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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.

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File URL: http://www.tandfonline.com/doi/abs/10.1080/713665877
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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Quantitative Finance.

Volume (Year): 1 (2001)
Issue (Month): 5 ()
Pages: 542-551

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Handle: RePEc:taf:quantf:v:1:y:2001:i:5:p:542-551

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Cited by:
  1. Cathy Chen & Simon Lin & Philip Yu, 2012. "Smooth Transition Quantile Capital Asset Pricing Models with Heteroscedasticity," Computational Economics, Society for Computational Economics, vol. 40(1), pages 19-48, June.
  2. Szafarz, Ariane & Chapelle, Ariane & Brière, Marie, 2012. "No contagion, only globalization and flight to quality," Economics Papers from University Paris Dauphine 123456789/7746, Paris Dauphine University.
  3. 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.
  4. Szego, Giorgio, 2002. "Measures of risk," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1253-1272, July.
  5. Ramaprasad Bhar, 2010. "Stochastic Filtering With Applications In Finance:," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 7736.
  6. Szego, Giorgio, 2005. "Measures of risk," European Journal of Operational Research, Elsevier, vol. 163(1), pages 5-19, May.
  7. Tjøstheim, Dag & Hufthammer, Karl Ove, 2013. "Local Gaussian correlation: A new measure of dependence," Journal of Econometrics, Elsevier, vol. 172(1), pages 33-48.
  8. Szafarz, Ariane & Brière, Marie, 2008. "Crisis-Robust Bond Portfolios," Economics Papers from University Paris Dauphine 123456789/7748, Paris Dauphine University.
  9. Alexeev, Vitali & Dungey, Mardi, 2013. "Equity portfolio diversification with high frequency data," Working Papers 2013-18, University of Tasmania, School of Economics and Finance, revised 01 Nov 2013.
  10. 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.
  11. Mittnik, Stefan, 2014. "VaR-implied tail-correlation matrices," Economics Letters, Elsevier, vol. 122(1), pages 69-73.
  12. 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.
  13. Demirer, Rıza & Jategaonkar, Shrikant P., 2013. "The conditional relation between dispersion and return," Review of Financial Economics, Elsevier, vol. 22(3), pages 125-134.
  14. Yang, J-H.S. & Satchell, S.E., 2003. "Endogenous Correlation," Cambridge Working Papers in Economics 0321, Faculty of Economics, University of Cambridge.
  15. Y. Malevergne & D. Sornette, 2002. "Investigating Extreme Dependences: Concepts and Tools," Papers cond-mat/0203166, arXiv.org.

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