- 學位論文
利用機器學習方式探討ESG分數對上市公司價值的影響
Using machine learning models to explore the impact of ESG scores on the value of listed companies
摘要
研究旨在探討ESG(環境、社會和公司治理)分數對上市公司價值的影響。在傳統投資中大多數投資者仰賴公司財務報表表現來做出決策，然而隨著全球永續意識抬頭，除了財務指標層面，還必須考量到非財務指標對於公司價值的影響。本研究中使用到的財務指標除了有常見的ROA以及ROE，新增了一個較少見的財務指標—Tobin’s Q，進而使用非財務指標—ESG分數(環境構面分數、社會構面分數、公司治理分數)，想要探討ESG分數對於財務績效之間是否具有影響以及並且利用機器學習模型建立預測模型。將ESG分數納入多元迴歸模型後檢測是否跟財務績效指標具有顯著相關性，並利用羅吉斯迴歸模型獲得預測分類準確率，而機器學習模型利用超參數選擇及梯度提升法，將迴歸模型結果進行改善並得到最佳的預測模型。近年來隨著各大企業對於ESG逐漸重視，ESG指標已成為一種新型態評估企業績效的數據及指標，而公司對於永續發展的作為則會影響到ESG分數，進而影響到財務績效指標表現以及一間公司的價值。 研究結果顯示，使用迴歸模型得到環境分數、社會分數、公司治理分數對於Tobin’s Q都有正向的顯著相關，然而ROA及ROE則不顯著，羅吉斯迴歸得到的預測準確率並不高，因此透過機器學習模型進行準確率改善，最終在三個財務績效指標都獲得相當高的改善成效。透過分析結果，可以得知使用Tobin’s Q指標來衡量公司價值及盈利能力是較好的選擇，而一間公司年度ESG分數確實能夠影響到公司未來發展，高ESG評分的公司在市場價值及盈利能力方面表現更好。綜合以上結果，永續發展對於可持續發展的重要性已是企業必須優先考量到的因素，因為這將大大的影響到ESG分數。
並列摘要
This study aims to explore the impact of ESG (Environmental, Social, and Governance) scores on the value of listed companies. In traditional investments, most investors rely on a company's financial statement performance to make decisions. However, with the rising awareness of global sustainability, it is necessary to consider the impact of non-financial indicators on a company's value in addition to financial indicators. The financial indicators used in this study include the commonly used Return on Assets (ROA) and Return on Equity (ROE), as well as the less commonly used Tobin's Q ratio. Additionally, non-financial indicators—ESG scores (environmental score, social score, governance score)—are used to explore whether ESG scores have an impact on financial performance. A machine learning model is employed to establish a predictive model. The inclusion of ESG scores in the multiple regression model is used to test for significant correlations with financial performance indicators. Logistic regression is used to obtain prediction accuracy for classification, and the machine learning model improves the regression model results using hyperparameter selection and gradient boosting methods to achieve the best predictive model.In recent years, as major companies have increasingly emphasized ESG, ESG indicators have become a new type of data and metrics for evaluating corporate performance. A company's sustainability practices can affect its ESG scores, thereby influencing financial performance indicators and the company's value. The results of the study show that using the regression model, environmental scores, social scores, and governance scores all have a positive significant correlation with Tobin's Q. However, ROA and ROE are not significant. The prediction accuracy obtained from logistic regression is not high, so the machine learning model is used to improve accuracy. Significant improvements in all three financial performance indicators are achieved through the machine learning model. The analysis results indicate that using Tobin's Q to measure company value and profitability is a better choice, and a company's annual ESG score can indeed affect its future development. Companies with high ESG scores perform better in terms of market value and profitability. In summary, sustainable development is a priority factor that companies must consider, as it significantly impacts ESG scores.