Option-implied information: What’s the vol surface got to do with it?

Maxim Ulrich () and Simon Walther ()
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Maxim Ulrich: Karlsruhe Institute of Technology (KIT)
Simon Walther: Karlsruhe Institute of Technology (KIT)

Review of Derivatives Research, 2020, vol. 23, issue 3, No 4, 323-355

Abstract: Abstract We find that option-implied information such as forward-looking variance, skewness and the variance risk premium are sensitive to the way the volatility surface is constructed. For some state-of-the-art volatility surfaces, the differences are economically surprisingly large and lead to systematic biases, especially for out-of-the-money put options. Estimates for risk-neutral variance differ across volatility surfaces by more than 10% on average, leading to variance risk premium estimates that differ by 60% on average. The variations are even larger for risk-neutral skewness. To overcome this problem, we propose a volatility surface that is built with a one-dimensional kernel regression. We assess its statistical accuracy relative to existing state-of-the-art parametric, semi- and non-parametric volatility surfaces by means of leave-one-out cross-validation, including the volatility surface of OptionMetrics. Based on 14 years of end-of-day and intraday S&P 500 and Euro Stoxx 50 option data we conclude that the proposed one-dimensional kernel regression represents option market information more accurately than existing approaches of the literature.

Keywords: Option-implied; Risk-neutral variance; Risk-neutral density; Tail risk; Option standardization; Interpolation (search for similar items in EconPapers)
JEL-codes: C14 G13 G17 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11147-020-09166-0

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