【华尔街系列】Optimal Mean Reversion Trading

Optimal Mean Reversion Trading: Mathematical Analysis and Practical Applications

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Optimal Mean Reversion Trading: Mathematical Analysis and Practical Applications provides a systematic study to the practical problem of optimal trading in the presence of mean-reverting price dynamics. It is self-contained and organized in its presentation, and provides rigorous mathematical analysis as well as computational methods for trading ETFs, options, futures on commodities or volatility indices, and credit risk derivatives.讲均值回归的，提供了严格的数学分析和计算办法，用于ETF，期权，期货，波动率指数和利率衍生品

This book offers a unique financial engineering approach that combines novel analytical methodologies and applications to a wide array of real-world examples. It extracts the mathematical problems from various trading approaches and scenarios, but also addresses the practical aspects of trading problems, such as model estimation, risk premium, risk constraints, and transaction costs. The explanations in the book are detailed enough to capture the interest of the curious student or researcher, and complete enough to give the necessary background material for further exploration into the subject and related literature.有提供新的金融工程办法和新的分析方法论，讲了数学，也在实践方面提供了指导，包括风险溢价、交易费用、模型评估等。时候学生党和研究人员。

This book will be a useful tool for anyone interested in financial engineering, particularly algorithmic trading and commodity trading, and would like to understand the mathematically optimal strategies in different market environments. 主要是针对金融工程人群、算法交易人群、商品交易，提供了在不同市场环境下数学最优化的均值回归策略。
作者是哥大助理教授和在美林干活的一个博士associate
About the Author
Tim Leung is an Assistant Professor at Columbia University's Industrial Engineering and Operations Research (IEOR) Department. He is also an affiliated faculty member of the Center for Financial Engineering, and Data Sciences Institute at Columbia. He received a PhD in Operations Research & Financial Engineering (ORFE) from Princeton University. Dr Leung's research areas are Financial Engineering and Optimal Stochastic Control, with a focus on the valuation of financial derivatives, and associated risk management and trading strategies. He has written extensively on exchange-traded funds (ETFs). His research has been funded by the National Science Foundation (NSF), and a Charlotte Procter Honorific Fellowship at Princeton University. He has published in various Financial Mathematics journals, including Mathematical Finance, Finance and Stochastics, SIAM Journal on Financial Mathematics, and Quantitative Finance. He is also an officer of the SIAM SIAG on Financial Mathematics and Engineering, and the INFORMS Finance Section.
Xin Li is currently an associate at Bank of America Merrill Lynch. She holds a PhD in Industrial Engineering and Operations Research (IEOR) and an MA degree in Statistics from Columbia University, as well as a BS degree in Biological Sciences and Biotechnology from Tsinghua University. Her research focuses on optimal stochastic control and optimal stopping problems in finance, with applications to pairs trading, mean reversion trading, and VIX futures portfolios. Her paper "Optimal Mean Reversion Trading with Transaction Costs and Stop-Loss Exit" won the first prize of the 2014 INFORMS Best Student Paper Award (Financial Services Section). She is also the recipient of the Class of 1988 Fellowship at Columbia University.

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