Global weather-based trading strategies

Ming Dong and Andréanne Tremblay

Journal of Banking & Finance, 2022, vol. 143, issue C

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 6.2%, corresponding to a Sharpe ratio of 0.462 relative to 0.243 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 (search for similar items in EconPapers)
JEL-codes: F39 G02 G11 G14 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378426622001546
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:143:y:2022:i:c:s0378426622001546

DOI: 10.1016/j.jbankfin.2022.106558

Access Statistics for this article

Journal of Banking & Finance is currently edited by Ike Mathur

More articles in Journal of Banking & Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().