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| Title: | 文字探勘ESG新聞情緒分析對股票報酬率之研究-以臺灣大型股為例
Analysis of Sentiment in ESG News with Text Mining for the Impact of Stock Market Returns - The Case of Large Cap Firms in Taiwan |
| Authors: | 廖渝瑄
Liao, Yu-Hsuan |
| Contributors: | 楊曉文
廖渝瑄
Liao, Yu-Hsuan |
| Keywords: | 企業社會責任
ESG新聞
情緒分析
文字探勘
資產定價
Corporate Social Responsibility
ESG News
Sentiment Analysis
Text Mining
Asset Pricing |
| Date: | 2023 |
| Issue Date: | 2023-03-09 18:35:34 (UTC+8) |
| Abstract: | 近年來由於經濟迅速發展造成環境破壞，全球永續意識抬頭，大眾、企業與政府逐漸重視企業社會責任 (CSR)，進而產生許多評估企業CSR表現的方式，但大多以永續報告書作為評估標準，每年發佈對於短期投資人來說並不效率，故本研究以ESG媒體情緒作為一種衡量企業CSR表現的指標，透過文字探勘、情感分析為投資人提供衡量企業CSR表現的分析模式，搜集主觀（PTT平台）與客觀（中央通訊社）媒體新聞進行文本分類與情緒分析，了解媒體對企業CSR表現的評價與形象。
本研究透過企業永續報告書建構ESG環境、社會、公司治理分類詞表作新聞文本分類，文本情感分析使用雙向長短記憶神經網路(Bi-LSTM)模型，並將新聞文本根據情緒傾向分為「正面」、「負面」，且將樣本資料分割為前疫情時期與後疫情時期，最後使用Fama-Macbeth(1973)迴歸模型分析，深入探討ESG媒體情緒與報酬率之關聯與後疫情時代ESG媒體情緒之影響力。
經本研究搜集資料對其進行分析之實證結果的研究結論主要如下：(1)ESG媒體情緒傾向於正向短期股價報酬率。(2)不同資料來源情緒傾向不同，對投資人的影響也不同。(3) ESG媒體情緒有分類衡量的必要。 (4)媒體情緒對個股報酬率有短期正向效果，延遲反向效果，且分類為正負面後，正面新聞有短期正向效果，負面新聞則有延遲反向效果。 (5)ESG負面新聞對股價報酬率有延遲反向效果，正面新聞不影響。(6)後疫情時代新聞情緒對個股報酬率影響程度提高，但ESG新聞則無。
In recent years, due to the environmental damage caused by the rapid economic development, the global awareness of sustainability has risen. The public, enterprises and governments have gradually paid attention to corporate social responsibility (CSR). There are many methods to evaluate the CSR performance of enterprises now, but most of them use the sustainability reports as the standard. It is not efficient to use yearly information for short-term investors. Therefore, this study uses ESG media sentiment as an indicator to measure corporate CSR performance, and provides investors with an analysis model to measure corporate CSR performance by text mining and sentiment analysis. By collecting subjective and objective media, the research conducts text classification and sentiment analysis of news to understand the media`s evaluation and image of corporate CSR performance.
This research constructs ESG environmental, social, and governance classification vocabulary for news classification through corporate sustainability reports. Bidirectional long short-term memory (Bi-LSTM) is used to text sentiment analysis. We divide news into "positive" and "negative" according to their emotional tendencies, and divide the sample data into pre-pandemic and post-pandemic periods. Finally, Fama-Macbeth (1973) regression model is used to analyze the relationship between ESG media sentiment and stock price returns. Furthermore, we study the influence of ESG media sentiment in the post-pandemic era.
The empirical results and analysis of the data collected in this study are mainly as follows: (1) ESG media sentiment tends to have a positive impact on the short-term stock price returns. (2) There are different sentimental tendencies and influences on investors from different news sources. (3) ESG media sentiment needs to be classified. (4) Media sentiment has a short-term positive effect and a delayed negative effect on the rate of return of individual stocks. After being classified into positive and negative, media sentiment of positive news has a short-term positive effect, and that of negative news has a delayed negative effect. (5) Negative ESG news has a delayed reverse effect on stock returns, while positive news has no effect. (6) In the post-pandemic era, the impact of news sentiment on stock returns has increased, but ESG news has not. |
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| Description: | 碩士
國立政治大學
金融學系
109352021 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0109352021 |
| Data Type: | thesis |
| Appears in Collections: | [金融學系] 學位論文
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