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On the Relationship Between the Conditional Mean and Volatility of Stock Returns: A Latent VAR Approach

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  • Michael W. Brandt
  • Qiang Kang
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    Abstract

    We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads to pronounced counter-cyclical variation in the Sharpe ratio. We document significant lead-lag correlations between the conditional moments that also appear related to business cycles. Finally, we show that although the conditional correlation between the mean and volatility is negative, the unconditional correlation is positive due to the lead-lag correlations.

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    Bibliographic Info

    Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 9056.

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    Date of creation: Jul 2002
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    Publication status: published as Brandt, Michael W. and Qiang Kang. "On The Relationship Between Conditional Mean And Volatility Of Stock Returns: A Latent VAR Approach," Journal of Financial Economics, 2004, v72(2,May), 217-257.
    Handle: RePEc:nbr:nberwo:9056

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    Cited by:
    1. Tim Bollerslev & Hao Zhou, 2003. "Volatility puzzles: a unified framework for gauging return-volatility regressions," Finance and Economics Discussion Series 2003-40, Board of Governors of the Federal Reserve System (U.S.).
    2. Ravi Bansal & Varoujan Khatchatrian & Amir Yaron, 2004. "Interpretable Asset Markets?," 2004 Meeting Papers 136b, Society for Economic Dynamics.

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