Description
Book SynopsisThis book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so 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.
Trade ReviewFrom 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)
Table of ContentsFinancial Markets and Financial Time Series.- Statistical Properties of Financial Market Data.- Functioning of Financial Markets and Theoretical Models for Returns.- Econometric Modeling of Asset Returns.- Modeling Volatility.- Modeling Higher Moments.- Modeling Correlation.- Extreme Value Theory.- Applications of Non-Gaussian Econometrics.- Risk Management and VaR.- Portfolio Allocation.- Option Pricing with Non-Gaussian Returns.- Fundamentals of Option Pricing.- Non-structural Option Pricing.- Structural Option Pricing.- Appendices on Option Pricing Mathematics.- Brownian Motion and Stochastic Calculus.- Martingale and Changing Measure.- Characteristic Functions and Fourier Transforms.- Jump Processes.- Lévy Processes.
