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

Studies in Nonlinear Dynamics & Econometrics, Volume 17, Issue 1, February 2013

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.

Keywords: conditional value at risk; value at risk; copula; fat-tailed models; Monte Carlo