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Recent years have witnessed a growing importance of quantitative methods in both financial research and industry. This development requires the use of advanced techniques on a theoretical and applied level, especially when it comes to the quantification of risk and the valuation of modern financial products. Applied Quantitative Finance (2nd edition) provides a comprehensive and state-of-the-art treatment of cutting-edge topics and methods. It provides solutions to and presents theoretical developments in many practical problems such as risk management, pricing of credit derivatives, quantification of volatility and copula modelling. The synthesis of theory and practice supported by computational tools is reflected in the selection of topics as well as in a finely tuned balance of scientific contributions on practical implementation and theoretical concepts. This linkage between theory and practice offers theoreticians insights into considerations of applicability and, vice versa, provides practitioners comfortable access to new techniques in quantitative finance. Themes that are dominant in current research and which are presented in this book include among others the valuation of Collaterized Debt Obligations (CDOs), the high-frequency analysis of market liquidity, the pricing of Bermuda options and realized volatility. All Quantlets for the calculation of the given examples are downloadable from the Springer web pages.
List of contents
Value at Risk.- Modeling Dependencies with Copulae.- Quantification of Spread Risk by Means of Historical Simulation.- A Copula-Based Model of the Term Structure of CDO Tranches.- VaR in High Dimensional Systems - a Conditional Correlation Approach.- Credit Risk.- Rating Migrations.- Cross- and Autocorrelation in Multi-Period Credit Portfolio Models.- Risk Measurement with Spectral Capital Allocation.- Valuation and VaR Computation for CDOs Using Stein's Method.- Implied Volatility.- Least Squares Kernel Smoothing of the Implied Volatility Smile.- Numerics of Implied Binomial Trees.- Application of Extended Kalman Filter to SPD Estimation.- Stochastic Volatility Estimation Using Markov Chain Simulation.- Measuring and Modeling Risk Using High-Frequency Data.- Valuation of Multidimensional Bermudan Options.- Econometrics.- Multivariate Volatility Models.- The Accuracy of Long-term Real Estate Valuations.- Locally Time Homogeneous Time Series Modelling.- Simulation Based Option Pricing.- High-Frequency Volatility and Liquidity.- Statistical Process Control in Asset Management.- Canonical Dynamics Mechanism of Monetary Policy and Interest Rate.
About the author
Wolfgang Härdle is a professor of statistics at the Humboldt-Universität zu Berlin and director of C.A.S.E. the Centre for Applied Statistics and Economics. He teaches quantitative finance and semiparametric statistical methods. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected ISI member and advisor to the Guanghua School of Management, Peking University and to National Central University, Taiwan.
Report
From the reviews of the second edition:
"The second edition ... compared with the first, has widened the scope of the overall message and topics. ... have also included more up-to-date data. ... designed for students and researchers who want to develop a professional skill in modern quantitative applications in finance. ... The aim is to make the course readable for graduate students in financial engineering but also to those who are newcomers to quantitative finance and who want to get a grip on modern statistical tools in financial data analysis." (Richard Kirby, The Mathematical Association of America, September, 2009)
