Applied Quantitative Finance

ISBN 13: 9783540691778

Applied Quantitative Finance

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9783540691778: Applied Quantitative Finance

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.

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"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)

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