Overview

Written in a highly accessible style, A Factor Model Approach to Derivative Pricing lays a clear and structured foundation for the pricing of derivative securities based upon simple factor model related absence of arbitrage ideas. This unique and unifying approach provides for a broad treatment of topics and models, including equity, interest-rate, and credit derivatives, as well as hedging and tree-based computational methods, but without reliance on the heavy prerequisites that often accompany such topics. Whether being used as text for an intermediate level course in derivatives, or by researchers and practitioners who are seeking a better understanding of the fundamental ideas that underlie derivative pricing, readers will appreciate the book’s ability to unify many disparate topics and models under a single conceptual theme.

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9781498763325

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Reviews

The approach that the author has taken should provide a new insight for derivative pricing, which is quite useful to learn the topic for students entering graduate studies or starting senior undergraduate projects. In particular, the book is recommended for students with engineering background as well as those in business schools. -Yuji Yamada, Professor and Chair of Master's Program in Systems Management, Faculty of Business Sciences, University of Tsukuba, Japan This book will be of tremendous help to those who either are new to the field and unsure where to start, or have started but are frustrated by not being able to apply what they learn. This is one of a kind book that provides a step by step recipe for developing the broadest possible set of derivating pricing models with the minimum reliance on sophisticated mathematical analysis. The style of the book is truly educational also - not only does it provide intuition behind every use of mathematics, but it also ensures the intuitions are coherent. The factor model approach not only simplifies the steps of derivations, but I believe provides also a great opportunity for students with or without finance background to appreciate the beauty of this fundamental model in finance. Well thought-out exercises are provided in each chapter, which makes the book a great choice for advanced undergraduate or graduate courses. -Jonathan Yu-Meng Li, Assistant Professor of Risk Management, University of Ottawa, Canada

The approach that the author has taken should provide a new insight for derivative pricing, which is quite useful to learn the topic for students entering graduate studies or starting senior undergraduate projects. In particular, the book is recommended for students with engineering background as well as those in business schools. -Yuji Yamada, Professor and Chair of Master's Program in Systems Management, Faculty of Business Sciences, University of Tsukuba, Japan This book will be of tremendous help to those who either are new to the field and unsure where to start, or have started but are frustrated by not being able to apply what they learn. This is one of a kind book that provides a step by step recipe for developing the broadest possible set of derivating pricing models with the minimum reliance on sophisticated mathematical analysis. The style of the book is truly educational also - not only does it provide intuition behind every use of mathematics, but it also ensures the intuitions are coherent. The factor model approach not only simplifies the steps of derivations, but I believe provides also a great opportunity for students with or without finance background to appreciate the beauty of this fundamental model in finance. Well thought-out exercises are provided in each chapter, which makes the book a great choice for advanced undergraduate or graduate courses. -Jonathan Yu-Meng Li, Assistant Professor of Risk Management, University of Ottawa, Canada

Author Information

James A. Primbs holds undergraduate degrees in Mathematics and Electrical Engineering from UC Davis, an MS degree in Electrical Engineering from Stanford, and a PhD in Control and Dynamical System from Caltech. From 2001-2012 he served as an Assistant and then a Consulting Associate Professor in the Management Science and Engineering department at Stanford University. From 2012 to 2014 he was an Associate Professor in the Systems Engineering department at UT Dallas. He is currently an Associate Professor of Finance in the Mihaylo College of Business and Economics at California State University, Fullerton. He has won teaching awards at both the undergraduate and graduate level, given short courses to and consulted for the financial industry, and organized numerous conference tutorials and workshops, especially in the application of systems and control methods to finance. He is active in INFORMS where he has held various officer positions in the Section on Finance. His research interests involve the use of systems, optimization, and control theory in finance.

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