Stochastic Models for Risk Estimation in Volatile Markets: A Survey
22 Pages Posted: 24 Dec 2010
Date Written: October 24, 2008
Portfolio risk estimation in volatile markets requires employing fat-tailed models for financial returns combined with copula functions to capture asymmetries in dependence and an appropriate downside risk measure. 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 capital allocation with the average value-at-risk measure (AVaR). AVaR is the average loss provided that the loss is larger than a predefined Value-at-Risk level. We consider in some detail the AVaR calculation and estimation and investigate the stochastic stability.
Keywords: Fat-Tailed Distributions, Stable Distributions, Downside Risk, Average Value-at-Risk, Conditional Value-at-Risk, Risk Budgeting
JEL Classification: G32, C16, C61
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