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Does Information Content of Option Prices Add Value for Asset Allocation?

Author

Listed:
  • Vladimir Zdorovenin

    (ICMA Centre, Henley Business School, University of Reading)

  • Jacques Pézier

    (ICMA Centre, Henley Business School, University of Reading)

Abstract

The aim of this paper is to determine whether forward-looking option- implied returns forecasts lead to better out-of-sample portfolio performance than conventional time series models. We consider a simple two-asset setting with a risk-free asset and the S&P 500 index the risky asset with monthly allocation revisions. We carry out a comprehensive analysis with a wide range of time-series models, two risk-neutral density inference methods, two utility functions, and several performance metrics. Portfolios are compared over the period of January 1994 to April 2010. Our main contribution is to compare the merits of implied volatility smoothing and maximum entropy risk-neutral density estimation techniques. By using bid/ask quotes in place of the closing prices, we obtain smooth probability densities using the maximum entropy principle that outperform the probability densities obtained using the implied volatility smoothing method. We also identify which moments of the option-implied probability densities contribute most to portfolio performance.

Suggested Citation

  • Vladimir Zdorovenin & Jacques Pézier, 2011. "Does Information Content of Option Prices Add Value for Asset Allocation?," ICMA Centre Discussion Papers in Finance icma-dp2011-03, Henley Business School, University of Reading.
    • Handle: RePEc:rdg:icmadp:icma-dp2011-03
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    File URL: http://www.icmacentre.ac.uk/files/discussion-papers/DP2011-03.pdf
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    References listed on IDEAS

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    Cited by:

    1. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.

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    More about this item

    Keywords

    Risk-neutral density; Real-world density; Index options; Maximum entropy; Implied volatility smoothing; Optimal portfolio;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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