Weather Sentiment Index and Stock Return Predictability: Evidence from China

ABSTRACT

This paper introduces a weather-related sentiment (mood) index (WSI) for the Chinese stock market based on precipitation and temperature data with the PLS method. We find that the WSI is negatively correlated with the equity market and has strong predictive power that is far greater than that of other market and macroeconomic variables. The predictability also holds under the characteristic-mimicking portfolios. The driving force of the WSI’s predictive power appears to stem from its ability to predict future cash flow, which reflects investor preference.

KEYWORDS:

• Weather
• investor sentiment
• Chinese equity markets

JEL:

• G11
• G12
• G14

Acknowledgements

The authors are grateful for the very constructive comments and suggestions from the editor, two anonymous reviewers, Chunmin Zhang, Benjian Wu, Xueyong Zhang, Liqing Zhang, Zhanyu Ying, and the seminar participants at Central University of Finance and Economics. Tian Ma and Cunfei Liao contribute equally and are the co-first authors of this paper.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1. The 5% setting is following the method in previous studies (Bressan and Romagnoli 2021; Wiklund 2021). Other setting such as 1% is also robust in our empirical results.

2. Appendix provides a detailed description of the process and considering the methodology we use monthly WSI and market return to make this empirical analysis.

3. The T + 1 trading rule is when an investor buys a stock in day t, she/he cannot sell it until day t + 1.

Additional information

Funding

We appreciate the financial supports from the National Social Science Fund of China with grant number 22&ZD063, as well as the National Natural Science Foundation of China with grant numbers 72072193, 71872195.