Synopses & Reviews
Building upon the ideas introduced in their previous book, Derivatives in Financial Markets with Stochastic Volatility, the authors study the pricing and hedging of financial derivatives under stochastic volatility in equity, interest-rate, and credit markets. They present and analyze multiscale stochastic volatility models and asymptotic approximations. These can be used in equity markets, for instance, to link the prices of path-dependent exotic instruments to market implied volatilities. The methods are also used for interest rate and credit derivatives. Other applications considered include variance-reduction techniques, portfolio optimization, forward-looking estimation of CAPM "beta," and the Heston model and generalizations of it. "Off-the-shelf" formulas and calibration tools are provided to ease the transition for practitioners who adopt this new method. The attention to detail and explicit presentation make this also an excellent text for a graduate course in financial and applied mathematics.
Synopsis
This book builds on previous and current research by the four authors, including results introduced in the book Derivatives in Financial Markets with Stochastic Volatility. Recent research demonstrates that the introduction of two time scales in volatility, a fast and a slow, is needed and efficient for capturing the main features of the observed term structure of implied volatility. For practitioners, the modeling of the implied volatility consistent with no-arbitrage is crucial. The authors present an approach to this problem which consists in combining singular and regular perturbation techniques. The book will serve a dual purpose: present 'off the shelf' formulas and calibration tools for practitioners, and introduce, explain and develop the mathematical framework to handle the multi-scale asymptotics. Detailed presentation of the analysis as well as a thorough insight into the modeling approach makes this an excellent text for a second level graduate course in financial and applied mathematics.
Synopsis
Building on previous and current research by the authors, including results introduced in the book Derivatives in Financial Markets with Stochastic Volatility. This book demonstrates that the introduction of fast and slow time scales in volatility, is needed for efficient capturing of the main features of the observed term structure of implied volatility. This is crucial for practitioners. Detailed presentation of the analysis as well as the modeling approach makes this an excellent text for second level graduates in financial mathematics but also as an 'off-the-shelf' reference for practitioners.
Synopsis
Follow up to authors previous book on volatility. Ideal for graduates and practitioners.
Synopsis
The authors consolidate and extend ideas from their previous book. Ideal for practitioners and as a graduate-level textbook.
Synopsis
This research monograph in financial mathematics can also be used as a graduate-level textbook. It explains financial models in which volatility of assets changes randomly over time. These are analyzed with a powerful approximation method and tested on financial data. More advanced topics are discussed in later chapters.
About the Author
Jean-Pierre Fouque studied at the University Pierre and Marie Curie in Paris. He held positions at the French CNRS and École Polytechnique, and at North Carolina State University. Since 2006, he has been Professor and Director of the Center for Research in Financial Mathematics and Statistics at the University of California, Santa Barbara.George Papanicolaou was Professor of Mathematics at the Courant Institute before moving to Stanford University in 1993. He is now Robert Grimmett Professor in the Department of Mathematics at Stanford.Ronnie Sircar taught for three years at the University of Michigan in the Department of Mathematics before moving to Princeton University in 2000. He is now a Professor in the Operations Research and Financial Engineering Department at Princeton and an affiliate member of the Bendheim Center for Finance and the Program in Applied and Computational Mathematics.Knut Sølna is a Professor in the Department of Mathematics at the University of California, Irvine. He received his undergraduate and Master's degrees from the Norwegian University of Science and Technology and his doctorate from Stanford University. He was an instructor at the Department of Mathematics, University of Utah before moving to Irvine.
Table of Contents
Introduction; 1. The Black-Scholes theory of derivative pricing; 2. Introduction to stochastic volatility models; 3. Volatility time scales; 4. First order perturbation theory; 5. Implied volatility formulas and calibration; 6. Application to exotic derivatives; 7. Application to American derivatives; 8. Hedging strategies; 9. Extensions; 10. Around the Heston model; 11. Other applications; 12. Interest rate models; 13. Credit risk I: structural models with stochastic volatility; 14. Credit risk II: multiscale intensity-based models; 15. Epilogue; Bibliography; Index.