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Conditional equity risk premia and realized variance jump risk

Author

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  • Zhanglong Wang
  • Kent Wang
  • Zheyao Pan

    (Research School of Finance, Actuarial Studies and Applied Statistics, Australian National University, Canberra, ACT, Australia)

Abstract

This study explores the relationship between realized variance jump risk and conditional equity risk premium. Using high frequency records of the Standard & Poor’s 500 index, we construct a realized variance measure and estimate its jump component using a Heterogeneous Autoregressive model augmented by a jump component. We find strong evidence that the realized variance jump risk measure significantly relates to excess stock market returns in-sample and out-of-sample from 1998 to 2010. Further, the predictive power of the variance jump remains both statistically and economically significant after controlling for commonly-used return predictors, and is also independent from variance risk premium and price jump risk. Calibration-based evidence is also consistent with our empirical findings.

Suggested Citation

  • Zhanglong Wang & Kent Wang & Zheyao Pan, 2015. "Conditional equity risk premia and realized variance jump risk," Australian Journal of Management, Australian School of Business, vol. 40(2), pages 295-317, May.
  • Handle: RePEc:sae:ausman:v:40:y:2015:i:2:p:295-317
    DOI: 10.1177/0312896214526602
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    References listed on IDEAS

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    Cited by:

    1. Zheyao Pan, 2018. "A state‐price volatility index for the U.S. government bond market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 573-597, November.

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    More about this item

    Keywords

    Conditional equity premia; HAR-J model; realized variance jump; stock return prediction;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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