Working papers

Option Characteristics as Cross-Sectional Predictors

Abstract: We provide the first comprehensive analysis of options-implied information for predicting the cross-section of stock returns by jointly examining extensive sets of firm and option characteristics. Using portfolio sorts and high-dimensional methods, we show that only few option characteristics have significant predictive power, after controlling for firm characteristics, earning a Fama-French three-factor alpha in excess of 20\% per annum. We study the successful predictors through the lense of option pricing models. This analysis reveals that the strongest option characteristics are associated with information about asset mispricing, overvaluation and future tail return realizations. Our findings are consistent with models of informed trading and limits to arbitrage. 

A Modified Wild Bootstrap Procedure for Laplace Transforms of Volatility

Abstract: In this note, we propose a modified wild (MW) bootstrap-based procedure for the realized Laplace transform (RLT) of volatility. We establish its first-order asymptotic validity.

Reflections on Predictive Regressions in Persistent Economic Systems

Abstract: This paper reviews results from Robinson & Marinucci (2001) and Tsay & Chung (2000) to describe the properties of standard OLS estimation for predictive regressions when the economic system is governed by persistent vector autoregressive dynamics for the state variables, letting them all be fractionally integrated of potentially different orders. Furthermore, we explain how the local spectrum (LCM) procedure of Andersen & Varneskov (2020) overcome spurious inference challenges. Finally, we extend numerical evidence on the LCM procedure, carry out several robustness checks and provide rule-of-thumb implementation advice.