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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 胡星陽 | |
| dc.contributor.author | Chung-Hong Huang | en |
| dc.contributor.author | 黃浚紘 | zh_TW |
| dc.date.accessioned | 2021-06-16T10:35:52Z | - |
| dc.date.available | 2013-08-20 | |
| dc.date.copyright | 2013-08-20 | |
| dc.date.issued | 2013 | |
| dc.date.submitted | 2013-08-14 | |
| dc.identifier.citation | [1] Askitas, N. and Zimmermann, K. F. ,2010. Google econometrics and unemployment forecasting. Applied Economics Quarterly, 2009, 55(2), 107-120
[2] Baker, S. and Fradkin, A., 2011. What drives job search? Evidence from Google search data. Working Paper, Stanford University. [3] Baker Wurgler 2007 Investor Sentiment in the stock market Worknig paper, National Bureau of Economic Research [4] Baker, Malcolm, and Jeremy Stein, 2004, Market liquidity as a sentiment indicator, Journal of Financial Markets 7, 271–299 [5] Barber, M.B, and Odean, T., 2008. All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors, Review of Financial Studies 21(2), 785-818 [6] Chemmanur, T. and Yan, A., 2009. Advertising, attention, and stock returns, Working paper, Boston College and Fordham University. [7] Choi, H. and Varian, H., 2009. Predicting the present with Google Trends, Working paper, GoogleInc. [8] Da, Z., Engelberg, J. and Gao, P., (b) 2010. The sum of all FEARS: Investor sentiment and Asset Price, Working paper, University of Notre Dame and University of North Carolina at Chapel Hill. [9] Da, Z., Engelberg, J. and Gao, P., 2011. In Search of Attention. Journal of Finance 66 (5), 1461-1499. [10] Dahlquist, M. and G. Robertsson, 2001, Direct foreign ownership, institutional investors, and firm characteristics, Journal of Financial Economics, 59, 413-440. [11] Driscoll, John C. and Aart C. Kraay, 1998, Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data, Review of Economics and Statistics 80, 549-560. [12] Dzielinksi, M., 2012. Measuring economic uncertainty and its impact on the stock market, Finance Research Letters 9 (3), 167-175. [13] Fama, E.F. and Macbeth, J. D., 1973. Risk return and equilibrium: Empirical tests, Journal of Political Economy 81 (3), 607–636. [14] Ginsberg, J., Mohebbi M.H., Patel, R,S., Brammer, L., Smolinski M,S., and Brilliant, L. 2009,Detecting influenza epidemics using search engine query data, Nature 457, 1012–1014. [15] Guzman, G,. 2011. Internet search behavior as an economic forecasting tool. The Journal of Economic and Social Measurement. 36 (3), 119-167. [16] Goel, S., Hofman, J.M., Lahaie, S, Pennock, D,M. and Watts, D,J. 2010. Predicting consumerbehavior with web search, Proceedings of the National Academy of Sciences, 7 (41), 17486-17490 . [17] Hirshleifer, D., and Teoh, S.H., 2003. Limited attention, information disclosure, and financial reporting, Journal of Accounting and Economics 36 (1-3), 337–386. [18] Hoechle, Daniel, Robust Standard Errors for Panel Regressions with Cross-Sectional Dependence [19] Kahneman, D.,1973, Attention and efforts. Prentice-Hall, Englewood Cliffs, NJ. [20] Lui, C., Panagiotis, T. and Mustafaraj, E., 2011. On the predictability of the U.S. elections through search volume activity, Department of Computer Science, Wellesley College [21] Mondria, J. and Wu, T., 2011. Asymmetric Attention and Stock Returns, Society for Economic Dynamics, Meeting Papers 134. [22] Merton, R.C., 1987. A simple model of capital market equilibrium with incomplete information, Journal of Finance 42 (3), 483–510. [23] Newey,W., and West, K., 1987. A simple positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix, Econometrica 55 (3), 703–708. [24] Odean, T., 1999. Do investors trade too much? American Economic Review 89 (5), 1279–1298. [25] Peng, L., and Wei., 2006. Investor attention, overconfidence and category learning, Journal of Financial Economics 80 (3), 563–602. [26] Seasholes, M,S. and Guojun W., 2007. Predictable behavior, profits, and attention, Journal of Empirical Finance 14 (5), 590–610. [27] The Economist, 2011. US Confidence indicators. Available online at: http://www.economist.com/blogs/dailychart/2011/08/us-confidence-indicators .Read: 11 October 2012. [28] Vlastakis, N. and Markellos, R., 2012. Information demand and stock market volatility, Journal of Banking and Finance 36 (6), 1808-1821. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/60908 | - |
| dc.description.abstract | Google於2006年5月推出Google Trends的服務，允許用戶查詢任意關鍵字於Google搜尋引擎中的搜尋指數。該服務推出後，越來越多領域使用該資料庫做為學術研究的用途，包括醫學、經濟、財務等，多數研究都將搜尋指數做為注意力代理變數，探討搜尋行為是否具有預測社會現象的能力。
本文使用Fama-Macbeth 兩階段迴歸探討Google搜尋指數做為注意力的代理變數，能否對於台灣的股價報酬具有解釋能力。研究結果顯示，Google搜尋指數對於下一週的股價報酬具有顯著的解釋能力，平均而言，搜尋指數的異常變動量每上升1個標準差，下一週股價的異常報酬率會上升7.11 basis points。 | zh_TW |
| dc.description.abstract | Google released the Google Trends services in May 2006 and it enable user to see the search volume index for any given term. Since the service was released, it has gradually been incorporated into academic research from various fields such as Medication, Economic and Finance. Most of the study regards search volume index as a proxy of attention and use it to see if the proxy have predictive power or not.
The purpose of this study is to analyze how search volume index affect stock price in Taiwan. The results indicate that the search volume index does have predictive power over the next week stock price. On average, 1 standard deviation increased in abnormal search volume index will raises abnormal return next week by 7.11 basis points. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T10:35:52Z (GMT). No. of bitstreams: 1 ntu-102-R00723074-1.pdf: 3755842 bytes, checksum: 3774edb9accd1c1fff79789505b7afaf (MD5) Previous issue date: 2013 | en |
| dc.description.tableofcontents | 致謝 i
中文摘要 ii 英文摘要 iii 目錄 iv 圖表目錄 vi 第 1 章 緒論 1 1.1 研究動機 1 1.2 論文背景 2 1.2.1 Google 2 1.2.2 理論背景 4 1.3 研究貢獻 5 第 2 章 文獻回顧 6 2.1 Search Volume Index相關文獻 6 2.1.1 其他領域Search Volume Index文獻 6 2.1.2 財務領域Search Volume Index文獻 8 2.2 財務及注意力相關文獻 10 第 3 章 研究假設 12 第 4 章 研究資料 14 4.1 股票資料 14 4.2 Serch Volume Index資料 15 4.3 最後樣本 19 第 5 章 研究方式 23 5.1 變數處理 23 5.2 Fama Macbeth迴歸的建立 24 第 6 章 研究結果 27 第 7 章 結語 34 7.1 總結 34 7.2 研究限制 36 7.3 未來展望 36 附錄 38 主要參考文獻 48 | |
| dc.language.iso | zh-TW | |
| dc.subject | zh_TW | |
| dc.subject | 搜尋 | zh_TW |
| dc.subject | 注意力 | zh_TW |
| dc.subject | 台灣 | zh_TW |
| dc.subject | 股價報酬 | zh_TW |
| dc.subject | en | |
| dc.subject | search volume | en |
| dc.subject | attention | en |
| dc.subject | Taiwan | en |
| dc.subject | stock return | en |
| dc.title | Google 是否能預測台灣股票報酬率？ | zh_TW |
| dc.title | Can Google Predict the Stock Return in Taiwan? | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 101-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 莊文議,何耕宇 | |
| dc.subject.keyword | Google,搜尋,注意力,台灣,股價報酬, | zh_TW |
| dc.subject.keyword | Google,search volume,attention,Taiwan,stock return, | en |
| dc.relation.page | 50 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2013-08-14 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 財務金融學研究所 | zh_TW |
| 顯示於系所單位： | 財務金融學系 | |
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