WILMOTT Magazine: July 2021 issue

Volume 2021, Issue 114. 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. 2021, iss. 114, p. 1–1, 2021.
    [Bibtex]
    @article {WILM:WILM10933,
    title = {Contents},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10933},
    doi = {10.1002/wilm.10933},
    pages = {1--1},
    year = {2021},
    }

  • D. Tudball, “Retorna me,” Wilmott, vol. 2021, iss. 114, p. 2–3, 2021.
    [Bibtex] [Abstract]

    The authors quantify additional risks that are relevant for assessing a manager's risk‐adjusted return ‐ that is, credit risk, liquidity risk, and correlation risk.

    @article {WILM:WILM10934,
    author = {Tudball, Dan},
    title = {Retorna Me},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10934},
    doi = {10.1002/wilm.10934},
    pages = {2--3},
    year = {2021},
    abstract = {The authors quantify additional risks that are relevant for assessing a manager's risk‐adjusted return ‐ that is, credit risk, liquidity risk, and correlation risk.},
    }

  • “News,” Wilmott, vol. 2021, iss. 114, p. 4–7, 2021.
    [Bibtex]
    @article {WILM:WILM10935,
    title = {News},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10935},
    doi = {10.1002/wilm.10935},
    pages = {4--7},
    year = {2021},
    }

  • A. Brown, “Twelve years to disaster doesn't mean what you think it does,” Wilmott, vol. 2021, iss. 114, p. 8–9, 2021.
    [Bibtex] [Abstract]

    Anthropogenic climate alarmists might prefer the blame game to getting something beneficial done.

    @article {WILM:WILM10936,
    author = {Brown, Aaron},
    title = {Twelve Years to Disaster Doesn't Mean What You Think It Does},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10936},
    doi = {10.1002/wilm.10936},
    pages = {8--9},
    year = {2021},
    abstract = {Anthropogenic climate alarmists might prefer the blame game to getting something beneficial done.},
    }

  • A. Spinner, “Path‐dependent benchmarks,” Wilmott, vol. 2021, iss. 114, p. 10–13, 2021.
    [Bibtex] [Abstract]

    The fragility of interest rate benchmarks suggests that thy should be analyzed as technical standards, similar to the compatibility of train gauges or electric power for appliances.

    @article {WILM:WILM10937,
    author = {Spinner, Albin},
    title = {Path‐Dependent Benchmarks},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10937},
    doi = {10.1002/wilm.10937},
    pages = {10--13},
    year = {2021},
    abstract = {The fragility of interest rate benchmarks suggests that thy should be analyzed as technical standards, similar to the compatibility of train gauges or electric power for appliances.},
    }

  • R. Poulsen, “Thomas björk in memoriam,” Wilmott, vol. 2021, iss. 114, p. 14–15, 2021.
    [Bibtex] [Abstract]

    The late Swedish financial mathematician influenced the author's views on quantitative finance enormously.

    @article {WILM:WILM10938,
    author = {Poulsen, Rolf},
    title = {Thomas Björk in Memoriam},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10938},
    doi = {10.1002/wilm.10938},
    pages = {14--15},
    year = {2021},
    abstract = {The late Swedish financial mathematician influenced the author's views on quantitative finance enormously.},
    }

  • G. Meissner, R. Bhaduri, L. Linsky, and E. Yuan, “Portfolio risk ‐ beyond volatility,” Wilmott, vol. 2021, iss. 114, p. 16–27, 2021.
    [Bibtex] [Abstract]

    Currently applied portfolio performance measures relate the portfolio return to the risk factor volatility or the risk factor correlation. In this study, Gunter Meissner, Ranjan Bhaduri, Lenny Linsky, and Eleanor Yuan quantify additional risks, which are relevant for assessing a manager's risk‐adjusted return (i.e., credit risk, liquidity risk, and correlation risk).

    @article {WILM:WILM10939,
    author = {Meissner, Gunter and Bhaduri, Ranjan and Linsky, Lenny and Yuan, Eleanor},
    title = {Portfolio Risk ‐ Beyond Volatility},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10939},
    doi = {10.1002/wilm.10939},
    pages = {16--27},
    year = {2021},
    abstract = {Currently applied portfolio performance measures relate the portfolio return to the risk factor volatility or the risk factor correlation. In this study, Gunter Meissner, Ranjan Bhaduri, Lenny Linsky, and Eleanor Yuan quantify additional risks, which are relevant for assessing a manager's risk‐adjusted return (i.e., credit risk, liquidity risk, and correlation risk).},
    }

  • M. Staunton, “In the footsteps of hermite,” Wilmott, vol. 2021, iss. 114, p. 28–31, 2021.
    [Bibtex] [Abstract]

    Julien Guyon's expansion of the price of the VIX future in the two‐factor Befrfomi model at order six in small volatility‐of‐volatility.

    @article {WILM:WILM10940,
    author = {Staunton, Mike},
    title = {In the Footsteps of Hermite},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10940},
    doi = {10.1002/wilm.10940},
    pages = {28--31},
    year = {2021},
    abstract = {Julien Guyon's expansion of the price of the VIX future in the two‐factor Befrfomi model at order six in small volatility‐of‐volatility.},
    }

  • L. MacLean and B. Ziemba, “The game box score in basketball ‐ linking statistics to game outcomes,” Wilmott, vol. 2021, iss. 114, p. 32–39, 2021.
    [Bibtex] [Abstract]

    Common uses of win probability and how win probability can be used to evaluate the overall impact of NBA players by wins added to their respective teams.

    @article {WILM:WILM10941,
    author = {MacLean, Len and Ziemba, Bill},
    title = {The Game Box Score in Basketball ‐ Linking Statistics to Game Outcomes},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10941},
    doi = {10.1002/wilm.10941},
    pages = {32--39},
    year = {2021},
    abstract = {Common uses of win probability and how win probability can be used to evaluate the overall impact of NBA players by wins added to their respective teams.},
    }

  • A. Swishchuk, A. Roldan‐Contreras, E. Soufiani, G. Martinez, M. Selfi, N. Agrawal, and Y. Yao, “Alternatives to black‐76 model for options valuations of futures contracts,” Wilmott, vol. 2021, iss. 114, p. 40–49, 2021.
    [Bibtex] [Abstract]

    In this paper, we propose some alternatives to the Black‐76 model to the value European options on figures contracts in which the underlying market prices can be negative or/and mean‐reverting. We specifically consider two models, namely Ornstein‐Uhlenbck (OU), for negative prices, and continuous‐time GARCH (or inhomogeneous geometric Brownian motion), for positive prices. We then analyze the results and compare them with Black‐76, the most commonly used model, when the underlying market prices are positive. Numerical examples are presented using WTI and NYMEX NG datasets.

    @article {WILM:WILM10942,
    author = {Swishchuk, Anatoliy and Roldan‐Contreras, Ana and Soufiani, Elham and Martinez, Guillermo and Selfi, Mohsen and Agrawal, Nishant and Yao, Yao},
    title = {Alternatives to Black‐76 Model for Options Valuations of Futures Contracts},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10942},
    doi = {10.1002/wilm.10942},
    pages = {40--49},
    year = {2021},
    abstract = {In this paper, we propose some alternatives to the Black‐76 model to the value European options on figures contracts in which the underlying market prices can be negative or/and mean‐reverting. We specifically consider two models, namely Ornstein‐Uhlenbck (OU), for negative prices, and continuous‐time GARCH (or inhomogeneous geometric Brownian motion), for positive prices. We then analyze the results and compare them with Black‐76, the most commonly used model, when the underlying market prices are positive. Numerical examples are presented using WTI and NYMEX NG datasets.},
    }

  • A. Kondratyev, “Non‐differentiable leaning of quantum circuit born machine with genetic algorithm,” Wilmott, vol. 2021, iss. 114, p. 50–61, 2021.
    [Bibtex] [Abstract]

    The Quantum Circuit Born Machine (QCBM) is a generative quantum machine learning model that can be efficiently trained and run on the NISQ‐era quantum processors. It is likely that QCBM will be one of the first quantum machine learning models to find productive applications in quantitative finance as a powerful market generator. In this paper we test QCBM performance on a dataset of spot FX log‐returns (heavy‐tailed distribution) as well as specially constructed mixture of Normal distributions (which models spiky light‐tailed distribution). The QCBM has greater expressive power than comparable classical neural networks such as restricted Boltzmann machine (RBM) and, therefore, has potential to demonstrate quantum advantage by generating high‐quality samples from the learned empirical distribution of the market risk factors while using less computational resources than its classical counterpart. However, efficient training of QCBM remains a challenging problem. Traditional differentiable learning approach may not work well when the loss function is highly non‐smooth. In such cases it may be more efficient to use the non‐differentiable learning methods. This paper proposes a non‐differentiable learning approach to the training of QCBM based on genetic glgorithm (GA). The paper also presents results of the numerical experiments which compare performance of QCBM trained with GA against performance of the equivalent classical RBM and investigates the question of GA convergence as a function of QCBM architecture and the choice of algorithm's hyperparameters.

    @article {WILM:WILM10943,
    author = {Kondratyev, Alex},
    title = {Non‐Differentiable Leaning of Quantum Circuit Born Machine with Genetic Algorithm},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10943},
    doi = {10.1002/wilm.10943},
    pages = {50--61},
    keywords = {generative models, quantum circuit Born machine, genetic algorithm, restricted Boltzmann machine, parametrized quantum circuit},
    year = {2021},
    abstract = {The Quantum Circuit Born Machine (QCBM) is a generative quantum machine learning model that can be efficiently trained and run on the NISQ‐era quantum processors. It is likely that QCBM will be one of the first quantum machine learning models to find productive applications in quantitative finance as a powerful market generator. In this paper we test QCBM performance on a dataset of spot FX log‐returns (heavy‐tailed distribution) as well as specially constructed mixture of Normal distributions (which models spiky light‐tailed distribution). The QCBM has greater expressive power than comparable classical neural networks such as restricted Boltzmann machine (RBM) and, therefore, has potential to demonstrate quantum advantage by generating high‐quality samples from the learned empirical distribution of the market risk factors while using less computational resources than its classical counterpart.
    However, efficient training of QCBM remains a challenging problem. Traditional differentiable learning approach may not work well when the loss function is highly non‐smooth. In such cases it may be more efficient to use the non‐differentiable learning methods. This paper proposes a non‐differentiable learning approach to the training of QCBM based on genetic glgorithm (GA). The paper also presents results of the numerical experiments which compare performance of QCBM trained with GA against performance of the equivalent classical RBM and investigates the question of GA convergence as a function of QCBM architecture and the choice of algorithm's hyperparameters.},
    }

  • K. Feldman, “Analytic calibration in andreasen‐huge sabr model,” Wilmott, vol. 2021, iss. 114, p. 62–69, 2021.
    [Bibtex] [Abstract]

    We derive analytic formulae which link alpha, nu and rho parameters in Andreasen‐Huge‐style SABR model to the ATM price and option prices at four strikes close to ATM. Based on these formulae we give a characterization for the SABR parameters in terms of derivatives of the swap rate forward probability density function. We test the analytic result in the application to the interest rate futures option market.

    @article {WILM:WILM10944,
    author = {Feldman, Konstantin},
    title = {Analytic Calibration in Andreasen‐Huge SABR Model},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10944},
    doi = {10.1002/wilm.10944},
    pages = {62--69},
    keywords = {swaptions, IR futures options, implied volatility, SABR model, local volatility, one‐time‐step finite difference},
    year = {2021},
    abstract = {We derive analytic formulae which link alpha, nu and rho parameters in Andreasen‐Huge‐style SABR model to the ATM price and option prices at four strikes close to ATM. Based on these formulae we give a characterization for the SABR parameters in terms of derivatives of the swap rate forward probability density function. We test the analytic result in the application to the interest rate futures option market.},
    }

  • M. Radley, “Cars,” Wilmott, vol. 2021, iss. 114, p. 70–71, 2021.
    [Bibtex] [Abstract]

    Audi joins the all‐electric luxury GT class, with a little help from one of its friends.

    @article {WILM:WILM10945,
    author = {Radley, Milford},
    title = {Cars},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10945},
    doi = {10.1002/wilm.10945},
    pages = {70--71},
    year = {2021},
    abstract = {Audi joins the all‐electric luxury GT class, with a little help from one of its friends.},
    }

  • J. Darasz, “The skewed world of jan darasz,” Wilmott, vol. 2021, iss. 114, p. 72–72, 2021.
    [Bibtex]
    @article {WILM:WILM10946,
    author = {Darasz, Jan},
    title = {The skewed world of Jan Darasz},
    journal = {Wilmott},
    volume = {2021},
    number = {114},
    publisher = {John Wiley & Sons, Ltd},
    issn = {1541-8286},
    url = {http://dx.doi.org/10.1002/wilm.10946},
    doi = {10.1002/wilm.10946},
    pages = {72--72},
    year = {2021},
    }

More information about Wilmott magazine, for potential subscribers and submission of articles and research papers, can be found here.