Air pollution, stock returns, and trading activities in China

Wu, Qinqin; Ying, Hao; Lu, Jing

doi:10.1016/j.pacfin.2018.08.018

Cited by 63 publications

(28 citation statements)

References 79 publications

(114 reference statements)

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“…It is notable that we succeed to identify the air quality and weather effects by employing quantile regression approach. This evidence on the existence of air quality effect and weather effect in the Shenzhen stock market is consistent with the findings of empirical studies focusing on the Shanghai Exchange [5,[8][9][10][11][12][17][18][19][20][21][22]. In Table 13, the results of the quantile regression using the 21-day MA-MSD model, we can find that high air pollution has significant and negative effects in the bull market (τ = 0.7), and extremely high temperature has significant and negative effects in the bear market (τ = 0.1 and τ = 0.3).…”

Section: Effects Of Air Quality and Weather On The Stock Returns Using Quantile Regressionsupporting

confidence: 89%

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The Effect of Air Quality and Weather on the Chinese Stock: Evidence from Shenzhen Stock Exchange

et al. 2021

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We investigated the impact of air quality and weather on the equity returns of the Shenzhen Exchange. To capture the air quality and weather effects, we used dummy variables created by employing a moving average and moving standard deviation. The important results are as follows. First, in the whole sample period (2005–2019), we find that high air pollution and extremely high temperature have significant and negative influence on the equity returns. In the sub-period I (2005–2012), the 11-day model and 31-day model show that high air pollution have significant and negative impacts 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 weather effect of the abnormal temperature on the stock returns is greater in severe bearish market. Whereas the effect of the air pollution on the stock returns is greater in the bullish market. 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 analyzing these effects in a very volatile emerging market such as the Shenzhen stock market.

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Section: Effects Of Air Quality and Weather On The Stock Returns Using Quantile Regressionsupporting

confidence: 89%

“…They concluded that air pollution is a behavioral factor linked to stock returns in China. Wu et al [17] explored the linkage between air pollution and equity prices of locally headquartered firms in China. They found that severe air pollution leads to low returns and volatility.…”

Section: Literature Reviewmentioning

confidence: 99%

The Effect of Air Quality and Weather on the Chinese Stock: Evidence from Shenzhen Stock Exchange

et al. 2021

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“…

are control variables, including the lagged abnormal return of firm i in month t −1 ( Lagged_Ret_Abnormal ) and other weather condition controls defined in Table 1 . Following Wu, Hao, and Lu [ 47 ], we include stock fixed effects to control for the unobservable firm-level factors (e.g., financial conditions and fundamentals) and include month fixed effects to control for the seasonal effects that might bias our results. Standard errors are clustered at the firm level and reported in parentheses below the regression coefficients.…”

Section: Resultsmentioning

confidence: 99%

“…Using this method, we can build a one-to-one correspondence between cities and observation stations annually. Some previous literature matches firm locations with the weather conditions by city names [ 47 ]. However, the matched weather conditions might be biased if one city has no station or multiple weather stations.…”

Section: Methodsmentioning

confidence: 99%

Extreme Temperatures and Firm-Level Stock Returns

2021

IJERPH

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By linking stock returns with weather conditions from 2007 to 2019 in China, we study how firm-level stock returns react to extreme temperatures. Based on a multivariate ordinary least squares regression model with fixed effects, empirical results show that firm-level stock returns decrease with exposure to extreme temperatures. We further explore the heterogeneity in the temperature-return relation to enrich our understanding of the economic mechanism behind it. The impact of extreme temperatures on abnormal stock returns is more pronounced in smaller, younger, more volatile, less profitable firms and firms with more intangible assets. The results indicate that the investor mood likely plays a role in the extreme temperature effect. The impact of extreme temperatures holds after addressing a series of concerns. Overall, our paper provides additional firm-level evidence on the environment-induced mood effect in the stock market.

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“…They concluded that air pollution is a behavioural factor linked to stock returns in China. Wu et al [24] explored the linkage between air pollution and equity prices of locally headquartered firms in China. They found that severe air pollution leads to low returns and volatility.…”

Section: Literature Reviewmentioning

confidence: 99%

The Effect of Air Quality and Weather on the Chinese Stock: Evidence from Shenzhen Stock Exchange

Jiang¹,

Gupta²,

Subramaniam³

et al. 2020

Preprint

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We investigate the impact of air quality and weather on the equity returns of the Shenzhen Exchange. To capture the air quality and weather effects, we use dummy variables created by employing a moving average and moving standard deviation. The important results are as follows. First, in the whole sample period (2005–2019), we find that high air pollution and extremely high temperature have significant and negative influence on the equity returns. In the sub-period I (2005–2012), the 11-day model and 31-day model show that high air pollution have significant and negative impacts 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 weather effect of the abnormal temperature on the stock returns is greater in severe bearish market. Whereas the effect of the air pollution on the stock returns is greater in the bullish market. 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 analyzing these effects in a very volatile emerging market such as the Shenzhen stock market.

show abstract

Air pollution, stock returns, and trading activities in China

Cited by 63 publications

References 79 publications

The Effect of Air Quality and Weather on the Chinese Stock: Evidence from Shenzhen Stock Exchange

The Effect of Air Quality and Weather on the Chinese Stock: Evidence from Shenzhen Stock Exchange

Extreme Temperatures and Firm-Level Stock Returns

The Effect of Air Quality and Weather on the Chinese Stock: Evidence from Shenzhen Stock Exchange

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