Too Good to Be True: Look-ahead Bias in Empirical Options Research

64 Pages Posted: 31 Oct 2023 Last revised: 11 Apr 2024

See all articles by Jefferson Duarte

Jefferson Duarte

Rice University - Jesse H. Jones Graduate School of Business

Christopher S. Jones

University of Southern California - Marshall School of Business - Finance and Business Economics Department

Mehdi Khorram

Rochester Institute of Technology (RIT)

Haitao Mo

University of Kansas

Junbo L. Wang

Louisiana State University, Baton Rouge

Date Written: October 2, 2023

Abstract

Numerous trading strategies examined in empirical options research exhibit remarkably high mean returns and Sharpe ratios. We show some of these seemingly 'good deals' are due to look-ahead biases. These biases stem from using information unavailable at the portfolio formation time to filter out noisy or possibly erroneous observations. Our results suggest that elevated Sharpe ratios may serve as potential indicators of such look-ahead biases. Furthermore, deviating from previous literature findings, we show that illiquidity is not strongly priced in stock options and that only a small set of stock characteristics are in fact associated with option expected returns.

Keywords: Options; look-ahead bias

JEL Classification: G12, G14

Suggested Citation

Duarte, Jefferson and Jones, Christopher S. and Khorram, Mehdi and Mo, Haitao and Wang, Junbo L., Too Good to Be True: Look-ahead Bias in Empirical Options Research (October 2, 2023). Available at SSRN: https://ssrn.com/abstract=4590083 or http://dx.doi.org/10.2139/ssrn.4590083

Jefferson Duarte (Contact Author)

Rice University - Jesse H. Jones Graduate School of Business ( email )

6100 South Main Street
P.O. Box 1892
Houston, TX 77005-1892
United States
713.3486137 (Phone)

HOME PAGE: http://www.jefferson-duarte.com/

Christopher S. Jones

University of Southern California - Marshall School of Business - Finance and Business Economics Department ( email )

Marshall School of Business
Los Angeles, CA 90089
United States

Mehdi Khorram

Rochester Institute of Technology (RIT) ( email )

Rochester, NY 14623
United States

Haitao Mo

University of Kansas

Lawrence, KS 66045
United States

Junbo L. Wang

Louisiana State University, Baton Rouge ( email )

Baton Rouge, LA 70803
United States

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