Testing for leverage effects in the returns of US equities

Abstract

This article questions the empirical usefulness of leverage effects to describe the dynamics of equity returns. Relying on both in and out of sample tests we consistently find a weak contribution of leverage effects over the past 25 years of S&P 500 returns. The skewness in the conditional distribution of the returns's time series model is found to explain most of the returns' distribution's asymmetry. This conclusion holds both at the index level and for 70% of the individual stocks constituents of the equity index.

Fraud Deterrence Institutions Reduce Intrinsic Honesty

“…While past estimations of deterrence effects focus almost exclusively on the targeted misbehavior, we defend that indirect effects may expand across contexts and impact both compliers and non-compliers. For example, it has been found that past exposure to institutions fostering pro-social norms can improve future pro-sociality even when the institution is no longer enforced (e.g., Cassar et al, 2014;Peysakhovich and Rand, 2016;Engl et al, 2017;Galbiati et al, 2018). Here, we look at possible spillover effects across contexts from inspecting and sanctioning people for rule violations on one of the most fundamental traits of human beings: intrinsic honesty.…”

Does the leverage effect affect the return distribution?

“…For example, Ait-Sahalia et al (2013) calculated that the correlation parameter at the high-frequency limit is ρ = −0, 77 by high-frequency data of S&P 500 data with a robust estimation, indicating that there is a strong leverage effect. However, when stochastic volatility models (SVMs) are fitted to the S&P 500, a puzzle arises: the fitting is insensitive to the correlation parameter (see, e.g., Chorro et al, 2018;Drgulescu and Yakovenko, 2002;Sepp, 2008). How can it be that the return distribution is insensitive to the correlation parameter?…”