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Risk factor beta conditional value-at-risk

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  • Andrei Semenov

    (Department of Economics, York University, Toronto, Ontario, Canada)

Abstract

We propose a new approach to the estimation of the portfolio Value-at-Risk. Based on the assumption that the same macroeconomic factors affect returns of all assets in a portfolio, this methodology allows the generation of the sequence of hypothetical future equilibrium portfolio returns given the historical values of the underlying macroeconomic factors and the asset betas with respect to these factors. Value-at-Risk is then found as an appropriate percentile of the corresponding hypothetical distribution of the portfolio profits and losses. The backtesting results for the six Fama-French benchmark portfolios and the S&P500 index show that this approach yields reasonably accurate estimates of the portfolio Value-at-Risk. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • Andrei Semenov, 2009. "Risk factor beta conditional value-at-risk," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(6), pages 549-558.
    • Handle: RePEc:jof:jforec:v:28:y:2009:i:6:p:549-558
    DOI: 10.1002/for.1116
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    References listed on IDEAS

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    1. Saita, Francesco, 2007. "Value at Risk and Bank Capital Management," Elsevier Monographs, Elsevier, edition 1, number 9780123694669.
    2. Travis Sapp & Ashish Tiwari, 2004. "Does Stock Return Momentum Explain the "Smart Money" Effect?," Journal of Finance, American Finance Association, vol. 59(6), pages 2605-2622, December.
    3. Christoffersen, Peter, 2011. "Elements of Financial Risk Management," Elsevier Monographs, Elsevier, edition 2, number 9780123744487.
    4. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    5. Robert Kosowski & Allan Timmermann & Russ Wermers & Hal White, 2006. "Can Mutual Fund “Stars” Really Pick Stocks? New Evidence from a Bootstrap Analysis," Journal of Finance, American Finance Association, vol. 61(6), pages 2551-2595, December.
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    Cited by:

    1. Stavros Degiannakis & Pamela Dent & Christos Floros, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," Manchester School, University of Manchester, vol. 82(1), pages 71-102, January.
    2. Degiannakis, Stavros & Floros, Christos & Dent, Pamela, 2013. "Forecasting value-at-risk and expected shortfall using fractionally integrated models of conditional volatility: International evidence," International Review of Financial Analysis, Elsevier, vol. 27(C), pages 21-33.
    3. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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