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Cyclicality and term structure of Value-at-Risk within a threshold autoregression setup

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  • Frédérique Bec

    (THEMA - Théorie économique, modélisation et applications - CNRS - Centre National de la Recherche Scientifique - CY - CY Cergy Paris Université)

Abstract

This paper explores empirically the link between stocks returns Value-at-Risk (VaR) and the state of financial markets across various holding horizons. The econometric analysis is based on a self-exciting threshold autoregression setup. Using quarterly French and US data from 1970Q4 to 2012Q4, it turns out that the k-year VaR of equities is actually dependent on the state of the market: the expected losses as measured by the VaR are smaller in bear market than in normal or bull market, whatever the horizon. These results suggest that the rules regarding the solvency capital requirements should adapt to the state of the financial market.
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Suggested Citation

  • Frédérique Bec, 2015. "Cyclicality and term structure of Value-at-Risk within a threshold autoregression setup," Post-Print hal-02980012, HAL.
    • Handle: RePEc:hal:journl:hal-02980012
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    1. Hansen, Bruce E. & Seo, Byeongseon, 2002. "Testing for two-regime threshold cointegration in vector error-correction models," Journal of Econometrics, Elsevier, vol. 110(2), pages 293-318, October.
    2. Campbell, John Y, 1991. "A Variance Decomposition for Stock Returns," Economic Journal, Royal Economic Society, vol. 101(405), pages 157-179, March.
    3. Rochet, J C., 2008. "Procyclicality of financial systems: is there a need to modify current accounting and regulatory rules?," Financial Stability Review, Banque de France, issue 12, pages 95-99, October.
    4. Gollier, Christian, 2008. "Intergenerational risk-sharing and risk-taking of a pension fund," Journal of Public Economics, Elsevier, vol. 92(5-6), pages 1463-1485, June.
    5. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    6. Adrian, T. & Shin, H S., 2008. "Liquidity and financial contagion," Financial Stability Review, Banque de France, issue 11, pages 1-7, February.
    7. Guillaume Plantin & Haresh Sapra & Hyun Song Shin, 2008. "Marking‐to‐Market: Panacea or Pandora's Box?," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 46(2), pages 435-460, May.
    8. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
    9. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    10. Escanciano, J. Carlos & Olmo, Jose, 2010. "Backtesting Parametric Value-at-Risk With Estimation Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 36-51.
    11. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2010. "Testing for co-integration in vector autoregressions with non-stationary volatility," Journal of Econometrics, Elsevier, vol. 158(1), pages 7-24, September.
    12. Giacomini, Raffaella & White, Halbert, 2003. "Tests of Conditional Predictive Ability," University of California at San Diego, Economics Working Paper Series qt5jk0j5jh, Department of Economics, UC San Diego.
    13. J. B. Taylor & M. Woodford (ed.), 1999. "Handbook of Macroeconomics," Handbook of Macroeconomics, Elsevier, edition 1, volume 1, number 1.
    14. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    15. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, February.
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    Cited by:

    1. Frédérique Bec & Annabelle de Gaye, 2019. "Le modèle autorégressif autorégressif à seuil avec effet rebond : Une application aux rendements boursiers français et américains ," Working Papers hal-02014663, HAL.

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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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