Air pollution and behavioral biases: Evidence from stock market anomalies

Nguyen, Harvey; Pham, Mia Hang

doi:10.1016/j.jbef.2020.100441

Cited by 16 publications

(6 citation statements)

References 144 publications

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“…As explained in the health business industry, both physiological and psychological factors play important roles in this positive relationship. Some prior health studies have demonstrated that air quality significantly affects people's cognitive functions ( 7 , 12 , 34 ). Contact with good air can increase the ability of red blood cells to transfer oxygen to human organs, which is beneficial for concentrating spirit and avoiding confusion.…”

Section: Data and Empirical Resultsmentioning

confidence: 99%

“…Kim and Yoo ( 67 ) discover that the effect of cumulative exposure to air pollutants on stock returns and volatility is greater than that of daily exposure. Nguyen and Pham ( 34 ) discover that stock market anomalies become more significant when severe air pollution occurs because air pollution accelerates behavioral biases. However, Andrikopoulos et al ( 68 ) hold a different opinion that mood changes caused by the weather do not significantly affect stock returns.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Third, the serious consequences of air pollution are not limited to human health, but also spread to economic fields. Some studies have proved that air pollution changes investors' mood and make them do biased decisions, and finally affects the stock market ( 12 , 19 , 31 – 34 ). In addition, the existing literature ( 10 , 13 ) almost focus on the effect of air pollution on stock return in developed states and regions.…”

Section: Introductionmentioning

confidence: 99%

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How Air Quality Affect Health Industry Stock Returns: New Evidence From the Quantile-on-Quantile Regression

Liu

Wang

Xiao

2021

Front. Public Health

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This paper discusses the asymmetric effect of air quality (AQ) on stock returns (SR) in China's health industry through the quantile-on-quantile (QQ) regression method. Compared to prior literature, our study provides the following contributions. Government intervention, especially industrial policy, is considered a fresh and essential component of analyzing frameworks in addition to investors' physiology and psychology. Next, because of the heterogeneous responses from different industries to AQ, industrial heterogeneity is thus considered in this paper. In addition, the QQ method examines the effect of specific quantiles between variables and does not consider structural break and temporal lag effects. We obtain the following empirical results. First, the coefficients between AQ and SR in the health service and health technology industries change from positive to negative as AQ deteriorates. Second, AQ always positively influences the health business industry, but the values of the coefficients are larger in good air. In addition, different from other industries, the coefficients in the health equipment industry are negative, but the values of the coefficients change with AQ. The conclusions provide important references for investors and other market participants to avoid biased decisions due to poor AQ and pay attention to government industrial policies.

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Section: Data and Empirical Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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How Air Quality Affect Health Industry Stock Returns: New Evidence From the Quantile-on-Quantile Regression

Liu

Wang

Xiao

2021

Front. Public Health

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“…e results found that collective awareness of air pollution significantly mediates between air pollution and stock returns. Nguyen and Pham [30] studied the relationship between air pollution and the efficiency of the financial market. e results showed that the stock market anomalies weakened after the severe pollution period.…”

Section: Effect Of Aqi On the Financial Marketsmentioning

confidence: 99%

Developing Machine Learning Techniques to Investigate the Impact of Air Quality Indices on Tadawul Exchange Index

et al. 2022

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The air quality index (AQI) can be described using different pollutant indices. Many investigators study the effect of stock prices and air quality in the field to show if there is a relationship between changing the stock market and the concentration of various pollutants. This study aims to find a relationship between Saudi Tadawul All Share Index (TASI) and multiple pollutants, including particulate matter (PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and AQI. Based on tree models, the relationship is created using linear regression and two prediction models, Chi-square Automatic Interaction Detection (CHAID), and CR-Tree. In order to achieve the target of this research, the TASI dataset relates to six pollutants using time; afterward, the new dataset is divided into three parts—test, validate, and train—after eliminating the outlier data. In order to test the performance of two prediction models, R2 and various error functions are used. The linear regression model results found that PM10, NO2, CO, month, day, and year are significant, whereas O3, SO2, and AQI indices are insignificant. The test dataset showed that R2 scores are 0.995 and 0.986 for CR-Tree and CHAID, respectively, with RMSE values of 387 and 227 for CR-Tree and CHAID, respectively. The prediction models showed that the CHAID model performed better than CR-Tree because it used only three indices, namely, PM10, AQI, and O3, with year and month. The results indicated an effect between changing TASI and the three pollutants, PM10, AQI, and O3.

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“…Many studies have been conducted on the relationship between energy consumption, air pollutant emissions, and economic growth for different individual countries (Kusuma et al, 2019;Nguyen and Pham 2021;Romero, et al, 2020;Shi et al, 2020;and Valencia et al, 2020). Several of these panel studies inform this article's approach.…”

Section: A Spatial Econometric Analysis Of Air Pollutant Concentratio...mentioning

confidence: 99%

A Spatial Econometric Analysis of Air Pollutant Concentrations and Economic Growth on Public Health: Empirical Evidence from Central Asian Countries

Turmunkh¹

2021

jefms

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Air pollution of the countries of Central Asia has affected not only the health of the population since 1990 but also influenced the environment. This study has been made empirically analyzes the spatial autocorrelation analysis that is based on the 1991 to 2017 database of Central Asian countries on the socio-economic factors influencing the concentration of Sulfur Dioxide (SO2), Carbon Monoxide (CO), Nitrogen Dioxide (NO2), Ozone (O3), and Particulate Matter (PM2.5) in the air. Besides, this study validated Global Moran's I statistics to determine spatial positive autocorrelations. The results show that there is a strong correlation between air pollution concentrations and Gross Domestic Product (GDP) per capita. The achievement identified that the concentrations of SO2, CO, NO2, O3, and PM2.5 have a spatial aggregation and distribution effect, which is significantly influenced by the spatial characteristics and the Central Asian Regional Economic Unions. It also determined that an energy policy of a country can be affected the emissions of air pollutants from neighboring countries due to policy effects. Therefore, there is a need for regional coordination of environmental policies and the transfer of pollution-intensive industries, to keep air pollution in countries of Central Asia at a normal level. In addition to the empirical results of this study, the following two conclusions can be identified. First, it identified the need for a unified policy to reduce air pollution to reduce emissions from air pollution sources. Second, there is a need for a renewable energy policy for the development and promotion of renewable energy.

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Air pollution and behavioral biases: Evidence from stock market anomalies

Cited by 16 publications

References 144 publications

How Air Quality Affect Health Industry Stock Returns: New Evidence From the Quantile-on-Quantile Regression

How Air Quality Affect Health Industry Stock Returns: New Evidence From the Quantile-on-Quantile Regression

Developing Machine Learning Techniques to Investigate the Impact of Air Quality Indices on Tadawul Exchange Index

A Spatial Econometric Analysis of Air Pollutant Concentrations and Economic Growth on Public Health: Empirical Evidence from Central Asian Countries

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