Stochastic models for risk estimation in volatile markets: a survey

Stoyan Stoyanov (), Borjana Racheva-Iotova (), Svetlozar Rachev () and Frank Fabozzi ()

Annals of Operations Research, 2010, vol. 176, issue 1, 293-309

Abstract: 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. Copyright Springer Science+Business Media, LLC 2010

Keywords: Fat-tailed distributions; Stable distributions; Downside risk; Average value-at-risk; Conditional value-at-risk; Risk budgeting (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (15)

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DOI: 10.1007/s10479-008-0468-1

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