Applied Quantitative Finance presents solutions, theoretical developments and method proliferation for many practical problems in quantitative finance. The combination of practice and theory supported by computational tools is reflected in the selection of topics as well as in a finely tuned balance of scientific contributions on the practical implementation and theoretical concepts. This concept offers theoreticians insight into the applicability of the methodology and, vice versa, practitioners access to new methods for their applications. The e-book design of the text links theory and computational tools in an innovative way. All "quantlets" for the calculation of given examples in the text are executable on an XploRe Quantlet Server (XQS) and can be modified by the reader via the internet. The electronic edition can be downloaded from the web site www i-xplore.de using the licence and registration number at the back cover.
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From the reviews:
"The book under review is designed for researchers who wish to develop professional skill in modern quantitative applications in finance. This electronic book will be welcomed by all who are interested in computational mathematical finance and students may derive much practical training working with the data sets and the XploRe programs. This book can be recommended to undergraduate libraries in statistics, econometrics and finance." (Ravi Sreenivasan, Journal of the Royal Statistical Society Series A: Statistics in Society, Vol. 157 (1), 2004)
From the reviews:
"The book under review ??? is designed for researchers who wish to develop professional skill in modern quantitative applications in finance. ??? This electronic book will be welcomed by all who are interested in computational mathematical finance and students may derive much practical training working with the data sets and the XploRe programs. This book can be recommended to undergraduate libraries in statistics, econometrics and finance." (Ravi Sreenivasan, Journal of the Royal Statistical Society Series A: Statistics in Society, Vol. 157 (1), 2004)
From the reviews:
"The book under review a ] is designed for researchers who wish to develop professional skill in modern quantitative applications in finance. a ] This electronic book will be welcomed by all who are interested in computational mathematical finance and students may derive much practical training working with the data sets and the XploRe programs. This book can be recommended to undergraduate libraries in statistics, econometrics and finance." (Ravi Sreenivasan, Journal of the Royal Statistical Society Series A: Statistics in Society, Vol. 157 (1), 2004)
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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