Volume 2024, Issue 134. Pages 1-72
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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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