Abstract
This paper revisits the weather effects with a comprehensive examination that includes all eight weather elements after controlling for the effect of seasonal affect disorder using the data from Taiwan between January 1, 1995, and October 31, 2021. We further employ principal component analysis to provide us with components that fittingly represent various multi-facet weather conditions and intuitively depict the relationship between the weather as we know it and investor behavior manifested in the overall market in returns, volatility, turnover, and liquidity. The results from a vector autoregression model based on both the individual weather elements and weather components show that the weather effects exist. We also find that warnings about extreme weather condition of a typhoon have a direct effect and heavy rain an indirect effect on market liquidity. In addition, institutional investors' buying and selling activity is linked to weather conditions. The robustness of the weather effects is further demonstrated by the results of the intraday return analysis and from considering different numbers of weather elements and conditions in the model.
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Notes
As pointed out in Goetzmann and Zhu (2005), the study of the weather effect can be traced back to Smith (1939) that explored the correlation between weather cycles and prices on the NYSE. While failing to find a significant connection between rainfall and stock prices, Smith did find some evidence of a link between rainfall and variance.
According to NOAA Office for Coastal Management, between 1980 and 2021, hurricanes caused the most damage among all weather disasters: over $1.1 trillion total, with an average cost of $20.5 billion per event. They are also responsible for the highest number of deaths: 6,697. (https://coast.noaa.gov/states/fast-facts/hurricane-costs.html).
While other weather-related events such as floods, landslides, and droughts also have impacts due to their disastrous consequences, they are not examined due to their infrequent occurrences that make it hard to perform adequate statistical analysis. Taiwan Central Weather Bureau starts providing information about typhoons in January 1990.
See Emanuel (2013). It also predicts stronger and more frequent tropical cyclones for the North Atlantic, where about 12% of the world's tropical cyclones occur each year.
The sample period they examine spans from January 3, 1991, to September 30, 2017.
Volatility, turnover, and liquidity cannot be estimated for intraday or overnight sessions due to the lack of available data required.
To simplify the presentation, a portion of the results are not shown in Table 13. The complete results are available upon request.
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Acknowledgements
The authors express gratitude to Taiwan Central Weather Bureau for providing thorough information on severe weather advisories. Chueh-Yung Tsao is grateful for research support from Chang Gung Univ. grant No. BMRP864.
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Lee, CI., Tsao, CY. A comprehensive reexamination of the weather effects. Empir Econ 66, 1333–1382 (2024). https://doi.org/10.1007/s00181-023-02492-w
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DOI: https://doi.org/10.1007/s00181-023-02492-w