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Option augmented density forecasts of market returns with monotone pricing kernel

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  • Brendan K. Beare
  • Asad Dossani

Abstract

Basic financial theory indicates that the ratio of the conditional density of the future value of a market index and the corresponding risk neutral density should be monotone, but a sizeable empirical literature finds otherwise. We therefore consider an option augmented density forecast of the market return obtained by transforming a baseline density forecast estimated from past excess returns so as to monotonize its ratio with a risk neutral density estimated from current option prices. To evaluate our procedure, we compare baseline and option augmented monthly density forecasts for the S&P 500 index over the period 1997–2013. We find that monotonizing the pricing kernel leads to a modest improvement in the calibration of density forecasts. Supplementary results supportive of this finding are given for market indices in France, Germany, Hong Kong, Japan and the UK.

Suggested Citation

  • Brendan K. Beare & Asad Dossani, 2018. "Option augmented density forecasts of market returns with monotone pricing kernel," Quantitative Finance, Taylor & Francis Journals, vol. 18(4), pages 623-635, April.
    • Handle: RePEc:taf:quantf:v:18:y:2018:i:4:p:623-635
    DOI: 10.1080/14697688.2017.1383626
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    Cited by:

    1. Brendan K. Beare & Juwon Seo, 2022. "Stochastic arbitrage with market index options," Papers 2207.00949, arXiv.org, revised Jul 2022.
    2. Beare, Brendan K. & Shi, Xiaoxia, 2019. "An improved bootstrap test of density ratio ordering," Econometrics and Statistics, Elsevier, vol. 10(C), pages 9-26.

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