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

Author

Listed:
  • Fabozzi Frank J.

    (EDHEC Business School, 393, Promenade des Anglais, BP 3116, 06202 Nice Cedex 3, France)

  • Stoyanov Stoyan V.

    (EDHEC Business School, EDHEC-Risk Institute–Asia, 1, George Street, #07-02, Singapore 049145)

  • Rachev Svetlozar T.

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.

Suggested Citation

  • Fabozzi Frank J. & Stoyanov Stoyan V. & Rachev Svetlozar T., 2013. "Computational aspects of portfolio risk estimation in volatile markets: a survey," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 103-120, February.
    • Handle: RePEc:bpj:sndecm:v:17:y:2013:i:1:p:103-120:n:1
    DOI: 10.1515/snde-2012-0004
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    References listed on IDEAS

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