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Implied volatility sentiment: a tale of two tails

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  • Luiz Félix
  • Roman Kräussl
  • Philip Stork

Abstract

We propose a sentiment measure jointly derived from out-of-the-money index puts and single stock calls: implied volatility (IV-) sentiment. In contrast to implied correlations, our measure uses information from the tails of the risk-neutral densities from these two markets rather than across their entire moneyness structures. We find that IV-sentiment measure adds value over and above traditional factors in predicting the equity risk premium out-of-sample. Forecasting results are superior when constrained ensemble models are used vis-à-vis unregularized machine learning techniques. In a mean-reversion strategy, our IV-sentiment measure delivers economically significant results, with limited exposure to a set of cross-sectional equity factors, including Fama and French's five factors, the momentum factor and the low-volatility factor, and seems valuable in preventing momentum crashes. Our novel measure reflects overweight of tail events, which we interpret as a behavioral bias. However, we cannot rule out a risk-compensation rationale.

Suggested Citation

  • Luiz Félix & Roman Kräussl & Philip Stork, 2020. "Implied volatility sentiment: a tale of two tails," Quantitative Finance, Taylor & Francis Journals, vol. 20(5), pages 823-849, May.
  • Handle: RePEc:taf:quantf:v:20:y:2020:i:5:p:823-849
    DOI: 10.1080/14697688.2019.1696018
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    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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