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Option-Implied Equity Premium Predictions via Entropic Tilting

Author

Listed:
  • Konstantinos Metaxoglou
  • Davide Pettenuzzo
  • Aaron Smith

Abstract

We propose a new method to improve density forecasts of the equity premium using information from options markets. We obtain predictive densities from stochastic volatility (SV) and GARCH models, which we then tilt using the second moment of the risk-neutral distribution implied by options prices while imposing a non-negativity constraint on the equity premium. By combining the backward-looking information contained in the GARCH and SV models with the forward-looking information from options prices, our procedure improves the performance of predictive densities. Using density forecasts of the U.S. equity premium from January 1990 to December 2014, we find that tilting leads to more accurate predictions using statistical and economic criteria.

Suggested Citation

  • Konstantinos Metaxoglou & Davide Pettenuzzo & Aaron Smith, 2019. "Option-Implied Equity Premium Predictions via Entropic Tilting," Journal of Financial Econometrics, Oxford University Press, vol. 17(4), pages 559-586.
    • Handle: RePEc:oup:jfinec:v:17:y:2019:i:4:p:559-586.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nby009
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    Cited by:

    1. Zhiyuan Pan & Jun Zhang & Yudong Wang & Juan Huang, 2024. "Modeling and forecasting stock return volatility using the HARGARCH model with VIX information," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1383-1403, August.
    2. Dragicevic, Arnaud Z., 2019. "Rethinking the forestry in the Aquitaine massif through portfolio management," Forest Policy and Economics, Elsevier, vol. 109(C).
    3. Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.

    More about this item

    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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