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The Risk of Individual Stocks’ Tail Dependence with the Market and Its Effect on Stock Returns

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Listed:
  • Guobin Fan
  • Eric Girardin
  • Wong K. Wong
  • Yong Zeng

Abstract

Traditional beta is only a linear measure of overall market risk and places equal emphasis on upside and downside risks, but actually the latter is always much stronger probably due to the trading mechanism like short-sale constraints. Therefore, this paper employs the nonlinear measure, tail dependence, to measure the extreme downside risks that individual stocks crash together with the whole market and investigates whether such tail dependence risks will affect stock returns. Our empirical evidence based on Shanghai A shares confirms that most stocks display nonnegligible tail dependence with the whole market, and, more importantly, such tail dependence risks can indeed provide additional information beyond beta and other factors for asset pricing. In cross-sectional regression, it is proved that this tail dependence does help to explain monthly returns on Shanghai A shares, whereas the time-series regression further indicates that mimicking portfolio returns for tail dependence can capture strong common variation of Shanghai A stock returns.

Suggested Citation

  • Guobin Fan & Eric Girardin & Wong K. Wong & Yong Zeng, 2015. "The Risk of Individual Stocks’ Tail Dependence with the Market and Its Effect on Stock Returns," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-17, November.
  • Handle: RePEc:hin:jnddns:980768
    DOI: 10.1155/2015/980768
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    References listed on IDEAS

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