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題名:新聞報導之資訊不對稱與市場恐慌情緒對台灣證劵市場股價反應之影響
作者:李飛涵
作者(外文):LEE, FEI-HAN
校院名稱:國立中正大學
系所名稱:企業管理系研究所
指導教授:王明昌
學位類別:博士
出版日期:2021
主題關鍵詞:文字探勘支援向量機新聞報導股價報酬率恐慌指數ext miningSVMnews coveragestock returnvolatility index
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本研究以台灣證劵市場之新聞報導、股價報酬和市場情續觀察投資人在信息和環境變動的情況下對股價報酬的反應,結合芝加哥選擇權交易所(CBOE)建立之恐慌指數(VIX)作為投資人情緒,探討在市場恐慌時期,投資人是否會因新聞報導引起對股價的不對稱反應,以及新聞報導是否會因投資人情緒對股價產生增額或減額效果。本研究以文字探勘(text mining)之支援向量機(SVM)作為機器學習的演算法,採用台灣經濟新報(TEJ)上市金融市場大事記資料庫之台灣50成分股的新聞報導和股價作為訓練樣本,研究樣本分成兩部份:(一) 2009至2016年之境內、外公司之新聞報導;(二)2011至2020年之新聞報導觀察恐慌指數變動對股價報酬之反應。研究結果發現境內和境外公司具有資訊不對稱之反應:新聞報導的發佈對事件超額報酬率具顯著相關,但在恐慌指數變動則為不相關;同時延長對新聞報導的觀察,以事件累積超額報酬發現恐慌指數變動下,正、負面新聞具有不對稱的股價反應。
The purpose of this study was to investigate news coverage, stock returns, and market sentiment to observe investors who responses to stock returns under market information and unstable environment on the Taiwan Stock Exchange. Simultaneously, combined with the volatility index (VIX) established by COBE is used as investor sentiment to examine whether investors would react asymmetrically to stock prices because of news coverage. In addition, whether the VIX_change had an additional effect of increasing the share price reaction of the Taiwan stock market in positive news and negative news.
The study the support vector machine (SVM) of text mining as the machine learning algorithm, and use the news coverage and stock returns of FTSE TWSE Taiwan 50 Index (TWSE 50) as a training sample from TEJ. And the research sample is divided into two parts: (1) the samples are domestic and offshore listed companies from 2009 to 2016. (2) the samples are all listed companies from 2011 to 2020. The results indicated that domestic and offshore listed companies have information asymmetry. The release of news coverage has a significant correlation with the stock returns, but it is not relevant when the VIX_change. On the other hand, this study extended to seven days to observe which found CAR(cumulative abnormal return in event period) had an asymmetric reaction between positive news and negative news under the VIX_changes.
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