The Effect of Air Quality and Weather on the Chinese Stock Market: Evidence from Shenzhen Stock Exchange
Zhuhua Jiang (),
Rangan Gupta (),
Sowmya Subramaniam () and
Seong-Min Yoon ()
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Zhuhua Jiang: Division of Chinese Foreign Affairs and Commerce, Hankuk University of Foreign Studies, Seoul 02450, Korea
Sowmya Subramaniam: Indian Institute of Management Lucknow, Prabandh Nagar off Sitapur Road, Lucknow, Uttar Pradesh 226013, India
Seong-Min Yoon: Department of Economics, Pusan National University, Busan 46241, Korea
No 202070, Working Papers from University of Pretoria, Department of Economics
We investigate the impact of air quality and weather on the stock market returns of the Shenzhen Exchange. To capture the air quality and weather effects, we apply dummy variables generated by applying a moving average and moving standard deviation. Our study provides several interesting results. First, in the whole sample period (2005â€“2019), we find that high air pollution and extremely high temperature have significant and negative effects on the Shenzhen stock returns. In the sub-period I (2005â€“2012), the 11-day model and 31-day model show that high air pollution have significant and negative effects on the Shenzhen stock returns. Second, the results of the quantile regression show that high air pollution have significant and negative effects during bullish market phase, and extremely high temperature have significant and negative effects during bearish market phase. This implies that the air quality and weather effects are asymmetric. Third, the more the Shenzhen stock returns drop, the greater the effect of the abnormal temperature is. Whereas, the more the Shenzhen stock returns increase, the greater the effect of the abnormal air quality is. Fourth, the least squares method underestimates the air quality and weather effects compared to the quantile regression method, suggesting that the quantile regression method is more suitable in analysing these effects in a very volatile emerging market such as the Shenzhen stock market.
Keywords: air quality; extreme weather; MA-MSD method; investor sentiment; behavioural finance (search for similar items in EconPapers)
JEL-codes: C32 F36 G11 G14 (search for similar items in EconPapers)
Pages: 29 pages
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:202070
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