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Authors = Roberto J. Santillán-Salgado ORCID = 0000-0001-5162-1403

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21 pages, 1175 KiB  
Article
The Effects of ESG Scores and ESG Momentum on Stock Returns and Volatility: Evidence from U.S. Markets
by Luis Jacob Escobar-Saldívar, Dacio Villarreal-Samaniego and Roberto J. Santillán-Salgado
J. Risk Financial Manag. 2025, 18(7), 367; https://doi.org/10.3390/jrfm18070367 - 2 Jul 2025
Cited by 1 | Viewed by 1391
Abstract
The impact of Environmental, Social, and Governance (ESG) scores on financial performance remains a subject of debate, as the literature reports mixed evidence regarding their effect on stock returns. This research aims to examine the relationship between ESG ratings and the change in [...] Read more.
The impact of Environmental, Social, and Governance (ESG) scores on financial performance remains a subject of debate, as the literature reports mixed evidence regarding their effect on stock returns. This research aims to examine the relationship between ESG ratings and the change in ESG scores, or ESG Momentum, concerning both returns and risk of a large sample of stocks traded on U.S. exchanges. The study examined a sample of 3856 stocks traded on U.S. exchanges, considering 20 years of quarterly data from December 2002 to December 2022. We applied multi-factor models and tested them through pooled ordinary, fixed effects, and random effects panel regression methods. Our results show negative relationships between ESG scores and stock returns and between ESG Momentum and volatility. Contrarily, we find positive associations between ESG Momentum and returns and between ESG scores and volatility. Although high ESG scores are generally associated with lower long-term stock returns, an increase in a company’s ESG rating tends to translate into immediate positive returns and reduced risk. Accordingly, investors may benefit from strategies that focus on companies actively improving their ESG performance, while firms themselves stand to gain by signaling continuous advancement in ESG-related areas. Full article
(This article belongs to the Special Issue Emerging Trends and Innovations in Corporate Finance and Governance)
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17 pages, 1558 KiB  
Article
Twitter Sentiment Analysis and Influence on Stock Performance Using Transfer Entropy and EGARCH Methods
by Román A. Mendoza-Urdiales, José Antonio Núñez-Mora, Roberto J. Santillán-Salgado and Humberto Valencia-Herrera
Entropy 2022, 24(7), 874; https://doi.org/10.3390/e24070874 - 25 Jun 2022
Cited by 25 | Viewed by 12951
Abstract
Financial economic research has extensively documented the fact that the impact of the arrival of negative news on stock prices is more intense than that of the arrival of positive news. The authors of the present study followed an innovative approach based on [...] Read more.
Financial economic research has extensively documented the fact that the impact of the arrival of negative news on stock prices is more intense than that of the arrival of positive news. The authors of the present study followed an innovative approach based on the utilization of two artificial intelligence algorithms to test that asymmetric response effect. Methods: The first algorithm was used to web-scrape the social network Twitter to download the top tweets of the 24 largest market-capitalized publicly traded companies in the world during the last decade. A second algorithm was then used to analyze the contents of the tweets, converting that information into social sentiment indexes and building a time series for each considered company. After comparing the social sentiment indexes’ movements with the daily closing stock price of individual companies using transfer entropy, our estimations confirmed that the intensity of the impact of negative and positive news on the daily stock prices is statistically different, as well as that the intensity with which negative news affects stock prices is greater than that of positive news. The results support the idea of the asymmetric effect that negative sentiment has a greater effect than positive sentiment, and these results were confirmed with the EGARCH model. Full article
(This article belongs to the Special Issue Granger Causality and Transfer Entropy for Financial Networks)
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