Extracting expected stock risk premia from option prices and the information contained in non-parametric-out-of-sample stochastic discount factors

Ana González-Urteaga, Belén Nieto and Gonzalo Rubio

Quantitative Finance, 2021, vol. 21, issue 5, 713-727

Abstract: This paper analyzes the factor structure and cross-sectional variability of a set of expected excess returns extracted from option prices and a non-parametric and out-of-sample stochastic discount factor. We argue that the existing potential segmentation between the equity and option markets makes it advisable to avoid using only option prices to extract expected equity risk premia. This set of expected risk premia significantly forecasts future realized returns, and the first two principal components explain 94.1% of the variability of expected returns. A multi-factor model with the market, quality, funding illiquidity, the default premium and the market-wide variance risk premium as factors significantly explains the cross-sectional variability of expected excess returns. The (asymptotically) different from zero adjusted cross-sectional R-squared statistic is 83.6%.

Date: 2021
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DOI: 10.1080/14697688.2020.1813903

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