Stable Paretian Models in Finance
Financial Economics and Quantitative Analysis Series

The authors reconsider the problem of parametrically specifying distribution suitable for asset-return models. They describe alternative distributions, showing how they can be estimated and applied to stock-index and exchange-rate data. The implications for options pricing are also investigated.

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

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.