Global Weather-Based Trading Strategies

49 Pages Posted: 6 Feb 2018 Last revised: 20 May 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: May 19, 2020

Abstract

We estimate the profitability of global index-level trading strategies formed on daily weather conditions across 49 countries. We use pre-market weather conditions (sunshine, wind, rain, snow, and temperature) and the statistical relationship between weather and returns to predict index returns each day. In the out-of-sample test for our 1993-2012 sample, a global weather-based hedge strategy produces a mean annual return of 15.2% compared to a mean world index return of 3.1%, corresponding to a Sharpe ratio of 0.462 relative to 0.005 for 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 (May 19, 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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