The Contribution of Frictions to Expected Returns: An Options-based Estimation Approach

Abstract

We document that properly scaled deviations from put-call parity estimate the contribution of market frictions to expected returns (CFER) accurately, by means of a non-parametric theoretically founded identification strategy. The required conditions are that our estimator predicts the underlying but not the synthetic stock's return. The data satisfy the two conditions; the alphas of the estimated CFER-sorted spread portfolios are up to 1.86% per month. The estimated CFER covaries non-linearly with proxies of market frictions. An agent-based equilibrium model explains our findings; alphas can be twice as big as the round-trip transaction costs, thus corroborating the accuracy of our estimator.

Keywords: Limits to arbitrage, Market frictions, Put-call parity, Return predictability

JEL Classification: C13, G10, G12, G13