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研究生： 林奇斌
Qi-Bin Lin
論文名稱： 文本情緒的報酬可預測性： 以中國股市爲例
The Return Predictability of Text-based Sentiment: Evidence from China
指導教授： 周賓凰
Pin-Huang Chou
口試委員:
學位類別： 碩士
Master
系所名稱： 管理學院 - 財務金融學系
Department of Finance
論文出版年： 2021
畢業學年度： 109
語文別： 中文
論文頁數： 46
中文關鍵詞： 投資者情緒 、文本探勘 、XgBoost模型 、報酬預測
外文關鍵詞： investor sentiment, text-mining, XgBoost model, return predictability
相關次數： 點閱：17  下載：0 
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    • 本研究以2019年6月至2019年12月中國大陸上證A股市場上市公司為樣本，爬取東方財富網站旗下論壇「股吧」個人用戶發帖內容，利用XGBoost模型對文本情緒進行提取並構建投資者情緒指標，探討投資者情緒對於大陸個股股票報酬之影響。實證結果發現情緒指標能夠預測下一期股票報酬，隨後股票報酬發生反轉；對於小市值公司而言，投資者情緒對下一期個股股票報酬有較强的影響，但隨後的反轉更加强烈；投資者偏好在股票交易時段進行發貼，且該時段帖子字數普遍較短，非交易時段情緒指標對於股票報酬有更强的預測能力，反轉較小。

    This paper takes the Shanghai A-share stock as sample, uses python to crawl data from the post content of individual users of the forum "Guba" of eastmoney website, and uses the XGBoost model to extract the sentiment of the text to construct investor sentiment indicators. This study explores how investor sentiment affects the individual stock returns in China. The results show that investor sentiment can predict the next period individual stock return, yet then the stock return exhibits reversal. The return of small stocks are more affected by investor sentiment. Individual investors prefer to send messages during the stock trading hours, and posts during this period are generally short in words. During non-trading hours investor sentiment has stronger predictive power for stock returns, with smaller reversals.

    第一章、緒論 1 1.1 研究背景 1 1.2 研究動機與目的 2 1.3 研究架構 3 第二章、文獻回顧 4 2.1 投資者情緒指標構建 4 2.1.1間接情緒指標構建 4 2.1.2 直接情緒指標構建 5 2.1.3 基於網路數據的投資者情緒指標構建 6 2.2 投資者情緒與股票市場之間的關係 7 第三章、研究方法 9 3.1 研究資料 9 3.1.1 資料來源 9 3.1.2 情緒指標構建 9 3.2 研究假設與模型 19 第四章、實證結果 22 4.1 敍述性統計 22 4.2 實證結果 24 第五章、結論 31 參考文獻 33

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