Peter Carr Gedenkschrift

Peter Carr Gedenkschrift

彼得·卡尔纪念文集：数学金融研究进展
政治经济学

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作者

Jarrow Robert et al.

出版社

World Scientific Publishing

出版时间

2023年11月10日

装帧

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ＩＳＢＮ

9789811280290

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400 pp

语种

英文

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This Gedenkschrift for Peter Carr, our dear friend and colleague who suddenly left us on March 1, 2022, was organized to honor the life and lasting contributions of Peter to Quantitative Finance. A group of Peter’s co-authors and professional friends contributed chapters for this Gedenkschrift shortly after his passing. The papers were received by September 15, 2022 and some were presented at the Peter Carr Gedenkschrift Conference held at the Robert H Smith School of Business on November 11, 2022. The contributed papers cover a wide range of topics corresponding to the vast range of Peter’s interests. Each paper represents new research results in recognition of Peter’s scholarly activities. The book serves as an important marker for the research knowledge existing at the time of the Gedenkschrift’s publication on a number of topics within quantitative finance. It reflects the diverse interactions between mathematics and finance and illustrates, for those interested, the breadth and depth of this development. The book also presents a collection of tributes to Peter from family and friends including those made at his Memorial Service on March 19, 2022. The result is hopefully a more complete testament to a personal and professional life well lived, and unexpectedly cut short.Key Feature: oGedenkschrift for Peter Carr that would be of interest to participants of the Quantitative Finance Community, reader of his writings and people who had interacted with him

Preface; Introduction; Tributes and Pictures: Tributes; Pictures and Statements; Papers Presented at the Peter Carr Gedenkschrift Conference: Backtestability and the Ridge Backtest (Carlo Acerbi and Balazs Szekely); A Deep Learning Scheme for Solving Fully Nonlinear Partial Differential Equation (Maxim Bichuch and Ke Chen); Data-Driven Non-Parametric Robust Control under Dependence Uncertainty (Erhan Bayraktar and Tao Chen); Option Pricing Generators (Peter Carr and Umberto Cherumbini); Representation for Martingales Living after a Random Time with Applications (Tahir Choulli and Ferdoos Alharbi); Derivatives’ Risks as Costs in a One-Period Network Model (Dorinel Bastide, Stéphane Crépey, Samuel Drapeau, and Mekonnen Tadese); Approximation with Independent Variables (Freddy Delbaen and Chitro Majumdar); Pricing Autocallables under Local-Stochastic Volatility (Walter Farkas, Francesco Ferrari and Urban Ulrych); Not All Oil Storage Shocks Are Alike: The Case of WTI during Times of COVID-19 (Helyette Geman and Yuanye Ma); Total Positivity and Relative Convexity of Option Prices (Paul Glasserman and Dan Pirjol); Supervised Deep Neural Networks (DNNs) for Pricing/Calibration of Vanilla/Exotic Options Under Various Different Processes (Tugce Karatas, Amir Oskoui, and Ali Hirsa); Asset Price 1 Bubbles, Wealth Preserving, Dominating and Replicating Trading Strategies (Robert A Jarrow and Yuxuan Liu); EMA-Type Trading Strategies Maximize Utility under Partial Information (Xiaodong Chen and Roger Lee); Option Returns (Dilip B Madan, Wim Schoutens and King Wang); Supermartingale Brenier’s Theorem with 10 Full-Marginal Constraint (Erhan Bayraktar, Shuoqing Deng and Dominykas Norgilas); Forward–Backward Stochastic Neural Networks: Deep Learning of High-Dimensional Partial Differential Equations (Maziar Raissi); How to Design a Derivatives Market? (Bastien Baldacci, Paul Jusselin and Mathieu Rosenbaum); A Moment Matching Calibration under the Bilateral Gamma Model and its Application (Jingyan Zhang and Wim Schoutens); Exploiting Arbitrage Requires Short Selling (Eckhard Platen and Stefan Tappe); Power Laws in Market Microstructure (Umut Çetin and Henri Waelbroeck); An Extension with Illustrations of the Azéma–Yor Algorithm for Solving Skorokhod Embedding Problem (Yuri Imamura and Ju-Yi Yen);

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