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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.

    (College of Business and Department of Applied Mathematics and Statistics, Stony Brook University, NY, USA FinAnalytica, Heavy Engineering S250, Stony Brook, NY 11794, USA)

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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