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Forecasting Portfolio Risk in Normal and Stressed Markets

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  • Vineer Bhansali
  • Mark B. Wise

Abstract

The instability of historical risk factor correlations renders their use in estimating portfolio risk extremely questionable. In periods of market stress correlations of risk factors have a tendency to quickly go well beyond estimated values. For instance, in times of severe market stress, one would expect with certainty to see the correlation of yield levels and credit spreads go to -1, even though historical estimates will miss this region of correlation. This event might lead to realized portfolio risk profile substantially different from what was initially estimated. The purpose of this paper is to explore the correlation driven effects on fixed income portfolio risks. To achieve this, we propose a methodology to estimate portfolio risks in both normal and stressed times using confidence weighted forecast correlations.

Suggested Citation

  • Vineer Bhansali & Mark B. Wise, 2001. "Forecasting Portfolio Risk in Normal and Stressed Markets," Papers nlin/0108022, arXiv.org, revised Sep 2001.
  • Handle: RePEc:arx:papers:nlin/0108022
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    References listed on IDEAS

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    1. Arturo Estrella & Frederic S. Mishkin, 1996. "The yield curve as a predictor of U.S. recessions," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 2(Jun).
    2. Middleton, Elliott, 1986. "Some Testable Implications of a Preference for Subjective Novelty," Kyklos, Wiley Blackwell, vol. 39(3), pages 397-418.
    3. D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541.
    4. Estrella, Arturo, 1998. "A New Measure of Fit for Equations with Dichotomous Dependent Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 198-205, April.
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    Cited by:

    1. Yu, Philip L.H. & Li, W.K. & Ng, F.C., 2014. "Formulating hypothetical scenarios in correlation stress testing via a Bayesian framework," The North American Journal of Economics and Finance, Elsevier, vol. 27(C), pages 17-33.
    2. Y. Malevergne & D. Sornette, 2002. "Investigating Extreme Dependences: Concepts and Tools," Papers cond-mat/0203166, arXiv.org.
    3. Linda Allen & Anthony Saunders, 2004. "Incorporating Systemic Influences Into Risk Measurements: A Survey of the Literature," Journal of Financial Services Research, Springer;Western Finance Association, vol. 26(2), pages 161-191, October.
    4. Alessio Caldarera & Celso Brunetti, 2005. "Asset Prices and Asset Correlations in Illiquid Markets," 2005 Meeting Papers 288, Society for Economic Dynamics.
    5. So, Mike K.P. & Wong, Jerry & Asai, Manabu, 2013. "Stress testing correlation matrices for risk management," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 310-322.
    6. Alejandro Reveiz Herault, 2008. "The Factor-Portfolios Approach to Asset Management using Genetic Algorithms," BORRADORES DE ECONOMIA 004626, BANCO DE LA REPÚBLICA.
    7. Paraschiv, Florentina & Mudry, Pierre-Antoine & Andries, Alin Marius, 2015. "Stress-testing for portfolios of commodity futures," Economic Modelling, Elsevier, vol. 50(C), pages 9-18.

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