Do low-carbon investments in emerging economies pay off? Evidence from the Brazilian stock market

Cunha, Felipe Arias Fogliano de Souza; Meira, Erick; Orsato, Renato J.; Klötzle, Marcelo Cabús; Lucena, André F.P.

doi:10.1016/j.irfa.2021.101700

Cited by 20 publications

(10 citation statements)

References 50 publications

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“…The former takes into account stranded asset risk [65,66], and the latter considers their ethical values and fiduciary duties [60]. Indeed, investing in carbon-efficient companies provides investors with positive portfolio performance [67]. As shown in this study, the mitigation strategies of firms are conditional on monetary profits, this is partly explained by a theory of Nordhaus -economic growths help address climate change [68].…”

Section: Discussionmentioning

confidence: 77%

Enterprise's Strategies to Improve Financial Capital under Climate Change Scenario – Evidence of the Leading Country

Nguyen¹,

Nguyen

et al. 2023

SSRN Journal

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Section: Discussionmentioning

confidence: 77%

Enterprise's Strategies to Improve Financial Capital under Climate Change Scenario – Evidence of the Leading Country

Nguyen¹,

Nguyen

et al. 2023

SSRN Journal

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Section: Discussionmentioning

confidence: 96%

Enterprise’s strategies to improve financial capital under climate change scenario – evidence of the leading country

Quang-Loc¹,

Nguyen²,

La³

et al. 2023

Preprint

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Climate change poses manifold consequences to human well-being as well as ecosystems. One of the most widely accepted measures to mitigate climate risks is at the firm level, aiming to reduce carbon dioxide and innovate climate-friendly technology. However, doing so requires comprehensive factors, including legislation, the company’s strategy, and finance. Using the Bayesian Mindsponge Framework (MBF) for analyzing 178 enterprises listed in S&P 500 companies from 2016 to 2021, the current study examined how their climate risk mitigation efforts can affect their stock price. We found that emitted carbon dioxide negatively affects the stock price. In contrast, the income and mitigating strategies, including producing eco-friendly products, using renewable energy, and environmental expenditures investments, are positively associated with the increase in share value. However, the mitigation efforts are conditional on the income of the company. The results indicate that investors expect corporations to transform financial capital from the stock market into bankable, climate-resilient projects. Based on these findings, we suggest that building an eco-surplus culture by stimulating climate change knowledge can be a promising approach to promoting a corporation’s mitigation efforts.

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“…Furthermore, Kar et al [22] indicated that Indian indices had recovered during the pandemic. However, a few scholars studied the relationship between air pollution and the stock market index, as Cunha et al [23] provided insight into the financial performance of a stock portfolio consisting of carbon-efficient Brazilian companies from 2010 to 2019 through different portfolio metrics.…”

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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Do low-carbon investments in emerging economies pay off? Evidence from the Brazilian stock market

Cited by 20 publications

References 50 publications

Enterprise's Strategies to Improve Financial Capital under Climate Change Scenario – Evidence of the Leading Country

Enterprise's Strategies to Improve Financial Capital under Climate Change Scenario – Evidence of the Leading Country

Enterprise’s strategies to improve financial capital under climate change scenario – evidence of the leading country

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

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