9th Symposium on Finance, Banking, and Insurance
Universität Karlsruhe (TH), Germany, December 11 - 13, 2002

Abstract

STABLE MODELING OF VALUE AT RISK

Irina Khindanova, Svetlozar Rachev and Eduardo Schwartz

University of California, Santa Barbara
University of Karlsruhe, Germany
University of California, Los Angeles

The Value-at-Risk (VAR) measurements are widely applied to estimate exposure to market risks. The traditional approaches to VAR computations - the variance- covariance method, historical simulation, Monte Carlo simulation, and stress-testing - do not provide satisfactory evaluation of possible losses. In this paper we analyze the use of stable Paretian distributions in VAR modeling.