Overview
- Provides comprehensive coverage of financial market modeling when the distribution is non-normal
- Emphasises practical examples and real applications tailored for non-mathematicians who want to model financial market prices
- Specially designed for course use, with the necessary background mathematics provided in appendices
Part of the book series: Springer Finance (FINANCE)
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Table of contents (17 chapters)
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Front Matter
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Financial Markets and Financial Time Series
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Front Matter
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Econometric Modeling of Asset Returns
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Front Matter
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Applications of Non-Gaussian Econometrics
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Front Matter
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Option Pricing with Non-Gaussian Returns
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Front Matter
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Appendices on Option Pricing Mathematics
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Front Matter
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Keywords
About this book
Non-Gaussian distributions are the key theme of this book which addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The aim is to bridge the gap between theoretical developments and the practical implementations of what many users and researchers perceive as "sophisticated" models. The emphasis throughout is on practice: there are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series, such as exchange and interest rates.
This book will be an essential reference for practitioners in the finance industry, especially those responsible for managing portfolios and monitoring financial risk, but it will also be useful for mathematicians who want to know more about how their mathematical tools are applied in finance, and as a text for advanced courses in empirical finance; financial econometrics and financial derivatives.
Reviews
From the reviews:
"Financial Modeling Under Non-Gaussian Distributions … is thus very welcome as it provides an accessible and easy-to-understand treatment of a broad range of topics, including core material to more advanced techniques on the subject of capturing non-Gaussian properties in the distributions of asset returns. … Financial Modeling Under Non-Gaussian Distributions is a very accessible textbook that covers a wide range of topics. … The authors define their target readers as specialized master and Ph.D. students, as well as financial industry practitioners." (Stephan Suess, Financial Markets and Portfolio Management, Vol. 22, 2008)
"This book is written for non-mathematicians who want to model financial market prices. ... It targets practioners in the financial industry. It is suitable for use as core text for students in empirical finance, financial econometrics and financial derivatives. It is useful for mathematician who want to know more about their mathematical tools are applied in finance." (Klaus Ehemann, Zentralblatt MATH, Vol. 1138 (16), 2008)
Authors and Affiliations
Bibliographic Information
Book Title: Financial Modeling Under Non-Gaussian Distributions
Authors: Eric Jondeau, Ser-Huang Poon, Michael Rockinger
Series Title: Springer Finance
DOI: https://doi.org/10.1007/978-1-84628-696-4
Publisher: Springer London
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag London 2007
Hardcover ISBN: 978-1-84628-419-9Published: 23 November 2006
Softcover ISBN: 978-1-84996-599-6Published: 21 October 2010
eBook ISBN: 978-1-84628-696-4Published: 05 April 2007
Series ISSN: 1616-0533
Series E-ISSN: 2195-0687
Edition Number: 1
Number of Pages: XVIII, 541
Topics: Quantitative Finance, Statistics for Business, Management, Economics, Finance, Insurance, Econometrics