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題名 基於BERT模型分析ESG新聞情緒對股票報酬之影響
Analyzing the Impact of ESG News Sentiment on Stock Returns Based on BERT Model
作者 賴亮瑋
Lai, Liang-Wei
貢獻者 楊曉文
Yang, Sheau-Wen
賴亮瑋
Lai, Liang-Wei
關鍵詞 ESG
ESG新聞
情緒分析
BERT
ESG
ESG News
Sentiment Analysis
BERT
日期 2023
上傳時間 6-Jul-2023 16:47:51 (UTC+8)
摘要 隨著市場開始重視ESG，以及投資人對ESG資訊的需求量增加，發布頻率高的ESG新聞成為投資人獲取ESG資訊的管道之一，而ESG資訊如何對報酬產生影響成為重要議題。過去文獻對此議題的結論不盡相同，且研究樣本多採用美國地區的ESG新聞，因此本文使用台灣上市及上櫃公司資料進行實證分析，並進一步區別環境、社會、公司治理三類別的新聞情緒對各產業之影響，本文有助於補充ESG新聞情緒在不同地區及產業的差異。
研究方法方面，證明BERT自然語言模型是合適的情緒分析工具，基於BERT具備強大的文章理解能力，提供準確的情緒分類結果，相較於其他情緒分析模型，在準確度、F1-Score都有較佳的表現。研究結果方面，台灣ESG新聞情緒對個股報酬有顯著的同向影響，且負面ESG新聞情緒對個股報酬的影響較正面ESG新聞情緒大，符合行為財務理論與假說預測。本文有兩點重要發現，第一，當新聞內容包含ESG因素，可提升正面新聞的正面影響力，同時降低負面新聞對報酬的負面效果。第二，整理環境、社會、公司治理三類別對各產業的反應，反應不盡相同，大部分產業報酬受正面新聞的反應為正面，負面新聞的反應為負面。關於社會與公司治理議題的消費品產業新聞，對報酬反應皆為負面，顯示仍有產業對於ESG議題持負面看法，存在成本增加、與代理人問題等擔憂。
As market funds flow into ESG investments and the increasing demand for ESG information from investors, ESG news with the highest frequency of release has become the best way for investors to obtain ESG information, and how ESG information affects returns has become an important issue. Previous literature has reached different conclusions, and focusing on ESG news from the United States. In this paper, I use the data from listed and OTC companies in Taiwan, and distinguishes the news sentiment of environment, society, and corporate governance. This study helps to complement the differences in ESG news sentiment across regions and industries.
In terms of research methods, it is proved that the BERT is a good sentiment analysis tool. BERT has a strong ability to understand articles and provides accurate sentiment classification results. Compared with other sentiment analysis models, it has better performance in accuracy and F1-Score. From the research results, it is found that ESG news sentiment has a significant impact on individual stock returns, and negative ESG news sentiment has a greater impact on returns than positive ESG news sentiment, which is consistent with the predictions from behavioral finance theories and hypotheses. This article mainly discovers that when news content includes ESG factors, it can enhance the positive impact of positive news and reduce the negative effects of negative news on returns. It also summarizes the responses of various industries to E, S, G news. Most industry’s returns are positive for positive news and negative for negative news. And found that some industries have a negative view on ESG issues, indicating that there are concerns about cost increases and agency issues.
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Aouadi, A., & Marsat, S. (2018). Do ESG controversies matter for firm value? Evidence from international data. Journal of Business Ethics, 151, 1027-1047.
Arvidsson, S., & Dumay, J. (2022). Corporate ESG reporting quantity, quality and performance: Where to now for environmental policy and practice? Business Strategy and the Environment, 31(3), 1091-1110.
Aupperle, K. E., Carroll, A. B., & Hatfield, J. D. (1985). An empirical examination of the relationship between corporate social responsibility and profitability. Academy of management Journal, 28(2), 446-463.
Aureli, S., Del Baldo, M., Lombardi, R., & Nappo, F. (2020). Nonfinancial reporting regulation and challenges in sustainability disclosure and corporate governance practices. Business Strategy and the Environment, 29(6), 2392-2403.
Baker, M., Bergstresser, D., Serafeim, G., & Wurgler, J. (2018). Financing the response to climate change: The pricing and ownership of US green bonds.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of economic perspectives, 21(2), 129-151.
Bonsall IV, S. B., Green, J., & Muller III, K. A. (2020). Market uncertainty and the importance of media coverage at earnings announcements. Journal of Accounting and Economics, 69(1), 101264.
Borms, S., Boudt, K., Holle, F. V., & Willems, J. (2021). Semi-supervised text mining for monitoring the news about the ESG performance of companies. In Data Science for Economics and Finance: Methodologies and Applications (pp. 217-239). Springer International Publishing Cham.
Boudoukh, J., Feldman, R., Kogan, S., & Richardson, M. (2013). Which news moves stock prices? A textual analysis.
Brammer, S., & Pavelin, S. (2005). Corporate reputation and an insurance motivation for corporate social investment. Journal of Corporate Citizenship(20), 39-51.
Cahan, S. F., Chen, C., Chen, L., & Nguyen, N. H. (2015). Corporate social responsibility and media coverage. Journal of Banking & Finance, 59, 409-422.
Capelle-Blancard, G., & Petit, A. (2019). Every little helps? ESG news and stock market reaction. Journal of Business Ethics, 157, 543-565.
Chan, L. K., Lakonishok, J., & Sougiannis, T. (2001). The stock market valuation of research and development expenditures. The Journal of Finance, 56(6), 2431-2456.
Chan, M. C., Watson, J., & Woodliff, D. (2014). Corporate governance quality and CSR disclosures. Journal of Business Ethics, 125, 59-73.
Chen, H.-Y., & Yang, S. S. (2020). Do investors exaggerate corporate ESG information? Evidence of the ESG momentum effect in the Taiwanese market. Pacific-Basin Finance Journal, 63, 101407.
Chen, M.-P., Chen, P.-F., & Lee, C.-C. (2013). Asymmetric effects of investor sentiment on industry stock returns: Panel data evidence. Emerging Markets Review, 14, 35-54.
Colquitt, L. L., & Hoyt, R. E. (1997). Determinants of corporate hedging behavior: Evidence from the life insurance industry. Journal of risk and insurance, 649-671.
Coqueret, G. (2020). Stock-specific sentiment and return predictability. Quantitative Finance, 20(9), 1531-1551.
Cordazzo, M., Bini, L., & Marzo, G. (2020). Does the EU Directive on non‐financial information influence the value relevance of ESG disclosure? Italian evidence. Business Strategy and the Environment, 29(8), 3470-3483.
Costola, M., Hinz, O., Nofer, M., & Pelizzon, L. (2023). Machine learning sentiment analysis, Covid-19 news and stock market reactions. Research in International Business and Finance, 101881.
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描述 碩士
國立政治大學
金融學系
110352023
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110352023
資料類型 thesis
dc.contributor.advisor 楊曉文zh_TW
dc.contributor.advisor Yang, Sheau-Wenen_US
dc.contributor.author (Authors) 賴亮瑋zh_TW
dc.contributor.author (Authors) Lai, Liang-Weien_US
dc.creator (作者) 賴亮瑋zh_TW
dc.creator (作者) Lai, Liang-Weien_US
dc.date (日期) 2023en_US
dc.date.accessioned 6-Jul-2023 16:47:51 (UTC+8)-
dc.date.available 6-Jul-2023 16:47:51 (UTC+8)-
dc.date.issued (上傳時間) 6-Jul-2023 16:47:51 (UTC+8)-
dc.identifier (Other Identifiers) G0110352023en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/145864-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 金融學系zh_TW
dc.description (描述) 110352023zh_TW
dc.description.abstract (摘要) 隨著市場開始重視ESG，以及投資人對ESG資訊的需求量增加，發布頻率高的ESG新聞成為投資人獲取ESG資訊的管道之一，而ESG資訊如何對報酬產生影響成為重要議題。過去文獻對此議題的結論不盡相同，且研究樣本多採用美國地區的ESG新聞，因此本文使用台灣上市及上櫃公司資料進行實證分析，並進一步區別環境、社會、公司治理三類別的新聞情緒對各產業之影響，本文有助於補充ESG新聞情緒在不同地區及產業的差異。
研究方法方面，證明BERT自然語言模型是合適的情緒分析工具，基於BERT具備強大的文章理解能力，提供準確的情緒分類結果，相較於其他情緒分析模型，在準確度、F1-Score都有較佳的表現。研究結果方面，台灣ESG新聞情緒對個股報酬有顯著的同向影響，且負面ESG新聞情緒對個股報酬的影響較正面ESG新聞情緒大，符合行為財務理論與假說預測。本文有兩點重要發現，第一，當新聞內容包含ESG因素，可提升正面新聞的正面影響力，同時降低負面新聞對報酬的負面效果。第二，整理環境、社會、公司治理三類別對各產業的反應，反應不盡相同，大部分產業報酬受正面新聞的反應為正面，負面新聞的反應為負面。關於社會與公司治理議題的消費品產業新聞，對報酬反應皆為負面，顯示仍有產業對於ESG議題持負面看法，存在成本增加、與代理人問題等擔憂。		zh_TW
dc.description.abstract (摘要) As market funds flow into ESG investments and the increasing demand for ESG information from investors, ESG news with the highest frequency of release has become the best way for investors to obtain ESG information, and how ESG information affects returns has become an important issue. Previous literature has reached different conclusions, and focusing on ESG news from the United States. In this paper, I use the data from listed and OTC companies in Taiwan, and distinguishes the news sentiment of environment, society, and corporate governance. This study helps to complement the differences in ESG news sentiment across regions and industries.
In terms of research methods, it is proved that the BERT is a good sentiment analysis tool. BERT has a strong ability to understand articles and provides accurate sentiment classification results. Compared with other sentiment analysis models, it has better performance in accuracy and F1-Score. From the research results, it is found that ESG news sentiment has a significant impact on individual stock returns, and negative ESG news sentiment has a greater impact on returns than positive ESG news sentiment, which is consistent with the predictions from behavioral finance theories and hypotheses. This article mainly discovers that when news content includes ESG factors, it can enhance the positive impact of positive news and reduce the negative effects of negative news on returns. It also summarizes the responses of various industries to E, S, G news. Most industry’s returns are positive for positive news and negative for negative news. And found that some industries have a negative view on ESG issues, indicating that there are concerns about cost increases and agency issues.		en_US
dc.description.tableofcontents 摘要 ii
Abstract iii
目錄 iv
圖目錄 vi
表目錄 vi
第一章 緒論 1
第一節 研究背景 1
第二節 研究目的 2
第三節 研究流程 3
第二章 文獻探討 4
第一節 CSR、ESG與報酬 4
第二節 新聞情緒與報酬 7
第三節 CSR、ESG新聞情緒與報酬 8
第三章 研究方法 10
第一節 研究架構 10
第二節 ESG新聞情緒分數之建構方法 11
第三節 篩選ESG相關新聞方法 17
第四節 研究假說 19
一、 ESG新聞情緒是否對報酬有顯著影響 19
二、 ESG新聞情緒類別對報酬影響程度不一致 19
三、 ESG新聞情緒對報酬的影響較非ESG新聞情緒低 20
四、 E、S、G新聞情緒在不同產業具不同影響 21
第五節 變數定義與資料來源 22
一、 應變數 22
二、 解釋變數 23
三、 控制變數 24
第六節 模型設定 26
第四章 實證結果分析 28
第一節 BERT情緒分析表現 28
第二節 敘述統計 30
第三節 相關性分析 33
第四節 實證結果分析 35
第五章 結論 48
第一節 研究結論 48
第二節 研究限制與建議 49
第六章 附錄 50
參考文獻 52		zh_TW
dc.format.extent 1597644 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110352023en_US
dc.subject (關鍵詞) ESGzh_TW
dc.subject (關鍵詞) ESG新聞zh_TW
dc.subject (關鍵詞) 情緒分析zh_TW
dc.subject (關鍵詞) BERTzh_TW
dc.subject (關鍵詞) ESGen_US
dc.subject (關鍵詞) ESG Newsen_US
dc.subject (關鍵詞) Sentiment Analysisen_US
dc.subject (關鍵詞) BERTen_US
dc.title (題名) 基於BERT模型分析ESG新聞情緒對股票報酬之影響zh_TW
dc.title (題名) Analyzing the Impact of ESG News Sentiment on Stock Returns Based on BERT Modelen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Antweiler, W., & Frank, M. Z. (2004). Is all that talk just noise? The information content of internet stock message boards. The Journal of Finance, 59(3), 1259-1294.
Aouadi, A., & Marsat, S. (2018). Do ESG controversies matter for firm value? Evidence from international data. Journal of Business Ethics, 151, 1027-1047.
Arvidsson, S., & Dumay, J. (2022). Corporate ESG reporting quantity, quality and performance: Where to now for environmental policy and practice? Business Strategy and the Environment, 31(3), 1091-1110.
Aupperle, K. E., Carroll, A. B., & Hatfield, J. D. (1985). An empirical examination of the relationship between corporate social responsibility and profitability. Academy of management Journal, 28(2), 446-463.
Aureli, S., Del Baldo, M., Lombardi, R., & Nappo, F. (2020). Nonfinancial reporting regulation and challenges in sustainability disclosure and corporate governance practices. Business Strategy and the Environment, 29(6), 2392-2403.
Baker, M., Bergstresser, D., Serafeim, G., & Wurgler, J. (2018). Financing the response to climate change: The pricing and ownership of US green bonds.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of economic perspectives, 21(2), 129-151.
Bonsall IV, S. B., Green, J., & Muller III, K. A. (2020). Market uncertainty and the importance of media coverage at earnings announcements. Journal of Accounting and Economics, 69(1), 101264.
Borms, S., Boudt, K., Holle, F. V., & Willems, J. (2021). Semi-supervised text mining for monitoring the news about the ESG performance of companies. In Data Science for Economics and Finance: Methodologies and Applications (pp. 217-239). Springer International Publishing Cham.
Boudoukh, J., Feldman, R., Kogan, S., & Richardson, M. (2013). Which news moves stock prices? A textual analysis.
Brammer, S., & Pavelin, S. (2005). Corporate reputation and an insurance motivation for corporate social investment. Journal of Corporate Citizenship(20), 39-51.
Cahan, S. F., Chen, C., Chen, L., & Nguyen, N. H. (2015). Corporate social responsibility and media coverage. Journal of Banking & Finance, 59, 409-422.
Capelle-Blancard, G., & Petit, A. (2019). Every little helps? ESG news and stock market reaction. Journal of Business Ethics, 157, 543-565.
Chan, L. K., Lakonishok, J., & Sougiannis, T. (2001). The stock market valuation of research and development expenditures. The Journal of Finance, 56(6), 2431-2456.
Chan, M. C., Watson, J., & Woodliff, D. (2014). Corporate governance quality and CSR disclosures. Journal of Business Ethics, 125, 59-73.
Chen, H.-Y., & Yang, S. S. (2020). Do investors exaggerate corporate ESG information? Evidence of the ESG momentum effect in the Taiwanese market. Pacific-Basin Finance Journal, 63, 101407.
Chen, M.-P., Chen, P.-F., & Lee, C.-C. (2013). Asymmetric effects of investor sentiment on industry stock returns: Panel data evidence. Emerging Markets Review, 14, 35-54.
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