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研究生： 陳盈臻
Chen, Ying-Jhen
論文名稱： 褐皮書是否會驅動建築投資?
Does the Beige Book Move Construction Investment?
指導教授： 陳明吉
Chen, Ming-Chi
口試委員: 張元晨
Chang, Yuan-Chen
楊智元
Yang, Chih-Yuan
學位類別： 碩士
Master
系所名稱： 商學院 - 財務管理學系
Department of Finance
論文出版年： 2019
畢業學年度： 107
語文別： 英文
論文頁數： 53
中文關鍵詞： 文字探勘 、情緒分析 、房地產市場 、褐皮書 、情緒指數
外文關鍵詞： Text mining, Sentiment analysis, Real estate market, Beige Book, Sentiment index
DOI URL： http://doi.org/10.6814/NCCU201900558
相關次數： 點閱：77  下載：2 
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    • The main purpose of this thesis was to explore whether the information in the important government documents could be applied in the real estate market. We used 160 Beige Books from January 1998 to December 2017 as our research materials, which were one of the representative official documents of the United States. We constructed a sentiment index based on the content of the Beige Book by text mining and lexicon-based approach for sentiment analysis. The sentiment index is the main factor that may affect real estate market, as we observed. The representative real estate market indicators included dependent variables, such as house prices, construction output, building permits and real estate stocks, and some macroeconomic data as control variables, such as unemployment rate, population, mortgage interest rate and personal income. The results showed that the sentiment index of the Beige Book was positively associated with changes in housing prices, construction output and building permits, that in particular, the current sentiment variables had a more significant impact on those real estate market indicators. However, the sentiment index of the Beige Book was not significantly associated with changes in S&P 500 Real Estate, in which the reason might be that S&P 500 Real Estate was only representing one sector of S&P 500; thus, we believed that real estate stocks would be more affected by variables relevant to the stock market. In this thesis, we found the Beige Book as a market sentiment index, which not only influenced the direction of monetary policy, but also impacted the real estate market.

    1. Introduction 1
    2. Literature Review 5
    2.1 The Relation between Macroeconomic Variables and the Real Estate Market 5
    2.2 The Relation between Investor Sentiment and the Financial Market 7
    2.3 The Relation between Investor Sentiment and the Real Estate Market 7
    2.4 The Relation between the Beige Book and the Economy 9
    2.5 Text Mining and Sentiment Analysis 11
    2.5.1 Definition of Text Mining 11
    2.5.2 Sentiment Analysis based on Text Mining 12
    2.6 Summary 12
    3. Models and Methodology 14
    3.1 Conceptual Framework 14
    3.2 Models 16
    3.2.1 Multiple Regression Model 16
    3.2.2 Panel Data Regression Model 18
    3.3 Data in The Beige Book 20
    3.3.1 The Content of the Beige Book 20
    3.3.2 Scoring the Beige Book 21
    3.4 Variables and Data 23
    3.4.1 The Dependent Variables 23
    3.4.2 Other Control Variables 25
    3.5 Methodology 29
    3.5.1 Unit Root Test 29
    3.5.2 Pearson Correlation 29
    3.5.3 Collinearity Diagnosis 29
    4. Empirical Analysis 30
    4.1 Unit Root Test 30
    4.2 Pearson Correlation Analysis 32
    4.3 The Relation between the Beige Book and Construction Investment 34
    4.3.1 The Relation between the Beige Book and Housing Prices 34
    4.3.2 The Relation between the Beige Book and Construction Output 38
    4.3.3 The Relation between the Beige Book and S&P 500 Real Estate 40
    4.3.4 The Relation between the Beige Book and Building Permits 42
    4.4 Collinearity Diagnosis 45
    5. Conclusion 46
    Appendix 49
    References 51

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