Svetlozar Rachev is Chair-Professor in the School of Economics and Business Engineering at the University of Karlsruhe, and Professor Statistics and Economics at the University of California, Santa Barbara. He has published five monographs and more than 200 research articles. His research areas include mathematical and empirical finance, econometrics, probability, and statistics. He is a Fellow of the Institute of Mathematical Statistics, Elected Member of the International Statistical Institute, Foreign Member of the Russian Academy of Natural Sciences, and holds an honorary doctorate degree from ST. Petersburg Technical University.
Stefan Mittnik is Professor of Statistics and Empirical Economics at the University of Kiel and Director of the Institute of Statistics Econometrics. His academic and consulting work covers the areas of empirical finance, forecasting financial risk, portfolio management, computational finance, econometrics, and time series analysis.

"The adoption of stable modeling in finance and econometrics is undoubtedly one of the most interesting and promising ideas which has arisen in these fields. It is now widely accepted that classical models for the description of the dynamics of financial and economic variable suffer form major structural weaknesses, as they fail to explain important features of the empirical data. Therefore, the search for new more powerful models is a fundamental and fascinating topic of research. In this book, Rachev and Mittnik, two of the most prominent experts in so-called Stable Finance, present a wealth of convincing arguments to support the claim that stable models offer the right approach to the subject. Their monograph, which collects a large part of the authors' work in sable financial modeling, brings together innovative insights as well as new elegant explanations financial and economic phenomena..."
"...The book explains in a lucid and understandable manner how to extend a wide range of financial paradigms to the stable case, presenting both new theoretical results and empirical applications. The material covered is truly impressive in its breadth and quality, and will be of great interest to researchers and advanced graduate students, as well as practitioners looking for state-of-the-art models with a better fit to real data."
Eduardo S. Schwartz, Professor of Finance, Anderson School of Management, University of California

Foreword
Preface
1 Introduction
2 Univariate Stable Distributions
3 Identification, Estimation and Goodness of Fit
4 Empirical Comparison
5 Subordinated, Fractional Stable and Stable ARIMA Processes
6 ARCH-type and Shot Noise Processes
7 Multivariate Stable Models
8 Estimation, Association, Risk, and Symmetry of Stable Portfolios
9 Asset-Pricing and Portfolio Theory Under Stable Paretian Laws
10 Risk Management: Value at Risk for Heavy-Tailed Distributed Rating
11 Option Pricing Under Alternative Stable Models
12 Option Pricing for Infinitely Divisible Return Models
13 Numerical Results on Option Pricing: Modeling and Forecasting
14 Stable Models in Econometrics
15 Stable Paretian Econometrics: Unit-Root Theory and Cointegrated Models
References
Indexes
Author-Index
Subject-Index