1. NCCU Academic Hub
  2. Publications
  3. College of Social Science
  4. Theses
  5. Item

Publications-Theses

Article View/Open

Publication Export

Google ScholarTM

NCCU Library

Citation Infomation

Related Publications in TAIR

題名 宏觀經濟事件下公眾注意力與金融市場反應：來自日本與美國Google趨勢的實證分析
Public Attention and Financial Market Reactions to Macroeconomic Events: Evidence from Google Trends in Japan and the United States
作者 澤竜輝
Sawa, Tatsuki
貢獻者 朱琇妍
Chu, Shiou-Yen
澤竜輝
Sawa, Tatsuki
關鍵詞 Google趨勢
投資人注意力
宏觀經濟事件
行為財務學
市場反應
Google Trends
Investor Attention
Macroeconomic Events
Behavioral Finance
Market Reaction
日期 2025
上傳時間 4-Aug-2025 14:17:49 (UTC+8)
摘要 本論文運用 Google 趨勢（Google Trends）資料，探討日本與美國在重大宏觀經濟事件（如央行會議與CPI公布）期間，公眾關注度與金融市場反應之間的關係。透過分析事件前後的搜尋量變化，研究旨在量化投資人注意力，並評估其對資產價格變動（包含匯率、股票指數與公債殖利率）的預測能力。事件研究法的實證結果顯示，尤其是在日本，針對直觀且具政策相關性的關鍵字之搜尋活動，能作為市場反應的領先指標。這可能與日本市場資訊傳遞較慢、散戶參與度較高的特性有關。本研究指出，數位注意力資料中所蘊含的行為信號，有助於理解市場如何處理經濟資訊，並對行為財務學、注意力資產定價理論及資訊經濟學領域提供實質貢獻。
This thesis investigates the relationship between public attention and financial market reactions to major macroeconomic events in Japan and the United States by utilizing Google Trends data. By analyzing changes in search volumes surrounding central bank meetings and CPI announcements, the study aims to quantify investor attention and examine its predictive power for asset price movements across exchange rates, stock indices, and government bond yields. A series of event-study regressions reveal that Google search activity—particularly for intuitive and policy-relevant keywords—can serve as a leading indicator of market responses, especially in Japan, where information diffusion is slower and retail investor participation is higher. The findings suggest that behavioral signals embedded in digital attention data provide valuable insights into how markets process economic information, contributing to the fields of behavioral finance, attention-based asset pricing, and information economics.
參考文獻 Akerlof, G. (1970). The market for "lemons": Quality uncertainty and the market mechanism. Quarterly Journal of Economics, 84(3), 488–500. https://doi.org/10.2307/1879431 Antweiler, W., & Frank, Z. (2004). Is all that talk just noise? The information content of Internet stock message boards. The Journal of Finance, 59(3), 1259–1294. https://doi.org/10.1111/j.1540-6261.2004.00662.x Atago, N. (2025). Why BOJ Communication Still Baffles the Market. Mizuho Research Institute. Baker, S., Bloom, N., & Davis, J. (2016). Measuring economic policy uncertainty. Quarterly Journal of Economics, 131(4), 1593–1636. https://doi.org/10.1093/qje/qjw024 Baker, S., Bloom, N., & Davis, J. (2018). The effect of central bank communication on asset prices: Evidence from unscheduled Federal Reserve announcements (IMF Working Paper WP/18/136). International Monetary Fund. https://www.imf.org/en/Publications/WP/Issues/2018/06/13/The-Effect-of-Central-Bank-Communication-on-Asset-Prices-Evidence-from-Unscheduled-Federal-45985 Barber, B., & Odean, T. (2008). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. The Review of Financial Studies, 21(2), 785–818. https://faculty.haas.berkeley.edu/odean/papers%20current%20versions/all%20that%20glitters.pdf Bordalo, P., Gennaioli, N., & Shleifer, A. (2013). Salience and asset prices. American Economic Review, 103(3), 623–628. https://doi.org/10.1257/aer.103.3.623 Chen, G., Kim, K., Nofsinger, J., & Rui, O. (2004). Behavior and performance of emerging market investors: Evidence from China. Pacific-Basin Finance Journal, 12(3), 347–369. https://doi.org/10.1016/S1042-4431(03)00047-4 Choi, H., & Varian, H. (2009). Predicting the present with Google Trends. Google Research. https://people.ischool.berkeley.edu/~hal/Papers/2011/ptp.pdf Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention. The Journal of Finance, 66(5), 1461–1499. https://doi.org/10.1111/j.1540-6261.2011.01679.x Gergaud, O., & Ginsburgh, V. (2017). Success: Talent, intelligence, and beauty. Springer. https://link.springer.com/book/10.1007/978-3-319-64379-4 Hirose, Y., & Kamada, K. (2004). A new technique for identifying the effects of monetary policy shocks: The case of Japan (IMES Discussion Paper No. 2004-E-10). Institute for Monetary and Economic Studies, Bank of Japan. https://www.imes.boj.or.jp/research/papers/english/04-E-10.pdf Hong, H., & Stein, J. (1999). A unified theory of underreaction, momentum trading and overreaction in asset markets. The Journal of Finance, 54(6), 2143–2184. https://www.nber.org/papers/w6556 Lucas, R. (1972). Expectations and the neutrality of money. Journal of Economic Theory, 4(2), 103–124. https://doi.org/10.1016/0022-0531(72)90142-1 Orphanides, A. (2023). Communication challenges at the zero lower bound: Lessons from Japan. Journal of Central Banking, 19(1), 43–67. Peng, L., & Xiong, W. (2006). Investor attention, overconfidence and category learning. Journal of Financial Economics, 80(3), 563–602. https://doi.org/10.1016/j.jfineco.2005.05.003 Research Institute of Economy, Trade and Industry (RIETI). (2019). The limits of BOJ forward guidance: Evidence from text analysis (RIETI Discussion Paper Series 19-E-023). Reuters. (2024, December 15). BOJ’s Ueda says even slight change in wording can shake markets. Retrieved from https://www.reuters.com Reuters. (2025, March 5). Critics say focus on “underlying inflation” clouds BOJ policy intent. Retrieved from https://www.reuters.com Shirai, S. (2013). Monetary policy and forward guidance in Japan: An evaluation. Asian Economic Policy Review, 8(2), 210–235. Sims, C. (2003). Implications of rational inattention. Journal of Monetary Economics, 50(3), 665–690. https://doi.org/10.1016/S0304-3932(03)00029-1 東京証券取引所. (2023). 株式分布状況調査（2022年度末）. 日本取引所グループ. https://www.jpx.co.jp/markets/statistics-equities/examination-distribution/index.html 金融庁. (2023). NISAの概要と拡充について. https://www.fsa.go.jp/policy/nisa2/about/
描述 碩士
國立政治大學
應用經濟與社會發展英語碩士學位學程(IMES)
112266009
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0112266009
資料類型 thesis
dc.contributor.advisor 朱琇妍zh_TW
dc.contributor.advisor Chu, Shiou-Yenen_US
dc.contributor.author (Authors) 澤竜輝zh_TW
dc.contributor.author (Authors) Sawa, Tatsukien_US
dc.creator (作者) 澤竜輝zh_TW
dc.creator (作者) Sawa, Tatsukien_US
dc.date (日期) 2025en_US
dc.date.accessioned 4-Aug-2025 14:17:49 (UTC+8)-
dc.date.available 4-Aug-2025 14:17:49 (UTC+8)-
dc.date.issued (上傳時間) 4-Aug-2025 14:17:49 (UTC+8)-
dc.identifier (Other Identifiers) G0112266009en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158543-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 應用經濟與社會發展英語碩士學位學程(IMES)zh_TW
dc.description (描述) 112266009zh_TW
dc.description.abstract (摘要) 本論文運用 Google 趨勢（Google Trends）資料，探討日本與美國在重大宏觀經濟事件（如央行會議與CPI公布）期間，公眾關注度與金融市場反應之間的關係。透過分析事件前後的搜尋量變化，研究旨在量化投資人注意力，並評估其對資產價格變動（包含匯率、股票指數與公債殖利率）的預測能力。事件研究法的實證結果顯示，尤其是在日本，針對直觀且具政策相關性的關鍵字之搜尋活動，能作為市場反應的領先指標。這可能與日本市場資訊傳遞較慢、散戶參與度較高的特性有關。本研究指出，數位注意力資料中所蘊含的行為信號，有助於理解市場如何處理經濟資訊，並對行為財務學、注意力資產定價理論及資訊經濟學領域提供實質貢獻。zh_TW
dc.description.abstract (摘要) This thesis investigates the relationship between public attention and financial market reactions to major macroeconomic events in Japan and the United States by utilizing Google Trends data. By analyzing changes in search volumes surrounding central bank meetings and CPI announcements, the study aims to quantify investor attention and examine its predictive power for asset price movements across exchange rates, stock indices, and government bond yields. A series of event-study regressions reveal that Google search activity—particularly for intuitive and policy-relevant keywords—can serve as a leading indicator of market responses, especially in Japan, where information diffusion is slower and retail investor participation is higher. The findings suggest that behavioral signals embedded in digital attention data provide valuable insights into how markets process economic information, contributing to the fields of behavioral finance, attention-based asset pricing, and information economics.en_US
dc.description.tableofcontents 1. Introduction 1 1.1 Background and Motivation 1 1.2 Research Questions 4 1.3 Contribution of the Study 4 2. Literature Review 6 2.1 Market Efficiency and the Role of Information 6 2.2 Attention and Investor Behavior 6 2.3 Salience, Overreaction, and Gradual Information Diffusion 7 2.4 Google Trends as an Attention Proxy 7 2.5 Keyword Semantics and Information Costs 8 2.6 Cross-country Comparisons and Market Structures 8 3. Data and Methodology 10 3.1 Data Overview 10 3.2 Event Window Setting 13 3.3 Regression Specification 14 4. Empirical Results 17 4.1 Descriptive Statistics 17 4.2 Regression results by Event × Keyword 20 4.2.1 BoJ Policy Meeting 20 4.2.2 Japan CPI Release 23 4.2.3 FOMC Statement 26 4.2.4 US CPI Release 30 4.3 Cross-sectional Comparison and Interpretation 32 5. Discussion and Implications 35 5.1 Interpretation of Results 35 5.2 Theoretical Implications 37 5.3 Practical Applications 38 5.4 Conclusion 39 5.5 Limitations and Future Research 40 Tables 42 Table A1. Descriptive Statistics – FOMC Statement 42 Table A2. Descriptive Statistics – US CPI Release 44 Table A3. Descriptive Statistics – BoJ Policy Meeting 45 Table A4. Descriptive Statistics – Japan CPI Release 46 Table B1. Regression Results – BoJ Policy Meeting × “日銀” 47 Table B2. Regression Results – BoJ Policy Meeting × “金融政策” 48 Table B3. Regression Results – Japan CPI Release × “インフレ” 49 Table B4. Regression Results – Japan CPI Release × “消費者物価指数” 50 Table B5. Regression Results – FOMC Statement × “rate hike” 51 Table B6. Regression Results – FOMC Statement × “FOMC” 52 Table B7. Regression Results – US CPI Release × “inflation” 53 Table B8. Regression Results – US CPI Release × “CPI” 54 Figures 55 References 59zh_TW
dc.format.extent 2297229 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0112266009en_US
dc.subject (關鍵詞) Google趨勢zh_TW
dc.subject (關鍵詞) 投資人注意力zh_TW
dc.subject (關鍵詞) 宏觀經濟事件zh_TW
dc.subject (關鍵詞) 行為財務學zh_TW
dc.subject (關鍵詞) 市場反應zh_TW
dc.subject (關鍵詞) Google Trendsen_US
dc.subject (關鍵詞) Investor Attentionen_US
dc.subject (關鍵詞) Macroeconomic Eventsen_US
dc.subject (關鍵詞) Behavioral Financeen_US
dc.subject (關鍵詞) Market Reactionen_US
dc.title (題名) 宏觀經濟事件下公眾注意力與金融市場反應：來自日本與美國Google趨勢的實證分析zh_TW
dc.title (題名) Public Attention and Financial Market Reactions to Macroeconomic Events: Evidence from Google Trends in Japan and the United Statesen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Akerlof, G. (1970). The market for "lemons": Quality uncertainty and the market mechanism. Quarterly Journal of Economics, 84(3), 488–500. https://doi.org/10.2307/1879431 Antweiler, W., & Frank, Z. (2004). Is all that talk just noise? The information content of Internet stock message boards. The Journal of Finance, 59(3), 1259–1294. https://doi.org/10.1111/j.1540-6261.2004.00662.x Atago, N. (2025). Why BOJ Communication Still Baffles the Market. Mizuho Research Institute. Baker, S., Bloom, N., & Davis, J. (2016). Measuring economic policy uncertainty. Quarterly Journal of Economics, 131(4), 1593–1636. https://doi.org/10.1093/qje/qjw024 Baker, S., Bloom, N., & Davis, J. (2018). The effect of central bank communication on asset prices: Evidence from unscheduled Federal Reserve announcements (IMF Working Paper WP/18/136). International Monetary Fund. https://www.imf.org/en/Publications/WP/Issues/2018/06/13/The-Effect-of-Central-Bank-Communication-on-Asset-Prices-Evidence-from-Unscheduled-Federal-45985 Barber, B., & Odean, T. (2008). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. The Review of Financial Studies, 21(2), 785–818. https://faculty.haas.berkeley.edu/odean/papers%20current%20versions/all%20that%20glitters.pdf Bordalo, P., Gennaioli, N., & Shleifer, A. (2013). Salience and asset prices. American Economic Review, 103(3), 623–628. https://doi.org/10.1257/aer.103.3.623 Chen, G., Kim, K., Nofsinger, J., & Rui, O. (2004). Behavior and performance of emerging market investors: Evidence from China. Pacific-Basin Finance Journal, 12(3), 347–369. https://doi.org/10.1016/S1042-4431(03)00047-4 Choi, H., & Varian, H. (2009). Predicting the present with Google Trends. Google Research. https://people.ischool.berkeley.edu/~hal/Papers/2011/ptp.pdf Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention. The Journal of Finance, 66(5), 1461–1499. https://doi.org/10.1111/j.1540-6261.2011.01679.x Gergaud, O., & Ginsburgh, V. (2017). Success: Talent, intelligence, and beauty. Springer. https://link.springer.com/book/10.1007/978-3-319-64379-4 Hirose, Y., & Kamada, K. (2004). A new technique for identifying the effects of monetary policy shocks: The case of Japan (IMES Discussion Paper No. 2004-E-10). Institute for Monetary and Economic Studies, Bank of Japan. https://www.imes.boj.or.jp/research/papers/english/04-E-10.pdf Hong, H., & Stein, J. (1999). A unified theory of underreaction, momentum trading and overreaction in asset markets. The Journal of Finance, 54(6), 2143–2184. https://www.nber.org/papers/w6556 Lucas, R. (1972). Expectations and the neutrality of money. Journal of Economic Theory, 4(2), 103–124. https://doi.org/10.1016/0022-0531(72)90142-1 Orphanides, A. (2023). Communication challenges at the zero lower bound: Lessons from Japan. Journal of Central Banking, 19(1), 43–67. Peng, L., & Xiong, W. (2006). Investor attention, overconfidence and category learning. Journal of Financial Economics, 80(3), 563–602. https://doi.org/10.1016/j.jfineco.2005.05.003 Research Institute of Economy, Trade and Industry (RIETI). (2019). The limits of BOJ forward guidance: Evidence from text analysis (RIETI Discussion Paper Series 19-E-023). Reuters. (2024, December 15). BOJ’s Ueda says even slight change in wording can shake markets. Retrieved from https://www.reuters.com Reuters. (2025, March 5). Critics say focus on “underlying inflation” clouds BOJ policy intent. Retrieved from https://www.reuters.com Shirai, S. (2013). Monetary policy and forward guidance in Japan: An evaluation. Asian Economic Policy Review, 8(2), 210–235. Sims, C. (2003). Implications of rational inattention. Journal of Monetary Economics, 50(3), 665–690. https://doi.org/10.1016/S0304-3932(03)00029-1 東京証券取引所. (2023). 株式分布状況調査（2022年度末）. 日本取引所グループ. https://www.jpx.co.jp/markets/statistics-equities/examination-distribution/index.html 金融庁. (2023). NISAの概要と拡充について. https://www.fsa.go.jp/policy/nisa2/about/zh_TW