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Large returns, conditional correlation and portfolio diversification: a value-at-risk approach

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  • P. Silvapulle
  • C. W. J. Granger

Abstract

This paper, using daily returns on 30 Dow Jones Industrial stocks for the period 1991-1999, investigates the possibility of portfolio diversification when there are negative large movements in the stock returns (i.e. when the market is bearish). We estimate the quantiles of stock return distributions using non-parametric and parametric methods that are widely being used in measuring value-at-risk (VaR). We find that the average conditional correlation of 30 stocks is much higher when the large movements are negative than that when the market is 'usual'. Further, we find that, contrary to the results of previous studies, there is no notable difference between the average conditional correlations when the large movements are positive and when the market is 'usual'. Moreover, it is evident from the results of the conditional CAPM that the portfolio's diversifiable and non-diversifiable risks, as measured by the error variance of the CAPM and beta respectively, are highly unstable when the market is bearish than that when it is 'usual' or bullish. The overall results suggest that the possibility of portfolio diversification would be eroded when the stock market is bearish. These findings have implications for portfolio diversification and risk management in particular and for finance in general. The ideas presented in this paper can be utilized for testing contagion in the international financial markets, a much-researched topic in international finance.

Suggested Citation

  • P. Silvapulle & C. W. J. Granger, 2001. "Large returns, conditional correlation and portfolio diversification: a value-at-risk approach," Quantitative Finance, Taylor & Francis Journals, vol. 1(5), pages 542-551.
  • Handle: RePEc:taf:quantf:v:1:y:2001:i:5:p:542-551
    DOI: 10.1080/713665877
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    Citations

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    Cited by:

    1. Brière, Marie & Chapelle, Ariane & Szafarz, Ariane, 2012. "No contagion, only globalization and flight to quality," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1729-1744.
    2. repec:dau:papers:123456789/7748 is not listed on IDEAS
    3. Mittnik, Stefan, 2014. "VaR-implied tail-correlation matrices," Economics Letters, Elsevier, vol. 122(1), pages 69-73.
    4. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, Open Access Journal, vol. 4(2), pages 1-15, June.
    5. Demirer, Rıza & Jategaonkar, Shrikant P., 2013. "The conditional relation between dispersion and return," Review of Financial Economics, Elsevier, vol. 22(3), pages 125-134.
    6. Szego, Giorgio, 2002. "Measures of risk," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1253-1272, July.
    7. Vitali Alexeev & Mardi Dungey, 2015. "Equity portfolio diversification with high frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1205-1215, July.
    8. Adam, Alexandre & Houkari, Mohamed & Laurent, Jean-Paul, 2008. "Spectral risk measures and portfolio selection," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1870-1882, September.
    9. Cathy W. S. Chen & Muyi Li & Nga T. H. Nguyen & Songsak Sriboonchitta, 2017. "On Asymmetric Market Model with Heteroskedasticity and Quantile Regression," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 155-174, January.
    10. repec:dau:papers:123456789/7746 is not listed on IDEAS
    11. Yang, J-H.S. & Satchell, S.E., 2003. "Endogenous Correlation," Cambridge Working Papers in Economics 0321, Faculty of Economics, University of Cambridge.
    12. Cathy Chen & Simon Lin & Philip Yu, 2012. "Smooth Transition Quantile Capital Asset Pricing Models with Heteroscedasticity," Computational Economics, Springer;Society for Computational Economics, vol. 40(1), pages 19-48, June.
    13. Aboura, Sofiane & Wagner, Niklas, 2016. "Extreme asymmetric volatility: Stress and aggregate asset prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 47-59.
    14. Yaya, OlaOluwa S. & Gil-Alana, Luis A., 2014. "The persistence and asymmetric volatility in the Nigerian stock bull and bear markets," Economic Modelling, Elsevier, vol. 38(C), pages 463-469.
    15. Y. Malevergne & D. Sornette, 2002. "Investigating Extreme Dependences: Concepts and Tools," Papers cond-mat/0203166, arXiv.org.
    16. Szego, Giorgio, 2005. "Measures of risk," European Journal of Operational Research, Elsevier, vol. 163(1), pages 5-19, May.
    17. Kim, Woo Chang & Kim, Jang Ho & Mulvey, John M. & Fabozzi, Frank J., 2015. "Focusing on the worst state for robust investing," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 19-31.
    18. Tjøstheim, Dag & Hufthammer, Karl Ove, 2013. "Local Gaussian correlation: A new measure of dependence," Journal of Econometrics, Elsevier, vol. 172(1), pages 33-48.
    19. Bhar, Ramaprasad & Hamori, Shigeyuki, 2007. "Co-movement in the price of risk of aggregate equity markets," Economic Systems, Elsevier, vol. 31(3), pages 256-271, September.
    20. Chiu, Yen-Chen & Chuang, I-Yuan, 2016. "The performance of the switching forecast model of value-at-risk in the Asian stock markets," Finance Research Letters, Elsevier, vol. 18(C), pages 43-51.

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