@article{WILM:WILM12163,

title = {Contents},

author = {Daniel Tudball},

url = {http://dx.doi.org/10.54946/wilm.12163},

doi = {10.54946/wilm.12163},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {Contents},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12164,

title = {The World We Knew (Over and Over)},

author = {Daniel Tudball},

url = {http://dx.doi.org/10.54946/wilm.12164},

doi = {10.54946/wilm.12164},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {This backward-looking navigation creates what Osband terms 'rationally turbulent expectations' - a state where markets behave like rational learning machines forced to make constant course corrections.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12165,

title = {Conspiracy Theories Are Out to Get You!},

author = {Aaron Brown},

url = {http://dx.doi.org/10.54946/wilm.12165},

doi = {10.54946/wilm.12165},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {If you really feel the need to connect all the dots a Bayesian statistician may be more useful to you than a psychiatrist.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12166,

title = {LSM Again: Part II, Table 1},

author = {Rolf Poulsen},

url = {http://dx.doi.org/10.54946/wilm.12166},

doi = {10.54946/wilm.12166},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {Replication is possible. Replication often requires you to think. Thinking is hard.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12167,

title = {Fly High with Low Wings},

author = {Uwe Wystup},

url = {http://dx.doi.org/10.54946/wilm.12167},

doi = {10.54946/wilm.12167},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {A trip back in time to the days of the Deutschmark, with trouble waiting in the wings.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12168,

title = {Is Classical Finance Too Much of a Stretch, Part Duh},

author = {David Orrell},

url = {http://dx.doi.org/10.54946/wilm.12168},

doi = {10.54946/wilm.12168},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {What if we had access to a completely objective and scientific academic review of the original Black-Scholes paper where the referee also had access to the latest thinking in Quantum Finance?},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12169,

title = {De Rerum Natura},

author = {Rudi Bogni},

url = {http://dx.doi.org/10.54946/wilm.12169},

doi = {10.54946/wilm.12169},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {What would the great Epicurean philosopher Lucretius make of this day and age?},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12170,

title = {Why Forecasting Fails - and How Option Logic Can Fix It},

author = {T Brutman},

url = {http://dx.doi.org/10.54946/wilm.12170},

doi = {10.54946/wilm.12170},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {A practical argument for treating forecasts as dynamic expectation curves \textemdash not static targets \textemdash using option-based modeling, AI, and governance intelligence},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12171,

title = {The Great Unraveling - Part 2: Contagion and Containment},

author = {Satyajit Das},

url = {http://dx.doi.org/10.54946/wilm.12171},

doi = {10.54946/wilm.12171},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {Part 1 of this two-part series looked at the factors that may make a new financial crisis inevitable. Part 2 looks at the transmission of shocks, resilience, and the capacity to respond to contain a new emergency.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12172,

title = {A Unifying Paradigm for Finance},

author = {Kent Osband},

url = {http://dx.doi.org/10.54946/wilm.12172},

doi = {10.54946/wilm.12172},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {An alternative paradigm that is both internally consistent and better able to explain major market features rests on a simple observation: predicting future risks and rewards is hard. We can't deduce their evolution from neat physical laws. We can't sample observations from the future.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12173,

title = {Understanding Lost Civilizations and Commodity Term Structures: The Signature Method},

author = {Yasutora Ito and Hari Krishnan and Adam Mullaney and Kathleen Shiffer and Stephan Sturm},

url = {http://dx.doi.org/10.54946/wilm.12173},

doi = {10.54946/wilm.12173},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {Advanced models in NLP, finance, and pattern recognition offer superior predictions but require vast data. Pooling similar datasets enhances training, tackles complexity, and boosts model stability.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12174,

title = {Gaussian Methods for Local Stochastic Volatility},

author = {J. Kienitz},

url = {http://dx.doi.org/10.54946/wilm.12174},

doi = {10.54946/wilm.12174},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {A data-driven and model-free1 approach termed GMMR Hedge or Proxy GMM Hedge has been introduced in Kienitz (2022) and Kienitz (2023). The method uses realizations of stochastic quantities on a discrete time-grid and combines fitted Gaussian Mixture Distributions (GMM), being an established method from statistical learning, with classic analytic techniques based on the properties of the Gaussian distribution. After applying GMMR, a regression method based on Gaussian Mixture Models, to many pricing and hedging problems, we use it for the calibration/simulation of Stochastic Local Volatility models.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12175,

title = {Quantum Binomial Tree, An Effective Method for Probability Distribution Loading for Derivative Pricing},

author = {Pracht D. Gatarek},

url = {http://dx.doi.org/10.54946/wilm.12175},

doi = {10.54946/wilm.12175},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {Efficiently generating or loading probability distributions on quantum computers is a foundational task in Quantum Monte Carlo methods. While the quantum amplitude estimation algorithm offers a quadratic speed-up over classical Monte Carlo techniques, this advantage can be negated if the probability distribution is not effectively loaded. Moreover, any practical approach must be flexible enough to accommodate a wide range of market models\textemdasha requirement unmet by existing methods. In this paper, we propose a novel and efficient approach for loading probability distributions tailored to derivative pricing. The proposed method, the Quantum Binomial Tree, serves as a quantum analog of the classical Binomial Tree model. This approach enables exponential scaling in the number of Monte Carlo paths, while retaining an overall quadratic speed-up compared to classical algorithms. We demonstrate how the Quantum Binomial Tree framework can load prominent financial models\textemdashincluding the local volatility model, and the Heston model onto a quantum computer. Furthermore, this paper includes a detailed implementation for option pricing under time-dependent volatility, as well as numerical results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12176,

title = {Using Generative AI for Robust Regulatory Stress Testing},

author = {S. Ahlawat},

url = {http://dx.doi.org/10.54946/wilm.12176},

doi = {10.54946/wilm.12176},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {Periodic stress testing of systemically significant financial institutions was introduced in the aftermath of the Great Financial Crisis (GFC) of 2007\textendash2008 as part of Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010 in the United States. Since its inception, the act has mandated regulatory agencies to conduct periodic stress testing to ensure systemically important financial institutions have the requisite capital to continue functioning as viable businesses during times of economic stress without jeopardizing the stability of the financial system. The tests envision a variety of hypothetical economic scenarios unfolding over the ensuing quarters and are designed to test the adequacy of capital reserves. Because they are hypothetical, they must be comprehensive enough to encompass a range of possible economically challenging scenarios and be realistic enough to capture the evolving correlations between macroeconomic variables that are expected to unfold in those scenarios. Manual design of these scenarios using historical data, exclusively or primarily, is hamstrung by the inherent limitations of historical experience, which may be inadequate to model unforeseen economic scenarios. To further compound the problem, correlations between macroeconomic variables may change and evolve in markedly different manner during those periods of economic malaise and a manual design of testing scenarios is likely to overlook those aspects of macroeconomic variable evolution. Generative artificial intelligence has the potential to confront these challenges by providing an automated tool for generating a range of economic scenarios, encompassing stressed economic scenarios that have not been witnessed in the past. The generated scenarios hew to the patterns of evolution of macroeconomic variables consistent with correlations observed in similar scenarios from the past. This work presents variational autoencoders coupled with LSTM (long-short-memory model)-based recurrent neural networks to generate new economic scenarios and presents a qualitative assessment of their consistency. It showcases the ability of variational auto-encoders and deep neural networks to generate novel and yet realistically evolving economic scenarios to enhance the robustness of stress testing framework. With the advent of new financial products such as crypto currencies and ever-evolving technologies such as blockchain, it is imperative for financial regulators to use automated tools for scenario generation to assure market participants, investors, and public about the continuing relevance of stress testing as reliable indicators of financial wellbeing of systemically important financial institutions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12177,

title = {A Fist Full of Dollars},

author = {Satyajit Das},

url = {http://dx.doi.org/10.54946/wilm.12177},

doi = {10.54946/wilm.12177},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {Two new books by well-credentialed economists examine the role of the US dollar in international finance.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12178,

title = {Some Kind of Utopia},

author = {Milford Radley},

url = {http://dx.doi.org/10.54946/wilm.12178},

doi = {10.54946/wilm.12178},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {Pagani reminds us that back-to-basics technology makes one the most connected supercars on the planet.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{WILM:WILM12179,

title = {The Skewed World of Jan Darasz},

author = {Jan Darasz},

url = {http://dx.doi.org/10.54946/wilm.12179},

doi = {10.54946/wilm.12179},

issn = {1541-8286},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Wilmott},

volume = {2025},

number = {139},

publisher = {Wilmott Magazine, Ltd},

abstract = {Cartoon},

keywords = {},

pubstate = {published},

tppubtype = {article}

}