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    Title: 新聞媒體情緒對於房價之影響
    The effect of news media sentiment on housing price
    Authors: 林筱真
    Contributors: 林左裕
    林筱真
    Keywords: 情緒分析
    新聞情緒
    房價
    向量自我迴歸模型
    Sentiment analysis
    News media
    Housing price
    VAR model
    Date: 2017
    Issue Date: 2017-08-28 11:47:49 (UTC+8)
    Abstract: 承如Shiller (1984)所述,市場投資者之行為會受到社會氛圍、潮流所影響,不動產市場受限於產品異質性與資訊不流通性,市場消息及情緒對於參與者預期與價格之影響更甚,而新聞作為不動產市場有限的資訊中公開且普及之資訊種類之一,對於市場情緒之影響不容小覷。過去亦有諸多研究指出新聞得以傳達或影響市場參與者之情緒,本研究嘗試以新聞進行情緒分析,將新聞情緒納入分析不動產市場之基礎,探討其與房價間之關係,補足過去研究建立在完全競爭市場假設、僅就基本面分析之不足。研究結果發現新聞情緒變數與市場參與者預期呈現中高程度之顯著正相關。此外,從向量自我迴歸模型結果亦發現前一期新聞情緒變數與房價間呈現正向顯著關聯,顯示前一期新聞媒體提及不動產市場時越樂觀,市場參與者對於市場景氣越看好,將進而投入市場造成未來房價上升。而透過格蘭傑因果關係檢定,本研究亦發現市場參與者情緒與新聞情緒間存在雙向因果關係,顯示新聞情緒確實將影響市場參與者預期,進而推升價格波動。可見透過新聞情緒不僅可補足過去總體經濟變數所無法解釋之市場意向,更可增加我們對於房地產市場之解釋、掌握能力。
    Real estate market, with heterogeneity and lack of information, tends to be affected by market trend or sentiment. It is plausible that investors` behavior is influenced by social movements (Shiller,1984). The impact of news media, as one of open and widespread sources of market information, on market sentiment should not be underestimated. There are some studies exploring the relationship between news media and market sentiment. This paper attempts to measure the real estate market sentiment by quantifying the qualitative tone of news media, and provides evidence for its effect on housing price. The result shows that sentiment of news media is highly correlated with investors’ expectation, with statistically significant. Besides, through VAR model, this paper also finds that news sentiment of first lag had positive and significant influence on housing price, indicating that when news sentiment rises, investors are more optimistic about the real estate market, promoting housing demand and housing price growth. This study also finds that each of the news sentiment and market expectation Granger-causes the other. It suggests that news sentiment, capturing the market emotion that cannot be interpreted by fundamental variables, serves as a useful factor for quantifying investor expectation and predicting housing price.
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    Description: 碩士
    國立政治大學
    地政學系
    104257006
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0104257006
    Data Type: thesis
    Appears in Collections:[地政學系] 學位論文

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