Option Momentum

73 Pages Posted: 20 May 2022

See all articles by Steven L. Heston

Steven L. Heston

University of Maryland - Department of Finance

Christopher S. Jones

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

Mehdi Khorram

Rochester Institute of Technology (RIT)

Shuaiqi Li

City University of Hong Kong

Haitao Mo

University of Kansas

Multiple version iconThere are 3 versions of this paper

Date Written: April 15, 2022

Abstract

This paper investigates the performance of option investments across different stocks by computing monthly returns on at-the-money straddles on individual equities. It finds that options with high historical returns continue to significantly outperform options with low historical returns over horizons ranging from 6 to 36 months. This phenomenon is robust to including out-of-the-money options or delta-hedging the returns. Unlike stock momentum, option return continuation is not followed by long-run reversal. Significant returns remain after factor risk adjustment and after controlling for implied volatility and other characteristics. Across stocks, trading costs are unrelated to the magnitude of momentum profits.

Keywords: options, momentum, reversal

JEL Classification: G12, G12, G14

Suggested Citation

Heston, Steven L. and Jones, Christopher S. and Khorram, Mehdi and Li, Shuaiqi and Mo, Haitao, Option Momentum (April 15, 2022). Journal of Finance, Forthcoming, Available at SSRN: https://ssrn.com/abstract=4113680

Steven L. Heston

University of Maryland - Department of Finance ( email )

Robert H. Smith School of Business
Van Munching Hall
College Park, MD 20742
United States

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

Shuaiqi Li

City University of Hong Kong ( email )

Haitao Mo (Contact Author)

University of Kansas

Lawrence, KS 66045
United States

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