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Correlation risk

Author

Listed:
  • Krishnan, C.N.V.
  • Petkova, Ralitsa
  • Ritchken, Peter

Abstract

Investors hold portfolios of assets with different risk-reward profiles for diversification benefits. Conditional on the volatility of assets, diversification benefits can vary over time depending on the correlation structure among asset returns. The correlation of returns between assets has varied substantially over time. To insure against future "low diversification" states, investors might demand securities that offer higher payouts in these states. If this is the case, then investors would pay a premium for securities that perform well in regimes in which the correlation is high. We empirically test this hypothesis and find that correlation carries a significantly negative price of risk, after controlling for asset volatility and other risk factors.

Suggested Citation

  • Krishnan, C.N.V. & Petkova, Ralitsa & Ritchken, Peter, 2009. "Correlation risk," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 353-367, June.
  • Handle: RePEc:eee:empfin:v:16:y:2009:i:3:p:353-367
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    3. Bethke, Sebastian & Kempf, Alexander & Trapp, Monika, 2013. "The correlation puzzle: The interaction of bond and risk correlation," CFR Working Papers 13-06, University of Cologne, Centre for Financial Research (CFR).
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    6. Gribisch, Bastian, 2013. "A latent dynamic factor approach to forecasting multivariate stock market volatility," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79823, Verein für Socialpolitik / German Economic Association.
    7. Paul De Grauwe & Zhaoyong Zhang & Kin-Yip Ho & Yanlin Shi & Zhaoyong Zhang, 2016. "It takes two to tango: A regime-switching analysis of the correlation dynamics between the mainland Chinese and Hong Kong stock markets," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(1), pages 41-65, February.
    8. Stephan Süss, 2012. "The pricing of idiosyncratic risk: evidence from the implied volatility distribution," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(2), pages 247-267, June.
    9. Dominik Wied & Daniel Ziggel & Tobias Berens, 2013. "On the application of new tests for structural changes on global minimum-variance portfolios," Statistical Papers, Springer, vol. 54(4), pages 955-975, November.
    10. Sylvia Gottschalk, 2016. "Entropy and credit risk in highly correlated markets," Papers 1604.07042, arXiv.org.
    11. Jacobs, Michael & Karagozoglu, Ahmet K., 2014. "On the characteristics of dynamic correlations between asset pairs," Research in International Business and Finance, Elsevier, vol. 32(C), pages 60-82.
    12. Lindaas, Knut F. & Simlai, Prodosh, 2014. "The value premium, aggregate risk innovations, and average stock returns," Finance Research Letters, Elsevier, vol. 11(3), pages 303-317.
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    14. Dror Y. Kenett & Xuqing Huang & Irena Vodenska & Shlomo Havlin & H. Eugene Stanley, 2014. "Partial correlation analysis: Applications for financial markets," Papers 1402.1405, arXiv.org.
    15. Dominik Wied & Matthias Arnold & Nicolai Bissantz & Daniel Ziggel, 2013. "Über die Anwendbarkeit eines neuen Fluktuationstests für Korrelationen auf Finanzzeitreihen," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 6(3), pages 87-103, March.
    16. Dominik Wied & Matthias Arnold & Nicolai Bissantz & Daniel Ziggel, 2012. "A new fluctuation test for constant variances with applications to finance," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(8), pages 1111-1127, November.
    17. Gottschalk, Sylvia, 2017. "Entropy measure of credit risk in highly correlated markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 478(C), pages 11-19.
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    19. Lee, Hsiang-Tai, 2010. "Regime switching correlation hedging," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2728-2741, November.

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