Computational aspects of portfolio risk estimation in volatile markets: A survey

Frank J. Fabozzi; Stoyan V. Stoyanov; Svetlozar T. Rachev

doi:10.1515/snde-2012-0004

Computational aspects of portfolio risk estimation in volatile markets: A survey

Frank J. Fabozzi, Stoyan V. Stoyanov, Svetlozar T. Rachev

Mathematics and Statistics

Research output: Contribution to journal › Review article › peer-review

Abstract

Portfolio risk estimation requires appropriate modeling of fat-tails and asymmetries in dependence in combination with a true downside risk measure. In this survey, we discuss computational aspects of a Monte Carlo based framework for risk estimation and risk capital allocation. We review different probabilistic approaches focusing on practical aspects of statistical estimation and scenario generation. We discuss value-at-risk and conditional value-at-risk and comment on the implications of using a fat-tailed Monte Carlo framework for the reliability of risk estimates including model risk and Monte Carlo variability.

Original language	English
Pages (from-to)	103-120
Number of pages	18
Journal	Studies in Nonlinear Dynamics and Econometrics
Volume	17
Issue number	1
DOIs	https://doi.org/10.1515/snde-2012-0004
State	Published - Feb 2013

Keywords

Conditional value at risk
Copula
Fat-tailed models
Monte Carlo
Value at risk

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10.1515/snde-2012-0004

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