Option Return Predictability with Machine Learning and Big Data

121 Pages Posted: 18 Aug 2021 Last revised: 11 Jan 2022

See all articles by Turan G. Bali

Turan G. Bali

Georgetown University - McDonough School of Business

Heiner Beckmeyer

University of Muenster - Finance Center Muenster

Mathis Moerke

University of St. Gallen - Swiss Institute of Banking and Finance

Florian Weigert

University of Neuchatel - Institute of Financial Analysis; University of Cologne - Centre for Financial Research (CFR)

Date Written: July 29, 2021

Abstract

Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample performance of option and stock characteristics in predicting future option returns. Besides statistical significance, the nonlinear machine learning models generate economically sizeable profits in the long-short portfolios of equity options even after accounting for transaction costs. Although option-based characteristics are the most important standalone predictors, stock-based measures offer substantial incremental predictive power when considered alongside option-based characteristics. Finally, we provide compelling evidence that option return predictability is driven by informational frictions and option mispricing.

Keywords: Machine learning, big data, option return predictability

JEL Classification: G10, G12, G13, G14

Suggested Citation

Bali, Turan G. and Beckmeyer, Heiner and Moerke, Mathis and Weigert, Florian, Option Return Predictability with Machine Learning and Big Data (July 29, 2021). Georgetown McDonough School of Business Research Paper No. 3895984, Available at SSRN: https://ssrn.com/abstract=3895984 or http://dx.doi.org/10.2139/ssrn.3895984

Turan G. Bali (Contact Author)

Georgetown University - McDonough School of Business ( email )

3700 O Street, NW
Washington, DC 20057
United States
(202) 687-5388 (Phone)
(202) 687-4031 (Fax)

HOME PAGE: https://sites.google.com/a/georgetown.edu/turan-bali

Heiner Beckmeyer

University of Muenster - Finance Center Muenster ( email )

Schlossplatz 2
Muenster, 48143
Germany

Mathis Moerke

University of St. Gallen - Swiss Institute of Banking and Finance ( email )

Rosenbergstrasse 52
St. Gallen, CH-9000
Switzerland

HOME PAGE: http://www.mathismoerke.com

Florian Weigert

University of Neuchatel - Institute of Financial Analysis ( email )

Pierre-a-Mazel,7
Neuchatel, CH-2000
Switzerland

University of Cologne - Centre for Financial Research (CFR) ( email )

Albertus-Magnus Platz
Cologne, 50923
Germany

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