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The cross-market index for volatility surprise

Author

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  • Sofiane Aboura
  • Julien Chevallier

    (IPAG Business School (IPAG Lab))

Abstract

This article proposes a new empirical methodology for computing a cross-market volatility index – coined CMIX – based on the Factor-Dynamic Conditional Correlation (DCC) model, implemented on volatility surprises. This approach solves problems in treating high-dimensional data and estimating time-varying conditional correlations. We provide an application to multi-asset market data composed of equities, bonds, foreign exchange rates and commodities during 1983–2013. This new methodology may be attractive to asset managers, because it provides a simple way to hedge multi-asset portfolios with derivatives contracts written on the CMIX.

Suggested Citation

  • Sofiane Aboura & Julien Chevallier, 2014. "The cross-market index for volatility surprise," Journal of Asset Management, Palgrave Macmillan, vol. 15(1), pages 7-23, February.
    • Handle: RePEc:pal:assmgt:v:15:y:2014:i:1:d:10.1057_jam.2014.5
    DOI: 10.1057/jam.2014.5
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    Cited by:

    1. Jana Vychytilová, 2014. "Intermarket Technical Research of the U.S. Capital Markets and the Czech Stock Market Performance," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 62(6), pages 1509-1519.

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