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Market Variance Risk Premiums in Japan as Predictor Variables and Indicators of Risk Aversion

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  • Masato Ubukata
  • Toshiaki Watanabe

Abstract

This article evaluates the predictive performance of the market variance risk premium (VRP) in Japan on the Nikkei 225 returns, credit spreads, and the composite index of coincident indicators. Different measures such as expected and ex-post VRPs, which are constructed from model-free implied and realized variances, are used to verify the predictability. Moreover, the VRP is estimated by the Bollerslev, Gibson and Zhou (2011) method using Japanese macroeconomic variables to approximate the dynamics of the representative investor's relative risk aversion. The main empirical findings are: (i) the ex-post VRP, which is defined as the difference between implied and ex-post realized variances, is useful in predicting the Nikkei 225 returns, whereas the expected VRPs, which are the differences between implied and current or model-based realized variances, lose their predictive ability, (ii) the expected and ex-post VRPs provide significant predictability of credit spreads and the composite index of coincident indicators, (iii) the VRP involving Japanese macroeconomic variables contains plausible business cycle dynamics of the Japanese economy.

Suggested Citation

  • Masato Ubukata & Toshiaki Watanabe, 2011. "Market Variance Risk Premiums in Japan as Predictor Variables and Indicators of Risk Aversion," Global COE Hi-Stat Discussion Paper Series gd11-214, Institute of Economic Research, Hitotsubashi University.
  • Handle: RePEc:hst:ghsdps:gd11-214
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    File URL: http://gcoe.ier.hit-u.ac.jp/research/discussion/2008/pdf/gd11-214.pdf
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    References listed on IDEAS

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    1. Bollerslev, Tim & Gibson, Michael & Zhou, Hao, 2011. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Journal of Econometrics, Elsevier, vol. 160(1), pages 235-245, January.
    2. Bollerslev, Tim & Marrone, James & Xu, Lai & Zhou, Hao, 2014. "Stock Return Predictability and Variance Risk Premia: Statistical Inference and International Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(03), pages 633-661, June.
    3. Bollerslev, Tim & Zhou, Hao, 2002. "Estimating stochastic volatility diffusion using conditional moments of integrated volatility," Journal of Econometrics, Elsevier, vol. 109(1), pages 33-65, July.
    4. Bollerslev, Tim & Zhou, Hao, 2006. "Volatility puzzles: a simple framework for gauging return-volatility regressions," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 123-150.
    5. Bandi, Federico M. & Russell, Jeffrey R., 2011. "Market microstructure noise, integrated variance estimators, and the accuracy of asymptotic approximations," Journal of Econometrics, Elsevier, vol. 160(1), pages 145-159, January.
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    More about this item

    Keywords

    Variance Risk Premium; Predictability; Realized Variance; Implied Variance; Relative Risk Aversion;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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