Global Weather-Based Trading Strategies

48 Pages Posted: 6 Feb 2018 Last revised: 13 Jan 2020

See all articles by Ming Dong

Ming Dong

York University - Schulich School of Business

Andreanne Tremblay

Université Laval - Département de Finance et Assurance

Date Written: January 10, 2020

Abstract

We estimate the profitability of global index-level trading strategies formed on daily weather across 49 countries. We use ex ante weather conditions (sunshine, wind, rain, snow, and temperature) and the statistical relationship between weather and returns to predict index returns on each day. During 1993-2012, a global weather-based hedge strategy produced a mean annual return of 15.2% as opposed to a mean world index return of 3.1%, corresponding to a Sharpe ratio of 0.462 compared to 0.005 of the world index. Our findings confirm that multiple weather conditions exert economically important impacts on stock returns around the globe.

Keywords: weather, stock returns, trading strategy, temperature region, time zone, investor psychology

JEL Classification: G02, G11, G14, F39

Suggested Citation

Dong, Ming and Tremblay, Andreanne, Global Weather-Based Trading Strategies (January 10, 2020). Available at SSRN: https://ssrn.com/abstract=3111467 or http://dx.doi.org/10.2139/ssrn.3111467

Ming Dong (Contact Author)

York University - Schulich School of Business ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada
416-736-2100 ext. 77945 (Phone)
416-736-5687 (Fax)

Andreanne Tremblay

Université Laval - Département de Finance et Assurance ( email )

Pavillon Palasis-Prince
Quebec G1K 7P4
Canada

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