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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
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    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.

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    File URL: http://gcoe.ier.hit-u.ac.jp/research/discussion/2008/pdf/gd11-214.pdf
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    Bibliographic Info

    Paper provided by Institute of Economic Research, Hitotsubashi University in its series Global COE Hi-Stat Discussion Paper Series with number gd11-214.

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    Date of creation: Dec 2011
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    Handle: RePEc:hst:ghsdps:gd11-214

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

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    1. Tim Bollerslev & Hao Zhou, 2001. "Estimating stochastic volatility diffusion using conditional moments of integrated volatility," Finance and Economics Discussion Series 2001-49, Board of Governors of the Federal Reserve System (U.S.).
    2. 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.
    3. M. Fukasawa & I. Ishida & N. Maghrebi & K. Oya & M. Ubukata & K. Yamazaki, 2011. "Model-Free Implied Volatility: From Surface To Index," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 14(04), pages 433-463.
    4. 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.
    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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