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研究生： 澤竜輝
Sawa, Tatsuki
論文名稱： 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
指導教授： 朱琇妍
Chu, Shiou-Yen
口試委員: 傅健豪
FU, Chien-Hao
林佑龍
Lin,Yo-Long
學位類別： 碩士
Master
系所名稱： 社會科學學院 - 應用經濟與社會發展英語碩士學位學程(IMES)
International Master's Program of Applied Economics and Social Development(IMES)
論文出版年： 2025
畢業學年度： 113
語文別： 英文
論文頁數： 62
中文關鍵詞： Google趨勢 、投資人注意力 、宏觀經濟事件 、行為財務學 、市場反應
外文關鍵詞： Google Trends, Investor Attention, Macroeconomic Events, Behavioral Finance, Market Reaction
相關次數： 點閱：65  下載：2 
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    • 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.

    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 59

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