English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113656/144643 (79%)
Visitors : 51707396      Online Users : 456
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 財務管理學系 > 學位論文 >  Item 140.119/124700
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/124700


    Title: 褐皮書是否會驅動建築投資?
    Does the Beige Book Move Construction Investment?
    Authors: 陳盈臻
    Chen, Ying-Jhen
    Contributors: 陳明吉
    Chen, Ming-Chi
    陳盈臻
    Chen, Ying-Jhen
    Keywords: 文字探勘
    情緒分析
    房地產市場
    褐皮書
    情緒指數
    Text mining
    Sentiment analysis
    Real estate market
    Beige Book
    Sentiment index
    Date: 2019
    Issue Date: 2019-08-07 16:05:03 (UTC+8)
    Abstract: 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.
    Reference: Akerlof, G. A., & Shiller, R. J. (2010). Animal Spirits. Princeton: NJ: Princeton University Press.
    Armesto, M. T., Hernández‐Murillo, R., Owyang, M. T., & Piger, J. (2009). Measuring the Information Content of the Beige Book: A Mixed Data Sampling Approach. Journal of Money,Credit and Banking, 41(1), 35-55.
    Baffoe-Bonnie, J. (1998). The Dynamic Impact of Macroeconomic Aggregates on Housing Prices and Stock of Houses: A National and Regional Analysis. The Journal of Real Estate Finance and Economics, 17(2), 179-197.
    Baker, M., & Wurgler, J. (2007). Investor Sentiment in the Stock Market. Journal of Economic Perspectives, 21(2), 129-152.
    Balke, N. S., Fulmer, M., & Zhang, R. (2016). Incorporating the Beige Book into a Quantitative Index of Economic Activity. Journal of Forecasting, 36(5), 497-514.
    Balke, N. S., & Petersen, D. A. (2002). How Well Does the Beige Book Reflect Economic Activity? Evaluating Qualitative Information Quantitatively Journal of Money, Credit and Banking, 34(1), 114-136.
    Balke, N. S., & Yücel, M. K. (2000). Evaluating the Eleventh District`s Beige Book. Federal Reserve Bank of Dallas Economic and Financial Review, 4(2-9).
    Bjørnland, H. C., & Jacobsen, D. H. (2010). The role of house prices in the monetary policy transmission mechanism in small open economies. Journal of Financial Stability, 6, 218-229.
    Capozza, D. R., Hendershott, P. H., Mack, C., & Mayer, C. J. (2002). Determinants of Real House Price Dynamics.
    Chen, M.-C., & Patel, K. (2002). An empirical analysis of determination of house prices in the Taipei area. Taiwan Economic Review, 30(4), 563-595.
    Chen, M.-C., Tsai, I.-C., & Chang, C.-O. (2007). House prices and household income: Do they move apart? Evidence from Taiwan. Habitat International, 31(2), 243-256.

    Clayton, J., Ling, D. C., & Naranjo, A. (2009). Commercial Real Estate Valuation: Fundamentals Versus Investor Sentiment. The Journal of Real Estate Finance and Economics, 38(1), 5-37.
    Collomb, A. ı., Costea, C., Joyeux, D., Hasan, O., & Brunie, L. (2014). A Study and Comparison of Sentiment Analysis Methods for Reputation Evaluation. Rapport de recherche RR-LIRIS-2014-002.
    Fenzl, T., & Pelzmann, L. (2012). Psychological and Social Forces Behind Aggregate Financial Market Behavior. Journal of Behavioral Finance, 13(1), 56-65.
    Grebler, L., & Mittelbach, F. G. (1979). The Inflation of House Prices, its Extent, Causes, and Consequences
    Hanley, K. W., & Hoberg, G. (2010). The Information Content of IPO Prospectuses. The Review of Financial Studies, 23(7), 2821-2864.
    Hendershott, P. H., & Abraham, J. M. (1992). Patterns and Determinants of Metropolitan House Prices, 1977 to 1991. L.E. Browne, E.S. Rosengren (Eds.), Real Estate and the Credit Crunch, Federal Reserve Bank of Boston, Boston(36), 18-42.
    Keynes, J. (1936). The General Theory of Employment, Interest and Money. Palgrave Macmillan.
    Lai, R. N., & Order, R. A. V. (2010). Momentum and House Price Growth in the United States: Anatomy of a Bubble. Real Estate Economics, 38(4), 753-773.
    Lee, M.-H., Chen, W.-T., & Peng, C.-W. (2014). Fundamental House Prices and Bubbles in Asian Cities. City and Planning, 41(2), 169-198.
    Levin, A., Chien-FuLin, & Chu, C.-S. J. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1-24.
    Loughran, T., & Mcdonald, B. (2014). Measuring Readability in Financial Disclosures. The Journal of Finance, 69(4), 1643-1671.
    Mahalik, M. K., & Mallick, H. (2016). Are house prices guided by fundamentals or speculative factors? An empirical inquiry for India Int. J. Economic Policy in Emerging Economies, 9(1).
    Marcato, G., & Nanda, A. (2016). Information Content and Forecasting Ability of Sentiment indicators: Case of Real Estate Market. Journal of Real Estate Research, 38(2), 165-203.
    Meen, G. P. (1990). The Removal of Mortgage Market Constraints and the Implications for Econometric Modelling of UK House Prices. Oxford Bulletin Economics and Statistics, 52(1), 1-23.
    Meen, G. P. (1993). The Treatment of House Prices in Macroeconometric Models: A Compariosn Exercise. Department of Environment Discussion Paper.
    Payne, D. R. (2001). Anticipating Monetary Policy with the Federal Reserve`s Beige Book: Re-specifying the Taylor Rule. Business Economics, 36(1), 21-30.
    Reichert, A. K. (1990). The Impact of Interest Rates, Income, and Employment upon Regional Housing Prices. The Journal of Real Estate Finance and Economics, 3(4), 373-391.
    Sadique, S., In, F., Veeraraghavan, M., & Wachtel, P. (2013). Soft information and economic activity: Evidence from the Beige Book. Journal of Macroeconomics, 37, 81-92.
    Sentiment Analysis: Nearly Everything You Need to Know (n.d.). Retrieved June 18, 2019, from https://monkeylearn.com/sentiment-analysis/
    Summary of Commentary on Current Economic Conditions by Federal Reserve District (2019), from https://www.federalreserve.gov/monetarypolicy/beige-book-default.htm
    Tsolacos, S. (2012). The Role of Sentiment Indicators for Real Estate Market Forecasting Journal of European Real Estate Research, 5(2), 109-120.
    Tetlock, P. C., Saar‐Tsechansky, M., & Macskassy, S. (2008). More Than Words: Quantifying Language to Measure Firms` Fundamentals. The Journal of Finance, 63(3), 1437-1467.
    Wang, Z., & Hui, E. C.-m. (2017). Fundamentals and Market Sentiment in Housing Market. Journal Housing, Theory and Society, 34(1), 57-78.
    Zavodny, M., & Ginther, D. K. (2005). Does the Beige Book Move Financial Markets. Southern Economic Journal, 72(1), 138-151.
    Description: 碩士
    國立政治大學
    財務管理學系
    106357026
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106357026
    Data Type: thesis
    DOI: 10.6814/NCCU201900558
    Appears in Collections:[財務管理學系] 學位論文

    Files in This Item:

    File SizeFormat
    702601.pdf779KbAdobe PDF20View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback