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題名 ESG評等與盈餘表現對股票報酬之影響：以台灣市場為例
The Impact of ESG Rating and Earnings Performance on Stock Return: Evidence in Taiwan
作者 呂星儒
Lu, Hsing-Ju
貢獻者 郭維裕<br>江彌修
Kuo, Wei-Yu<br>Chiang, Mi-Hsiu
呂星儒
Lu, Hsing-Ju
關鍵詞 ESG
ESG評等
盈餘表現
盈餘驚喜
機器學習
分類迴歸樹
ESG
ESG ratings
Earnings performance
Earnings surprise
Machine learning
Classification and regression trees
日期 2024
上傳時間 5-Aug-2024 14:18:22 (UTC+8)
摘要 本研究旨在探討ESG評等對台灣股市報酬率的影響，並使用非線性機器學習模型，分類迴歸樹（CART）分析ESG評等與公司盈餘表現之間的交互作用。研究期間涵蓋2016至2023年，採用台灣經濟新報資料庫中的台灣上市公司資料進行多變量分析。本文首先探討公司盈餘表現與ESG評等對股票報酬的單一變量影響，隨後利用分類迴歸樹進一步分析每股盈餘變化量、每股盈餘不符預期的程度及ESG評等對股票報酬的共同對報酬率的影響。實證結果顯示，雖然ESG評等與股票報酬率間並無顯著線性關係且相對盈餘表現，ESG評等對於股票報酬影響之貢獻程度亦不大，但透過迴歸樹模型仍可以識別出影響股票報酬的關鍵非線性交互關係。本研究結果提供投資人若欲將ESG因子納入投資決策時，並不建議單獨評估ESG評等，該指標對於股票報酬影響遠不足其他因素，亦或是建議可以進一步探討ESG評等之細項評估指標，例如將ESG評等拆解成環境(E)、社會(S)與治理(G)不同維度之細項指標，找出其中對於影響股票報酬相對重要的ESG指標。
The purpose of this study was to investigate the impact of ESG ratings on stock returns in the Taiwanese market. Another aim was to explore the specific impact of the interac-tion between ESG ratings and corporate earnings performance on stock returns. Em-ploying a quantitative methodology, the Classification and Regression Tree (CART) model was utilized to analyze data from publicly listed companies in Taiwan, as record-ed in the Taiwan Economic Journal database for the period 2016 to 2023. The empirical results revealed no significant relationship between ESG ratings and stock returns, and the contribution of ESG ratings was found to be minimal when compared to other fac-tors such as EPS changes and EPS surprise. However, the CART model identified the non-linear interactions that impact stock returns. The study concludes that relying solely on ESG ratings for investment decisions is insufficient and recommends further inves-tigation into specific ESG indicators that could profoundly affect stock returns, thereby aiding investors in making more informed decisions.
參考文獻 李大維(2022)。ESG對臺灣上市櫃公司股票報酬之影響：以新冠肺炎疫情期間為例。國立台灣大學財務金融所碩士論文，台北市。 游琇螢(2019)。ESG分數對公司績效表現與風險的影響 —以台灣市場為例。國立中央大學財務金融所碩士論文，桃園市。 孫嘉蔚(2021)。運用機器學習模型分析影響公司風險的ESG因子：以台灣市場為例。國立政治大學金融所碩士論文，台北市。 安聯投資. (2020). 深度分析：ESG如何提升潛在超額回報？ 檢自：https://hk.allianzgi.com/zh-hk/retail/insights/sustainability/esg-insights/esg-strategy-alpha-analysis 台灣經濟新報. (2022). ESG評等 比一比 - 3大國際評等介紹. 檢自： https://www.tejwin.com/news/esg%E8%A9%95%E7%AD%89/#%E5%88%86%E9%A1%9E%E6%A8%99%E6%BA%96 台灣經濟新報. (2022). SASB產業分類 更貼近ESG精神. 檢自： https://www.tejwin.com/news/sasb%E7%94%A2%E6%A5%AD%E5%88%86%E9%A1%9E_%E6%9B%B4%E8%B2%BC%E8%BF%91esg%E7%B2%BE%E7%A5%9E/ 國立臺北大學. (2023). 台灣永續投資調查. 檢自： https://cgcss.ntpu.edu.tw/lyadmin/pages/uploads/file/f1_xwk0lax0oc.pdf CSRone. (2023). 2023 臺灣暨亞太永續報告現況與趨勢. 檢自： https://csrone.com/reports/5777 Ashwin Kumar, N. C., Smith, C., Badis, L., Wang, N., Ambrosy, P., & Tavares, R. (2016). ESG factors and risk-adjusted performance: a new quantitative model. Journal of Sustainable Finance & Investment, 6(4), 292–300. https://doi.org/10.1080/20430795.2016.1234909 Breiman, L., Friedman, J., Olshen, R. A., & Stone, C. J. (1984). Classification and re-gression trees (1st ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781315139470 Halbritter, G., & Dorfleitner, G. (2015). The wages of social responsibility—where are they? A critical review of ESG investing. Review of Financial Economics, 26, 25-35. https://doi.org/10.1016/j.rfe.2015.03.004 Lewis, R. J. (2000). An introduction to classification and regression tree (CART) anal-ysis. In Annual Meeting of the Society of Academic Emergency Medicine. San Francisco, California. Loh, W.-Y. (2014). Fifty years of classification and regression trees. International Sta-tistical Review / Revue Internationale de Statistique, 82(3), 329-348. Naffa, H., & Fain, M. (2021). A factor approach to the performance of ESG leaders and laggards. Finance Research Letters. https://doi.org/10.1016/j.frl.2021.102073 PwC. (2023). Global investor survey 2023. from: https://www.pwc.com/gx/en/issues/c-suite-insights/global-investor-survey.html Sorensen, E., Mussalli, G., Lancetti, S., & Belanger, D. (2022). ESG, fundamentals, and stock returns. The Journal of Portfolio Management, 48(10). https://doi.org/10.3905/jpm.2022.1.408 Verheyden, T., Eccles, R. G., & Feiner, A. (2016). ESG for all? The impact of ESG screening on return, risk and diversification. Journal of Applied Corporate Fi-nance, 28(2), 47-55. Available at SSRN: https://ssrn.com/abstract=2834790 World Economic Forum. (2021). The Global Risks Report 2021 (16th ed.). Geneva: World Economic Forum. World Economic Forum. (2022). The Global Risks Report 2022: 17th edition — In-sight report. Geneva: World Economic Forum. World Economic Forum. (2023). The Global Risks Report 2023: 18th edition — In-sight report. Geneva: World Economic Forum.
描述 碩士
國立政治大學
國際金融碩士學位學程
111ZB1006
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0111ZB1006
資料類型 thesis
dc.contributor.advisor 郭維裕<br>江彌修zh_TW
dc.contributor.advisor Kuo, Wei-Yu<br>Chiang, Mi-Hsiuen_US
dc.contributor.author (Authors) 呂星儒zh_TW
dc.contributor.author (Authors) Lu, Hsing-Juen_US
dc.creator (作者) 呂星儒zh_TW
dc.creator (作者) Lu, Hsing-Juen_US
dc.date (日期) 2024en_US
dc.date.accessioned 5-Aug-2024 14:18:22 (UTC+8)-
dc.date.available 5-Aug-2024 14:18:22 (UTC+8)-
dc.date.issued (上傳時間) 5-Aug-2024 14:18:22 (UTC+8)-
dc.identifier (Other Identifiers) G0111ZB1006en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/152838-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 國際金融碩士學位學程zh_TW
dc.description (描述) 111ZB1006zh_TW
dc.description.abstract (摘要) 本研究旨在探討ESG評等對台灣股市報酬率的影響，並使用非線性機器學習模型，分類迴歸樹（CART）分析ESG評等與公司盈餘表現之間的交互作用。研究期間涵蓋2016至2023年，採用台灣經濟新報資料庫中的台灣上市公司資料進行多變量分析。本文首先探討公司盈餘表現與ESG評等對股票報酬的單一變量影響，隨後利用分類迴歸樹進一步分析每股盈餘變化量、每股盈餘不符預期的程度及ESG評等對股票報酬的共同對報酬率的影響。實證結果顯示，雖然ESG評等與股票報酬率間並無顯著線性關係且相對盈餘表現，ESG評等對於股票報酬影響之貢獻程度亦不大，但透過迴歸樹模型仍可以識別出影響股票報酬的關鍵非線性交互關係。本研究結果提供投資人若欲將ESG因子納入投資決策時，並不建議單獨評估ESG評等，該指標對於股票報酬影響遠不足其他因素，亦或是建議可以進一步探討ESG評等之細項評估指標，例如將ESG評等拆解成環境(E)、社會(S)與治理(G)不同維度之細項指標，找出其中對於影響股票報酬相對重要的ESG指標。zh_TW
dc.description.abstract (摘要) The purpose of this study was to investigate the impact of ESG ratings on stock returns in the Taiwanese market. Another aim was to explore the specific impact of the interac-tion between ESG ratings and corporate earnings performance on stock returns. Em-ploying a quantitative methodology, the Classification and Regression Tree (CART) model was utilized to analyze data from publicly listed companies in Taiwan, as record-ed in the Taiwan Economic Journal database for the period 2016 to 2023. The empirical results revealed no significant relationship between ESG ratings and stock returns, and the contribution of ESG ratings was found to be minimal when compared to other fac-tors such as EPS changes and EPS surprise. However, the CART model identified the non-linear interactions that impact stock returns. The study concludes that relying solely on ESG ratings for investment decisions is insufficient and recommends further inves-tigation into specific ESG indicators that could profoundly affect stock returns, thereby aiding investors in making more informed decisions.en_US
dc.description.tableofcontents 第一章 緒論 6 第一節 研究背景及動機 6 第二節 研究目的與研究架構 8 第二章 文獻探討 10 第一節 ESG如何影響報酬與風險 10 第二節 ESG評等與股票市場報酬和風險 10 第三節 迴歸樹介紹 11 第四節 機器學習於ESG與報酬和風險的應用 13 第三章 研究方法與資料 15 第一節 變數資料來源 15 第二節 樣本選擇 16 第三節 實證模型與變數定義 16 第四章 實證結果與分析 19 第一節 敘述性統計分析 19 第二節 單變量分析結果 19 第三節 所有年度迴歸樹結果 21 第四節 個別年度迴歸樹結果 26 第五節 變量之特徵重要性分析 30 第五章 研究結論 31 參考文獻 33zh_TW
dc.format.extent 2057758 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0111ZB1006en_US
dc.subject (關鍵詞) ESGzh_TW
dc.subject (關鍵詞) ESG評等zh_TW
dc.subject (關鍵詞) 盈餘表現zh_TW
dc.subject (關鍵詞) 盈餘驚喜zh_TW
dc.subject (關鍵詞) 機器學習zh_TW
dc.subject (關鍵詞) 分類迴歸樹zh_TW
dc.subject (關鍵詞) ESGen_US
dc.subject (關鍵詞) ESG ratingsen_US
dc.subject (關鍵詞) Earnings performanceen_US
dc.subject (關鍵詞) Earnings surpriseen_US
dc.subject (關鍵詞) Machine learningen_US
dc.subject (關鍵詞) Classification and regression treesen_US
dc.title (題名) ESG評等與盈餘表現對股票報酬之影響：以台灣市場為例zh_TW
dc.title (題名) The Impact of ESG Rating and Earnings Performance on Stock Return: Evidence in Taiwanen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 李大維(2022)。ESG對臺灣上市櫃公司股票報酬之影響：以新冠肺炎疫情期間為例。國立台灣大學財務金融所碩士論文，台北市。 游琇螢(2019)。ESG分數對公司績效表現與風險的影響 —以台灣市場為例。國立中央大學財務金融所碩士論文，桃園市。 孫嘉蔚(2021)。運用機器學習模型分析影響公司風險的ESG因子：以台灣市場為例。國立政治大學金融所碩士論文，台北市。 安聯投資. (2020). 深度分析：ESG如何提升潛在超額回報？ 檢自：https://hk.allianzgi.com/zh-hk/retail/insights/sustainability/esg-insights/esg-strategy-alpha-analysis 台灣經濟新報. (2022). ESG評等 比一比 - 3大國際評等介紹. 檢自： https://www.tejwin.com/news/esg%E8%A9%95%E7%AD%89/#%E5%88%86%E9%A1%9E%E6%A8%99%E6%BA%96 台灣經濟新報. (2022). SASB產業分類 更貼近ESG精神. 檢自： https://www.tejwin.com/news/sasb%E7%94%A2%E6%A5%AD%E5%88%86%E9%A1%9E_%E6%9B%B4%E8%B2%BC%E8%BF%91esg%E7%B2%BE%E7%A5%9E/ 國立臺北大學. (2023). 台灣永續投資調查. 檢自： https://cgcss.ntpu.edu.tw/lyadmin/pages/uploads/file/f1_xwk0lax0oc.pdf CSRone. (2023). 2023 臺灣暨亞太永續報告現況與趨勢. 檢自： https://csrone.com/reports/5777 Ashwin Kumar, N. C., Smith, C., Badis, L., Wang, N., Ambrosy, P., & Tavares, R. (2016). ESG factors and risk-adjusted performance: a new quantitative model. Journal of Sustainable Finance & Investment, 6(4), 292–300. https://doi.org/10.1080/20430795.2016.1234909 Breiman, L., Friedman, J., Olshen, R. A., & Stone, C. J. (1984). Classification and re-gression trees (1st ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781315139470 Halbritter, G., & Dorfleitner, G. (2015). The wages of social responsibility—where are they? A critical review of ESG investing. Review of Financial Economics, 26, 25-35. https://doi.org/10.1016/j.rfe.2015.03.004 Lewis, R. J. (2000). An introduction to classification and regression tree (CART) anal-ysis. In Annual Meeting of the Society of Academic Emergency Medicine. San Francisco, California. Loh, W.-Y. (2014). Fifty years of classification and regression trees. International Sta-tistical Review / Revue Internationale de Statistique, 82(3), 329-348. Naffa, H., & Fain, M. (2021). A factor approach to the performance of ESG leaders and laggards. Finance Research Letters. https://doi.org/10.1016/j.frl.2021.102073 PwC. (2023). Global investor survey 2023. from: https://www.pwc.com/gx/en/issues/c-suite-insights/global-investor-survey.html Sorensen, E., Mussalli, G., Lancetti, S., & Belanger, D. (2022). ESG, fundamentals, and stock returns. The Journal of Portfolio Management, 48(10). https://doi.org/10.3905/jpm.2022.1.408 Verheyden, T., Eccles, R. G., & Feiner, A. (2016). ESG for all? The impact of ESG screening on return, risk and diversification. Journal of Applied Corporate Fi-nance, 28(2), 47-55. Available at SSRN: https://ssrn.com/abstract=2834790 World Economic Forum. (2021). The Global Risks Report 2021 (16th ed.). Geneva: World Economic Forum. World Economic Forum. (2022). The Global Risks Report 2022: 17th edition — In-sight report. Geneva: World Economic Forum. World Economic Forum. (2023). The Global Risks Report 2023: 18th edition — In-sight report. Geneva: World Economic Forum.zh_TW