Apophenia? Data Under-Mining the Volatility Leverage-Effect.

39 Pages Posted: 25 Oct 2014

See all articles by Alessandro Palandri

Alessandro Palandri

University of Florence - Department of Statistics, Computer Science, Applications

Date Written: October 24, 2014

Abstract

The inverse relation between stock returns and their volatility, known as volatility leverage-effect (VLE), is documented as a strikingly robust empirical regularity. This paper argues that existing explanations of the phenomenon either suffer from logical inconsistencies or have secondary implications that contradict empirical evidence. Robustness of the empirical findings is re-examined by conducting a thorough investigation of VLE in S&P500 data. Combining misspecification analysis with a novel approach to outlier detection reveals that the VLE relation is indeed very fragile. Implications range from the empirical validity of VLE itself to its use as a moment condition for structural models.

Keywords: Volatility, Leverage Effect, Outliers, Omitted Variable Bias, Realized Measures.

JEL Classification: C01, C14, G00

Suggested Citation

Palandri, Alessandro, Apophenia? Data Under-Mining the Volatility Leverage-Effect. (October 24, 2014). Available at SSRN: https://ssrn.com/abstract=2514364 or http://dx.doi.org/10.2139/ssrn.2514364

Alessandro Palandri (Contact Author)

University of Florence - Department of Statistics, Computer Science, Applications ( email )

Florence
Italy

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