Expected 1DTE Option Returns

47 Pages Posted: 14 Mar 2024

See all articles by Michael S. Johannes

Michael S. Johannes

Graduate School of Business, Columbia University

Andreas Kaeck

University of Sussex

Norman Seeger

VU Amsterdam - School of Business and Economics

Neel Shah

Columbia University - Columbia Business School

Date Written: February 14, 2024

Abstract

This paper analyzes short-dated one-day-to-expiry (1DTE) index option returns. Theoretically, we provide new analytical tools to calculate higher-order moments of option returns for models with known (or easily calculable) characteristic functions and the impact of macroeconomic event risk on option return distributions for hold-to-maturity option returns. Analytical moments are useful for understanding observed option returns, for evaluating statistical significance, and for GMM-based estimation. Empirically, we analyze 1DTE option returns and document that raw call and put returns are not statistically significant on most days but are highly significant on macroeconomic announcement days. We also analyze variance risk premiums and fit models to observed option returns to understand the underlying risk factors and premia.

Keywords: 1DTE, short-term options, expected option returns, variance risk premium, macroeconomic announcements

JEL Classification: G12, G13, G14, C53

Suggested Citation

Johannes, Michael Slater and Kaeck, Andreas and Seeger, Norman and Shah, Neel, Expected 1DTE Option Returns (February 14, 2024). Columbia Business School Research Paper No. 4729757, Available at SSRN: https://ssrn.com/abstract=4729757 or http://dx.doi.org/10.2139/ssrn.4729757

Michael Slater Johannes (Contact Author)

Graduate School of Business, Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Andreas Kaeck

University of Sussex ( email )

Sussex House
Falmer
Brighton, Sussex BNI 9RH
United Kingdom

Norman Seeger

VU Amsterdam - School of Business and Economics ( email )

De Boelelaan 1105
Amsterdam, 1081HV
Netherlands

Neel Shah

Columbia University - Columbia Business School ( email )

665 W 130th St
New York, NY 10027
United States

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