Stochastic models for risk estimation in volatile markets: a survey

Abstract The problem of portfolio risk estimation in volatile markets requires employing fat-tailed models for financial instrument returns combined with copula functions to capture asymmetries in dependence and a true downside risk measure for risk estimation. In this survey, we discuss how these three essential components can be combined together in a Monte Carlo based framework for risk estimation and risk budgeting with the average value-at-risk measure (AVaR). We consider in detail the questions of AVaR calculation and estimation and also stochastic stability of AVaR when combined with heavy-tailed scenarios. Keywords fat-tailed distributions

• Type: Journal
• Year: 2010
• Where: ANOR
• Authors: Stoyan V. Stoyanov, Borjana Racheva-Iotova, Svetlozar T. Rachev, Frank J. Fabozzi
• Keywords: ANOR 2010, Downside Risk, Portfolio Risk Estimation, Risk Estimation