Optimal Mean Reversion Trading: Mathematical Analysis and Practical Applications
Nov 2015 · Modern Trends in Financial Engineering Book 1 · World Scientific
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About this ebook
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.
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.
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.
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 ana...
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1 review
Mark Trader
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December 29, 2019
Readership: Doctoral and master's students, advanced undergraduates, practitioners, and researchers in financial engineering, with a particular interest or specialization in algorithmic trading (especially pairs trading) and ETFs, futures, commodities, volatility derivatives and credit risk.
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About the author
Tim Leung is a professional software developer based in England. For the past 12 years, he has specialized in enterprise application development using products from the Microsoft technology stack. In particular, he possesses deep knowledge of the Microsoft.NET Framework and SQL Server. He is an active member of the U.K. developer community and often delivers presentations on technical topics. He is also a chartered member of the British Computer Society. He is passionate about the concept of rapid application development and was awarded the Microsoft Community Contributor Award in 2011 for contributions to the LightSwitch community.
Xin Li is Professor at the Cold and Arid Regions Environmental and Engineering Research Institute (CAREERI), Chinese Academy of Sciences (CAS). His primary research interests include land data assimilation, application of remote sensing and GIS in hydrology and cryosphere science, and integrated watershed study. He is currently director of the World Data Center for Glaciology and Geocryology, Chair of the working group on remote sensing of the Chinese Committee for WCRP/CliC and IUGG/IACS, co-chair of the working group on theory and method of the China Association for Geographic Information Systems, and a member of the American Geophysical Union. He is also the secretary of G-WADI Asia established by UNESCO IHP. He has published over 120 journal articles and monographs. He was recipient of the Outstanding Science and Technology Achievement Prize of the CAS in 2005, First Class Science and Technology Progress Prize of Gansu Province, and the Seventh National Award for Young Geographers in 2003.
Tim Leung is a professional software developer based in England. For the past 12 years, he has specialized in enterprise application development using products from the Microsoft technology stack. In particular, he possesses deep knowledge of the Microsoft.NET Framework and SQL Server. He is an a...
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