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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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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