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Global weather-based trading strategies

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  • Dong, Ming
  • Tremblay, Andréanne

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.

Suggested Citation

  • Dong, Ming & Tremblay, Andréanne, 2022. "Global weather-based trading strategies," Journal of Banking & Finance, Elsevier, vol. 143(C).
    • Handle: RePEc:eee:jbfina:v:143:y:2022:i:c:s0378426622001546
    DOI: 10.1016/j.jbankfin.2022.106558
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    References listed on IDEAS

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    Cited by:

    1. Jiawen Luo & Qun Zhang, 2024. "Air pollution, weather factors, and realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 151-217, February.

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    More about this item

    Keywords

    Weather; Stock returns; Trading strategy; Temperature region; Time zone;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • F39 - International Economics - - International Finance - - - Other

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