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研究生: 錡宥銘
Chi, You-Ming
論文名稱: 萬聖節效應是否存在?以美國產業報酬為例
Does the Halloween Effect Exist? Evidence from U.S. Industry Returns
指導教授: 陳鴻毅
Chen, Hong-Yi
口試委員: 黃家威
邱健嘉
林智勇
何柏欣
顏汝芳
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: 2026
畢業學年度: 115
語文別: 英文
論文頁數: 53
中文關鍵詞: Fama-French 五因子模型景氣衰退萬聖節效應一月效應
外文關鍵詞: Fama-French five-factor model, recession period, the Halloween effect, the January effect
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  • 本文探討萬聖節效應是否存在於美國產業報酬,實證結果顯示,在控制市場、規模、價值、獲利能力與投資因子後,萬聖節效應仍在部分美國生產相關與製造相關產業中維持顯著,表示該效應無法完全由標準資產定價因子解釋。景氣衰退模型的結果顯示,萬聖節效應在汽車、零售、航運與娛樂產業會被強化。在控制一月效應後,萬聖節效應仍於部分產業中維持顯著,顯示冬季報酬優勢並非單純由一月效應所驅動。整體而言,本文發現萬聖節效應並非一致存在於所有產業,而是具有產業差異的季節性現象。


    This paper examines whether the Halloween effect exists in U.S. industry returns. The empirical results show that the Halloween effect remains significant in several production-related and manufacturing-related industries after controlling for market, size, value, profitability, and investment factors. This suggests that the effect cannot be fully explained by standard asset pricing factors. The recession analysis shows that the effect becomes stronger in automobiles, retail, shipping, and entertainment industries. The Halloween effect remains significant in several industries after controlling for the January effect, indicating that the winter return premium is not solely driven by the January effect. Overall, this paper finds that the Halloween effect does not exist uniformly across all industries, but rather represents an industry-specific seasonal pattern.

    1. Introduction 1
    2. Literature review 3
    2.1 The Halloween effect and Fama-French five-factor model 3
    2.2 The Halloween effect and recession periods 5
    2.3 The Halloween effect and the January effect 6
    3. Data and methodology 9
    3.1 Data 9
    3.2 Summary statistics 10
    3.3 Methodology and variable definitions 14
    4. Empirical results 17
    4.1 The Halloween effect under the three-factor and five-factor models 17
    4.2 The Halloween effect during recession periods 20
    4.3 The Halloween effect after controlling for the January effect 23
    5. Conclusion 26
    5.1 Conclusion and implications 26
    5.2 Limitations and future work 26
    References 28
    Appendix 30

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