg Kienitz and Leenesh Moodliyar propose to apply Gaussian Process Regression (GPR) for the extrapolation. The method is compared to two market standard methods — the Nelson-Siegel-Svensson (NSS) and the Smith-Wilson (SW) methods}}
* D. Orrell, “Mental Interference,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
This excerpt from Chapter 4 looks at how the quantum approach can be used to model the cognitive interference that often occurs when making decisions.
@article{WILM:WILM12091,title = {{Mental Interference}},author = {Orrell, David},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12091},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12091},abstract = {This excerpt from Chapter 4 looks at how the quantum approach can be used to model the cognitive interference that often occurs when making decisions.}}
* S. Renzitti, “Jump-at-Default Exposure Modeling with Physical Collateral,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
Jump-at-default exposure modeling seeks to capture the impact of hard (or systemic) wrong-way risk on counterparty credit exposure. In this work, the authors extend the jump-at-default framework to deal with embedded collateral optionality. In order to ensure a consistent treatment of the value jumps that may affect portfolio and/or collateral basket during close-out, Puetter and Renzitti propose a simple regression-based Monte Carlo approach to project these jumps. They illustrate its impact on potential future exposure and selected valuation adjustments through basic examples.
@article{WILM:WILM12092,title = {{Jump-at-Default Exposure Modeling with Physical Collateral}},author = {Renzitti, Stefano},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12092},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12092},abstract = {Jump-at-default exposure modeling seeks to capture the impact of hard (or systemic) wrong-way risk on counterparty credit exposure. In this work, the authors extend the jump-at-default framework to deal with embedded collateral optionality. In order to ensure a consistent treatment of the value jumps that may affect portfolio and/or collateral basket during close-out, Puetter and Renzitti propose a simple regression-based Monte Carlo approach to project these jumps. They illustrate its impact on potential future exposure and selected valuation adjustments through basic examples.}}
* M. Smerlak, “Great Year Bad Sharpe,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
Returns distributions are heavy tailed across asset classes. In this note, Smerlak examines the implications of this well-known stylized fact for the joint statistics of performance (absolute return) and Sharpe ratio (risk-adjusted return). Using both synthetic and real data, He shows that, all other things being equal, the investments with the best in-sample performance are never associated with the best in-sample Sharpe ratios (and vice versa). This counter-intuitive effect is unrelated to the risk-return tradeoff familiar from portfolio theory: it is, rather, a consequence of asymptotic correlations between the sample mean and sample standard deviation of heavy-tailed variables. In addition to its large sample noise, this non-monotonic association of the Sharpe ratio with performance puts into question its status as the gold standard metric of investment quality.
@article{WILM:WILM12093,title = {{Great Year Bad Sharpe}},author = {Smerlak, Matteo},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12093},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12093},abstract = {Returns distributions are heavy tailed across asset classes. In this note, Smerlak examines the implications of this well-known stylized fact for the joint statistics of performance (absolute return) and Sharpe ratio (risk-adjusted return). Using both synthetic and real data, He shows that, all other things being equal, the investments with the best in-sample performance are never associated with the best in-sample Sharpe ratios (and vice versa). This counter-intuitive effect is unrelated to the risk-return tradeoff familiar from portfolio theory: it is, rather, a consequence of asymptotic correlations between the sample mean and sample standard deviation of heavy-tailed variables. In addition to its large sample noise, this non-monotonic association of the Sharpe ratio with performance puts into question its status as the gold standard metric of investment quality.}}
* M. Radley, “Forced Air Flair/Wild Thing,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
Lamborghini throws out its rule book and finally introduces turbocharging to its latest supercar.
@article{WILM:WILM12094,title = {{Forced Air Flair/Wild Thing}},author = {Radley, Milford},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12094},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12094},abstract = {Lamborghini throws out its rule book and finally introduces turbocharging to its latest supercar.}}
* J. Darasz, “The Skewed World of Jan Darasz,” Wilmott, vol. 2024, iss. 134, 2024.
[Bibtex] [Abstract]
Cartoon
@article{WILM:WILM12095,title = {{The Skewed World of Jan Darasz}},author = {Darasz, Jan},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 134,doi = {10.54946/wilm.12095},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12095},abstract = {Cartoon}}
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Volume 2024, Issue 133. Pages 1-72
Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here.
In this issue:* D. Tudball, “Contents,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
Contents
@article{WILM:WILM12062,title = {{Contents}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12062},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12062},abstract = {Contents}}
* D. Tudball, “Dream a Little Dream,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
Principal Component Analysis is used to construct “microstructure modes” that describe the most common flow/return patterns and allow one to separate them into bid-ask symmetric and bid-ask anti-symmetric.
@article{WILM:WILM12063,title = {{Dream a Little Dream}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12063},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12063},abstract = {Principal Component Analysis is used to construct "microstructure modes" that describe the most common flow/return patterns and allow one to separate them into bid-ask symmetric and bid-ask anti-symmetric.}}
* D. Tudball, “News,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
News
@article{WILM:WILM12064,title = {{News}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12064},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12064},abstract = {News}}
* A. Brown, ” Soccer Match Fixing,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
Looking for internal evidence of unsportsmanlike behavior in data covering the results of over 30,000 matches around the world.
@article{WILM:WILM12065,title = {{ Soccer Match Fixing}},author = {Brown, Aaron},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12065},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12065},abstract = {Looking for internal evidence of unsportsmanlike behavior in data covering the results of over 30,000 matches around the world.}}
* R. Poulsen, “Confused: My Danish Collection,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
Forvirret: Min danske Samling, in other words.
@article{WILM:WILM12066,title = {{Confused: My Danish Collection}},author = {Poulsen, Rolf},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12066},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12066},abstract = {Forvirret: Min danske Samling, in other words.}}
* U. Wystup, “Worth a TRY?,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
How to make $20 million in USD-TRY with zero cost and zero risk
@article{WILM:WILM12067,title = {{Worth a TRY?}},author = {Wystup, Uwe},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12067},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12067},abstract = {How to make $20 million in USD-TRY with zero cost and zero risk}}
* L. Ballabio, “Adding a New Cash Flow to QuantLib, Part II,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
The quest continues to implement a coupon whose rate must be interpolated between the fixings of two quoted indexes.
@article{WILM:WILM12068,title = {{Adding a New Cash Flow to QuantLib, Part II}},author = {Ballabio, Luigi},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12068},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12068},abstract = {The quest continues to implement a coupon whose rate must be interpolated between the fixings of two quoted indexes.}}
* W. Schoutens, “Time to Toss ESG in the Trash: The Brutal Reality of a Failed Experiment,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
Wim Schoutens says it’s time to face the facts and take out the trash.
@article{WILM:WILM12069,title = {{Time to Toss ESG in the Trash: The Brutal Reality of a Failed Experiment}},author = {Schoutens, Wim},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12069},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12069},abstract = {Wim Schoutens says it’s time to face the facts and take out the trash.}}
* P. Boyle, “The Golden Age of Private Credit? ,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
Phelim P Boyle takes an overview of the private credit market and details the reasons for its popularity.
@article{WILM:WILM12070,title = {{The Golden Age of Private Credit? }},author = {Boyle, Phelim},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12070},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12070},abstract = {Phelim P Boyle takes an overview of the private credit market and details the reasons for its popularity.}}
* D. Orrell, “Rejection Therapy,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
On the difficulty of getting new ideas accepted in science when they fly in the face of mainstream results.
@article{WILM:WILM12071,title = {{Rejection Therapy}},author = {Orrell, David},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12071},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12071},abstract = {On the difficulty of getting new ideas accepted in science when they fly in the face of mainstream results.}}
* K. Smith, “Price Myopia Does Not Deliver Value,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
‘Any Sale is a Good Sale’ burns repeat business but margin-mania is still pervasive and does not deliver value to corporate clients.
@article{WILM:WILM12072,title = {{Price Myopia Does Not Deliver Value}},author = {Smith, Kurt},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12072},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12072},abstract = {‘Any Sale is a Good Sale’ burns repeat business but margin-mania is still pervasive and does not deliver value to corporate clients.}}
* J. Riposo, “The Potential Impact of Blockchain on Real Estate: Insights from Conventional Mortgage Market Data ,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
For years, centralized systems within the real estate market have perpetuated inefficiencies. Blockchain emerges as the disruptor, offering a consolidated source of truth for all transaction data.
@Article {WILM:WILM12073, author= {Riposo, Julien}, title = {{The Potential Impact of Blockchain on Real Estate: Insights from Conventional Mortgage Market Data}}, journal = {Wilmott}, volume = {2024}, number = {133}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.54946/wilm.12073}, doi = {10.54946/wilm.12073}, year = {2024}, abstract ={For years, centralized systems within the real estate market have perpetuated inefficiencies. Blockchain emerges as the disruptor, offering a consolidated source of truth for all transaction data.},}
* S. Elomari-Kessab, G. Maitrier, J. Bonart, and J. Bouchaud, ““Microstructure Modes” – Disentangling the Joint Dynamics of Prices & Order Flow,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
Understanding the micro-dynamics of asset prices in modern electronic order books is crucial for investors and regulators. In this paper, we use an order-by-order Eurostoxx database spanning over 3 years to analyze the joint dynamics of prices and order flow. In order to alleviate various problems caused by high-frequency noise, we propose a double coarse-graining procedure that allows us to extract meaningful information at the minute time scale. We use Principal Component Analysis to construct “microstructure modes” that describe the most common flow/return patterns and allow one to separate them into bid-ask symmetric and bid-ask anti-symmetric. We define and calibrate a Vector Auto-Regressive (VAR) model that encodes the dynamical evolution of these modes. The parameters of the VAR model are found to be extremely stable in time, and lead to relatively high R^2 prediction scores, especially for symmetric liquidity modes. The VAR model becomes marginally unstable as more lags are included, reflecting the long-memory nature of flows and giving some further credence to the possibility of “endogenous liquidity crises”. Although very satisfactory on several counts, we show that our VAR framework does not account for the well-known square-root law of price impact.
@article{WILM:WILM12074,title = {{“Microstructure Modes” – Disentangling the Joint Dynamics of Prices & Order Flow}},author = {Elomari-Kessab, S and Maitrier, G and Bonart, J and Bouchaud, JP},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12074},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12074},abstract = {Understanding the micro-dynamics of asset prices in modern electronic order books is crucial for investors and regulators. In this paper, we use an order-by-order Eurostoxx database spanning over 3 years to analyze the joint dynamics of prices and order flow. In order to alleviate various problems caused by high-frequency noise, we propose a double coarse-graining procedure that allows us to extract meaningful information at the minute time scale. We use Principal Component Analysis to construct "microstructure modes" that describe the most common flow/return patterns and allow one to separate them into bid-ask symmetric and bid-ask anti-symmetric. We define and calibrate a Vector Auto-Regressive (VAR) model that encodes the dynamical evolution of these modes. The parameters of the VAR model are found to be extremely stable in time, and lead to relatively high R^2 prediction scores, especially for symmetric liquidity modes. The VAR model becomes marginally unstable as more lags are included, reflecting the long-memory nature of flows and giving some further credence to the possibility of “endogenous liquidity crises”. Although very satisfactory on several counts, we show that our VAR framework does not account for the well-known square-root law of price impact.}}
* D. Orrell, “Quantum Economics and Finance: Some Basics,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
This excerpt from Chapter 2 of David Orrell’s book, Quantum Economics and Finance, introduces some of the key mathematical tools that are used throughout the book. We’ll start by describing some terms and symbols. Most of them are similar to the terms used in matrix algebra, with the twist that the matrices now involve complex numbers.
@article{WILM:WILM12075,title = {{Quantum Economics and Finance: Some Basics}},author = {Orrell, David},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12075},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12075},abstract = {This excerpt from Chapter 2 of David Orrell’s book, Quantum Economics and Finance, introduces some of the key mathematical tools that are used throughout the book. We’ll start by describing some terms and symbols. Most of them are similar to the terms used in matrix algebra, with the twist that the matrices now involve complex numbers.}}
* P. LeFloch, J. Mercier, and S. Miryusupov, “Extrapolation and Generative Algorithms for Three Applications in Finance,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
For three applications of central interest in finance, we demonstrate the relevance of numerical algorithms based on reproducing kernel Hilbert space (RKHS) techniques. Three use cases are investigated. First, we show that extrapolating from a few pricer examples leads to sufficiently accurate and computationally efficient results so that our algorithm can serve as a pricing framework. The second use case concerns reverse stress testing, which is formulated as an inversion function problem and is treated here via an optimal transport technique in combination with the notions of kernel-based encoders, decoders, and generators. Third, we show that standard techniques for time series analysis can be enhanced by using the proposed generative algorithms. Namely, we use our algorithm in order to extend the validity of any given quantitative model, so that our approach allows for conditional analysis as well as for escaping the ‘Gaussian world’. This latter property is illustrated with a strategy of portfolio investment.
@article{WILM:WILM12076,title = {{Extrapolation and Generative Algorithms for Three Applications in Finance}},author = {LeFloch, PG and Mercier, JM and Miryusupov, S},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12076},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12076},abstract = {For three applications of central interest in finance, we demonstrate the relevance of numerical algorithms based on reproducing kernel Hilbert space (RKHS) techniques. Three use cases are investigated. First, we show that extrapolating from a few pricer examples leads to sufficiently accurate and computationally efficient results so that our algorithm can serve as a pricing framework. The second use case concerns reverse stress testing, which is formulated as an inversion function problem and is treated here via an optimal transport technique in combination with the notions of kernel-based encoders, decoders, and generators. Third, we show that standard techniques for time series analysis can be enhanced by using the proposed generative algorithms. Namely, we use our algorithm in order to extend the validity of any given quantitative model, so that our approach allows for conditional analysis as well as for escaping the ‘Gaussian world’. This latter property is illustrated with a strategy of portfolio investment.}}
* S. Stoykov, “Numerical Solution of Fokker-Planck Equation by Variational Approach – an Application to Pricing Barrier Options,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
The Fokker-Planck equation is a partial differential equation (PDE) that defines the time evolution of the probability density function of a stochastic process. By applying appropriate boundary conditions to the PDE and obtaining the corresponding probability density function, one can price a variety of derivatives, assuming different stochastic processes. The current work presents a numerical procedure for solving the Fokker-Planck equation. It is based on a variational approach for discretizing the PDE and converting it into a system of ordinary differential equations. Space discretization is achieved by using non-uniform B-Splines, which are shown to be appropriate for representing initial conditions like the Dirac delta function. The proposed numerical methods are presented for pricing barrier options under the Heston stochastic volatility process.
@article{WILM:WILM12077,title = {{Numerical Solution of Fokker-Planck Equation by Variational Approach – an Application to Pricing Barrier Options}},author = {Stoykov, S},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12077},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12077},abstract = {The Fokker-Planck equation is a partial differential equation (PDE) that defines the time evolution of the probability density function of a stochastic process. By applying appropriate boundary conditions to the PDE and obtaining the corresponding probability density function, one can price a variety of derivatives, assuming different stochastic processes. The current work presents a numerical procedure for solving the Fokker-Planck equation. It is based on a variational approach for discretizing the PDE and converting it into a system of ordinary differential equations. Space discretization is achieved by using non-uniform B-Splines, which are shown to be appropriate for representing initial conditions like the Dirac delta function. The proposed numerical methods are presented for pricing barrier options under the Heston stochastic volatility process.}}
* M. Radley, “Analog Perfection/Sweet Spot,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
GMA T.50/Porsche Carrera 911 GTS
@article{WILM:WILM12078,title = {{Analog Perfection/Sweet Spot}},author = {Radley, Milford},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12078},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12078},abstract = {GMA T.50/Porsche Carrera 911 GTS}}
* J. Darasz, “The Skewed World of Jan Darasz,” Wilmott, vol. 2024, iss. 133, 2024.
[Bibtex] [Abstract]
Cartoon
@article{WILM:WILM12079,title = {{The Skewed World of Jan Darasz}},author = {Darasz, Jan},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 133,doi = {10.54946/wilm.12079},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12079},abstract = {Cartoon}}
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Will GenAI Make a Dent in the Quant Ecosystem? If 2023 was the year of the GPT then 2024 has been the year of reality checks, reflection and knowing that no one can really predict anything ten years out.
While there has been a huge influx of investment from venture capital in AI based ventures, to the point that anything with “AI” in the strapline of the pitch would warrant interest, the reality is that the hype is starting to wear off.
So Much Noise and Very Little Signal Goldman Sachs June 2024 Global Macro Research report, “Gen AI: Too much spend, too little benefit?”, laid out the harsh reality of how many artificial intelligence efforts are not worth the time or the money for their expected returns.
In the report Jim Covello states, “AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn’t designed to do.”
This has been the main problem with generative AI in general once you get past the basics of text generation then there is little else of merit in the technology. It is great for marketing copy, code generation (as I wrote about in March 2024) but for anything else it is going to take tacit domain knowledge and an awful lot of money to do anything complex. It is more cost effective to hire people.
We Need to Talk About NVIDIA With the realities of the AI hype starting to cool, so did NVIDIA’s share price. With a nine percent drop from mid-June to mid-July (at the time of writing) some of the realities of AI are starting to dent GPU reliance. With over 80% of NVIDIA’s revenue coming from AI activities any form of cooling of GenAI hype will influence the share price.
And it is not just NVIDIA suffering, the other main players in the AI arena Microsoft, Alphabet (Google) and other chip makers are starting to see corrections in the stock prices as the harsh reality is that AI might not live up to expectations.
Sam Altman, the poster child of GenAI, is steering OpenAI to a projected $5bn loss in 2024.
Put the Singularity on Ice for NowThere is some debate on whether a new AI winter is approaching, the stock market has shown their opinions in the pricing of the major players. The correction was long due as the last eighteen months of hype have not delivered much apart from questionable marketing copy.
For now, jobs are safer in the hands of the people that do them. The real question is how the conversation will look in the next two, five and ten years.
References https://www.goldmansachs.com/intelligence/pages/gs-research/gen-ai-too-much-spend-too-little-benefit/report.pdf
https://wilmott.com/jensens-interceptor-are-coders-redundant/
Jason Bell is a software developer of over thirty five years. He is also the author of Machine Learning: Hands on for Developers and Technical Professionals – published by Wiley in 2014 and a second edition in 2022.
Dim drums throbbing, in the hills half heard,
Where only on a nameless throne a crownless prince has stirred,
Where, risen from a doubtful seat and half attainted stall,
The last knight of Europe takes weapons from the wall,
The last and lingering troubadour to whom the bird has sung,
That once went singing southward when all the world was young,
In that enormous silence, tiny and unafraid,
Comes up along a winding road the noise of the Crusade.
from Lepanto by G. K. Chesterton**
Somewhere during my third year at UCT, while majoring in Physics and Applied Maths, I begin to detect the sound of distant drums.
There are universities in England and America where serious people go to do advanced physics. (Yes, we say “to do” physics, not “to study” physics. Physics is a vocation.) People I know have pulled up stakes and gone abroad to get a PhD, people serious and ambitious
and willing to leave home even though they don’t have to. They want to do something wonderful.
Some of them do. I first learn about overseas PhD-ers from my Oranjezicht neighbor Jeffrey Bub, the older brother of my classmate Julian. Jeffrey has left Cape Town to do a PhD in London with David Bohm on hidden variable theories of quantum mechanics and will eventually become a well-known philosopher of quantum mechanics.
The physics department likes to tell you it’s not necessary to leave UCT to do good physics. But, when we learn quantum mechanics, they teach it as though it’s mysterious and hard to grasp, something bewildering …
| DOWNLOAD FULL ARTICLE: WILMOTT Magazine - July 2024 -Derman |
Emanuel Derman makes a very welcome appearance on the latest episode of the CQF Institute podcast, QuantSpeak. Hosted by Wilmott Editor, Dan Tudball, the episode delves deep into Derman’s fascinating journey from a Polish-Jewish community in Cape Town to the financial world of Wall Street.
About the episode
QuantSpeak listeners are in for a treat in this episode as Derman discusses his upcoming memoir, Brief Hours and Weeks: My Life as a Capetonian, which will be released later this year. Influenced by the writing style of South African and Australian novelist, J. M. Coetzee, the memoir explores the formative years of Derman’s life growing up in an immigrant Jewish community cloistered in Cape Town between the late 40s and early 60s. Derman and Tudball discuss the impact and lessons that Derman has taken from those early years and their role in his later life and career.
During the discussion, Derman also takes us back to his arrival in New York in 1966, a pivotal moment that set the stage for his illustrious career. He received his Ph.D. in theoretical physics in 1973 and initially struggled to find jobs and gain tenure in academic roles, despite his passion for the field. His transition to finance began in 1985 when he joined Goldman Sachs, marking the start of a groundbreaking career in financial modeling.
One of the highlights of the episode is Derman’s reflections on his influential work in financial modeling. Listeners will gain valuable insights into the creation and impact of the Black-Derman-Toy model, a groundbreaking interest rate model he originally thought would become a general theory for all fixed income. Derman describes how, interestingly, it was the legendary Fisher Black who was more certain that each sector would have its own model, and that there would be no overarching theory. Derman also discusses the Derman-Kani model, a local volatility model that has become an essential tool in quantitative finance. His insider’s perspective on these models’ development and significance is truly enlightening.
Derman also shares anecdotes from his collaboration with Fisher Black, co-creator of the Black-Scholes option pricing model. Their partnership was instrumental in advancing the field of quantitative finance, and Derman’s reflections on their work together offer a rare glimpse into the minds of two of finance’s most innovative thinkers.
Where can you listen?
Don’t miss this opportunity to hear from one of the foremost thinkers in financial engineering. Listen to the episode now on QuantSpeak’s official page or your favorite podcast platform. Be sure to subscribe to stay updated on future episodes featuring thought leaders in quantitative finance.
Volume 2024, Issue 132. Pages 1-84
Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here.
In this issue:* D. Tudball, “Contents,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
Contents
@article{WILM:WILM12046,title = {{Contents}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12046},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12046},abstract = {Contents}}
* D. Tudball, “You Think You’ve Seen the Sun, but You Ain’t Seen it Shine ,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
Doyne’s research has led to compelling models for understanding financial markets and economic systems, highlighting how complex adaptive systems can better predict and manage economic crises and market behaviors.
@article{WILM:WILM12047,title = {{You Think You've Seen the Sun, but You Ain't Seen it Shine }},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12047},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12047},abstract = {Doyne's research has led to compelling models for understanding financial markets and economic systems, highlighting how complex adaptive systems can better predict and manage economic crises and market behaviors.}}
* E. O. Thorp, “A Different Way to Give: A Million Dollars for Mathematics – Twenty Years Later,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
You can make a modest charitable donation now, which can become a gigantic future legacy. That’s the central idea of this article.
@article{WILM:WILM12048,title = {{A Different Way to Give: A Million Dollars for Mathematics – Twenty Years Later}},author = {Thorp, Edward O},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12048},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12048},abstract = {You can make a modest charitable donation now, which can become a gigantic future legacy. That's the central idea of this article.}}
* A. Brown, “Did baseball have a Steroid Era?,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
A decade ago, statistics from the 1990s and early 2000s appeared to confirm there had been a ‘Steroid Era’ in baseball, but subsequent to that, evidence has mounted significantly in the opposite direction.
@article{WILM:WILM12049,title = {{Did baseball have a Steroid Era?}},author = {Brown, Aaron},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12049},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12049},abstract = {A decade ago, statistics from the 1990s and early 2000s appeared to confirm there had been a 'Steroid Era' in baseball, but subsequent to that, evidence has mounted significantly in the opposite direction.}}
* R. Poulsen, “Rose’s suede shoes are blue by any other name, Violet read ,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
Common communications can cause consternation.
@article{WILM:WILM12050,title = {{Rose’s suede shoes are blue by any other name, Violet read }},author = {Poulsen, Rolf},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12050},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12050},abstract = {Common communications can cause consternation.}}
* U. Wystup, “Why are AUD-USD Risk Reversals always Negative? ,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
Out-of-the money USD put JPY call options are often priced at a higher volatility than USD call JPY put options. In this issue, we look into why this is the case.
@article{WILM:WILM12051,title = {{Why are AUD-USD Risk Reversals always Negative? }},author = {Wystup, Uwe},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12051},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12051},abstract = {Out-of-the money USD put JPY call options are often priced at a higher volatility than USD call JPY put options. In this issue, we look into why this is the case.}}
* E. Derman, “Distant Drums,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
In this extract from Emanuel Derman’s memoir, Brief Hours and Weeks: My Life as a Capetonian, the author recalls plotting resonances, programming a computer to write poems, the serendipity of acne, and mystic teachers.
@article{WILM:WILM12052,title = {{Distant Drums}},author = {Derman, Emanuel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12052},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12052},abstract = {In this extract from Emanuel Derman's memoir, Brief Hours and Weeks: My Life as a Capetonian, the author recalls plotting resonances, programming a computer to write poems, the serendipity of acne, and mystic teachers.}}
* S. Das, “The Rich Are Different!,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
No one enters financial markets to save the world. The primary motivation is to earn loads and get rich. Guido Alfani’s As Gods Among Men shows that this is unlikely to be possible. Most wealth is inherited. An algorithm to ensure that you are born to rich parents is a better answer.
@article{WILM:WILM12053,title = {{The Rich Are Different!}},author = {Das, Satyajit},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12053},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12053},abstract = {No one enters financial markets to save the world. The primary motivation is to earn loads and get rich. Guido Alfani's As Gods Among Men shows that this is unlikely to be possible. Most wealth is inherited. An algorithm to ensure that you are born to rich parents is a better answer.}}
* A. Spinner, “What does a singularity in the financial market look like ?,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
Albin Spinner brings the issues of financial abstraction to the masses in his upcoming book, The Financial Metaverse: Tokens, Derivatives and other Synthetic Assets. Here, the author suggests that the Financial Singularity has already occurred in a non Sci-Fi way.
@article{WILM:WILM12054,title = {{What does a singularity in the financial market look like ?}},author = {Spinner, Albin},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12054},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12054},abstract = {Albin Spinner brings the issues of financial abstraction to the masses in his upcoming book, The Financial Metaverse: Tokens, Derivatives and other Synthetic Assets. Here, the author suggests that the Financial Singularity has already occurred in a non Sci-Fi way.}}
* L. Ballabio, “Adding a new cash flow to QuantLib, part I,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
The quest begins: how to implement a short stub at the beginning of a floating-rate bond (or an interest-rate swap) whose rate must be interpolated between the fixings of two quoted indexes
@article{WILM:WILM12055,title = {{Adding a new cash flow to QuantLib, part I}},author = {Ballabio, Luigi},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12055},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12055},abstract = {The quest begins: how to implement a short stub at the beginning of a floating-rate bond (or an interest-rate swap) whose rate must be interpolated between the fixings of two quoted indexes}}
* J. Farmer Doyne, “A Better Economics for a Better World,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
In Paris on 13th May 2024, J. Doyne Farmer presented the foundational ideas and research underpinning his new book, Making Sense of Chaos: A Better Economics for a Better World. Here, we reproduce Farmer’s talk and his post-talk discussion with Jean-Philippe Bouchaud. We are also fortunate to be able to reproduce a chapter from Making Sense of Chaos, looking at ‘How Credit Causes Financial Turbulence’.
@article{WILM:WILM12056,title = {{A Better Economics for a Better World}},author = {Farmer, Doyne, J},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12056},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12056},abstract = {In Paris on 13th May 2024, J. Doyne Farmer presented the foundational ideas and research underpinning his new book, Making Sense of Chaos: A Better Economics for a Better World. Here, we reproduce Farmer's talk and his post-talk discussion with Jean-Philippe Bouchaud. We are also fortunate to be able to reproduce a chapter from Making Sense of Chaos, looking at 'How Credit Causes Financial Turbulence'.}}
* D. Bloch, “Stocks and Options Portfolio Optimisation With Reinforcement Learning,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
We present a model-free reinforcement learning (RL) framework for portfolio optimization across multiple assets and option prices. We directly model the relationship between the portfolio weights and the predictors with a network and maximize performance metrics for portfolio construction by using RL. We construct a portfolio, such that for any quantity of option that we buy or sell, we have a quasi-replicating portfolio made of a quantity of stock and a quantity of cash. We propose Cross-Asset-Option Transformers (CAOTs) to recover the interrelationships among options and their corresponding assets, which we use to construct a long-short or a bottom-up portfolio. We then maximize performance metrics of our portfolio with RL.
@article{WILM:WILM12057,title = {{Stocks and Options Portfolio Optimisation With Reinforcement Learning}},author = {Bloch, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12057},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12057},abstract = {We present a model-free reinforcement learning (RL) framework for portfolio optimization across multiple assets and option prices. We directly model the relationship between the portfolio weights and the predictors with a network and maximize performance metrics for portfolio construction by using RL. We construct a portfolio, such that for any quantity of option that we buy or sell, we have a quasi-replicating portfolio made of a quantity of stock and a quantity of cash. We propose Cross-Asset-Option Transformers (CAOTs) to recover the interrelationships among options and their corresponding assets, which we use to construct a long-short or a bottom-up portfolio. We then maximize performance metrics of our portfolio with RL.}}
* I. Ruiz and M. Zeron, “Tensoring volatility calibration,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
A series of papers have explored the use of Deep Neural Nets to substantially speed up the calibration of pricing models. This paper uses Chebyshev Tensors for the same purpose. In particular, it shows how the computational bottleneck in the calibration of the rough Bergomi volatility model can be alleviated using Chebyhsev Tensors. The calibration speed and accuracy obtained in this paper is comparable to when Deep Neural Nets are used. Building efforts, however, are up to 100 times lower, allowing for much faster pricing model proxy update – a feature of particular importance at times of market distress. This constitutes a further enhancement over the already sizable improvement provided by Deep Neural Nets.
@article{WILM:WILM12058,title = {{Tensoring volatility calibration}},author = {Ruiz, Ignacio and Zeron, Mariano},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12058},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12058},abstract = {A series of papers have explored the use of Deep Neural Nets to substantially speed up the calibration of pricing models. This paper uses Chebyshev Tensors for the same purpose. In particular, it shows how the computational bottleneck in the calibration of the rough Bergomi volatility model can be alleviated using Chebyhsev Tensors. The calibration speed and accuracy obtained in this paper is comparable to when Deep Neural Nets are used. Building efforts, however, are up to 100 times lower, allowing for much faster pricing model proxy update - a feature of particular importance at times of market distress. This constitutes a further enhancement over the already sizable improvement provided by Deep Neural Nets.}}
* T. P. Davis, “A Likely Gamma,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
Automatic differentiation is now used extensively in finance to determine the greeks of financial securities. Unfortunately, when using this technique with binomial trees, the second order sensitivities, such as gamma, cannot be calculated due to the interaction of the structure of the lattice and singularities in the derivatives of payoff functions. In this paper, we use recent results on the likelihood ratio method on binomial trees to overcome this issue. The algorithm for determining delta via the likelihood ratio method is extremely easy and efficient to implement, and when combined with automatic differentiation yields continuous gammas.
@article{WILM:WILM12059,title = {{A Likely Gamma}},author = {Davis, Tom P},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12059},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12059},abstract = {Automatic differentiation is now used extensively in finance to determine the greeks of financial securities. Unfortunately, when using this technique with binomial trees, the second order sensitivities, such as gamma, cannot be calculated due to the interaction of the structure of the lattice and singularities in the derivatives of payoff functions. In this paper, we use recent results on the likelihood ratio method on binomial trees to overcome this issue. The algorithm for determining delta via the likelihood ratio method is extremely easy and efficient to implement, and when combined with automatic differentiation yields continuous gammas.}}
* M. Radley, “Charging Ahead/ Rare Flair,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
Alfa Romeo Junior/Alfa Romeo Guilia GTA
@article{WILM:WILM12060,title = {{Charging Ahead/ Rare Flair}},author = {Radley, Milford},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12060},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12060},abstract = {Alfa Romeo Junior/Alfa Romeo Guilia GTA}}
* J. Darasz, “The Skewed World of Jan Darasz,” Wilmott, vol. 2024, iss. 132, 2024.
[Bibtex] [Abstract]
Cartoon
@article{WILM:WILM12061,title = {{The Skewed World of Jan Darasz}},author = {Darasz, Jan},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 132,doi = {10.54946/wilm.12061},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12061},abstract = {Cartoon}}
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The mathematician, quant finance pioneer and philanthropist, Jim Simons has died at the age of 86.
James Harris Simons was born on April 25th, 1938, in Newton, Massachusetts and raised in Brookline. Studying at MIT he received his bachelor’s degree in mathematics from MIT and later received his PhD in mathematics from Berkeley in 1961 aged 23.
Simons worked as a code breaker for the National Security Agency in 1964, later with the Communications Research Division of the Institute for Defense Analysis and taught mathematics at MIT and Harvard. His views on the Vietnam war led him to be forced to leave the IDA and he moved to Stony Brook University where he served as chair of the math department.
Simons created Monemetrics in 1978, a hedge fund management firm. Initially Simons did not use advanced mathematics in his work in finance, but later realised the important role that mathematical models could play in fund management. He changed the firm’s name to Renaissance Technologies LLC in 1982.
Simons began to hire academics with a non-finance background, emphasising computer science, physics and mathematics. Using a mixture of data warehousing the company was able to access the statistical probabilities of the price directions of securities.
The Medallion fund is regarded as having the best track record on Wall Street with an average of 66% returns before fees from 1988 to 2018. In 1993 the fund became an internal fund for employees only and ran alongside two other funds for external investors. In 2006 the Financial Times called Simons, “the world’s smartest billionaire” in the “Alternative Rich List” and in 2008 he was inducted into the Alpha’s Hedge Fund Manager Hall of Fame. Bloomberg Markets included Simons in the “50 Most Influential” in 2011.
Simons retired in 2009, taking up the role of non-executive chair of Renaissance Technologies, which he then stepped down from in 2019. With his wife Marilyn, Simons created the Simons Foundation in 1994 with the aim of supporting projects in health, education and science.
The story of Simons’ life was documented by author Gregory Zuckerberg in the
book, “The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution.”
Jim Simons is survived by his wife, Marilyn, their three children, and five grandchildren.
Image: Jim Simons by Glueschk, from the Wikipedia Media Library used under the Creative Commons https://creativecommons.org/licenses/by-sa/3.0/
Volume 2024, Issue 131. Pages 1-84
Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here.
In this issue:* D. Tudball, “Contents,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
Contents
@article{WILM:WILM12028,title = {{Contents}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12028},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12028},abstract = {Contents}}
* D. Tudball, “A Sigh is Just a Sigh,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex]
@article{WILM:WILM12029,title = {{A Sigh is Just a Sigh}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12029},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12029},abstract = {}}
* A. Brown, “The Most Unkindest Cut of All,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
When a fee decrease is actually a fee increase in the world of fine art and luxury goods auctions.
@article{WILM:WILM12030,title = {{The Most Unkindest Cut of All}},author = {Brown, Aaron},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12030},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12030},abstract = {When a fee decrease is actually a fee increase in the world of fine art and luxury goods auctions.}}
* R. Poulsen, “Part one: Got it in one‽,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
Does more data make for happy, harmonious, and honest estimators?
@article{WILM:WILM12031,title = {{Part one: Got it in one‽}},author = {Poulsen, Rolf},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12031},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12031},abstract = {Does more data make for happy, harmonious, and honest estimators?}}
* U. Wystup, “Lumberjack and the AUD-USD TARF during the Corona Pandemic ,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
Whoever always wanted to be a lumberjack, may not have considered trading Target Forwards during the corona pandemic.
@article{WILM:WILM12032,title = {{Lumberjack and the AUD-USD TARF during the Corona Pandemic }},author = {Wystup, Uwe},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12032},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12032},abstract = {Whoever always wanted to be a lumberjack, may not have considered trading Target Forwards during the corona pandemic.}}
* G. Giller, “It Turns out Other Countries Aren’t Normal Either,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
This article will demonstrate that the “mature” stock markets of other countries are also not Normal and, in fact, their abnormality is close to that of the US in its nature.
@article{WILM:WILM12033,title = {{It Turns out Other Countries Aren’t Normal Either}},author = {Giller, Graham},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12033},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12033},abstract = {This article will demonstrate that the “mature” stock markets of other countries are also not Normal and, in fact, their abnormality is close to that of the US in its nature.}}
* L. Ballabio, “Cash flows and bonds in QuantLib,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
Building sequences of coupons and how to get started using them to build bonds.
@article{WILM:WILM12034,title = {{Cash flows and bonds in QuantLib}},author = {Ballabio, Luigi},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12034},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12034},abstract = {Building sequences of coupons and how to get started using them to build bonds.}}
* M. Staunton, “Assurances Générales for COS,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
A renovation of the Fourier cosine expansion method will extend its life for a few decades more!
@article{WILM:WILM12035,title = {{Assurances Générales for COS}},author = {Staunton, Mike},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12035},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12035},abstract = {A renovation of the Fourier cosine expansion method will extend its life for a few decades more!}}
* R. Bogni, “Is There Enough Capital to Keep the World Economy Growing?,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
The global sentiment of impotence, pessimism, and division doesn’t help make the answer a positive one.
@article{WILM:WILM12036,title = {{Is There Enough Capital to Keep the World Economy Growing?}},author = {Bogni, Rudi},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12036},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12036},abstract = {The global sentiment of impotence, pessimism, and division doesn’t help make the answer a positive one.}}
* J. Guerard, “Sir David Hendry: An Appreciation from Wall Street and What Macroeconomics Got Right,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
Professor Hendry’s software, Autometrics, could be a great resource of enormous value to portfolio construction and management as a tool for portfolio lambda setting.
@article{WILM:WILM12037,title = {{Sir David Hendry: An Appreciation from Wall Street and What Macroeconomics Got Right}},author = {Guerard, John},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12037},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12037},abstract = {Professor Hendry’s software, Autometrics, could be a great resource of enormous value to portfolio construction and management as a tool for portfolio lambda setting.}}
* D. Tudball, “Psi Ops,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
The increasing viability of quantum computing prompts us to catch up with David Orrell on his ongoing mission to incorporate lessons from quantum mechanics into finance.
@article{WILM:WILM12038,title = {{Psi Ops}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12038},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12038},abstract = {The increasing viability of quantum computing prompts us to catch up with David Orrell on his ongoing mission to incorporate lessons from quantum mechanics into finance.}}
* A. Pena, “Quantum Computing for Finance: A Guided Tour,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
Alonso Peña introduces qubits, quantum gates, quantum circuits, and the IBM Quantum platform for real/simulated quantum computing.
@article{WILM:WILM12039,title = {{Quantum Computing for Finance: A Guided Tour}},author = {Pena, Alonso},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12039},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12039},abstract = {Alonso Peña introduces qubits, quantum gates, quantum circuits, and the IBM Quantum platform for real/simulated quantum computing.}}
* O. Kondratyev, “Perspectives of Quantum Computing,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
Here, we are facing two fundamental questions.First, can we run quantum computing protocol on classical hardware? That is, can we simulate a quantum computer on the classical one?Second, can we find the way of controlling an actual quantum mechanical system, such that it executes intended computational instructions? That is, can we build the quantum processing unit (QPU)?
@article{WILM:WILM12040,title = {{Perspectives of Quantum Computing}},author = {Kondratyev, Oleksiy},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12040},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12040},abstract = {Here, we are facing two fundamental questions.First, can we run quantum computing protocol on classical hardware? That is, can we simulate a quantum computer on the classical one?Second, can we find the way of controlling an actual quantum mechanical system, such that it executes intended computational instructions? That is, can we build the quantum processing unit (QPU)?}}
* D. Orrell, “A Quantum Model of Implied Volatility,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
The quantum implied volatility (QIV) model is a minimalistic model of an implied volatility surface. It is derived by assuming that the implied volatility is the volatility which, when used as input to the Black-Scholes model, will produce the correct option price under a previously derived quantum model of asset price. In its base form, the model uses only two parameters to simulate a volatility surface over different strikes and expirations. Results can be improved by adding additional parameters, such as a drift term. The method is illustrated using data from the S&P 500 index, as well as individual stocks.
@article{WILM:WILM12041,title = {{A Quantum Model of Implied Volatility}},author = {Orrell, David},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12041},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12041},abstract = {The quantum implied volatility (QIV) model is a minimalistic model of an implied volatility surface. It is derived by assuming that the implied volatility is the volatility which, when used as input to the Black-Scholes model, will produce the correct option price under a previously derived quantum model of asset price. In its base form, the model uses only two parameters to simulate a volatility surface over different strikes and expirations. Results can be improved by adding additional parameters, such as a drift term. The method is illustrated using data from the S&P 500 index, as well as individual stocks.}}
* T. Sakuma, “Application of Deep Quantum Neural Networks to Finance,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
The recent development of quantum computing gives us an opportunity to explore its potential applications to many fields, with the field of finance being no exception. In this paper, we apply the deep quantum neural network proposed by Beer et al. (2020) and discuss such potential in the context of simple experiments, such as learning implied volatilities and option prices. Furthermore, Greeks, such as delta and gamma, which are important measures in risk management, can be computed analytically with the neural network, and our numerical experiments show that the deep quantum neural network is a promising technique for solving such numerical problems arising in finance.
@article{WILM:WILM12042,title = {{Application of Deep Quantum Neural Networks to Finance}},author = {Sakuma, Takayuki},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12042},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12042},abstract = {The recent development of quantum computing gives us an opportunity to explore its potential applications to many fields, with the field of finance being no exception. In this paper, we apply the deep quantum neural network proposed by Beer et al. (2020) and discuss such potential in the context of simple experiments, such as learning implied volatilities and option prices. Furthermore, Greeks, such as delta and gamma, which are important measures in risk management, can be computed analytically with the neural network, and our numerical experiments show that the deep quantum neural network is a promising technique for solving such numerical problems arising in finance.}}
* L. Fongang, W. Leduc, R. Mahi, M. Marouen, A. Reghai, and A. Sahnoun, “LSV Vega KT : Partial AD a Practical Approach,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
We present an efficient algorithm for computing the Vega KT in the local stochastic volatility model based on the calculation of the leverage Vega sensitivities through Monte Carlo simulation and algorithmic differentiation. In comparison with the classical AD, it consumes much less memory. Our algorithm is applicable for general multi-dimensional exotic options.
@article{WILM:WILM12043,title = {{LSV Vega KT : Partial AD a Practical Approach}},author = {Fongang, Leopold and Leduc, William and Mahi, Rida and Marouen, Messaoud and Reghai, Adil and Sahnoun, Abdessamad},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12043},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12043},abstract = {We present an efficient algorithm for computing the Vega KT in the local stochastic volatility model based on the calculation of the leverage Vega sensitivities through Monte Carlo simulation and algorithmic differentiation. In comparison with the classical AD, it consumes much less memory. Our algorithm is applicable for general multi-dimensional exotic options.}}
* M. Radley, “Add Vantage/Zed Mist,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
Aston Martin Vantage/ Nissan Zed Nismo
@article{WILM:WILM12044,title = {{Add Vantage/Zed Mist}},author = {Radley, Milford},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12044},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12044},abstract = {Aston Martin Vantage/ Nissan Zed Nismo}}
* J. Darasz, “The Skewed World of Jan Darasz,” Wilmott, vol. 2024, iss. 131, 2024.
[Bibtex] [Abstract]
Cartoon
@article{WILM:WILM12045,title = {{The Skewed World of Jan Darasz}},author = {Darasz, Jan},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 131,doi = {10.54946/wilm.12045},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12045},abstract = {Cartoon}}
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The NVIDIA CEO Jensen Huang has been on the media rounds over the last month, ramping up the share price and market cap of the company that he steers. Huang has even done an interview with Jim Kramer which, in some circles, may be the strongest signal to short the lot.
One comment that’s garnered a lot of attention is that Jensen has suggested that software engineering isn’t worth studying anymore as AI will do the code generation for us. The Linkedin AI experts, of which there seems a plentiful supply, all had their opinion.
So, is Generative AI the death of coding that NVIDIA’s CEO, Jensen Huang, suggests? [i]
Along with the discussion on CQF December 2023 podcast between Dan Turnbull and Paul Wilmott. The use of artificial intelligence and the creation of programming code in the context of quant finance. What will the impact on the human talent pool of software developers with the advent of this technology?
It’s a matter I’ve kept a close eye on since October 2022, as OpenAI released the GPT4 model to a rather stunned and surprised world, I started to get concerned about my own career of over thirty years in software.
Prompting With CoPilot and ChatGPTLet’s look at two methods for code creation: OpenAI’s ChatGPT web interface, the second is using Github’s Co-Pilot within Microsoft’s Visual Studio Code (VSCode).
Both mechanisms require a prompt to be entered for the AI model make its prediction. The key to good output is asking the right kind of questions, “the quality of the question determines the quality of the answer”[ii].
To illustrate, I’m going to take a well documented requirement and see what CoPilot gives as output. I’m going to use Python as my language of choice, a reason I will get on to later. It’s not a quant problem, but I do want to use an example that is well used to give you a clear and predictable example.
'''Create a function that outputs a haversine distance between two points on the earth given their latitude and longitude in decimal degrees.'''
The instruction is simple, create a function for a haversine equation. Once I’ve entered this into the code editor CoPilot is creating the output based on the code it’s been previously trained on. For something like Haversine, there are plenty of examples, therefore the output quality is predictably good.
The result is generated as I started typing in the ‘def’ keyword into the editor. CoPilot suggests the code I should use and all I need to do is agree to accept the prediction with the tab key. I’m impressed but at the same time a little concerned about my future.
Moving to ChatGPT and using the exact same prompt, the output is not what I was expecting.[iii]
Interestingly the model (GPT4 in this instance) didn’t generate any useful code, the reason for which is clear to me, I never asked it to produce anything in a particular language in my original prompt. Adding the desired language to the prompt, Python, GPT then gives me a more useful answer. Our jobs are safe!
It’s also worth pointing out that the code suggested by both generative methods are starkly different, this being down to the way the respective models have been trained. CoPilot is trained on code repositories from services such as GitHub whereas ChatGPT is trained on large text corpus’ some of which include programming language and code. If CoPilot can’t give a meaningful prediction it will rely on code that you have within the development environment.
While it’s helpful for these kinds of generative models to generate code for us, they leave out the more critical areas of software development. First, there are no unit tests, while the code outputs are generated, I still am unsure whether the code works reliably. There’s a high degree of confidence that the code will work, the question is whether output is correct?
This is easily tested with something like my haversine example, when it comes to quant finance the rigors of testing must hold up to closer scrutiny, repeated testing and review.
Our role as developers is to deliver the full solution, not just the code. The tests, the fresh set of eyes, our skill and tacit domain knowledge. Those pushing AI will suggest it’s all possible, that’s marketing, but I’ll take human intelligence and skill over AI in the real world.
Ethics and VulnerabilitiesHow do I know I’m not breaking another company’s copyright? This is the part of generative AI that is up for some serious debate. Microsoft, GitHub’s now owner, was subject to a lawsuit in 2022[iv] for training CoPilot on licenced code. Where does that leave us as developers who are generating code? I’ve no idea while generating code of the provenance of the original training corpus. Does this leave me, or the company I’m working for, liable?
Some institutions will never let code or data leave the premises, this gives them the limited options to protect human skills or use trained in-house predictive models.
Emphasis much be placed on software security within the finance industry. Generative AI coding has come under attack from bad actors who are adding incorrect or fictitious package names in code output.[v] These “hallucinations” can cause untold damage to a business if trojan code is released. The vigilance from developers, testers and QA must be increased to reduce the likelihood of this happening.
It is also vital to review each of the providers terms and conditions to see how code the organisation is creating is protected from being reintroduced to these models for further training and fine tuning. Samsung were caught out by some very simple copy and pasting of information into ChatGPT.[vi] Samsung eventually banned ChatGPT from being used.
So, What About My Job?While 2023 was the year of GPT and CoPilot, the mild cooling of 2024 is underway as businesses try to figure out if the effort is worth the payoff. Eyes are also on the number of legal challenges some organisations are making against the model owners. I know a number of companies who are resistant, for now.
The two primary languages that generative AI is trained are Java and Python. For those using things like Matlab, R or C++ then while AI will generate code there’s a lot of reviewing and general checking that needs to happen. For example, I have seen Go code generated where variable names are different during the output of the generated code. The general logic is there though the code will never work.
On AI panels in the past I’ve predicted we’ll see two types of developer: a junior role where the task is to take a specification and, using prompts, generate the basic code for the application. It will then be passed to a senior developer to review, test and decide whether that code will go on to QA for release.
I believe, as software developers, we are in a good place where our careers are concerned. Our skills and domain knowledge outshines the model’s output, especially in the lesser used languages and specialist algorithms are used. We do, however, need to keep a very close eye on the next few years to see how the landscape develops. The media may play up our demise though I think it’s a long way off.
References[i] https://www.techradar.com/pro/nvidia-ceo-predicts-the-death-of-coding-jensen-huang-says-ai-will-do-the-work-so-kids-dont-need-to-learn
[ii] https://www.dgmlive.com/in-depth/guitar-craft-aphorisms
[iii] https://chat.openai.com/share/f9eba4e5-5d9c-441b-8244-65d4949d9c63
[iv] https://www.theverge.com/2022/11/8/23446821/microsoft-openai-github-copilot-class-action-lawsuit-ai-copyright-violation-training-data
[v] https://vulcan.io/blog/ai-hallucinations-package-risk/
[vi] https://www.forbes.com/sites/siladityaray/2023/05/02/samsung-bans-chatgpt-and-other-chatbots-for-employees-after-sensitive-code-leak/?sh=7f6244ec6078
BioJason Bell is a software developer of over thirty five years. He is also the author of Machine Learning: Hands on for Developers and Technical Professionals – published by Wiley in 2014 and a second edition in 2022.
Volume 2024, Issue 130. Pages 1-84
Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here.
In this issue:* D. Tudball, “Contents,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
Contents
@article{WILM:WILM12013,title = {{Contents}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12013},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12013},abstract = {Contents}}
* D. Tudball, “Follow Me in Merry Measure,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
A new model for a stock price, namely, Geometric Compound Hawkes process
@article{WILM:WILM12014,title = {{Follow Me in Merry Measure}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12014},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12014},abstract = {A new model for a stock price, namely, Geometric Compound Hawkes process}}
* A. Brown, “Champions,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
Baseball fans express disappointment in the 2023 postseason, where the World Series featured mid-tier teams. Here, playoff systems are analyzed, and a focus on overcoming quality opponents is suggested. A statistical approach, Wins Above Average, and historical playoff data are presented.
@article{WILM:WILM12015,title = {{Champions}},author = {Brown, Aaron},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12015},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12015},abstract = {Baseball fans express disappointment in the 2023 postseason, where the World Series featured mid-tier teams. Here, playoff systems are analyzed, and a focus on overcoming quality opponents is suggested. A statistical approach, Wins Above Average, and historical playoff data are presented.}}
* R. Poulsen, “Nobel Prizes, Part I: Anecdotes,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
As a former Nobel Peace Prize winner the author offers a unique perspective.
@article{WILM:WILM12016,title = {{Nobel Prizes, Part I: Anecdotes}},author = {Poulsen, Rolf},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12016},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12016},abstract = {As a former Nobel Peace Prize winner the author offers a unique perspective.}}
* U. Wystup, “TKO for DKOs,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
Replication a EUR-paying Double-No-Touch with a Single Double-Knock-Out Option
@article{WILM:WILM12017,title = {{TKO for DKOs}},author = {Wystup, Uwe},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12017},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12017},abstract = {Replication a EUR-paying Double-No-Touch with a Single Double-Knock-Out Option}}
* L. Ballabio, “Schedules in QuantLib,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
How to use QuantLib to generate schedules, i.e., regular sequences of dates, choosing from a number of market conventions.
@article{WILM:WILM12018,title = {{Schedules in QuantLib}},author = {Ballabio, Luigi},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12018},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12018},abstract = {How to use QuantLib to generate schedules, i.e., regular sequences of dates, choosing from a number of market conventions.}}
* G. Giller, “It Turns Out Other Countries Aren’t Normal Either,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
This article will demonstrate that the “mature” stock markets of other countries are also not Normal and, in fact, their abnormality is close to that of the US in its nature.
@article{WILM:WILM12019,title = {{It Turns Out Other Countries Aren’t Normal Either}},author = {Giller, Graham},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12019},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12019},abstract = {This article will demonstrate that the “mature” stock markets of other countries are also not Normal and, in fact, their abnormality is close to that of the US in its nature.}}
* S. Das, “Longitudinal – Reflections On Recent Economic Writing,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
Your humble writer has shunned economic works for years for various reasons, as well as laziness. Recently, masochism led him to delve into several newish economic books, selected with a careless randomness
@article{WILM:WILM12020,title = {{Longitudinal - Reflections On Recent Economic Writing}},author = {Das, Satyajit},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12020},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12020},abstract = {Your humble writer has shunned economic works for years for various reasons, as well as laziness. Recently, masochism led him to delve into several newish economic books, selected with a careless randomness}}
* A. Swishchuk, “Geometric Compound Hawkes Process and its Applications in Finance,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
The authors introduce a new model for a stock price, namely, geometric compound Hawkes process, and show how this model can be applied to solving many problems in finance, including European and American option pricing (perpetual American options), and Merton portfolio optimization problem. This model is a generalization of some well-known models in finance, such as Cox-Ross-Rubinstein model (1976) (geometric binomial process), Aase model (1988) (geometric compound Poisson process) and geometric Markov renewal model (2013). numerical examples are presented as well
@article{WILM:WILM12021,title = {{Geometric Compound Hawkes Process and its Applications in Finance}},author = {Swishchuk, Anatoliy},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12021},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12021},abstract = {The authors introduce a new model for a stock price, namely, geometric compound Hawkes process, and show how this model can be applied to solving many problems in finance, including European and American option pricing (perpetual American options), and Merton portfolio optimization problem. This model is a generalization of some well-known models in finance, such as Cox-Ross-Rubinstein model (1976) (geometric binomial process), Aase model (1988) (geometric compound Poisson process) and geometric Markov renewal model (2013). numerical examples are presented as well}}
* L. Ballotta, “Is the VIX Just Volatility? The Devil is in the (De)tails,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
Last year marked twenty years since the redesign of the ‘Fear Index’ shifting its focus to OTM options on the S&P500. Two decades on this change in emphasis still raises interesting implications
@article{WILM:WILM12022,title = {{Is the VIX Just Volatility? The Devil is in the (De)tails}},author = {Ballotta, Laura},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12022},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12022},abstract = {Last year marked twenty years since the redesign of the 'Fear Index' shifting its focus to OTM options on the S&P500. Two decades on this change in emphasis still raises interesting implications}}
* S. Renzitti, “Structured XVAs: Diffusive Portfolios,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
In this paper, a continuous-time, structural model of a dealer-bank is presented to derive fair value equations for credit-risky financial products that are not perfectly hedged. The impact these contracts has on the dealer-bank’s earnings volatility and, consequently, their solvency and financing costs, is taken into account. Explicit relationships between credit, debit, funding, and capital valuation adjustments (CVA, DVA, FVA, and KVA, respectively) are established, highlighting the interdependencies between unhedged credit risk and financing adjustments. To illustrate the practical application of the model, several straightforward numerical examples are provided.
@article{WILM:WILM12023,title = {{Structured XVAs: Diffusive Portfolios}},author = {Renzitti, Stefano},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12023},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12023},abstract = {In this paper, a continuous-time, structural model of a dealer-bank is presented to derive fair value equations for credit-risky financial products that are not perfectly hedged. The impact these contracts has on the dealer-bank’s earnings volatility and, consequently, their solvency and financing costs, is taken into account. Explicit relationships between credit, debit, funding, and capital valuation adjustments (CVA, DVA, FVA, and KVA, respectively) are established, highlighting the interdependencies between unhedged credit risk and financing adjustments. To illustrate the practical application of the model, several straightforward numerical examples are provided.}}
* S. Ahlawat, “Sector Investing Risks in Different Market Conditions,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
GICS sector investing is a popular investment style that offers increased liquidity and reduced idiosyncratic risk as compared with investing in individual stocks. This is attested by the increase in trading volumes of ETFs tracking GICS sectors. While most investors are aware of macro-economic risks associated with GICS sectors by virtue of industry type constituting the sector, information about the relative performance of sectors in different market environments is not as keenly understood. For example, most investors know that utilities and consumer staples perform well during recessions; but most are unaware of how the sectors perform relative to one another during inflationary periods or during periods of wide credit spreads. Most of the knowledge about relative sector performance is restricted to associating the economic conditions with recessionary or expansionary phases of the business cycle. Further, individual components of certain sectors behave very differently during certain market periods, forming sub-sectors within the sectors. Investors who are focused on positioning their portfolio for certain market environments may find it beneficial to concentrate their holding in that sub-sector to the extent that it meets their growth mandates while staying within risk tolerance. This work presents a detailed comparison of risk and return characteristics of the 11 GICS sectors in five market environments: business-cycle recession, rising interest rates, rising inflation, high market volatility, and wide credit spreads. Further, it dissects the behavior of individual sector components to glean information about when it may be advisable for sector investors to focus on industry groups within sectors. Looking at the current market environment and the likely evolution of macroeconomic conditions in the near future, it extrapolates the findings to make general recommendations for sector investing in the near future.
@article{WILM:WILM12024,title = {{Sector Investing Risks in Different Market Conditions}},author = {Ahlawat, Samit},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12024},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12024},abstract = {GICS sector investing is a popular investment style that offers increased liquidity and reduced idiosyncratic risk as compared with investing in individual stocks. This is attested by the increase in trading volumes of ETFs tracking GICS sectors. While most investors are aware of macro-economic risks associated with GICS sectors by virtue of industry type constituting the sector, information about the relative performance of sectors in different market environments is not as keenly understood. For example, most investors know that utilities and consumer staples perform well during recessions; but most are unaware of how the sectors perform relative to one another during inflationary periods or during periods of wide credit spreads. Most of the knowledge about relative sector performance is restricted to associating the economic conditions with recessionary or expansionary phases of the business cycle. Further, individual components of certain sectors behave very differently during certain market periods, forming sub-sectors within the sectors. Investors who are focused on positioning their portfolio for certain market environments may find it beneficial to concentrate their holding in that sub-sector to the extent that it meets their growth mandates while staying within risk tolerance. This work presents a detailed comparison of risk and return characteristics of the 11 GICS sectors in five market environments: business-cycle recession, rising interest rates, rising inflation, high market volatility, and wide credit spreads. Further, it dissects the behavior of individual sector components to glean information about when it may be advisable for sector investors to focus on industry groups within sectors. Looking at the current market environment and the likely evolution of macroeconomic conditions in the near future, it extrapolates the findings to make general recommendations for sector investing in the near future.}}
* C. Stanford, W. Luk, S. Weston, C. Guo, J. Babaie-Harmon, and K. Vytelingum, “Agent-Based Modelling for Scenario Analysis in Management Consulting,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
This paper investigates the modernization of a corporate practice called scenario analysis. It is widely used across the globe, originating from World War II, helping companies to gain a better understanding of potential future outcomes. In order to modernize scenario analysis, this paper will explore the novel approaches; of a hybrid development between agent-based modelling (ABM) and scenario analysis, the utilization of bottom-up and industry view approaches and introducing elements of human social behaviour. All these features are integrated in a single scenario analysis ABM that will model the fundamental philosophy behind the daily operations of a large corporation, such as Deloitte. This paper addresses more natural evolutions for scenarios, by looking at the firms’ fundamental building blocks, rather than just an objective view based on the firms’ financial statements. This model will focus upon accurate representations of the daily interactions of an enterprise, especially improving the explainability and transparency of causality in scenario analysis generated by the models, in order to achieve enduring agreements among executives about the firm’s future. With this novel approach to scenario analysis, the modelling of a firm with the use of an ABM, there is the potential to provide more in-depth micro-observations of the future, rather than the conventional scenario analysis methods performed today.
@article{WILM:WILM12025,title = {{Agent-Based Modelling for Scenario Analysis in Management Consulting}},author = {Stanford, Christopher and Luk,Wayne and Weston, Stephen and Guo, Ce and Babaie-Harmon, Jiyan and Vytelingum, Krishnen},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12025},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12025},abstract = {This paper investigates the modernization of a corporate practice called scenario analysis. It is widely used across the globe, originating from World War II, helping companies to gain a better understanding of potential future outcomes. In order to modernize scenario analysis, this paper will explore the novel approaches; of a hybrid development between agent-based modelling (ABM) and scenario analysis, the utilization of bottom-up and industry view approaches and introducing elements of human social behaviour. All these features are integrated in a single scenario analysis ABM that will model the fundamental philosophy behind the daily operations of a large corporation, such as Deloitte. This paper addresses more natural evolutions for scenarios, by looking at the firms’ fundamental building blocks, rather than just an objective view based on the firms’ financial statements. This model will focus upon accurate representations of the daily interactions of an enterprise, especially improving the explainability and transparency of causality in scenario analysis generated by the models, in order to achieve enduring agreements among executives about the firm’s future. With this novel approach to scenario analysis, the modelling of a firm with the use of an ABM, there is the potential to provide more in-depth micro-observations of the future, rather than the conventional scenario analysis methods performed today.}}
* M. Radley, “Suspension of Disbelief/Lightening Seed,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
Porsche Panamera/ Lamborghini Revuelto
@article{WILM:WILM12026,title = {{Suspension of Disbelief/Lightening Seed}},author = {Radley, Milford},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12026},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12026},abstract = {Porsche Panamera/ Lamborghini Revuelto}}
* J. Darasz, “The Skewed World of Jan Darasz,” Wilmott, vol. 2024, iss. 130, 2024.
[Bibtex] [Abstract]
Cartoon
@article{WILM:WILM12027,title = {{The Skewed World of Jan Darasz}},author = {Darasz, Jan},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 130,doi = {10.54946/wilm.12027},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12027},abstract = {Cartoon}}
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Volume 2024, Issue 129. Pages 1-84
Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here.
In this issue:* D. Tudball, “Contents,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
Contents
@article{WILM:WILM11999,title = {{Contents}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.11999},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11999},abstract = {Contents}}
* D. Tudball, ,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex]
@article{WILM:WILM12000,title = {{}},author = {Tudball, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12000},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12000},abstract = {}}
* U. Wystup, “The Pedigree of Exotics – Or Derivatives Lego ,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
In enumerating how many exotic options there are, should we exclude all that are replications of other building blocks?
@article{WILM:WILM12001,title = {{The Pedigree of Exotics – Or Derivatives Lego }},author = {Wystup, Uwe},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12001},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12001},abstract = {In enumerating how many exotic options there are, should we exclude all that are replications of other building blocks?}}
* A. Brown, “The Mathematics of Scratch Seven,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
Analyzing a novel card game introduced in a science fiction novel.
@article{WILM:WILM12002,title = {{The Mathematics of Scratch Seven}},author = {Brown, Aaron},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12002},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12002},abstract = {Analyzing a novel card game introduced in a science fiction novel.}}
* L. Ballabio, “Holidays in Quantlib,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
The season’s upon us.
@article{WILM:WILM12003,title = {{Holidays in Quantlib}},author = {Ballabio, Luigi},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12003},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12003},abstract = {The season’s upon us.}}
* D. Orrell, “Is Non-Quantum Finance too Much of a Stretch?,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
A considered response to people who believe quantum economics/finance is too much of a stretch.
@article{WILM:WILM12004,title = {{Is Non-Quantum Finance too Much of a Stretch?}},author = {Orrell, David},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12004},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12004},abstract = {A considered response to people who believe quantum economics/finance is too much of a stretch.}}
* P. Benda, “Finding Safe Harbor in the Supply Chain: Covid Impact on Market Performance and Market Risk Up and Down the Supply Chain,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
Being downstream may offer a safer haven for agile companies to weather supply chain disruptions. Vertically integrated industries may have the highest exposure to supply chain risks.
@article{WILM:WILM12005,title = {{Finding Safe Harbor in the Supply Chain: Covid Impact on Market Performance and Market Risk Up and Down the Supply Chain}},author = {Benda, Peter},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12005},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12005},abstract = {Being downstream may offer a safer haven for agile companies to weather supply chain disruptions. Vertically integrated industries may have the highest exposure to supply chain risks.}}
* J. Guerard, D. D. Thomakos, F. Kyriazi, and K. Mamais, “On the Predictability of the DJIA and S&P500 Indexes,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
We obtained from Standard and Poor’s Corporation the complete 126-year history of the Dow Jones Industrial Average (DJIA) daily closing prices. We are applying rolling window averaging and adaptive learning methodologies, coupled with robust estimation methods, to examine which are the best forecasting models over a broad range of economic and financial conditions during the life of the index, based on daily and monthly stock index prices, and daily, monthly, and semi-annual stock returns. Why is an AR(1) model a reasonable benchmark of stock prices? Why do we have it? What should be our forecasting benchmarks? Do we find forecasting improvements from the Hendry-Castle-Doornik-Clements approach using robust forecasting methodologies and saturation variables in the prices of the index? Given that the DJIA fell over 15% during the first half of 2022, is this one of the worst six-month periods ever? What has happened to the Dow, historically, during such periods in the past with regard to six-month, one-year, and three-year-ahead stock returns? Is capitalism dead or doomed? We report statistically significant forecasting improvement from saturation and robust forecasting techniques during the 1896–June 2022 period. We report forecast stock returns for the next six months and three years that are bullish. In the King’s English, June 30, 2022, was another excellent common stock buying opportunity and Capitalism is not dead.
@article{WILM:WILM12006,title = {{On the Predictability of the DJIA and S&P500 Indexes}},author = {Guerard, John and Thomakos, Dimitrios D and Kyriazi, Foteini and Mamais, Konstantinos},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12006},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12006},abstract = {We obtained from Standard and Poor’s Corporation the complete 126-year history of the Dow Jones Industrial Average (DJIA) daily closing prices. We are applying rolling window averaging and adaptive learning methodologies, coupled with robust estimation methods, to examine which are the best forecasting models over a broad range of economic and financial conditions during the life of the index, based on daily and monthly stock index prices, and daily, monthly, and semi-annual stock returns. Why is an AR(1) model a reasonable benchmark of stock prices? Why do we have it? What should be our forecasting benchmarks? Do we find forecasting improvements from the Hendry-Castle-Doornik-Clements approach using robust forecasting methodologies and saturation variables in the prices of the index? Given that the DJIA fell over 15% during the first half of 2022, is this one of the worst six-month periods ever? What has happened to the Dow, historically, during such periods in the past with regard to six-month, one-year, and three-year-ahead stock returns? Is capitalism dead or doomed? We report statistically significant forecasting improvement from saturation and robust forecasting techniques during the 1896–June 2022 period. We report forecast stock returns for the next six months and three years that are bullish. In the King’s English, June 30, 2022, was another excellent common stock buying opportunity and Capitalism is not dead.}}
* I. Lai, “Sentiment Analysis Is Virtually Useless in Financial Forecasting,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
The practical utility of sentiment analysis as applied in financial forecasting is limited, and often exaggerated in a potentially misleading way.
@article{WILM:WILM12007,title = {{Sentiment Analysis Is Virtually Useless in Financial Forecasting}},author = {Lai, Isabella},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12007},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12007},abstract = {The practical utility of sentiment analysis as applied in financial forecasting is limited, and often exaggerated in a potentially misleading way.}}
* D. Pirjol, “The SABR Short-Maturity Expansion is Asymptotic,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
Short-maturity expansions offer a convenient alternative to numerical methods for option pricing. We discuss how methods from the theory of asymptotic series can be used to inform their optimal use and understand their limits of applicability.
@article{WILM:WILM12008,title = {{The SABR Short-Maturity Expansion is Asymptotic}},author = {Pirjol, Daniel},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12008},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12008},abstract = {Short-maturity expansions offer a convenient alternative to numerical methods for option pricing. We discuss how methods from the theory of asymptotic series can be used to inform their optimal use and understand their limits of applicability.}}
* A. Swishchuk and J. McGilivray, “Covariance and Correlation Swaps in Energy Markets,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
Many valuations of variance and volatility derivatives already exist, especially in discrete time, but continuous-time valuations of covariance and correlation swaps do not currently exist for assets following the Heston stochastic volatility model. Energy commodity markets contain some of the broadest and most liquid options markets. Thus, the development of covariance and correlation swap valuation will be of significant use to investors looking to hedge covariance or correlation. In this paper, we derive approximations for an arbitrage-free valuation of natural gas and crude oil covariance and correlation swaps in the Heston model using a continuous-time regime. The approximations are obtained through the use of successive Talyor approximations on otherwise intractable terms. We find that the first order approximations of covariance and correlation swap fair strikes are reasonably effective. When the approximations are taken to the second order, a significant problem with the ML-ARCH approximation of the GARCH(1,1) process creates a large error in the valuation and its error bounds. Leveraging the properties of the Lagrange error bound, we refine our approximation to avoid the use of a frequently miscalibrated parameter, leading to a better approximation of the fair strikes of the two swaps.
@article{WILM:WILM12009,title = {{Covariance and Correlation Swaps in Energy Markets}},author = {Swishchuk, Anatoliy and McGilivray, Joshua},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12009},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12009},abstract = {Many valuations of variance and volatility derivatives already exist, especially in discrete time, but continuous-time valuations of covariance and correlation swaps do not currently exist for assets following the Heston stochastic volatility model. Energy commodity markets contain some of the broadest and most liquid options markets. Thus, the development of covariance and correlation swap valuation will be of significant use to investors looking to hedge covariance or correlation. In this paper, we derive approximations for an arbitrage-free valuation of natural gas and crude oil covariance and correlation swaps in the Heston model using a continuous-time regime. The approximations are obtained through the use of successive Talyor approximations on otherwise intractable terms. We find that the first order approximations of covariance and correlation swap fair strikes are reasonably effective. When the approximations are taken to the second order, a significant problem with the ML-ARCH approximation of the GARCH(1,1) process creates a large error in the valuation and its error bounds. Leveraging the properties of the Lagrange error bound, we refine our approximation to avoid the use of a frequently miscalibrated parameter, leading to a better approximation of the fair strikes of the two swaps.}}
* A. Kumiega, G. Sterijevski, and B. Van Vliet, “Using “Greeks” from a Dynamic Program Real Option Framework to Quantitatively Manage an Innovation Project/Startup,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
In this paper, we extend the Dynamic Programming Real Option Framework via a numerical example (Kumiega, Sterijevski and Van Vliet, 2023). The numerical example details a new idea called control maps. The control maps are multi-state “Greek” that will allow management to make more robust decisions at project gate meetings. This framework will shift the decisions at each gate from a purely qualitative decision to quantitative decision. The qualitative decision will be based upon the change in the current project’s expected value and the additional projected cost to change state at a gate. Simulated costs and times to completion are generated by a continuous-time Markov chain with states.
@article{WILM:WILM12010,title = {{Using “Greeks” from a Dynamic Program Real Option Framework to Quantitatively Manage an Innovation Project/Startup}},author = {Kumiega, Andrew and Sterijevski, Greg and Van Vliet, Ben},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12010},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12010},abstract = {In this paper, we extend the Dynamic Programming Real Option Framework via a numerical example (Kumiega, Sterijevski and Van Vliet, 2023). The numerical example details a new idea called control maps. The control maps are multi-state “Greek” that will allow management to make more robust decisions at project gate meetings. This framework will shift the decisions at each gate from a purely qualitative decision to quantitative decision. The qualitative decision will be based upon the change in the current project’s expected value and the additional projected cost to change state at a gate. Simulated costs and times to completion are generated by a continuous-time Markov chain with states.}}
* M. Radley, “Birthday Bash, Last Blast,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
Porsche 911 S/T/Lotus Emira i4
@article{WILM:WILM12011,title = {{Birthday Bash, Last Blast}},author = {Radley, Milford},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12011},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12011},abstract = {Porsche 911 S/T/Lotus Emira i4}}
* J. Darasz, “The Skewed World of Jan Darasz,” Wilmott, vol. 2024, iss. 129, 2024.
[Bibtex] [Abstract]
Cartoon
@article{WILM:WILM12012,title = {{The Skewed World of Jan Darasz}},author = {Darasz, Jan},year = 2024,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2024,number = 129,doi = {10.54946/wilm.12012},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.12012},abstract = {Cartoon}}
If you are a current subscriber login to see all articles as PDFs.
re information about Wilmott magazine, for potential subscribers and submission of articles and research papers, can be found here.
Volume 2023, Issue 128. Pages 1-108
Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here.
In this issue:* D. Tudball, “Contents,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Contents
@article{WILM:WILM1115876,title = {{Contents}},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115876},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115876},abstract = {Contents}}
* D. Tudball, “Anytime, Anywhere,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex]
@article{WILM:WILM1115877,title = {{Anytime, Anywhere}},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115877},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115877},abstract = {}}
* G. Giller, “Learning About Trading Strategy by Driving Around,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Driving in traffic is a stochastic optimization problem
@article{WILM:WILM1115878,title = {{Learning About Trading Strategy by Driving Around}},author = {Giller, Graham},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115878},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115878},abstract = {Driving in traffic is a stochastic optimization problem}}
* U. Wystup and S. Van Mulken, “Slope Matters to Land on the Right Price,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Traders and Sales often argue that if you already have a volatility surface and can hence price all vanilla options for exotics, e.g., barrier options, all you need to do is add a barrier to the contract description and extract entry on the pricing screen. We will illustrate in this column why, unfortunately, it is not so easy, even for simple European digitals.
@article{WILM:WILM1115879,title = {{Slope Matters to Land on the Right Price}},author = {Wystup, Uwe and Van Mulken, Sebastiaan},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115879},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115879},abstract = {Traders and Sales often argue that if you already have a volatility surface and can hence price all vanilla options for exotics, e.g., barrier options, all you need to do is add a barrier to the contract description and extract entry on the pricing screen. We will illustrate in this column why, unfortunately, it is not so easy, even for simple European digitals.}}
* J. Andreasen, “Bump and Run,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Banks use ridiculous amounts of computational resources on computing various risk measures. We discuss how this can be avoided using a cocktail of a big hybrid simulation model, adjoint differentiation and machine learning techniques, aka differential machine learning.
@article{WILM:WILM1115880,title = {{Bump and Run}},author = {Andreasen, Jesper},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115880},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115880},abstract = {Banks use ridiculous amounts of computational resources on computing various risk measures. We discuss how this can be avoided using a cocktail of a big hybrid simulation model, adjoint differentiation and machine learning techniques, aka differential machine learning.}}
* L. Ballabio, “The Observer Pattern in QuantLib,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Where the pattern meets the road. Using the Observer pattern in QuantLibt to show some of the trade-offs and changes that a design pattern might have to undergo, in order to address constraints that come from real-world usage of a library
@article{WILM:WILM1115881,title = {{The Observer Pattern in QuantLib}},author = {Ballabio, Luigi},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115881},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115881},abstract = {Where the pattern meets the road. Using the Observer pattern in QuantLibt to show some of the trade-offs and changes that a design pattern might have to undergo, in order to address constraints that come from real-world usage of a library}}
* M. Kelly, “Financial Visualization and Trading Strategies,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
In this article we will focus on the various graphical and computational methods that are used to convey financial information, in particular on candlestick, price change and trading charts. We will also consider how financial indicators can be used to build trading strategies which allow for dynamic updating with changing stock prices
@article{WILM:WILM1115882,title = {{Financial Visualization and Trading Strategies}},author = {Kelly, Michael},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115882},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115882},abstract = {In this article we will focus on the various graphical and computational methods that are used to convey financial information, in particular on candlestick, price change and trading charts. We will also consider how financial indicators can be used to build trading strategies which allow for dynamic updating with changing stock prices}}
* D. Tudball, “CQF 20th Anniversary,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex]
@article{WILM:WILM1115883,title = {{CQF 20th Anniversary}},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115883},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115883},abstract = {}}
* CQF, “CQF 20th Anniversary,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
20 years ago, Dr. Paul Wilmott, designed the Certificate in Quantitative Finance (CQF) to teach practical quant finance skills and bridge the gap between academia and industry. Fast forward two decades, the program and its syllabus have evolved to meet industry demands throughout the pre-financial crisis, post-financial crisis, and the modern era. As we celebrate the 20th anniversary of the qualification, Dr. Randeep Gug, Managing Director of the CQF and CQF Institute, joins Wilmott Magazine Editor, Dan Tudball, to reflect on key milestones for the program, discuss the secrets behind the two decades of success, and examine how the typical CQF delegate has changed over the years.
@article{WILM:WILM1115884,title = {{CQF 20th Anniversary}},author = {CQF,},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115884},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115884},abstract = {20 years ago, Dr. Paul Wilmott, designed the Certificate in Quantitative Finance (CQF) to teach practical quant finance skills and bridge the gap between academia and industry. Fast forward two decades, the program and its syllabus have evolved to meet industry demands throughout the pre-financial crisis, post-financial crisis, and the modern era. As we celebrate the 20th anniversary of the qualification, Dr. Randeep Gug, Managing Director of the CQF and CQF Institute, joins Wilmott Magazine Editor, Dan Tudball, to reflect on key milestones for the program, discuss the secrets behind the two decades of success, and examine how the typical CQF delegate has changed over the years.}}
* P. Wilmott, “A Quick Trip to the Risk-Neutral Planet,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Thanks to many years of re-educating people in quantitative finance, I know thatthere is a lot of confusion about the concept of risk neutrality. I say “re”-educating because very often it is those with classical Master’s in Finance qualifications who are the most confused, precisely those who should have the best understanding. In my experience, Master’s can demonstrate that it works, i.e., go through the motions of proof, but that is less of a problem than the interpretation. In this paper, I give a description that I’ve been using on the CQF1 for decades but never fully put in writing before. This is a description of how it works, not why.
@article{WILM:WILM1115885,title = {{A Quick Trip to the Risk-Neutral Planet}},author = {Wilmott, Paul},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115885},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115885},abstract = {Thanks to many years of re-educating people in quantitative finance, I know thatthere is a lot of confusion about the concept of risk neutrality. I say “re”-educating because very often it is those with classical Master’s in Finance qualifications who are the most confused, precisely those who should have the best understanding. In my experience, Master’s can demonstrate that it works, i.e., go through the motions of proof, but that is less of a problem than the interpretation. In this paper, I give a description that I’ve been using on the CQF1 for decades but never fully put in writing before. This is a description of how it works, not why.}}
* CQF, “Chelvi Paramanathan,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Chelvi Paramanathan earned the CQF in 2018. Chelvi started her career as an engineer in the scientific research industry in Singapore, before transitioning to a career in finance, and working her way up to her current role as Global Head of Pricing and Analytics for Agency Securities Finance and Collateral Services business at J.P. Morgan Chase & Co. We spoke to Chelvi about how she made the move into finance, the biggest challenges facing the industry over the next few years, and her advice for people looking for their next role in quant finance.
@article{WILM:WILM1115886,title = {{Chelvi Paramanathan}},author = {CQF,},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115886},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115886},abstract = {Chelvi Paramanathan earned the CQF in 2018. Chelvi started her career as an engineer in the scientific research industry in Singapore, before transitioning to a career in finance, and working her way up to her current role as Global Head of Pricing and Analytics for Agency Securities Finance and Collateral Services business at J.P. Morgan Chase & Co. We spoke to Chelvi about how she made the move into finance, the biggest challenges facing the industry over the next few years, and her advice for people looking for their next role in quant finance.}}
* P. Jäckel, “A Singular Gamma Variance Expansion,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
We give an analytical expansion for option prices and Black implied volatilities consistent with the Variance Gamma model [MCC98] based on a singular expansion of the standard gamma density in terms of the Dirac functions and its derivatives
@article{WILM:WILM1115887,title = {{A Singular Gamma Variance Expansion}},author = {Jäckel, Peter},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115887},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115887},abstract = {We give an analytical expansion for option prices and Black implied volatilities consistent with the Variance Gamma model [MCC98] based on a singular expansion of the standard gamma density in terms of the Dirac functions and its derivatives}}
* CQF, “Borja Garcia Haendler,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Borja Garcia Haendler earned the CQF in 2013. Borja started his career as a Consultant for Indra and has since worked his way up to become Head of Market Risk and Product Control Asia at Julius Baer. We spoke to Borja about his transition from law to finance, the impact of new technologies, and the importance of interpersonal skills.
@article{WILM:WILM1115888,title = {{Borja Garcia Haendler}},author = {CQF,},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115888},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115888},abstract = {Borja Garcia Haendler earned the CQF in 2013. Borja started his career as a Consultant for Indra and has since worked his way up to become Head of Market Risk and Product Control Asia at Julius Baer. We spoke to Borja about his transition from law to finance, the impact of new technologies, and the importance of interpersonal skills.}}
* R. Ahmad, “The Full Monte – Euler vs. Milstein,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
A common problem in computational finance is the pricing of option contracts on single or multiple underlying financial assets. Calculating expected values of payoff functions contingent upon state variables, whose dynamics can be modeled by stochastic differential equations. Hence, Monte Carlo methods are a powerful technique for solving these equations computationally. This article uses the working of Fabrice Douglas Rouah to discuss the derivation of both Euler and Milstein schemes.
@article{WILM:WILM1115889,title = {{The Full Monte - Euler vs. Milstein}},author = {Ahmad, Riaz},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115889},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115889},abstract = {A common problem in computational finance is the pricing of option contracts on single or multiple underlying financial assets. Calculating expected values of payoff functions contingent upon state variables, whose dynamics can be modeled by stochastic differential equations. Hence, Monte Carlo methods are a powerful technique for solving these equations computationally. This article uses the working of Fabrice Douglas Rouah to discuss the derivation of both Euler and Milstein schemes.}}
* CQF, “Naomi Yarrow,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Naomi Yarrow earned the CQF in 2006. Naomi started her career as a Quant in the product Control Valuations Group at ABN AMRO Bank before working her way up to her current role as Head of Capital Risk Oversight at NatWest Group. We spoke to Naomi to find out more about why she decided to pursue a career in quant finance, her advice for people looking to advance in quant finance roles, and the most rewarding things about working in the field.
@article{WILM:WILM1115890,title = {{Naomi Yarrow}},author = {CQF,},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115890},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115890},abstract = {Naomi Yarrow earned the CQF in 2006. Naomi started her career as a Quant in the product Control Valuations Group at ABN AMRO Bank before working her way up to her current role as Head of Capital Risk Oversight at NatWest Group. We spoke to Naomi to find out more about why she decided to pursue a career in quant finance, her advice for people looking to advance in quant finance roles, and the most rewarding things about working in the field.}}
* M. Henrard, “Bond futures: Delivery Option with Term Structure Modelling,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Bond futures are characterized by a set of underlying bonds; the short party has the option to deliver at expiry any of those underlying bonds. Bond futures thus embed a choice option between bonds with different maturities and coupons. The delivery mechanism also incorporates conversion factors that create an implicit strike. The option is impacted by different maturities and different moneyness for each bond. It is important to take into account the full term structure of volatility with smile. A recent paper Bang and Daboussi (2022) developed such an approach for swap ratebased products like CMS. In this paper, we extend their approach to cover futures and apply it to the specific case of bond futures. We show the impact of smile, term structure of volatility and correlations between rates on the delivery option and convexity adjustment values.
@article{WILM:WILM1115891,title = {{Bond futures: Delivery Option with Term Structure Modelling}},author = {Henrard, Marc},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115891},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115891},abstract = {Bond futures are characterized by a set of underlying bonds; the short party has the option to deliver at expiry any of those underlying bonds. Bond futures thus embed a choice option between bonds with different maturities and coupons. The delivery mechanism also incorporates conversion factors that create an implicit strike. The option is impacted by different maturities and different moneyness for each bond. It is important to take into account the full term structure of volatility with smile. A recent paper Bang and Daboussi (2022) developed such an approach for swap ratebased products like CMS. In this paper, we extend their approach to cover futures and apply it to the specific case of bond futures. We show the impact of smile, term structure of volatility and correlations between rates on the delivery option and convexity adjustment values.}}
* CQF, “Tony Parish,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Tony started his finance career as Vice President of Product Analysis at Oppenheimer Funds in New York back in 2002 and now works as the Chief Investment Officer of Alphastar Capital Management. We spoke to Tony about his career highlights, new challenges facing the industry today, and how the CQF added value to his career
@article{WILM:WILM1115892,title = {{Tony Parish}},author = {CQF,},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115892},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115892},abstract = {Tony started his finance career as Vice President of Product Analysis at Oppenheimer Funds in New York back in 2002 and now works as the Chief Investment Officer of Alphastar Capital Management. We spoke to Tony about his career highlights, new challenges facing the industry today, and how the CQF added value to his career}}
* S. Lleo, “Risk-Sensitive Investment Management: A Guide for Quants,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Risk-sensitive investment management (RSIM) has emerged as a powerful approach that leverages the mathematics of stochastic control to address dynamic investment management problems. This note discusses RSIM and examines three practical implications of RSIM for investment managers. Firstly, RSIM models serve as a valuable tool for understanding and explaining the outcomes of realistic dynamic models. For example, they offer closed-form approximations of stochastic programming models. Secondly, RSIM sheds light on crucial investment management questions. RSIM enables practitioners to analyze the impact of various factors on investment performance, unravel the dynamics between active and passive management strategies, investigate the mechanics of learning within investment decisions, assess the value of expert opinions, and evaluate the effectiveness of stress test scenarios. Lastly, RSIM casts light on perilous strategies and practices that can lead to catastrophic losses for investment funds, such asexcessive betting or overbetting.
@article{WILM:WILM1115893,title = {{Risk-Sensitive Investment Management: A Guide for Quants}},author = {Lleo, Sebastien},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115893},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115893},abstract = {Risk-sensitive investment management (RSIM) has emerged as a powerful approach that leverages the mathematics of stochastic control to address dynamic investment management problems. This note discusses RSIM and examines three practical implications of RSIM for investment managers. Firstly, RSIM models serve as a valuable tool for understanding and explaining the outcomes of realistic dynamic models. For example, they offer closed-form approximations of stochastic programming models. Secondly, RSIM sheds light on crucial investment management questions. RSIM enables practitioners to analyze the impact of various factors on investment performance, unravel the dynamics between active and passive management strategies, investigate the mechanics of learning within investment decisions, assess the value of expert opinions, and evaluate the effectiveness of stress test scenarios. Lastly, RSIM casts light on perilous strategies and practices that can lead to catastrophic losses for investment funds, such asexcessive betting or overbetting.}}
* CQF, “Werner Trabesinger,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Werner Trabesinger earned the CQF in 2016. Werner started his career as a Risk and Model Auditor at Zürcher Kantonalbank and has since worked his way up to become Head of Quant Products at Pexapark. We spoke to Werner about how he got to his current role, quant career opportunities in energy trading, and the skills quants will need in the future.
@article{WILM:WILM1115894,title = {{Werner Trabesinger}},author = {CQF,},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115894},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115894},abstract = {Werner Trabesinger earned the CQF in 2016. Werner started his career as a Risk and Model Auditor at Zürcher Kantonalbank and has since worked his way up to become Head of Quant Products at Pexapark. We spoke to Werner about how he got to his current role, quant career opportunities in energy trading, and the skills quants will need in the future.}}
* E. Haug, “God’s Money ,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
The Key to Unlimited Clean Energy and the Age of Abundance Ahead
@article{WILM:WILM1115895,title = {{God's Money }},author = {Haug, Espen},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115895},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115895},abstract = {The Key to Unlimited Clean Energy and the Age of Abundance Ahead}}
* P. Bielstein, J. Jaegers, and P. Wesson, “A Novel way to Diversify Portfolio Weights,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
There is broad agreement among academics and practitioners that, in general, a diversified portfolio delivers more robust out-of-sample performance than a concentrated one. This paper develops a new method to diversify portfolio weights, which does not rely on expected returns or volatilities and is therefore robust to measurement error in these variables. It uses pair-wise regressions to estimate how much variation each asset explains in terms of another asset. The optimization function finds the portfolio weights that maximize the unexplained variation of the portfolio. We benchmark our method against established methods from the literature, such as the minimum volatility and the equal risk contribution portfolios. We demonstrate that our method adheres to established diversification properties and it performs well in empirical tests.
@article{WILM:WILM1115896,title = {{A Novel way to Diversify Portfolio Weights}},author = {Bielstein, Patrick and Jaegers, Jean-Paul and Wesson, Paul},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115896},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115896},abstract = {There is broad agreement among academics and practitioners that, in general, a diversified portfolio delivers more robust out-of-sample performance than a concentrated one. This paper develops a new method to diversify portfolio weights, which does not rely on expected returns or volatilities and is therefore robust to measurement error in these variables. It uses pair-wise regressions to estimate how much variation each asset explains in terms of another asset. The optimization function finds the portfolio weights that maximize the unexplained variation of the portfolio. We benchmark our method against established methods from the literature, such as the minimum volatility and the equal risk contribution portfolios. We demonstrate that our method adheres to established diversification properties and it performs well in empirical tests.}}
* M. Radley, “Final Fling,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Aston Martin DBS 770 Ultimate/Ferrari SF90 XX
@article{WILM:WILM1115897,title = {{Final Fling}},author = {Radley, Milford},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115897},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115897},abstract = {Aston Martin DBS 770 Ultimate/Ferrari SF90 XX}}
* J. Darasz, “The Skewed World of Jan Darasz,” Wilmott, vol. 2023, iss. 128, 2023.
[Bibtex] [Abstract]
Cartoon
@article{WILM:WILM1115898,title = {{The Skewed World of Jan Darasz}},author = {Darasz, Jan},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 128,doi = {10.54946/wilm.1115898},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.1115898},abstract = {Cartoon}}
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Volume 2023, Issue 127. Pages 1-96 Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here. In this issue: D. Tudball, “Contents,” Wilmott, vol. 2023, iss. 127, [...]
By Scott Sobolewski, Partner at Acadia What is ORE? Acadia has successfully supported the non-cleared derivatives market through regulatory compliance of all six phases of the global Uncleared Margin Rules and emerged as a key [...]
Harry Markowitz, the creator of modern portfolio theory, Nobel Laureate and John von Neumann Theory Prize winner passed on June 22, 2023. Who was Harry Markowitz and how did his mind work? John Guerard, having worked for, worked with, and co-authored papers for years with Harry Markowitz knows who he is. In Part II of this appreciation Dr Guerard discusses Markowitz’ academic career, his years as a consultant and entrepreneur, recognition, awards and his lasting impact on quantitative finance [...]
Harry Markowitz, the creator of modern portfolio theory, Nobel Laureate and John von Neumann Theory Prize winner passed on June 22, 2023. Who was Harry Markowitz and how did his mind work? John Guerard, having worked for, worked with, and co-authored papers for years with Harry Markowitz knows who he is. In Part I, Dr Guerard discusses Markowitz’ early career through to 1972 [...]
“My portfolio theory says you, the investor have to pick out a universe of stocks; it may not be stocks, it may be asset classes, and you can have very detailed asset classes, or you [...]
Volume 2023, Issue 126. Pages 1-108 THIS SPECIAL ISSUE IS ALSO AVAILABLE FOR SEPARATE PURCHASE Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here. In this [...]
https://wilmott.com/wp-content/uploads/2023/05/Introducing-The-CQF-Careers-Guide-2023.mp4The past few years have seen turbulent times for the global financial markets. Challenges include the COVID-19 pandemic, the war in the Ukraine, pressure on energy supplies in Europe, and rising inflation which has driven some central banks to raise interest rates dramatically. Throughout this period, quants have played an important role in shaping investing and hedging strategies to meet investors’ needs. In creating the CQF Careers Guide to Quantitative Finance 2023, we spoke to a number of recruiters who all stated that last year saw an increased demand for quants across the industry. Looking ahead, this demand is expected to continue across many functions within financial services.
Produced by the CQF Institute, the CQF Careers Guide to Quantitative Finance 2023 explores this increasing demand for quant skills and presents the typical roles and general salary ranges quants can currently earn in America, Asia, and Europe across six career paths:
- Portfolio Management
- Risk Management
- Quant Strategies and Research
- Data Science and Machine Learning
- Technology
- Quant Trading
For each of these paths, CQF alumni share further insights by describing a typical working day in their role from the moment they get to the office to the time they return home. This Guide features a typical working day for a Portfolio Manager, Market and Liquidity Risk Manager, Quant Advisor, Lead Data Scientist, Quant Developer, and a Quantitative Equity Trader.
The Guide also looks towards the future – according to a poll conducted at the Quant Insights Conference in November 2022, approximately 62% of respondents indicated that Data Science and Machine Learning would offer the greatest increase in career opportunities in 2023. An additional 17% felt that the greatest increase would come from quantum computing. For each of these areas, the Guide explores how these fields are becoming more prominent in the industry, the changing skills needed to succeed in these areas, and the new career opportunities that are starting to emerge as a result.
Reflecting on the release on the new Guide, Dr. Randeep Gug, Managing Director of the CQF and CQF Institute stated: “ As we celebrate the 20th Anniversary of the CQF program, we are delighted to present the CQF Careers Guide to Quantitative Finance 2023 to support your journey through the world of quant finance, with real-world alumni stories to showcase the various roles within the field and guidance on how you can gain the skills you need for a successful career in the future.”
Find out more about careers in quantitative finance today. Download the full CQF Careers Guide here.
About the CQF
The Certificate in Quantitative Finance (CQF) is awarded by the CQF Institute and delivered online by Fitch Learning. The program is focused on teaching the essential skills used by quant practitioners in today’s financial markets. The curriculum is updated quarterly in consultation with faculty and senior alumni to ensure that the skills taught in the program are meeting industry demand. Following their graduation, all CQF alumni are given permanent access to the CQF Lifelong Learning library to help them keep their skills competitive throughout their careers. They also have access to the alumni Career Services, which includes regular job posting communications, CV advice, and more.
The CQF Institute, Fitch Learning, and Wilmott are excited to announce that registrations are now open for the June 2023 Quant Insights Conference, which will celebrate the 50th anniversary of the Black-Scholes model. Join your fellow quants for an exclusive, online conference packed with world-leading experts and discussions, virtual networking opportunities, and more.
Free for members of the CQF Institute
Event DetailsDate: Wednesday, 14th June 2023
Time: 09:00 – 15:30 EDT
Location: Online
Tickets: Free for CQF Institute Members
Speakers confirmed so far:Dr. Paul Wilmott, Founder, Certificate in Quantitative Finance (CQF)
Dr. Robert Litterman, Founder, Kepos Capital
Professor Emanuel Derman, Professor of Financial Engineering, Columbia University
Dr. Ilia Bouchauev, Managing Partner, Pentathlon Investments
Professor Laura Ballotta, Professor of Mathematical Finance, Bayes Business School
Professor Jessica James, Senior Quantitative Researcher, Commerzbank
Dr. David Orrell, Principal, Systems Forecasting
Dr. Jörg Kienitz, Partner, Acadia
Dr. Randeep Gug, Managing Director, CQF Institute
Sponsors:Acadia
Acadia is a leading industry provider of integrated risk management services for the derivatives community. Our risk, margin and collateral tools enable a holistic risk management strategy on a real-time basis within a centralized industry standard platform.
Acadia’s comprehensive suite of analytics solutions and services helps firms manage risk better, smarter, and faster, while optimizing resources across the entire trade life cycle. Through an open-access model, Acadia brings together a network of banks and other derivatives participants, along with several market infrastructures and innovative vendors.
Acadia is used by a community of over 3,000 firms exchanging more than $1 trillion of collateral on daily basis via its margin automation services. Acadia is headquartered in Norwell, MA and has offices in Boston, Dublin, Dusseldorf, London, New York, Manila, and Tokyo. Acadia® is a registered trademark of AcadiaSoft, Inc.
Acadia is an LSEG Business within the Post Trade division. For more information, visit acadia.inc. Follow us on Twitter and LinkedIn
Capital Market Development Fund (CMDF)
Founded in 2019, the Capital Market Development Fund (CMDF) is a development fund organization in Thailand. It was established to promote the sustainable growth and development of Thailand’s capital market, across industries. The CMDF prioritizes improving and developing human capital skills and talent, investments, and capital market development. One of the statutory objectives of the CMDF is to promote and encourage the development of human resources and supervision of the capital markets.
Volume 2023, Issue 125. Pages 1-96
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In this issue:* D. Tudball, “Contents,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Contents
@article{WILM:WILM11116,title = {{Contents}},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11116},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11116},abstract = {Contents}}
* D. Tudball, ,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex]
@article{WILM:WILM11117,title = {{}},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11117},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11117},abstract = {}}
* A. Brown, “The Hunting of the Snark,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
For people who want to understand what zk-SNARKs are, why they are important, how to use them safely, and what the future might hold; without unnecessary technical detail.
@article{WILM:WILM11118,title = {{The Hunting of the Snark}},author = {Brown, Aaron},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11118},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11118},abstract = {For people who want to understand what zk-SNARKs are, why they are important, how to use them safely, and what the future might hold; without unnecessary technical detail.}}
* R. Poulsen, “We Hold These Truths not to be Self-evident, Part 3: Mission Impossible?,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
In Math, you can prove a negative. Let’s take a look at some mostly model based examples.
@article{WILM:WILM11119,title = {{We Hold These Truths not to be Self-evident, Part 3: Mission Impossible?}},author = {Poulsen, Rolf},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11119},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11119},abstract = {In Math, you can prove a negative. Let’s take a look at some mostly model based examples.}}
* G. Giller, “Yes, Quants Should Care about Money Left on the Table,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
What if, in some way, we had access to some counterfactual measure of how well wecould have done with our trading?
@article{WILM:WILM11120,title = {{Yes, Quants Should Care about Money Left on the Table}},author = {Giller, Graham},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11120},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11120},abstract = {What if, in some way, we had access to some counterfactual measure of how well wecould have done with our trading?}}
* S. Das, “Alice Through The Crypto Glass: Part 4 ,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Bringing this series to a close, the author considers potential applications of blockchain technology.
@article{WILM:WILM11121,title = {{Alice Through The Crypto Glass: Part 4 }},author = {Das, Satyajit},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11121},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11121},abstract = {Bringing this series to a close, the author considers potential applications of blockchain technology.}}
* P. Balan, “Designing Banking Book balance forecasting models to support multiple use cases Part II,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
In this article, we discuss the design framework for a single model for a portfolio of similar Banking Book products shared across all use cases requiring balance or associated forecasts in detail.
@article{WILM:WILM11122,title = {{Designing Banking Book balance forecasting models to support multiple use cases Part II}},author = {Balan, Priya},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11122},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11122},abstract = {In this article, we discuss the design framework for a single model for a portfolio of similar Banking Book products shared across all use cases requiring balance or associated forecasts in detail.}}
* M. Kelly, “Financial Time Series,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
In this article, we will focus on the time series data which is the basis of all financial analysis, and which can be encapsulated with the functions TimeSeries, for single series, and TemporalData, for a collection of time series.
@article{WILM:WILM11123,title = {{Financial Time Series}},author = {Kelly, Michael},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11123},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11123},abstract = {In this article, we will focus on the time series data which is the basis of all financial analysis, and which can be encapsulated with the functions TimeSeries, for single series, and TemporalData, for a collection of time series.}}
* D. Tudball, “Black Scholes 50th Anniversary,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
How time flies when you are making money
@article{WILM:WILM11124,title = {{Black Scholes 50th Anniversary}},author = {Tudball, Dan},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11124},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11124},abstract = {How time flies when you are making money}}
* P. Wilmott, “The Marketing Department’s Derivation of Black-Scholes-Merton: An alternative history from a parallel universe,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
There are many derivations of the Black-Scholes-Merton partial differential equation and formulæ for the value of derivatives. Some are easy to understand, some are not. Some are easy to generalize, some are not. But to my knowledge only one derivation comes from a collaboration between someone wearing a fine pair of Crockett & Jones, and the other definitely not.
@article{WILM:WILM11125,title = {{The Marketing Department's Derivation of Black-Scholes-Merton: An alternative history from a parallel universe}},author = {Wilmott, Paul},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11125},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11125},abstract = {There are many derivations of the Black-Scholes-Merton partial differential equation and formulæ for the value of derivatives. Some are easy to understand, some are not. Some are easy to generalize, some are not. But to my knowledge only one derivation comes from a collaboration between someone wearing a fine pair of Crockett & Jones, and the other definitely not.}}
* P. Boyle, “How Black Scholes changed my life,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Why the option model became the dominant paradigm of the author’s career.
@article{WILM:WILM11126,title = {{How Black Scholes changed my life}},author = {Boyle, Phelim},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11126},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11126},abstract = {Why the option model became the dominant paradigm of the author’s career.}}
* A. Lewis, “The limit where Black-Scholes “works”,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
The seminal (Black and Scholes, 1973) publication celebrated in this issue introduced a (stock price evolution) model and an (option value) formula—two ideas worth distinguishing. Nowadays, the formula is used to represent option prices via an implied volatility, IV (T, K), where T is a time-to-maturity and K is a strike price. The formula is very useful. At the same time, because of the K-dependence, the model is strongly rejected in statistical tests. However, with T very large at fixed K, IV (T, K) typically flattens IV(T,K)→ σ∞imp , where σ∞imp is independent of K. Flattening happens both with real data and many (more complicated) models. At fixed strike, the implied volatility parameter tends to a pure constant. But a constant volatility returns us to the original BS model in a sense. As somewhat of an abuse, I say that in the limit, the BS model again works”. What is this mysterious σ∞imp and how do we compute it? How is the limit approached? Answering those questions is the subject of this note. While my approach is largely expository, results for non- standard cases in the Heston model are likely novel. Their analysis requires a generalized saddle point method.
@article{WILM:WILM11127,title = {{The limit where Black-Scholes "works"}},author = {Lewis, Alan},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11127},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11127},abstract = {The seminal (Black and Scholes, 1973) publication celebrated in this issue introduced a (stock price evolution) model and an (option value) formula—two ideas worth distinguishing. Nowadays, the formula is used to represent option prices via an implied volatility, IV (T, K), where T is a time-to-maturity and K is a strike price. The formula is very useful. At the same time, because of the K-dependence, the model is strongly rejected in statistical tests. However, with T very large at fixed K, IV (T, K) typically flattens IV(T,K)→ σ∞imp , where σ∞imp is independent of K. Flattening happens both with real data and many (more complicated) models. At fixed strike, the implied volatility parameter tends to a pure constant. But a constant volatility returns us to the original BS model in a sense. As somewhat of an abuse, I say that in the limit, the BS model again works”. What is this mysterious σ∞imp and how do we compute it? How is the limit approached? Answering those questions is the subject of this note. While my approach is largely expository, results for non- standard cases in the Heston model are likely novel. Their analysis requires a generalized saddle point method.}}
* J. Hull, “Why Has Black-Scholes-Merton Been So Successful? ,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
It is not because the model is a really good description of the way options are priced by the market.
@article{WILM:WILM11128,title = {{Why Has Black-Scholes-Merton Been So Successful? }},author = {Hull, John},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11128},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11128},abstract = {It is not because the model is a really good description of the way options are priced by the market.}}
* A. Lipton and A. Reghai, “SPX, VIX and scale-invariant LSV∗,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Local Stochastic Volatility (LSV) models have been used for pricing and hedging derivatives positions for over 20 years. An enormous body of literature covers analytical and numerical techniques for calibrating the m model to market data. However, the literature misses a potent approach commonly used in physics and works with absolute (dimensional) variables rather than with relative (nondimensional) ones. While model parameters defined in absolute terms are counter-intuitive for trading desks and tend to be heavily time-dependent, relative parameters are intuitive and stable, making it easy to steer the model adequately and consistently with its Profit and Loss (PnL) explanation power. We propose a specification that first explores historical data and uses physically well-defined relative quantities to design the model. We then develop an efficient hybrid method to price derivatives under this specification. We also show how our method can be used for robust scenario generation purposes—an important risk management task vital for buy-side firms.
@article{WILM:WILM11129,title = {{SPX, VIX and scale-invariant LSV∗}},author = {Lipton, Alexander and Reghai, Adil},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11129},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11129},abstract = {Local Stochastic Volatility (LSV) models have been used for pricing and hedging derivatives positions for over 20 years. An enormous body of literature covers analytical and numerical techniques for calibrating the m model to market data. However, the literature misses a potent approach commonly used in physics and works with absolute (dimensional) variables rather than with relative (nondimensional) ones. While model parameters defined in absolute terms are counter-intuitive for trading desks and tend to be heavily time-dependent, relative parameters are intuitive and stable, making it easy to steer the model adequately and consistently with its Profit and Loss (PnL) explanation power. We propose a specification that first explores historical data and uses physically well-defined relative quantities to design the model. We then develop an efficient hybrid method to price derivatives under this specification. We also show how our method can be used for robust scenario generation purposes—an important risk management task vital for buy-side firms.}}
* J. Bouchaud, “Welcome to a post Black-Scholes World,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Black-Scholes is simultaneously extraordinarily important and woefully flawed.
@article{WILM:WILM11130,title = {{Welcome to a post Black-Scholes World}},author = {Bouchaud, Jean-Philippe},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11130},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11130},abstract = {Black-Scholes is simultaneously extraordinarily important and woefully flawed.}}
* D. Gatarek, “The principle of two models: the cases of Black-Scholes formula for interest rates and of Gaussian copula for credit ,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
In this article, I try to show that a given market segment needs at least two models: one as a pricing convention and one to run the portfolio of securities. These models should be related in such a way that the model to manage the books is an extension of the pricing convention. Financial modeling succeeded in the case of options, but it failed with the CDOs, resulting in the credit crunch.
@article{WILM:WILM11131,title = {{The principle of two models: the cases of Black-Scholes formula for interest rates and of Gaussian copula for credit }},author = {Gatarek, Dariusz},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11131},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11131},abstract = {In this article, I try to show that a given market segment needs at least two models: one as a pricing convention and one to run the portfolio of securities. These models should be related in such a way that the model to manage the books is an extension of the pricing convention. Financial modeling succeeded in the case of options, but it failed with the CDOs, resulting in the credit crunch.}}
* W. Schoutens, “A contemporary view on the golden anniversary of the celebrated Black-Scholes-Merton model,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Luckily, in 1973, normality was normal.
@article{WILM:WILM11132,title = {{A contemporary view on the golden anniversary of the celebrated Black-Scholes-Merton model}},author = {Schoutens, Wim},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11132},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11132},abstract = {Luckily, in 1973, normality was normal.}}
* J. Andreasen, “Holes in Black-Scholes?,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
In this article, we provide a model-free test for whether the dynamic hedging argument actually works in practice and a quantification of how much jumps influence the delta hedge.
@article{WILM:WILM11133,title = {{Holes in Black-Scholes?}},author = {Andreasen, Jesper},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11133},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11133},abstract = {In this article, we provide a model-free test for whether the dynamic hedging argument actually works in practice and a quantification of how much jumps influence the delta hedge.}}
* C. Alexander, “Can you Beat Black-Scholes at Delta Hedging?,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Not a bad question given Black-Scholes assumes zero correlation between underlying price and volatility, the consequence of which is an entirely flat volatility surface.
@article{WILM:WILM11134,title = {{Can you Beat Black-Scholes at Delta Hedging?}},author = {Alexander, Carol},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11134},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11134},abstract = {Not a bad question given Black-Scholes assumes zero correlation between underlying price and volatility, the consequence of which is an entirely flat volatility surface.}}
* L. Ballabio, “The Black-Scholes Model in QuantLib,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Any remaining errors are our fault, not theirs.
@article{WILM:WILM11135,title = {{The Black-Scholes Model in QuantLib}},author = {Ballabio, Luigi},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11135},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11135},abstract = {Any remaining errors are our fault, not theirs.}}
* U. Wystup, “Quick and Dirty – Short Cuts for Option Lovers,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Highlighting a few shortcuts in option pricing, in the spirit of sanity checks, quick answers, and passing interview questions.
@article{WILM:WILM11136,title = {{Quick and Dirty – Short Cuts for Option Lovers}},author = {Wystup, Uwe},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11136},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11136},abstract = {Highlighting a few shortcuts in option pricing, in the spirit of sanity checks, quick answers, and passing interview questions.}}
* M. Radley, “Quick Charge,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Rimac Nevera/Honda Civic Type R
@article{WILM:WILM11137,title = {{Quick Charge}},author = {Radley, Milford},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11137},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11137},abstract = {Rimac Nevera/Honda Civic Type R}}
* J. Darasz, “The Skewed World of Jan Darasz,” Wilmott, vol. 2023, iss. 125, 2023.
[Bibtex] [Abstract]
Cartoon
@article{WILM:WILM11138,title = {{The Skewed World of Jan Darasz}},author = {Darasz, Jan},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 125,doi = {10.54946/wilm.11138},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11138},abstract = {Cartoon}}
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In 2003, Dr. Paul Wilmott set out to bridge the gap between academia and industry by creating a professional qualification that focused on teaching practical quant finance techniques, rather than just theoretical concepts. This led to the creation of the Certificate in Quantitative Finance (CQF), a program designed to equip professionals with essential quant finance and machine learning skills.
Fast forward 20 years and the CQF has gained widespread recognition as the industry benchmark qualification in financial engineering, with a faculty of renowned quant practitioners teaching the latest techniques used in the industry. Over the past two decades, the CQF has attracted over 8,000 professionals from over 90 countries and more than 900 firms globally have sponsored their employees on the program.
Reflecting on the growth of the CQF and CQF Institute, Managing Director, Dr. Randeep Gug, stated: “The CQF has always been about empowering financial professionals to transform their careers. Our focus on practical skills, combined with a cutting-edge syllabus, has made the program the preferred choice for professionals looking to upskill. The continued support and recognition from leading quants across the industry and the positive impact the program has had on our alumni’s careers are highlights of the past 20 years.”
The success of the CQF can be attributed to a number of factors, including its flexible and accessible delivery, practical syllabus, expert faculty, and dedicated alumni community. Delivered online and on a part-time basis, the CQF is designed to meet the needs of busy professionals who want to upskill without sacrificing their full-time employment. The program is updated regularly in consultation with senior alumni and faculty to ensure that it stays relevant and responsive to the evolving needs of the industry. Delegates are taught by practitioners who use real-life examples to bring their lessons to life, giving them the knowledge and confidence needed to apply their new skills on the job.
In addition to its practical curriculum, the CQF also provides delegates with permanent access to the latest full CQF syllabus, masterclasses, and talks through the Lifelong Learning library. This helps to ensure that the skills they have acquired remain competitive throughout their careers. To celebrate the 20th anniversary, the CQF will be releasing an updated version of its Lifelong Learning platform later this year. The updated platform will offer even more user-friendly content, including over 900 hours of material to help alumni stay ahead of the curve.
Another key milestone has been the growth of the CQF Institute, the awarding body of the CQF, which now has more than 20,000 members worldwide and attracts speakers at the forefront of the industry. For example, at the recent Quant Insights Conferences, delegates have had the opportunity to hear from Nobel Laureates like Dr. Harry Markowitz and Professor Robert Engle, as well as other industry luminaries like Dr. Aaron Brown, Professor Bob Litterman, Professor Carol Alexander, and Dr. Jean-Philippe Bouchaud.
“The future of finance is changing rapidly and the CQF and CQF Institute are committed to keeping pace with these changes,” says Dr. Randeep Gug. “We will continue to partner with our alumni and offer them the support and resources they need to succeed in their careers. The CQF and CQF Institute will always be at the forefront of financial education, delivering the skills and knowledge that financial professionals need to succeed in the 21st century.”
Find out more about the CQFTo find out more about the CQF program, download a brochure or register now to join the next online information session with CQF Managing Director, Dr. Randeep Gug.
Certificate in Quantitative Finance (CQF)Founded by Dr Paul Wilmott and delivered by Fitch Learning, the Certificate in Quantitative Finance (CQF) is the world’s largest professional qualification in quantitative finance with more than 8000 alumni and delegates in over 90 countries. The CQF program is designed to transform careers by equipping professionals with essential quant finance and machine learning skills.
Over the past 20 years, the CQF has become the industry benchmark for professional qualifications in quantitative finance and is highly regarded by employers around the globe.
Who is it for:• Professionals who want to progress in their careers• Companies looking to upskill and retain employees technologiesWhy choose the CQF Program:• Can be studied part-time over 6 months• Has an immediate impact on careers and company productivity• Focused on real-world financial engineering taught by industry practitioners• Comprises a practical curriculum based on the industry demands• Delivered via flexible online learning• Gain permanent access to the Lifelong Learning library for CQF alumniThe next CQF program starts on 26th January 2023.
Learn more about the CQF and find out how you can benefit from the program.
Visit the CQF website to find out more
The CQF InstituteAbout the InstituteThe CQF Institute is a thriving membership community for quant finance professionals across the globe, where you can connect with your peers, enhance your skills and professional development, and gain access to expert quant finance knowledge.
Why become a CQFI member?The CQF Institute is a thriving membership community for quant finance professionals across the globe, where you can connect with your peers, enhance your skills and professional development, and gain access to expert quant finance knowledge.
Become a member and gain access to exclusive benefits:• Community: Be part of a global network of quant professionals• Events: Attend global and regional industry talks and career talks, and the Quant Insights Conferences• Educational Resources: Access educational resources featured on the CQFI website• Local Societies: Join Societies for local networking opportunities.Join the CQF Institute and get access to member-only resources and networking opportunities.
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Hello, and thanks for looking at this new feature of Wilmott Magazine.
Why don’t I skip the usual introductions — we can circle back to that later — and show you some code instead? Let’s see if you find something interesting in it. The full listing is in its own box; its comments
correspond to the subheadings of this column, so you can find your way around the code as I describe it. I’ll try to keep this a quick tour and show the forest rather than the trees; so I’ll gloss over, or completely
ignore, a lot of details. Here we go.
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Volume 2023, Issue 124. Pages 1-96
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In this issue:* D. Tudball, “Contents,” Wilmott, vol. 2023, iss. 124, p. 1–1, 2023.
[Bibtex] [Abstract]
Contents
@article{WILM:WILM11095,title = {{Contents}},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {1--1},doi = {10.54946/wilm.11095},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11095},abstract = {Contents}}
* D. Tudball, “I Stand At Your Gate …,” Wilmott, vol. 2023, iss. 124, p. 2–3, 2023.
[Bibtex]
@article{WILM:WILM11096,title = {{I Stand At Your Gate …}},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {2--3},doi = {10.54946/wilm.11096},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11096},abstract = {}}
* D. Tudball, “News,” Wilmott, vol. 2023, iss. 124, p. 4–5, 2023.
[Bibtex] [Abstract]
News
@article{WILM:WILM11097,title = {{News}},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {4--5},doi = {10.54946/wilm.11097},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11097},abstract = {News}}
* A. Brown, “The Establishment Clause,” Wilmott, vol. 2023, iss. 124, p. 6–12, 2023.
[Bibtex] [Abstract]
Why have quantitative football analysts mostly dismissed the concept of establishing the run despite strong statistical support for it, and near universal acceptance among coaches?
@article{WILM:WILM11098,title = {{The Establishment Clause}},author = {Brown, Aaron},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {6--12},doi = {10.54946/wilm.11098},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11098},abstract = {Why have quantitative football analysts mostly dismissed the concept of establishing the run despite strong statistical support for it, and near universal acceptance among coaches?}}
* R. Poulsen, “We Hold These Truths not to be Self-evident, Part 2: Strong and simple,” Wilmott, vol. 2023, iss. 124, p. 14–15, 2023.
[Bibtex] [Abstract]
Continuing with non-self-evident results from quantitative finance. After a short detour into Russian 19th century literature, we look at some of my favorite examples of simple arguments with strong consequences: Carry, parity, convexity, and sufficiency.
@article{WILM:WILM11099,title = {{We Hold These Truths not to be Self-evident, Part 2: Strong and simple}},author = {Poulsen, Rolf},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {14--15},doi = {10.54946/wilm.11099},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11099},abstract = {Continuing with non-self-evident results from quantitative finance. After a short detour into Russian 19th century literature, we look at some of my favorite examples of simple arguments with strong consequences: Carry, parity, convexity, and sufficiency.}}
* U. Wystup, “The Salzburg Financial Scandal ,” Wilmott, vol. 2023, iss. 124, p. 16–17, 2023.
[Bibtex] [Abstract]
When Imprisonment Depends on the Value of a Structured Interest Rate Swap
@article{WILM:WILM11100,title = {{The Salzburg Financial Scandal }},author = {Wystup, Uwe},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {16--17},doi = {10.54946/wilm.11100},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11100},abstract = {When Imprisonment Depends on the Value of a Structured Interest Rate Swap}}
* A. Kumiega, G. Sterijevski, and B. Van Vliet, “Synchronizing decisions: A dynamic programming, real option framework for New Product Development with stage-to-stage correlations,” Wilmott, vol. 2023, iss. 124, p. 18–26, 2023.
[Bibtex] [Abstract]
Much research has investigated the application of real options to staged, new product development projects. Still, this literature has not addressed an important intuition—that bad projects may stay bad. A new product development project or a technology startup backed venture capital may include stage-to-stage dependencies. Its “state” at one gate may influence the transition probabilities at later gates. We develop a novel real option model that captures this intuition using dynamic programming and serial correlations. In a subsequent paper, we introduce partial derivatives similar to the Greeks that we named “control maps”. These control maps will assist the firm’s management to assess the financial impact of resource reallocations to project success factors. Such reallocations have the intent of turning bad projects into good ones. Thus, the proposed framework enables management to synchronize its management decision with financial ones.
@article{WILM:WILM11101,title = {{Synchronizing decisions: A dynamic programming, real option framework for New Product Development with stage-to-stage correlations}},author = {Kumiega, Andrew and Sterijevski, Greg and Van Vliet, Ben},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {18--26},doi = {10.54946/wilm.11101},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11101},abstract = {Much research has investigated the application of real options to staged, new product development projects. Still, this literature has not addressed an important intuition—that bad projects may stay bad. A new product development project or a technology startup backed venture capital may include stage-to-stage dependencies. Its “state” at one gate may influence the transition probabilities at later gates. We develop a novel real option model that captures this intuition using dynamic programming and serial correlations. In a subsequent paper, we introduce partial derivatives similar to the Greeks that we named “control maps”. These control maps will assist the firm’s management to assess the financial impact of resource reallocations to project success factors. Such reallocations have the intent of turning bad projects into good ones. Thus, the proposed framework enables management to synchronize its management decision with financial ones.}}
* R. Bogni, “On Memory,” Wilmott, vol. 2023, iss. 124, p. 28–29, 2023.
[Bibtex] [Abstract]
On Memory, Impostor Syndrome and Investing.
@article{WILM:WILM11102,title = {{On Memory}},author = {Bogni, Rudi},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {28--29},doi = {10.54946/wilm.11102},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11102},abstract = {On Memory, Impostor Syndrome and Investing.}}
* C. Alexander, “Crypto Risks to Watch in 2023 ,” Wilmott, vol. 2023, iss. 124, p. 30–33, 2023.
[Bibtex] [Abstract]
Most financial risks originate in mismanaged, misunderstood or fraudulent operations.
@article{WILM:WILM11103,title = {{Crypto Risks to Watch in 2023 }},author = {Alexander, Carol},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {30--33},doi = {10.54946/wilm.11103},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11103},abstract = {Most financial risks originate in mismanaged, misunderstood or fraudulent operations.}}
* J. Andreasen, “Fun with Finite Difference,” Wilmott, vol. 2023, iss. 124, p. 34–40, 2023.
[Bibtex] [Abstract]
We summarize most of what you need to know about finite difference solution for one-dimensional partial differential equations in finance. We demonstrate the theoretical results by numerical experiments. The reader is invited and encouraged to replicate the experiments using the C++ code and spreadsheets in our GitHub repository.
@article{WILM:WILM11104,title = {{Fun with Finite Difference}},author = {Andreasen, Jesper},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {34--40},doi = {10.54946/wilm.11104},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11104},abstract = {We summarize most of what you need to know about finite difference solution for one-dimensional partial differential equations in finance. We demonstrate the theoretical results by numerical experiments. The reader is invited and encouraged to replicate the experiments using the C++ code and spreadsheets in our GitHub repository.}}
* G. Giller, “When Building Alphas, Should we Do the Right Thing?,” Wilmott, vol. 2023, iss. 124, p. 42–46, 2023.
[Bibtex] [Abstract]
: Taking a closer look at the idea that taking proper account of the evident complexity of realistic descriptions of financial markets doesn’t have a practical effect
@article{WILM:WILM11105,title = {{When Building Alphas, Should we Do the Right Thing?}},author = {Giller, Graham},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {42--46},doi = {10.54946/wilm.11105},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11105},abstract = {: Taking a closer look at the idea that taking proper account of the evident complexity of realistic descriptions of financial markets doesn’t have a practical effect}}
* L. Ballabio, “Handling dependencies in QuantLib,” Wilmott, vol. 2023, iss. 124, p. 48–51, 2023.
[Bibtex] [Abstract]
On pointer semantics, wrapper classes and migrations
@article{WILM:WILM11106,title = {{Handling dependencies in QuantLib}},author = {Ballabio, Luigi},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {48--51},doi = {10.54946/wilm.11106},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11106},abstract = {On pointer semantics, wrapper classes and migrations}}
* Wolfram, “Financial Derivatives,” Wilmott, vol. 2023, iss. 124, p. 52–56, 2023.
[Bibtex] [Abstract]
Dr Michael Kelly puts Mathematica to work deriving the mathematical and numerical results for option prices by solving PDEs, SDEs using the discounted expectation of stochastic variables and simulations of underlying expiry prices, as well as discovering the risk-neutral value of the rate of return and establishing theorems such as the Put-Call parity formula
@article{WILM:WILM11107,title = {{Financial Derivatives}},author = {Wolfram},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {52--56},doi = {10.54946/wilm.11107},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11107},abstract = {Dr Michael Kelly puts Mathematica to work deriving the mathematical and numerical results for option prices by solving PDEs, SDEs using the discounted expectation of stochastic variables and simulations of underlying expiry prices, as well as discovering the risk-neutral value of the rate of return and establishing theorems such as the Put-Call parity formula}}
* D. Orrell and L. Richards, “Keep on smiling: Market imbalance, option pricing, and the volatility smile,” Wilmott, vol. 2023, iss. 124, p. 58–64, 2023.
[Bibtex] [Abstract]
This article argues that the volatility smile is “real” in the sense that volatility and price change are correlated through the degree of market imbalance.
@article{WILM:WILM11108,title = {{Keep on smiling: Market imbalance, option pricing, and the volatility smile}},author = {Orrell, David and Richards, Larry},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {58--64},doi = {10.54946/wilm.11108},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11108},abstract = {This article argues that the volatility smile is “real” in the sense that volatility and price change are correlated through the degree of market imbalance.}}
* P. Balan, “Designing Banking Book balance forecasting models to support multiple use cases,” Wilmott, vol. 2023, iss. 124, p. 66–69, 2023.
[Bibtex] [Abstract]
In this introductory article we discuss, in the context of a few key usage areas, why fine-tuning models to the needs of each can introduce inconsistencies and hard to detect errors into reporting and decision making
@article{WILM:WILM11109,title = {{Designing Banking Book balance forecasting models to support multiple use cases}},author = {Balan, Priya},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {66--69},doi = {10.54946/wilm.11109},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11109},abstract = {In this introductory article we discuss, in the context of a few key usage areas, why fine-tuning models to the needs of each can introduce inconsistencies and hard to detect errors into reporting and decision making}}
* L. Ballotta, “Demystifying generic beliefs on jump models,” Wilmott, vol. 2023, iss. 124, p. 70–73, 2023.
[Bibtex] [Abstract]
Despite a history of convincing results, jump-based models are often met by skepticism. Typical criticisms include limited tractability, incomplete markets and associations with market crashes. Are these beliefs valid?
@article{WILM:WILM11110,title = {{Demystifying generic beliefs on jump models}},author = {Ballotta, Laura},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {70--73},doi = {10.54946/wilm.11110},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11110},abstract = {Despite a history of convincing results, jump-based models are often met by skepticism. Typical criticisms include limited tractability, incomplete markets and associations with market crashes. Are these beliefs valid?}}
* R. Ziemba, “Finding an Edge: Lessons from the Work of William T Ziemba,” Wilmott, vol. 2023, iss. 124, p. 74–76, 2023.
[Bibtex] [Abstract]
William T Ziemba, known as Dr Z, has been a contributor to Wilmott Magazine since its inception 20 years ago and a major player in the field. He passed away in June 2022. This column, written by his daughter Rachel Ziemba, a political economist, market strategist and occasional collaborator, pays tribute to some of his contributions to the field and to related areas of investment research. It draws on and extends some of the work presented at the November 2022 Quantitative Finance Conference and on work previously presented in this magazine.
@article{WILM:WILM11111,title = {{Finding an Edge: Lessons from the Work of William T Ziemba}},author = {Ziemba, Rachel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {74--76},doi = {10.54946/wilm.11111},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11111},abstract = {William T Ziemba, known as Dr Z, has been a contributor to Wilmott Magazine since its inception 20 years ago and a major player in the field. He passed away in June 2022. This column, written by his daughter Rachel Ziemba, a political economist, market strategist and occasional collaborator, pays tribute to some of his contributions to the field and to related areas of investment research. It draws on and extends some of the work presented at the November 2022 Quantitative Finance Conference and on work previously presented in this magazine.}}
* C. Huber, “Asset Allocation Hands-On, with Examples in R,” Wilmott, vol. 2023, iss. 124, p. 78–87, 2023.
[Bibtex] [Abstract]
This paper suggests a framework for building an Asset Allocation tool and comes with about 300 lines of R code that implements its building blocks, which are calculation of Excess Returns including FX effects, as well as FX Forward Hedging, Optimization and Risk Decomposition. It draws on data from public sources and references the R code in the relevant passages of the text. All data and the R code are available for download. Four use cases are discussed: 1) drawing Efficient Frontiers based on different risk measures, like standard deviation or Expected Tail Loss; 2) studying the impact of varying FX Forward Hedge Ratios; 3) changing the Base Currency; and 4) Risk Decomposition. The examples are chosen with a view on practical implementation, reproducibility, and self-study.
@article{WILM:WILM11112,title = {{Asset Allocation Hands-On, with Examples in R}},author = {Huber, Claus},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {78--87},doi = {10.54946/wilm.11112},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11112},abstract = {This paper suggests a framework for building an Asset Allocation tool and comes with about 300 lines of R code that implements its building blocks, which are calculation of Excess Returns including FX effects, as well as FX Forward Hedging, Optimization and Risk Decomposition. It draws on data from public sources and references the R code in the relevant passages of the text. All data and the R code are available for download. Four use cases are discussed: 1) drawing Efficient Frontiers based on different risk measures, like standard deviation or Expected Tail Loss; 2) studying the impact of varying FX Forward Hedge Ratios; 3) changing the Base Currency; and 4) Risk Decomposition. The examples are chosen with a view on practical implementation, reproducibility, and self-study.}}
* M. Arnsdorf, “The Two KVAs,” Wilmott, vol. 2023, iss. 124, p. 88–93, 2023.
[Bibtex] [Abstract]
The capital valuation adjustment (KVA) is one of the more recent additions to the XVA family. In this article, we examine two key questions surrounding KVA: What is the correct return on equity (RoE) that should be assigned to a derivatives portfolio and what impact should changes in a firm’s equity capital levels or leverage have on valuation? Addressing these questions leads naturally to the definition of two distinct valuation adjustments we refer to as KVA1 and KVA2. KVA1 is a reflection of unpriced risk which can be present in incomplete markets. At the firm level it is proportional to the RoE but insensitive to changes in leverage. KVA2 on the other hand represents the shareholder cost of changes in leverage and is proportional to capital levels. However, the effective rate on the capital is the form’s junior funding rate and not the RoE. This article is a high-level summary of two more detailed recent papers by the author.
@article{WILM:WILM11113,title = {{The Two KVAs}},author = {Arnsdorf, Matthias},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {88--93},doi = {10.54946/wilm.11113},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11113},abstract = {The capital valuation adjustment (KVA) is one of the more recent additions to the XVA family. In this article, we examine two key questions surrounding KVA: What is the correct return on equity (RoE) that should be assigned to a derivatives portfolio and what impact should changes in a firm's equity capital levels or leverage have on valuation? Addressing these questions leads naturally to the definition of two distinct valuation adjustments we refer to as KVA1 and KVA2. KVA1 is a reflection of unpriced risk which can be present in incomplete markets. At the firm level it is proportional to the RoE but insensitive to changes in leverage. KVA2 on the other hand represents the shareholder cost of changes in leverage and is proportional to capital levels. However, the effective rate on the capital is the form's junior funding rate and not the RoE. This article is a high-level summary of two more detailed recent papers by the author.}}
* M. Radley, “Four Tune/Live Wire,” Wilmott, vol. 2023, iss. 124, p. 94–95, 2023.
[Bibtex] [Abstract]
BMW launches its most pared-back M4 in the shape of the limited edition M4 CSL
@article{WILM:WILM11114,title = {{Four Tune/Live Wire}},author = {Radley, Milford},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {94--95},doi = {10.54946/wilm.11114},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11114},abstract = {BMW launches its most pared-back M4 in the shape of the limited edition M4 CSL}}
* J. Darasz, “The Skewed World of Jan Darasz,” Wilmott, vol. 2023, iss. 124, p. 96–96, 2023.
[Bibtex] [Abstract]
Cartoon
@article{WILM:WILM11115,title = {{The Skewed World of Jan Darasz}},author = {Darasz, Jan},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 124,pages = {96--96},doi = {10.54946/wilm.11115},issn = {1541-8286},url = {http://dx.doi.org/10.54946/wilm.11115},abstract = {Cartoon}}
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Volume 2023, Issue 123. Pages 1-84
Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here.
In this issue:* D. Tudball, “Contents,” Wilmott, vol. 2023, iss. 123, p. 1–1, 2023.
[Bibtex] [Abstract]
Contents
@article{WILM:WILM11079,title = {Contents},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {1--1},doi = {10.1002/wilm.11079},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11079},abstract = {Contents}}
* D. Tudball, “Somethin’s gotta give,” Wilmott, vol. 2023, iss. 123, p. 2–3, 2023.
[Bibtex]
@article{WILM:WILM11080,title = {Somethin’s Gotta Give},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {2--3},doi = {10.1002/wilm.11080},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11080},abstract = {}}
* D. Tudball, “News,” Wilmott, vol. 2023, iss. 123, p. 4–4, 2023.
[Bibtex] [Abstract]
News
@article{WILM:WILM11081,title = {News},author = {Tudball, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {4--4},doi = {10.1002/wilm.11081},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11081},abstract = {News}}
* A. Brown, “Five and dime,” Wilmott, vol. 2023, iss. 123, p. 6–9, 2023.
[Bibtex] [Abstract]
Aaron Brown takes us on a trip to the transition zone between Mediocristan and Extremistan. Don’t forget your baseball bat!
@article{WILM:WILM11082,title = {Five and Dime},author = {Brown, Aaron},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {6--9},doi = {10.1002/wilm.11082},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11082},abstract = {Aaron Brown takes us on a trip to the transition zone between Mediocristan and Extremistan. Don’t forget your baseball bat!}}
* R. Poulsen, “We hold these truths not to be self-evident, part 1: two wrongs making a right,” Wilmott, vol. 2023, iss. 123, p. 10–11, 2023.
[Bibtex] [Abstract]
Risk-neutral pricing, swap valuation, and the Black-Scholes call option Delta.
@article{WILM:WILM11083,title = {We Hold These Truths not to be Self-evident, Part 1: Two Wrongs Making a Right},author = {Poulsen, Rolf},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {10--11},doi = {10.1002/wilm.11083},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11083},abstract = {Risk-neutral pricing, swap valuation, and the Black-Scholes call option Delta.}}
* U. Wystup, “How a long call option can be long gamma, long theta and short theta,” Wilmott, vol. 2023, iss. 123, p. 12–14, 2023.
[Bibtex] [Abstract]
All at the same time. No kidding.
@article{WILM:WILM11084,title = {How a Long Call Option can be Long Gamma, Long Theta and Short Theta},author = {Wystup, Uwe},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {12--14},doi = {10.1002/wilm.11084},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11084},abstract = {All at the same time. No kidding.}}
* M. Benzaquen, “Cross-impact in derivative markets,” Wilmott, vol. 2023, iss. 123, p. 16–28, 2023.
[Bibtex] [Abstract]
Trading a financial asset pushes its price as well as the prices of other assets, a phenomenon known as cross-impact. The empirical estimation of this effect on complex financial instruments, such as derivatives, is an open problem, tackled in this issue’s cover article ‘Cross-impact in Derivative Markets’ by Michael Benzaquen, Mehdi Tomas and Iacopo Mastromatteo. To address this, the authors consider a setting in which the prices of derivatives is a deterministic function of stochastic factors where trades on both factors and derivatives induce price impact. Benzaquen, Tomas and Mastromatteo show that a specific cross-impact model satisfies key properties which make its estimation tractable in applications. Using E-Mini futures, European call and put options and VIX futures, the authors estimate cross-impact and show our simple framework successfully captures some of the empirical phenomenology. Benzaquen et al’s framework for estimating cross-impact on derivatives may be used in practice for estimating hedging costs or building liquidity metrics on derivative markets.
@article{WILM:WILM11085,title = {Cross-impact in Derivative Markets},author = {Benzaquen, Michael},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {16--28},doi = {10.1002/wilm.11085},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11085},abstract = {Trading a financial asset pushes its price as well as the prices of other assets, a phenomenon known as cross-impact. The empirical estimation of this effect on complex financial instruments, such as derivatives, is an open problem, tackled in this issue’s cover article ‘Cross-impact in Derivative Markets’ by Michael Benzaquen, Mehdi Tomas and Iacopo Mastromatteo. To address this, the authors consider a setting in which the prices of derivatives is a deterministic function of stochastic factors where trades on both factors and derivatives induce price impact. Benzaquen, Tomas and Mastromatteo show that a specific cross-impact model satisfies key properties which make its estimation tractable in applications. Using E-Mini futures, European call and put options and VIX futures, the authors estimate cross-impact and show our simple framework successfully captures some of the empirical phenomenology. Benzaquen et al’s framework for estimating cross-impact on derivatives may be used in practice for estimating hedging costs or building liquidity metrics on derivative markets.}}
* C. Alexander, “Volume and volatility spillovers between crypto exchanges,” Wilmott, vol. 2023, iss. 123, p. 30–34, 2023.
[Bibtex] [Abstract]
With increasing institutional adoption of crypto assets and derivatives positions Carol Alexander, Andreas Kaeck, and Daniel Heck examine the need for in-depth understanding of the microstructure in these fragmented markets.
@article{WILM:WILM11086,title = {Volume and Volatility Spillovers Between Crypto Exchanges},author = {Alexander, Carol},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {30--34},doi = {10.1002/wilm.11086},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11086},abstract = {With increasing institutional adoption of crypto assets and derivatives positions Carol Alexander, Andreas Kaeck, and Daniel Heck examine the need for in-depth understanding of the microstructure in these fragmented markets.}}
* S. Das, “Alice through the crypto glass part 3 – the empire strikes back: central bank digital currencies (cbdcs),” Wilmott, vol. 2023, iss. 123, p. 36–38, 2023.
[Bibtex] [Abstract]
All indications are that the introduction of CBDCs is probable. Could this completely undermine the crypto project?
@article{WILM:WILM11087,title = {Alice Through The Crypto Glass Part 3 – The Empire Strikes Back: Central Bank Digital Currencies (CBDCs)},author = {Das, Satyajit},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {36--38},doi = {10.1002/wilm.11087},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11087},abstract = {All indications are that the introduction of CBDCs is probable. Could this completely undermine the crypto project?}}
* J. Andreasen, “Catch up,” Wilmott, vol. 2023, iss. 123, p. 40–45, 2023.
[Bibtex] [Abstract]
We consider finite difference implementation of local volatility models when the underlying has a non-trivial drift. For this case, we develop a finite difference scheme that guarantees positive transition probabilities and also handle the case where the input option prices are not fully arbitrage consistent. We include C++ code for our finite difference solver.
@article{WILM:WILM11088,title = {Catch Up},author = {Andreasen, Jesper},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {40--45},doi = {10.1002/wilm.11088},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11088},abstract = {We consider finite difference implementation of local volatility models when the underlying has a non-trivial drift. For this case, we develop a finite difference scheme that guarantees positive transition probabilities and also handle the case where the input option prices are not fully arbitrage consistent. We include C++ code for our finite difference solver.}}
* G. Giller, “The sharpe ratio is a terrible statistic to use to optimize trading strategies,” Wilmott, vol. 2023, iss. 123, p. 46–49, 2023.
[Bibtex] [Abstract]
All the theory associated with the Sharpe Ratio is based upon ex ante estimates of return and risk, but the overwhelming majority of its use is as an ex post measure of performance: that is, as a statistic.
@article{WILM:WILM11089,title = {The Sharpe Ratio is a Terrible Statistic to Use to Optimize Trading Strategies},author = {Giller, Graham},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {46--49},doi = {10.1002/wilm.11089},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11089},abstract = {All the theory associated with the Sharpe Ratio is based upon ex ante estimates of return and risk, but the overwhelming majority of its use is as an ex post measure of performance: that is, as a statistic.}}
* L. Ballabio, “A taste of quantlib,” Wilmott, vol. 2023, iss. 123, p. 50–52, 2023.
[Bibtex] [Abstract]
What is it and what can it do for you?
@article{WILM:WILM11090,title = {A Taste of QuantLib},author = {Ballabio, Luigi},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {50--52},doi = {10.1002/wilm.11090},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11090},abstract = {What is it and what can it do for you?}}
* Wolfram, “Fixed income and debt instruments: annuities, bonds, cashflows and mortgages,” Wilmott, vol. 2023, iss. 123, p. 54–58, 2023.
[Bibtex] [Abstract]
This is the first in a sequence of articles on finance using the Wolfram language. While this essay covers fixed-income instruments, future essays will cover financial derivatives, time series analysis, machine learning in finance, financial visualization and data services.
@article{WILM:WILM11091,title = {Fixed Income and Debt Instruments: Annuities, Bonds, Cashflows and Mortgages},author = {Wolfram},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {54--58},doi = {10.1002/wilm.11091},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11091},abstract = {This is the first in a sequence of articles on finance using the Wolfram language. While this essay covers fixed-income instruments, future essays will cover financial derivatives, time series analysis, machine learning in finance, financial visualization and data services.}}
* J. Marsden, “Referential objects: a coda,” Wilmott, vol. 2023, iss. 123, p. 60–61, 2023.
[Bibtex] [Abstract]
If we shadows have offended, think but this and all is mended.
@article{WILM:WILM11092,title = {Referential Objects: A Coda},author = {Marsden, Joseph},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {60--61},doi = {10.1002/wilm.11092},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11092},abstract = {If we shadows have offended, think but this and all is mended.}}
* D. Bloch, “Option prices expansions and applications,” Wilmott, vol. 2023, iss. 123, p. 62–81, 2023.
[Bibtex] [Abstract]
Daniel Bloch presents a general pricing approximation technique for European call option prices in a jump-diffusion model with stochastic interest rates. The author considers the dynamics of the logarithm of the forward price, under the forward measure, in the class of multifactor Affine and Quadratic models without jumps, and devise the dynamics of its associated variance swap. Bloch expresses the expected future average volatility as a function of that variance swap, and uses classical Ito’s calculus to expand prices around the Black formula. The author then adds jumps to the dynamics of the log-forward price and condition the expectation of the call price with respect to the number of jumps. Applying a change of measure, option prices decompose into a weighted sum of approximated multifactor Affine and Quadratic models. Bloch uses these prices decompositions to define an analytical formula that approximate the implied volatility surface in the class of Affine and Quadratic models with jumps. At last, the author compares a few prices approximations against Monte Carlo simulations for a range of maturities covering one year, and provide accuracy measures. Bloch then uses these prices as benchmark to measure the accuracy of the implied volatility surface expansion. The author obtains very low MAE and RMSE, both on the prices and IVS, demonstrating that the series expansions are very precise for short and long maturities. Applications include: fast prices and Greeks estimation for European options, initial values for numerical computation of IVS, and control variate for complex pricing models in Monte Carlo and Machine Learning.
@article{WILM:WILM11093,title = {Option Prices Expansions and Applications},author = {Bloch, Daniel},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {62--81},doi = {10.1002/wilm.11093},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11093},abstract = {Daniel Bloch presents a general pricing approximation technique for European call option prices in a jump-diffusion model with stochastic interest rates. The author considers the dynamics of the logarithm of the forward price, under the forward measure, in the class of multifactor Affine and Quadratic models without jumps, and devise the dynamics of its associated variance swap. Bloch expresses the expected future average volatility as a function of that variance swap, and uses classical Ito's calculus to expand prices around the Black formula. The author then adds jumps to the dynamics of the log-forward price and condition the expectation of the call price with respect to the number of jumps. Applying a change of measure, option prices decompose into a weighted sum of approximated multifactor Affine and Quadratic models. Bloch uses these prices decompositions to define an analytical formula that approximate the implied volatility surface in the class of Affine and Quadratic models with jumps. At last, the author compares a few prices approximations against Monte Carlo simulations for a range of maturities covering one year, and provide accuracy measures. Bloch then uses these prices as benchmark to measure the accuracy of the implied volatility surface expansion. The author obtains very low MAE and RMSE, both on the prices and IVS, demonstrating that the series expansions are very precise for short and long maturities. Applications include: fast prices and Greeks estimation for European options, initial values for numerical computation of IVS, and control variate for complex pricing models in Monte Carlo and Machine Learning.}}
* M. Radley, “Family affair,” Wilmott, vol. 2023, iss. 123, p. 82–83, 2023.
[Bibtex] [Abstract]
Ferrari Purosangue/Ferrari Daytona SP3. Ferrari launches the unthinkable: a race-bred SUV. In case you thought the Prancing Horse has gone soft, the specs on this suggest otherwise.
@article{WILM:WILM11094,title = {Family Affair},author = {Radley, Milford},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {82--83},doi = {10.1002/wilm.11094},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11094},abstract = {Ferrari Purosangue/Ferrari Daytona SP3. Ferrari launches the unthinkable: a race-bred SUV. In case you thought the Prancing Horse has gone soft, the specs on this suggest otherwise.}}
* J. Darasz, “The skewed world of jan darasz,” Wilmott, vol. 2023, iss. 123, p. 84–84, 2023.
[Bibtex] [Abstract]
Cartoon
@article{WILM:WILM11095,title = {The Skewed World of Jan Darasz},author = {Darasz, Jan},year = 2023,journal = {Wilmott},publisher = {Wilmott Magazine, Ltd},volume = 2023,number = 123,pages = {84--84},doi = {10.1002/wilm.11095},issn = {1541-8286},url = {http://dx.doi.org/10.1002/wilm.11095},abstract = {Cartoon}}
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Data from AI news analytics pioneer Blu Analytics shows that negative Twitter news is not the main driver of the Tesla share price despite claims the high-profile acquisition is hitting the stock market performance of [...]
Congratulations to the latest graduates from the Certificate in Quantitative Finance (CQF). This is the 39th cohort of students to complete the master’s-level, online program. [...]
Volume 2022, Issue 122. Pages 1-84 Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here. In this issue: D. Tudball, “Contents,” Wilmott, vol. 2022, iss. 122, [...]
Daniel J. Duffy's historical review focuses on the applicability of partial differential equation (PDE) techniques and related numerical methods, particularly Finite Difference Method (FDM) that are applied to option pricing and hedging applications. [...]
Volume 2022, Issue 121. Pages 1-120 Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here. In this issue: D. Tudball, “Contents,” Wilmott, vol. 2022, iss. 121, [...]
On the sad event of Bill Ziemba's passing Wilmott extends its condolences to Bill's family, friends, and colleagues. [...]
Volume 2022, Issue 120. Pages 1-84 Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here. In this issue: “Contents,” Wilmott, vol. 2022, iss. 120, p. 1–1, [...]
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This column is written jointly by John Swetye of Hypernormal Enterprises, Darien, CT and William T. Ziemba and an earlier version was published in: John Swetye & William T. Ziemba (2016) Using Zweig’s monetary and momentum models in the modern era, Quantitative Finance Letters, 4:1, 35–39, DOI: 10.1080/21649502.2015.1165917. A version of this article will also appear in Stock Market Crashes: Predictable and Unpredictable and What to do About Them (World Scientific, 2017). [...]
London Business School Professor of Finance joins academics from Harvard University, the University of California Berkeley, New York University, the University of Oxford, and Tsinghua University, as well as experienced financial services professionals [...]
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Scientific Financial Systems, Inc. (SFS) have announced its acceptance into the FinTech Sandbox. FinTech Sandbox is a nonprofit that promotes innovation in financial technology and financial services globally by providing fintech entrepreneurs and startups with free access to critical data and resources. Boston FinTech Week and Mass Fintech Hub are also initiatives under the Fintech Sandbox umbrella. The FinTech Sandbox allows FinTech startups access to market data and infrastructure technologies from partners like Refinitiv, Factset, and S&P. The startups, in return, collaborate with other startup residents to share innovations.
The Quotient platform, from SFS, provides modern, efficient, and powerful analysis combined with simplified access to a wide array of financial content. With Quotient, investment managers can develop differentiated investment strategies using novel python tools and data science in an open environment.
“The partnership with the FinTech Sandbox will greatly enhance our go-to-market strategy by broadening Quotient’s appeal to institutional investment managers and hedge funds,” said Colin Longval, SFS Sales and Business Development Manager.
“We are thrilled to be part of the FinTech Sandbox,” said SFS Founder and Chief Technology Officer Peter Millington. “The breadth and depth of data available will benefit our product offering immensely since we provide our clients an open and data-agnostic environment from which to develop differentiated investment ideas.”
“Data is one of the most important resources for early-stage FinTechs as its inaccessibility poses a consistent challenge and impedes innovation for their business and ultimately the entire financial services sector,” said Kelly Fryer, executive director, FinTech Sandbox. “We are pleased to welcome Scientific Financial Systems to our Data Access Residency program, which enables entrepreneurs to build their companies, use their resources in more beneficial ways, and work more closely with financial firms to help them innovate.”
22nd MathFinance Conference
21-22 March 2022
https://www.mathfinance.com/events/mathfinance-conference-2022/
Providing cutting-edge research and brand-new practical applications, the conference is intended for practitioners in the areas of trading, quantitative or derivative research, risk and asset management, insurance as well as for academics studying or researching in the field of financial mathematics.
This year the conference tackles rough volatility, crypto derivatives, market regimes, volatility modeling, climate finance, market data, stable Monte Carlo Greeks. This year MathFinance are especially pleased to welcome very distinguished speakers from the quantitative finance world such as Paul Wilmott, Adil Reghai, Antoine Jacquier, Caroline Mauron and many others. The speakers and their talks comprise:
– Dr. Josef Teichmann (ETH Zurich) Frontiers in Mathematical Finance
– Dr. Peter Tankov (ENSAE, Institut Polytechnique de Paris) Asset Pricing under Transition Scenario Uncertainty
– Dr. Jack Jacquier (Imperial College London, Director of the MSc in Mathematics and Finance) As Rough as it can get
– Dr. Blanka Horvarth (King’s College London) Clustering Market Regimes using Wasserstein Distance
– Dr. Torsten Langner (YUCE-8) Introducing a New Regime Change Indicator for Bitcoin
– Dr. Caroline Mauron, (OrBit Markets) Exotic Payoffs in the DeFi World
– Dr. Nathalie Packham (Berlin School of Economics and Law) Crypto Markets – the Good, the Bad and the Quant’s Field Lab
– Dr. Uwe Wystup (MathFinance) Uncle Herbert’s Savings Plan with Bonus and the Legal Aftermath
– Dr. Stefan Ebenfeld (Deloitte) Quantitative Climate Stress Testing
– Dr. Christian Bayer (Weierstrass Institute) Simulating Rough Volatility Models
– Dr. Bastian von Harrach (Goethe University Frankfurt) Stable Differentiation of Monte Carlo Priced Options with Discontinuous Payoffs
– Dr. Wolfgang Eholzer (Board Member, Eurex) Option and Futures Trading @ Eurex
– Dr. Karel in’t Hout (University of Antwerp) Operator Splitting Schemes for Pricing European and American Options und Two-Asset Jump-Diffusion Models
– Dr. Stefano de Marco (Ecole Polytechnique Paris) Local volatility from rough volatility
– Dr. Mathieu Rosenbaum (Ecole Polytechnique Paris) TBA
– Dr. Adil Reghai (Natixis) Local Stochastic Volatility Saga – Episode III
– Mauricio I. Gonzales-Evans (BCC Group) Market Data in the Cloud
– Dr. Markus Hertrich (Bundesbank) Foreign Exchange Interventions under a Minimum Exchange Rate Regime and the Swiss Franc
Springer will introduce new books by Robert Jarrow, Thomas Barrau (AXA), and Agatha Murgoci, (Ørsted) with live interviews
Additionally, the conference will also have a panel discussion on Climate Finance and the challenges faced in the quantitative finance industry. Prof. Martin Simon (MathFinance) will moderate the discussion with the following panelists:
Stefan Ebenfeld, Director | Risk Advisory, Deloitte
Eva Meyer, Head of Company Engagement, BNP Paribas
Hannah Helmke, Founder, based on science
Jan Köpper, Head of Impact Transparency & Sustainability, GLS Bank
Stefan Bohlius, Senior Manager, d-fine
An Interview with Paul Wilmott will conclude the conference.
A blend of world-renowned speakers ensures that a variety of topics and issues of immediate importance are covered. This event is a must for all quantitative finance professionals.
For updates on the agenda and registration please visit:
https://www.mathfinance.com/events/mathfinance-conference-2022/
MathFinance are happy for supporting sponsors Deloitte, BCC Group and thank our Media Partners Wilmott, Springer, Financial Risk Hub and our affiliate partner UAE FMA.
It’s the mid-1990s, the Wall Street of the Masters of the Universe is partying like it’s 1999, LTCM and the dotcom bubble are yet to spoil the good times. Peter Carr and Dilip Madan have developed a robust hedge for variance swaps using vanilla options such that static positions in the options combine with dynamic trading in the underlying. The amazing thing is that the hedge works in a big class of models.
Carr, then at Morgan Stanley, goes to a guy in marketing and says: “Wow! We should be selling these variance swaps; they’re simple contracts, people should want them, and they can be hedged in a big class of models!” The marketing guy says: “No one’s interested in variance. If you can create a volatility swap, that’s what we can sell.” And probably turns his attention back to his mid-morning glass of Petrus.
To a marketer, the difference between a variance and a volatility is just a detail in a contract. Carr, however, could not see past the square root which had just punched him in the face. The square root you have to take to go from a variance to a volatility, to someone who is trying to hedge in a model-free way, is a huge problem because it’s a nonlinear function. “Trust me,” Carr says, “It’s not a minor detail.”
But Carr’s overwhelming sense of diligence won’t allow him to drop it and he asks himself: “Is there an analog to this variance swap, where you can take the square root or more generally any nonlinear function? If you do a linear function, it’s obvious that it would work, but with a nonlinear function
could you still do it?”
Carr “struggled and struggled and struggled,” but couldn’t make it work robustly: “You could do it all in
theory but not in the absence of strong assumptions, let’s say.” The struggle would result in the piece of work of which Carr is most proud – even though it has never been published.
With the help of Roger Lee, the realization came that you could do it, if you were willing to make one more assumption compared to the standard theory. That one additional assumption is called ‘uncorrelatedness,’ a technical assumption. “It’s an assumption that feels wrong in many contexts, and
that’s what held me back from publishing it,” Carr says, but he “… was happy to make this progress because at least it was only one more assumption and not a lot more.”
Five years after the comment that sent him off on his quest, Carr then bumps into a different marketing
type and says: “Hey! I can do a vol swap now instead of a variance swap, semi-robustly!” “No one’s interested in vol swaps now,” the marketer replies.”Everybody’s doing variance swaps.” An appreciation of symmetry, in all its forms, is essential to understanding Peter Carr.
To read the rest of the article click the PDF link below:
| DOWNLOAD FULL ARTICLE: Peter Carr's Hall of Mirrors |
I met Peter for the first time in February 1989 in New York, at a Colloquium of the American Stock Exchange. We were in the same session: Peter was presenting an essay of his dissertation dedicated to an exchange option where one party could choose the asset to deliver out of a defined set. I was presenting a paper on ‘Portfolios of Bonds and Futures on Bonds’ where the ‘Cheapest to Deliver’ was chosen by the seller of the Future among a basket of Treasuries. We were very happy to meet and soon after, Peter accepted my invitation to ESSEC, probably because he knew that France was a country with a long tradition in Probability – a subject he had not fully studied in his first education and fascinated him. He came for two weeks in the Finance Department, where my colleagues (all US Finance PhDs after a French Grande Ecole) were already quite familiar with the intricacies of complex Derivatives and greatly contributed to the construction of the ‘DEA Probabilities Finance’ and to the ‘school in Mathematical Finance’ which was growing in France, in particular after the long visit of Ioannis Karatzas invited by Nicole Elkaroui and the weekly Seminar started by Thierry Jeulin. Peter was carrying around the young and enthusiastic look he would keep all his life, as well as an immense kindness. His paper on American options (‘Alternative Characterizations of American Put Options’, Carr, Jarrow and Myneni, Mathematical Finance, 1992) contained so many rich results unknown at the time by many of us.
I met Dilip Madan in 1995 at a conference in Montreal and a three-way collaboration started after Dilip had joined Peter at Morgan Stanley. Our first joint paper discussed ‘Acceptability’ to address ‘Market Incompleteness’(CGM , Journal of Financial Economics, 2001). Dilip would come to Paris for two months a year; I naturally introduced him to Marc Yor and this is how the CGMY model came into existence. Marc Yor was bringing his ‘total’ knowledge of Brownian Motion and Levy Processes — I also salute his memory with emotion. Dilip had worked with Eugene Seneta on the ‘Variance Gamma Process (‘The Variance Gamma Process for Share Markets’, Madan and Seneta, Journal of Business, 1995) Peter had the perspective of a practitioner searching for a model better ‘adapted’ to the markets of the time. In my case, I had been very interested since 1995 in the ‘Subordination’ introduced in Finance by Clark, who offered to represent Cotton Futures prices by subordinated processes ( A Subordinated Stochastic with Finite Variance Model , Clark, Econometrica , 1973) This paper was remarkable for several reasons: firstly, Clark rejects the processes with infinite variance proposed by Mandelbrot in 1965 (‘Forecasts of Future Prices, Unbiased Markets and Martingale Models’, Mandelbrot, Journal of Business, 1965). Secondly, he introduces Subordination in Finance, which was a brilliant way to create new processes to address the non-normality of returns observed already in 1960 by Fama and many others after him. Thirdly, his paper first had an unfortunate fate because of the exclusive attention brought to the papers by Black & Scholes (1973) and Merton (1973) and time went by before the original contribution of Clark received deserved attention.
I read Clark’s paper with fascination, but the limits of subordination imposed by the mathematical constraints on the subordinator — when one wants precisely to account for the non-uniform arrival of the order flow in the markets and the resulting stochastic volatility — rapidly convinced me of the value of extending subordination to ‘stochastic time changes’ ( Geman, RISK, 1996). In Summer 1997, Joe Horowitz, a probabilist at the University of Massachusetts, brought to my attention the beautiful paper written by Monroe in 1978: ‘ Any semimartingale is a time-changed Brownian Motion’, (Itrel Monroe , ‘Processes that can be embedded in Brownian motion’, Annals of Probability, 1978). This paper was written after the Clark (1973) article (which Monroe certainly ignored) — and extended to semimartingales the theorem established for martingales by Dubins and Schwartz (1965). This brought the final piece …
By No Arbitrage, discounted stock prices are martingales under an equivalent probability measure Q (Harrison, Kreps, Pliska, Delbaen, Schachermayer). Consequently, stock prices have to be semimartingales under the real probability measure P, and, up to a change of filtration, they are ‘Time Changed Brownian Motion’.( G.& Ane, 2000, Journal of Finance). One can then go to market data to infer properties of the stochastic clock as we did with my Ph.D. student. Or one can decide to choose the stochastic time change that brings a ‘compound’ stochastic process with desirable mathematical properties, which was our approach in CGMY (Journal of Business, 2002), CGMY with Stochastic Volatility (Mathematical Finance, 2003), and other papers, for instance looking at Options on Variance. Peter used similar techniques in his work on FX options with his Ph.D. student Liuren Wu to study FX options (‘Stochastic Skew in Currency Options, Journal of Financial Economics, 2009).
So many other papers of Peter’s deserve to be mentioned and discussed, but I prefer to end on a joyful memory.
In 2008, the CGMY model received an Award from the Alma Mater Studiorum Institute of the University of Bologna (the oldest University in the world, and a remarkable place). The four of us had to each give a talk on the genesis of CGMY, and beyond. And we received an allowance’ of $500 per person that had to be spent exclusively in Bologna. I was the fastest one to fill the mission, obviously; the three others were walking all around the city where so many choices were offered. The result was that at departure, my three co-authors looked like elegant Italian gentlemen rather than usual mathematicians …
Since then, I have continued to meet Peter at conferences or at friendly dinners, mostly with Dilip and Master and doctoral students, sometimes with my Ph.D. student Nassim who had become his colleague at NYU Tandon.
Peter, we will miss your kindness and generosity. Your abrupt departure is another proof of the lack of Antifragility in human life.
Peter Carr left us, saddened and shocked, on the morning of March 1, 2022, after an earlier devastating internal hemorrhage. I spoke with Peter on January 29 asking about his response to my remarks on a discussion that took place at a virtual seminar on January 25, the second day of the Spring semester of 2022. He replied that he had not been feeling well and would get back to me when he was better. This was the first time, and now also the last time, that Peter responded in such a manner. I have never known him to be in such a state. Something was clearly amiss.
Undoubtedly, Peter leaves us with many wonderful memories of our interactions with him and here I try and relate some of them.
I first met Peter in the summer of 1991 at a Cornell conference that initiated the journal Mathematical Finance. At the time I had just arrived back to the US from twelve years in Australia and was an unknown personality in the US community of mathematicians with an interest in Finance. The meeting was brief, but we got to appreciate each other. We got to know each other much better in the Fall of 1995 when I spent the Fall semester on sabbatical at Cornell. Many discussions followed on the theory of no-arbitrage pricing.
By the summer of 1996, Peter had moved from Cornell to essentially head the quant group at Morgan Stanley. He may not have been the head, but was recognized by his brilliance, intellect, and energy as such by those around him. His natural inclination was to question, debate, and challenge what is being discussed from multiple directions in the friendliest way possible. Recognizing this the rest of the team just fell in place.
Peter arranged to have me hired as a consultant at Morgan Stanley in the summer of 1996 and I have since spent two to three days a week there. The spring of 1995 saw the birth of the variance gamma model with skewness added into it. Trader overrides were posing a strain on capital requirements supporting the options trading business. Marking to the variance gamma model was proposed, tried out on a small set of underliers, and then adopted firm-wide. The marking activity needed fast computation of variance gamma prices for thousands of underliers at market close. It must have been Thanksgiving of 1996, when my family and I were making our annual visit to my brother-in-law in Connecticut, where instead of joining the families to go shopping, the following Friday, I met Peter at Morgan Stanley and worked on developing the fast Fourier transform method for pricing options. This is what made the marking possible. Neither Peter nor I were interested in shopping. For many years the Friday after Thanksgiving was spent this way. These two papers are among our most cited papers. Many asked Peter to take charge of the model and its implementation. But Peter’s active mind had to move on to other pastures. It cannot stand in the light of any past glories.
Since then, we have worked in many ways and places. When it came to financial mathematics Peter did not take breaks. We worked in Sydney, Budapest, Paris, and London on numerous occasions. Once on the barrier reef in Australia when most of the conference party was taking dives or snorkeling, Peter could be seen on deck, laptop in hand, interviewing colleagues on matters of mathematical detail. He embraced early on the idea of proof in mathematics and loved it all the way. Directing donations to the math museum is most appropriate.
Peter moved on to revising the VIX computation and developing hedges for the variance and volatility swaps. I interacted with him on hedging insurance risks. We worked on the implications of the absence of static arbitrage. This led us to the study of additive processes of which the Sato process was another contribution. My conversation with Peter between January 25 and 29 of this year was on additive processes and has led to a new paper, now without him, that we could have co-authored. Peter, prolific with both ideas and the personalities he engaged with has published with many other co-authors on numerous aspects of the subject and we may note in this regard the extensive work with Liuren Wu, Roger Lee, Gurdip Bakshi, Andrey Itkin, Johannes Ruf, Travis Fisher, Matthew Lorig, Lorrenzo Torricelli, Sergey Nadtochiy to mention a few.
Apart from the papers and investigations, Peter gave freely of his time in delivering courses at conferences during the years he was with the financial industry. I participated in a few of these. One of these was a weeklong course, in January 2012, at the Tata Institute of Fundamental Research in Bombay, my hometown. Peter could not take financial remunerations for these and diverted the funds to be received to various causes. One of which was funding my FestSchrift conference in 2006. In 2016 Peter, Philip Protter, Rene Carmona, and myself worked in bringing the World Congress of the Bachelier Finance Society to New York.
Let me close by noting that there is much to fondly remember Peter by. I remember a night in Paris when we went to dinner at a restaurant with no menu, but you got what the house had prepared that day. The line to enter was too long and at Peter’s suggestion, we returned the next night to be first in line. Another time in the financial district of London we went to a pub and on some rare occasions Peter would take an alcoholic beverage, standard fare for me, but to my surprise, he took to a cherry flavored beer. A bit courageous for my taste but Peter delved into the new easily. Bought an electric vehicle easily and really enjoyed driving it. Would go out of the way to extend the ride. In Sydney, we enjoyed the early morning swim at Manly beach followed by Tasmanian scallops, one of my favorites there. He bought me a gigantic wine glass that holds a bottle of wine so I could say I just had one glass of wine at night! On another occasion, Peter stayed at my house overnight for a joint presentation in Baltimore the next morning. Peter was using the shower in my daughter’s bedroom when there were just the two of us in the house. Neither of us, with three PhDs between us, could figure out how to turn the shower on. We gave up and he finally showered in my bedroom shower.
His spirit will definitely live on in our memories and our lives. Many thanks, Peter for uplifting all the lives you touched so deeply.
“… there’s following the leader and then there’s being a leader intellectually. You are given a task, it’s a difficult balance; you can solve that task or you can think, is this the right task? I am probably more the latter, and say, here are the results – perhaps the original task doesn’t get solved but, instead of getting a passable solution to the problem at hand, the hope is that you can think outside the box and open up whole new vistas.”
Peter Carr, Wilmott Magazine, May 2017
Wilmott has received a missive from Satyajit Das, well known to readers for his acerbic takes on the economic mise en scene. Only apt then that the communication begins with a doff of the cap to the theatre:
In Shakespeare’s Romeo and Juliet, the male lead declares that he is “fortune’s fool”, subject to the whims of fate. The phrase (no copyright issues; author long dead!) provides the inspiration for Fortune’s Fool: Australia’s Choices.
Australia’s prosperity relies on the continent’s extraordinary natural — primarily mineral —riches and good fortune. But economic, financial, environmental, geopolitical, and societal pressures now threaten the nation’s high living standards. The COVID-19 pandemic is the first of many trials to come. Lackluster reform proposals are mired in ideological necrophilia: ideas which have been tried and failed. Politics is trading insults and slogans. Institutions lack the quality, skills, organizational memory, and courage to deliver the required solutions. A disengaged citizenry is focused on preserving their entitled way of life, refusing to accept that the well of plenty is approaching exhaustion. Critics are derided as permanent professional pessimists, the doubting Irishman Hanrahan in John O’Brien’s poem warning of ‘roon’. Cognitive dissonance is a national religion.
Written in accessible, acerbic prose, Fortune’s Fool cuts through these issues to expose Australia’s current dilemmas and choices. It dissects the pandemic, global trends, Australia’s narrow ‘house and holes’ economy, and its dependency on China, spotlighting a political paralysis that must be overcome and the changes that are urgently needed. For Australians remotely concerned about their own future and their children’s, as well as the country’s, Fortune’s Fool is essential reading.
The book mines Samuel Beckett seeking to fail even better than last year’s A Banquet of Consequences – Reloaded. The disaster was related to civil engineering: “Readers need an ‘off-ramp’!” It seems potential buyers prefer happy endings and solutions requiring no work, cost, sacrifice, pain, or any other unfair or burdensome demands — strangely — though much of what was said in that work has proved to be largely accurate.
Fortune’s Fool … has the advantage of brevity — only 96 pages. This reflects my weary soul, attention spans shaped by Twitter and Tik-Tok, and the undeniable fact that Australia is small in the scheme of things.
The work evidences my defiance of Einstein (repeating the same actions hoping for a different outcome) and inability to understand that few have the slightest interest in what I think.
Fortune’s Fool – Purchase Options (such choice!)
Book Depository
Blackwells
Waterstones
Amazon
Walmart
Or you could try a real bookshop but, oh, they won’t stock it — silly me!
Romeo’s attempts to oppose destiny did not do him much good. This — most likely my last work (I have exhausted publishers and goodwill and must ‘meet the time as it seeks us’) — will not have a different outcome.
Satyajit Das
Financial technology provider Iress will expand its backbone infrastructure and QuantFEED platform to the new Euronext colocation site in Bergamo, Italy. Iress is amongst the first market data vendors to take up residence at the new site, as Euronext builds out its new data center at the location.
The agreement with Euronext provides Iress with hosting space and connectivity services which will allow them to continue to offer the lowest possible latency API data solutions to its customers. Iress will host part of its core market data platform from the new site, which will be an additional site supporting its flagship API data product, QuantFEED, and enhancing its infrastructure and connectivity proposition.
The new data center is anticipated to be online and connected to the company’s network of 19 other data centers in the coming weeks. Iress is already helping existing clients to seamlessly relocate to Bergamo IT3.
Iress’ head of product – APIs, Sebastien Tiphine, said: “We’re excited to announce that Iress continues to cement its position as the leading provider of API data solutions. By proactively taking this important next step, we are demonstrating our commitment to investing in our infrastructure and technology platforms to offer and maintain the highest-performance API data solutions available. We’re confident our clients will experience a seamless transition as we bring our services online at the new site and enjoy the benefits of the new location as soon as the site is operational.”
“We will continue to listen to the changing requirements of our growing customer base, just as we listen to the ecosystem itself, and will always look for new ways to provide customers with the very best solutions, not just for right now, but also for the future.”
Pictured in this chart are the implied rates (solid line) versus the zero curve rates (dotted line) for the Euro from January 2020 through December 2021. The chart illustrates how OptionMetrics’ new options implied methodology, constructed with a term structure of implied risk-free rates from options on major indices, offers greater accuracy over those based on zero curve rates (typically used by other providers) in options calculations such as implied volatility, forward price, index dividend, borrow rate and others. In applying leading overnight rates from the options market (such as with SOFR replacing LIBOR) and data from index options, OptionMetrics’ methodology more accurately reflects the cost of borrowing and lending in the options markets in Europe, North America, and Asia Pacific. (Graphic: Business Wire)
OptionMetrics, an options database and analytics provider for institutional investors and academic researchers worldwide, is announcing its new options implied methodology, offering even greater accuracy in options calculations in the U.S., Europe, Asia Pacific. OptionMetrics replaces the zero curve (used by other providers) with its implied yield curve, constructed with a term structure of overnight rates and implied risk-free rates from options on major indices, for more accurate implied volatility, forward price, index dividend, and borrow rate calculations.
In leveraging data from index options, OptionMetrics more accurately reflects costs of borrowing and lending in options markets. The methodology reduces implied volatility spreads and offers true volatility and Greek calculations compared to leveraging private bank lending rates or other measures that may include credit risk or unrealistic borrowing assumptions.
Overnight rates, such as SOFR, are also used in the methodology for options expiring in less than 30 days to reduce noise associated with short-dated contracts. As the new standard over LIBOR, SOFR also has nearly zero credit risk exposure.
OptionMetrics constructs term structures of implied rates curves for the:
- Dollar using SOFR (Secured Overnight Financing Rate) and S&P 500 Index options,
- Swiss Franc using SARON (Swiss Average Rate Overnight) and SMI Index options,
- Euro using ESTR (Euro Short-Term Rate) overnight rates and EUROSTOXX 50 options,
- British Pound using SONIA (Sterling Overnight Index Average) and FTSE 100 options,
- Yen using TONAR (Tokyo Overnight Average Rate) and Nikkei 225 options.
OptionMetrics applies a specialized smoothing filter to remove noise from estimates.
“At OptionMetrics, we are committed to ensuring the most accurate options data, Greeks, and implied volatility calculations. Our options implied methodology draws from the options market to more accurately reflect borrowing and lending risks, continuing our strategy to provide the most accurate data to backtest strategies and assess risk,” said OptionMetrics CEO David Hait, Ph.D.
Volatilities are automatically calculated with the new rates across OptionMetrics’ IvyDB US, IvyDB Europe, IvyDB Asia Pacific, and IvyDB Global Indices. No changes are made to table format, file naming, historical calculations.
The global convertible bond market, which languished in the doldrums since the great financial crisis of 2008/2009, has staged something of a comeback over the past 18 months. This whitepaper explores the exigencies of this instrument, the reasons for its resurgence, and whether the trend will continue. Download Whitepaper
The convertible bond market picked up dramatically with the onset of COVID-19. The convertible became one of the only ways in which stressed organizations could raise desperately needed capital at a halfway acceptable cost. These notes found ready buyers as they were priced comparatively cheaply with high coupons and low conversion premiums.
As the economy bounced back surprisingly strongly in the second half of 2020, the convertible market was again popular with a new set of borrowers. These were names that had done well in the crisis and saw the opportunity to offer investors the chance to participate in their formidable stock rally.
Issuance boomed in 2020 and continued to do so in 2021 to levels not seen since before 2008/2009. At the end of November 2021, secondary market outstanding in the global convertible market was $509.5bn, according to investment bank calculations, of which 67 percent was held in the US. Issuance over the course of the year was $137bn.
Convertible arbitrage has also become popular again. It is estimated that arbitrage funds now constitute around 40 percent of the market while outright buyers make up the remaining 60 percent – less than before the crisis but still a healthy proportion.
This resurgence has been driven partly by renewed issuance. There are a lot more trading opportunities if outright buyers need to sell old bonds and buy new ones to rebalance. The elevated volatility environment is also helpful to arbitrage players as it promotes gamma trading, allowing more frequent and more profitable rebalancing.
In the boom year of 2020, convertibles returned almost 30 percent to their investors and $160bn was issued. 2021 was less dramatic but they returned almost 10 percent to their holders, comfortably ahead of many asset classes, while a little shy of $140bn has been sold.
However, there is now inflation to contend with. The October 2021 Consumer Price Index increase was the biggest for 30 years. Although 2022 will perhaps not see the same fevered issuance as 2020 and 2021, interest in the product from both borrowers and investors remains strong.
Generally, convertibles fare relatively well in an inflationary environment. They have lower durations than most other fixed-income assets so the credit component of the security is to some degree shielded from rising prices and rising rates. The average effective duration of the US convertible market is estimated to be 1.8, while for government bonds it is 7.2, and 8.3 for investment-grade bonds.
But the equity market exposure inherent in convertibles must give us pause. Over the past 18 months or so the convertible market has been dominated by new, high-growth borrowers with limited earnings history. For these sorts of companies, inflation is particularly worrisome.
Nonetheless, no one expects the convertible bond market to slide off a cliff edge in 2022. Strategists are still calling for $100bn of global issuance in 2022, and while this is less than the past two years it is not to be sneezed at – it is well above the 2012–2019 yearly average of around $80bn.
Convertibles are particularly difficult to value because they contain a number of advanced call and put features. To make informed decisions and take advantage of investment opportunities firms need access to powerful modeling, analytical, and pricing capabilities – as used by technology providers such as Quantifi.
For more information visit https://www.quantifisolutions.com/
From the largest firms trading on Wall Street to banks providing customers with fraud protection to fintechs recommending best-fit products to consumers, AI is driving innovation across the financial services industry.
New research from NVIDIA found that 78 percent of financial services professionals state that their company uses accelerated computing to deliver AI-enabled applications through machine learning, deep learning, or high-performance computing.
The survey results, detailed in NVIDIA’s “State of AI in Financial Services” report, are based on responses from over 500 C-suite executives, developers, data scientists, engineers, and IT teams working in financial services.
AI Prevents Fraud, Boosts Investments
With more than 70 billion real-time payment transactions processed globally in 2020, financial institutions need robust systems to prevent fraud and reduce costs. Accordingly, fraud detection involving payments and transactions was the top AI use case across all respondents at 31 percent, followed by conversational AI at 28 percent and algorithmic trading at 27 percent.
There was a dramatic increase in the percentage of financial institutions investing in AI use cases year-over-year. AI for underwriting increased fourfold, from 3 percent penetration in 2021 to 12 percent this year. Conversational AI jumped from 8 to 28 percent year-over-year, a 3.5x rise.
Meanwhile, AI-enabled applications for fraud detection, know your customer (KYC), and anti-money laundering (AML) all experienced growth of at least 300 percent in the latest survey. Nine of 13 use cases are now utilized by over 15 percent of financial services firms, whereas none of the use cases exceeded that penetration mark in last year’s report.
Future investment plans remain steady for top AI cases, with enterprise investment priorities for the next six to 12 months marked in green.
Top Current AI Use Cases in Financial Services (Ranked by Industry Sector)
Green highlighted text signifies top AI use cases for investment in next six to 12 months. Overcoming AI Challenges
Financial services professionals highlighted the main benefits of AI in yielding more accurate models, creating a competitive advantage, and improving customer experience. Overall, 47 percent said that AI enables more accurate models for applications such as fraud detection, risk calculation, and product recommendations.
However, there are challenges in achieving a company’s AI goals. Only 16 percent of survey respondents agreed that their company is spending the right amount of money on AI, and 37 percent believed “lack of budget” is the primary challenge in achieving their AI goals. Additional obstacles included too few data scientists, lack of data, and explainability, with a third of respondents listing each option.
Financial institutions such as Munich Re, Scotiabank, and Wells Fargo have developed explainable AI models to explain lending decisions and construct diversified portfolios.
Biggest Challenges in Achieving Your Company’s AI Goals (by Role)
Cybersecurity, data sovereignty, data gravity, and the option to deploy on-prem, in the cloud, or using hybrid cloud are areas of focus for financial services companies as they consider where to host their AI infrastructure. These preferences are extrapolated from responses to where companies are running most of their AI projects, with over three-quarters of the market operating on either on-prem or hybrid instances.
Where Financial Services Companies Run Their AI Workloads
Executives Believe AI Is Key to Business Success
Over half of C-suite respondents agreed that AI is important to their company’s future success. The top total responses to the question “How does your company plan to invest in AI technologies in the future?” were:
- Hiring more AI experts (43 percent)
- Identifying additional AI use cases (36 percent)
- Engaging third-party partners to accelerate AI adoption (36 percent)
- Spending more on infrastructure (36 percent)
- Providing AI training to staff (32 percent)
However, only 23 percent overall of those surveyed believed their company has the capability and knowledge to move an AI project from research to production. This indicates the need for an end-to-end platform to develop, deploy and manage AI in enterprise applications.
Read the full “State of AI in Financial Services 2022” report to learn more.
Explore NVIDIA’s AI solutions and enterprise-level AI platforms driving the future of financial services.
This article is a reproduction of a blog post by Kevin Levitt, Global Industry Business Development, Financial Services at NVIDIA
Global asset manager Schroders and Artificial Intelligence (AI) solutions firm Nexus FrontierTech today announced the successful development of a Proof-of-Concept (POC) for a data parsing and extraction solution that achieved over 97% extraction accuracy. The successful POC is the first step in developing and integrating an AI solution that will help Schroders’ Fund Accounting to accurately complete reporting validation checks in just half the current timeframe.
The collaboration between the two parties took root in March 2021 on the Infocomm Media Development Authority’s (IMDA) Open Innovation Platform (OIP), hosted by Investment Management Association of Singapore (IMAS)’s Digital Accelerator Programme, that connects and matches problem owners, consisting of small and medium enterprises (SMEs), large enterprises, and government agencies, to a pool of problem solvers with a range of expertise.
As a global active asset manager that provides a range of wealth management services for institutions and individuals, Schroders sought to address problems of highly manual data extraction workflows and gaps in data coverage faced by many of Schroders’ business teams, including its Fund Accounting team.
Nexus, an AI software and systems development firm that automates and accelerates business processes involving large amounts of fragmented and unstructured data, proposed the creation of a custom-built, industry-specific data parsing and extraction solution.
Using a combination of a new, multi-step engineering method combining Computer Vision and Machine Learning techniques, traditional Optical Character Recognition (“OCR”), and financial- industry specific Natural Language Processing (“NLP”) to detect domain-specific content, the solution’s POC aimed to achieve three main objectives:
- complete data extraction coverage of the three main tables[i] that the Schroders’ Fund Accounting team uses in their validation checks: Portfolio Statement, Statement of Total Return, and Balance Sheet;
- deliver an output accuracy of 80-85%[ii]; and
- develop a model that is scalable for production use.
The timeframe of the POC build was just over 3 months, beginning early September and successfully completed in December. Results far exceeded expectations, with Nexus’ Intelligent Document Processing (IDP) model:
- achieving over 90% accuracy across all three types of tables;
- establishing a systematic way to transform document structure into AI-readable logic;
- proving usability and scalability for future use; and
- proving the effectiveness of applying the Expert-In-The-Loop feature.
The POC successfully demonstrated the technical feasibility and potential business value of applying intelligent data parsing to address user pain points and improve user productivity.
Chwee Kan Chua, Global Head of Operations Innovation, Schroders, commented, “Next- gen NLP-as-a-service is fueled by the demands of accessible AI models to quickly and accurately extract and process complex data that was previously impossible or extremely labor-intensive. By leveraging such capabilities, Schroders can rapidly scale up operations to meet the increasing demands of the business without compromising our quality of service to our clients.”
“With Schroders’ deep domain knowledge of the asset management industry and our IDP capabilities, we’re confident that this partnership will yield numerous benefits for not only the two companies but for the asset management industry as a whole,” added Nexus FrontierTech Chief Operating Officer, Derrick Liao.
“This POC is an important milestone in an industry that is witnessing tremendous growth and under enormous pressure to enhance operational efficiency and satisfy customers. Asset managers are now more than ever depending on Machine Learning and AI technologies to stay competitive, and we couldn’t be more thrilled to join forces with Schroders in their move towards digitalization.”
Schroders and Nexus are moving forward to define the path to production, integrating the models built into the Schroders Fund Accounting team’s day-to-day operations, and will continue working together to achieve further breakthroughs for the asset management sector via intelligent data parsing and reap significantly improved operational efficiencies.
[i] These tables had high variation due to non-standardized structures featuring multiple pages and columns, increasing the level of difficulty in achieving high accuracy in typical data extraction projects
[ii] Estimated market standard for accuracy levels in artificial intelligence
Volume 2022, Issue 118. Pages 1-72
Every issue we bring you original material from some of the best columnists, educators and cutting-edge researchers. Subscribe here.
In this issue:
* “Contents,” Wilmott, vol. 2022, iss. 118, p. 1–1, 2022.
[Bibtex]
@Article {WILM:WILM10991, title = {Contents}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.10991}, doi = {10.1002/wilm.10991}, pages = {1--1}, year = {2022}, abstract ={Contents},}
* “Now i’m reaching back for yesterdays,” Wilmott, vol. 2022, iss. 118, p. 2–3, 2022.
[Bibtex]
@Article {WILM:WILM10992, title = {Now I'm Reaching Back for Yesterdays}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.10992}, doi = {10.1002/wilm.10992}, pages = {2--3}, year = {2022}, abstract ={In this issue Colin Turfus and Aurelio Romero-Bermudez consider how to go about choosing the best short rate model combining analytic tractability with accurate representation of the term structure of interest rate volatility},}
* “News,” Wilmott, vol. 2022, iss. 118, p. 4–9, 2022.
[Bibtex]
@Article {WILM:WILM10993, title = {News}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.10993}, doi = {10.1002/wilm.10993}, pages = {4--9}, year = {2022}, abstract ={News},}
* “Can markets predict supreme court rulings for corporate cases?,” Wilmott, vol. 2022, iss. 118, p. 10–11, 2022.
[Bibtex]
@Article {WILM:WILM10994, title = {Can Markets Predict Supreme Court Rulings for Corporate Cases?}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.10994}, doi = {10.1002/wilm.10994}, pages = {10--11}, year = {2022}, abstract ={What happens when a company’s case goes to the Supreme Court? How does it influence stock and options prices? And do investors price their anticipation of the outcome into these markets},}
* “Correlation and causation,” Wilmott, vol. 2022, iss. 118, p. 12–14, 2022.
[Bibtex]
@Article {WILM:WILM10995, title = {Correlation and Causation}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.10995}, doi = {10.1002/wilm.10995}, pages = {12--14}, year = {2022}, abstract ={In social science, we can rarely perform experiments rigorous enough to establish causality. Ironically, it is in just such areas of study that people are prone to rely on correlation to prove causation.},}
* “Picture post espen haug 007,” Wilmott, vol. 2022, iss. 118, p. 15–15, 2022.
[Bibtex]
@Article {WILM:WILM10996, title = {Picture Post Espen Haug 007}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.10996}, doi = {10.1002/wilm.10996}, pages = {15--15}, year = {2022}, abstract ={Pictorial},}
* “Can volga of a long vanilla option be negative?,” Wilmott, vol. 2022, iss. 118, p. 16–18, 2022.
[Bibtex]
@Article {WILM:WILM10997, title = {Can Volga of a Long Vanilla Option be Negative? }, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.10997}, doi = {10.1002/wilm.10997}, pages = {16--18}, year = {2022}, abstract ={More volatility would cause less volatility risk, which may feel counter-intuitive at first glance. Uwe Wystup gets negative in the most positive way},}
* “Rank competence,” Wilmott, vol. 2022, iss. 118, p. 20–21, 2022.
[Bibtex]
@Article {WILM:WILM10998, title = {Rank Competence}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.10998}, doi = {10.1002/wilm.10998}, pages = {20--21}, year = {2022}, abstract ={In a previous column, I looked at the perils of heavy-handed rounding. This month I delve into a quite related, yet somewhat reversed problem: Tiebreaker rules — using exclusively examples from sport due to limitations in publication space and my mental capacities},}
* “Economy ala carte,” Wilmott, vol. 2022, iss. 118, p. 22–23, 2022.
[Bibtex]
@Article {WILM:WILM10999, title = {Economy Ala Carte}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.10999}, doi = {10.1002/wilm.10999}, pages = {22--23}, year = {2022}, abstract ={Looking at economic issues in a fragmented way is today the equivalent of asking to order a la carte in a fast-food outlet},}
* “Thinking my way through covid,” Wilmott, vol. 2022, iss. 118, p. 24–27, 2022.
[Bibtex]
@Article {WILM:WILM11000, title = {Thinking My Way Through Covid}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.11000}, doi = {10.1002/wilm.11000}, pages = {24--27}, year = {2022}, abstract ={Sound Risk Management in the face of the SARS-CoV-2 virus.},}
* “What short rate model should i use?,” Wilmott, vol. 2022, iss. 118, p. 28–38, 2022.
[Bibtex]
@Article {WILM:WILM11001, title = {What Short Rate Model Should I Use?}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.11001}, doi = {10.1002/wilm.11001}, pages = {28--38}, year = {2022}, abstract ={how to go about choosing the best short rate model combining analytic tractability with accurate representation of the term structure of interest rate volatility},}
* “Risk arbitrage in the 2021 nba championship,” Wilmott, vol. 2022, iss. 118, p. 40–48, 2022.
[Bibtex]
@Article {WILM:WILM11002, title = {Risk Arbitrage in the 2021 NBA Championship}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.11002}, doi = {10.1002/wilm.11002}, pages = {40--48}, year = {2022}, abstract ={Mean reversion risk arbitrage is an ideal way to bet on and watch the NBA.},}
* “Xva estimates with empirical martingale simulation,” Wilmott, vol. 2022, iss. 118, p. 50–59, 2022.
[Bibtex]
@Article {WILM:WILM11003, title = {XVA Estimates with Empirical Martingale Simulation}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.11003}, doi = {10.1002/wilm.11003}, pages = {50--59}, year = {2022}, abstract ={explore simple finite sample adjustments to simulated spot FX rates, zero bonds, forward IBORs and the numeraire to ensure the martingale asset pricing property of linear IR and FX products holds exactly with a finite number of Monte Carlo simulations},}
* “A note on a pde approach to option pricing under xva,” Wilmott, vol. 2022, iss. 118, p. 60–69, 2022.
[Bibtex]
@Article {WILM:WILM11004, title = {A note on a PDE approach to option pricing under xVA}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.11004}, doi = {10.1002/wilm.11004}, pages = {60--69}, year = {2022}, abstract ={how to solve the PDE analytically in the Black-Scholes setting to get new semi-closed formulas that the authors compare to the widely used standard approximations by Monte-Carlo simulations and by numerical finite-differences solutions of the PDE},}
* “Ferrari/bmw,” Wilmott, vol. 2022, iss. 118, p. 70–71, 2022.
[Bibtex]
@Article {WILM:WILM11005, title = {Ferrari/BMW}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.11005}, doi = {10.1002/wilm.11005}, pages = {70--71}, year = {2022}, abstract ={Ferrari/BMW},}
* “The skewed world of jan darasz,” Wilmott, vol. 2022, iss. 118, p. 72–72, 2022.
[Bibtex]
@Article {WILM:WILM11006, title = {The Skewed World of Jan Darasz}, journal = {Wilmott}, volume = {2022}, number = {118}, publisher = {Wilmott Magazine, Ltd}, issn = {1541-8286}, url = {http://dx.doi.org/10.1002/wilm.11006}, doi = {10.1002/wilm.11006}, pages = {72--72}, year = {2022}, abstract ={Cartoon},}
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Zafin, a SaaS cloud- native product and pricing platform for banks and credit unions has acquired FINCAD, a provider of pricing and risk analytics of financial derivatives and fixed income products. By acquiring FINCAD, Zafin expands its product portfolio and analytics capabilities to become one of Canada’s largest B2B fintech companies with significant global presence including more than 450 institutional clients, over 60 ecosystem partners, and more than 500 employees spread out across 13 global offices.
FINCAD provides derivative and fixed-income pricing, modeling, and risk analytics to many of the world’s banks, asset management firms, insurance companies and hedge funds. The addition of FINCAD’s capital markets expertise, next-generation analytics, and extensive global client base will position the combined company for extraordinary growth.
For Zafin, the acquisition is a key milestone in the company’s history as they will now be able to offer pricing and advanced analytics solutions to institutions across all segments of banking, including retail, corporate and
commercial, and capital markets – a key differentiator in the marketplace. As a result of the transaction, FINCAD will operate as the Capital Markets Group of Zafin under the established FINCAD brand.
Al Karim Somji, Founder and Group CEO of Zafin, said: “As we look to further accelerate our global growth and enhance our end-to-end pricing and analytics offering to the marketplace, this move into the Capital Markets space is a key step. FINCAD naturally stood out to us given their impressive track record of being the leading provider of derivative analytics and pricing with a strong team that delivers for some of the world’s most trusted institutions. Working together as one global team, there is tremendous opportunity for us to scale our business by sharing deep subject-matter expertise and talent in key areas such as pricing, risk analytics and cloud technology. I believe with this strategic acquisition we’re truly going to disrupt the industry and set a new standard for how institutions can partner with fintechs like Zafin and FINCAD to deliver powerful product, pricing and advanced analytics solutions.”
Backed by a career in the capital markets, Christian Kahl, Head of Product Strategy and Client Service at FINCAD, will become Interim President, Capital Markets at Zafin. FINCAD Analytics leader and current Head of Product Development, Russell Goyder will become Chief Analytics Officer of Zafin. Both Kahl and Goyder will report to Al Karim Somji, Founder and Group CEO of Zafin.
“This is an exciting opportunity to align two leading financial software providers to drive innovation and advancement across the industry,” said Kahl. “Our clients will benefit from Zafin’s expertise in cloud-native platform technologies, unparalleled user experience, as well as Zafin’s impressive ecosystem. The combined offerings of Zafin and FINCAD will enable us to deliver an unmatched portfolio of services to our clients, and further positions us as global market leaders.”
To remain competitive in today’s derivative markets, clients are seeking sophisticated risk and valuation capabilities embedded in trade decision, hedging and risk management. The acquisition offers a key opportunity for FINCAD to leverage Zafin’s 24/7 client support and proven cloud-native platform technology to enhance its suite of patented products, and further accelerate FINCAD’s ability to empower its client base to solve complex analytics problems with innovative simplicity and speed. FINCAD expects cloud computing to be a game changer for institutions looking for advanced computations powered by leading cloud technologies.
The acquisition of FINCAD also further differentiates Zafin in the marketplace with a new Analytics-as-a-Service offering, which the company expects to launch later in the year.
“FINCAD’s patented analytics have for decades been recognized as part of the standard toolset for quantitative analysts. By coming together with Zafin and leaning on their deep expertise in unharnessing the power of cloud computing, I’m thrilled at the art of the possible as we look to further enhance our products to provide our clients with the next generation of valuations and risk analysis,” said Goyder.
Quantifi, a provider of risk, analytics and trading solutions, has been selected by Sona Asset Management (Sona), a London and New York based investment manager with $1.8bn in assets under management. To support the launch of its new investment strategy, Sona has chosen to enhance its existing risk infrastructure with Quantifi’s sophisticated risk analytics.
As firms search for returns and value-added alpha they face pressure from market volatility, shifts in investor behavior and intense competition. Sophisticated risk analytics play an important role as investment managers seek to remain competitive and take advantage of opportunities. With the launch of a new strategy, the portfolio management team and trading desk at Sona required a robust risk analytics solution to run risk for complex instruments including stress testing as well as sensitivity and scenario analysis. Quantifi was selected for its rich functionality, modern technology and ability to scale.
“The launch of our new strategy depended on finding a technology provider that could deliver the same quality of analytics used by leading tier-1 banks. Following a demanding selection process, Quantifi was the only provider with the proven technology, flexibility and expertise that matched the unique needs of our investment strategy. It was key for us to find a solution that is scalable and flexible to evolve with our business needs,” comments Antonio Di Flumeri, Partner and Portfolio Manager at Sona Asset Management. “The advanced functionality of the solution combined with the expertise of the team demonstrates why Quantifi is the provider of choice for investment managers,” continues Antonio.
For investment managers, Quantifi delivers cross-asset trading, front-to-back operations, position management, enterprise risk management and regulatory reporting, all on an integrated platform. As well as supporting the key regulatory requirements, Quantifi applies the latest technology innovations to provide new levels of usability, flexibility and ease of integration. This translates into dramatically lower time to market, lower total cost of ownership and significant improvements in operational efficiency.
“We are excited to be working with Sona to help it achieve its objectives and establish best practices to align its business for future growth. Sona selecting Quantifi is another example of our expertise in helping clients transform their business models to capitalize on opportunities,” comments Rohan Douglas, CEO, Quantifi. “We see strong demand from the investment management community because the combination of our institutional quality infrastructure, modelling expertise, and client support is a powerful differentiator. We look forward to a long, successful relationship with Sona,” continues Rohan.
For more information visit https://www.quantifisolutions.com/
SigTech, a quant technologies provider, has seen multi-fold growth in 2021. Clients with combined AUM of over $5 trillion in are now using its enterprise SaaS platform in over a dozen countries including mainland China.
In addition to hedge funds and asset managers, clients now include pension funds, investment banks, fintechs, data vendors and the world’s largest sovereign wealth funds.
SigTech now employs around 70 people, more than doubling its headcount during the course of last year.
The firm’s rapid growth is due to its relentless focus on providing an extraordinary customer experience, the accelerating adoption of a data-driven investment process and more investment managers embracing cloud services.
The firm also benefited from the continual rollout of new product features. The latest new offerings include the launch of its Data Showroom to bridge the gap in bringing alternative data to market. It enables portfolio managers and quant researchers to assess the true value in alternative data within days rather than months by providing preloaded, mapped and harmonized data along with interactive code examples and case studies.
Bin Ren, Founder and CEO of SigTech, said: “2021 was an exciting year for us – we enjoyed multi-fold growth in many aspects of the business by focusing on the continual improvement of the customer experience and product range. SigTech’s mission is to unlock the true worth of data. There are many inefficiencies and imbalances in the fast-growing data economy. We’ll continue to innovate at a fast pace to grow the financial data ecosystem for all participants.”
For more information visit https://www.sigtech.com/
Quantitative Brokers (QB), a provider of advanced execution algorithms and data-driven analytics for global futures, options and OTC Fixed Income markets, today launched a free online tool that allows institutional traders to track market liquidity and quote size at a level of transparency and ease never before available. Today’s announcement also marks a new direction for QB, who aims to offer an integrative suite of market microstructure analytics soon.
“The Liquidity Tracker provides guidance and visibility across multiple markets,” said Robert Almgren, QB’s Co-Founder and Chief Scientist. “We are very transparent with our clients and strongly believe the wider trading community can benefit from this open-source tool.”
Phase 1 of QB’s Liquidity Tracker initially charts 20+ markets worldwide[1], analyzes historical and real-time liquidity and quote size activity in each asset class, updates intra-day and serves as a health monitor of the markets. Traders can use the tool to minimize the price impact of their orders. QB Liquidity Tracker is accessible to anyone here.
“QB Liquidity Tracker marks a significant milestone for us since the launch of QB’s Roll Tracker, strengthening our position as a leading algorithmic and analytics provider,” said QB Head of Research, Shankar Narayanan. “Identifying the state of liquidity is a vital step to understanding and utilizing the next frontier in algorithmic execution, which we call Regimes. In 2022, we look forward to expanding QB’s analytics tools to help empower users to optimize their trading decisions.”
QB DRIVING INNOVATION
The Liquidity Tracker is QB’s latest innovation, providing clients with a multi-asset class multi-exchange analysis using real-time liquidity and quote size data.
In recent years, QB has expanded its suite of execution algorithms with the addition of Octane, The Roll, and, most recently, the launch of Striker 2.0. QB’s long-term view is that clients use the Liquidity Tracker to infer and minimize slippage when making trading decisions. QB’s clients have long inquired about robust liquidity reports. The challenge has constantly been the normalization of large data sets and using the same standards across the board when comparing markets. While reporting presents its challenges, QB has been predicting liquidity and quote size change, for a long time, by having its algorithmic strategies built upon these models.