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研究生: 鍾怡玲
Chung, Yi-Ling
論文名稱: 比特幣報酬率與市場情緒指數之間的關聯性
指導教授: 周賓凰
Chou, Pin-huang
口試委員:
學位類別: 碩士
Master
系所名稱: 管理學院 - 財務金融學系在職專班
Executive Master of Finance
論文出版年: 2025
畢業學年度: 113
語文別: 中文
論文頁數: 39
中文關鍵詞: 比特幣情緒指數景氣循環波動性
外文關鍵詞: Bitcoin, Market Sentiment Index, Business Cycle, Volatility
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  • 本研究旨在探討比特幣報酬率與市場情緒指數之間的關聯性,研究期間涵蓋2017年至2023年,資料頻率為週資料。研究方法採用最小平方法(OLS)進行迴歸分析,並納入五項情緒指數作為自變數,分別為:代表美國散戶投資人情緒的美國個人投資人情緒指數(AAII)、代表傳統避險資產情緒的CBSI黃金情緒指數、反映整體市場情緒的CBSI股票市場情緒指數、代表美元貨幣情緒的CBSI美元指數情緒指數,以及納斯達克綜合指數用以觀察比特幣報酬率與傳統科技股市之互動關係。
    本研究主要發現如下:
    1. 實證結果顯示,CBSI股票市場情緒指數的變動對比特幣報酬率具有顯著正向影響,顯示專業機構對股市的情緒變化能有效預測比特幣的價格走勢。相對地,AAII與CBSI黃金情緒指數對比特幣報酬率的影響則不具顯著性。
    2. 研究亦發現,專業機構對美元指數的情緒變化與比特幣報酬率呈現負向關係,顯示美元情緒與比特幣之間存在替代性資產的特性。
    3. CBSI黃金情緒指數與比特幣報酬率之間缺乏顯著關聯,顯示比特幣與傳統避險資產之間存在脫鉤現象。
    綜上所述,本研究有助於深化對不同投資人情緒,特別是專業機構情緒,對比特幣報酬率波動影響的理解,並補充比特幣市場與情緒指數互動關係之相關文獻。


    This study aims to explore the relationship between Bitcoin returns and various market sentiment indices, using weekly data spanning from 2017 to 2023. The analysis is conducted through Ordinary Least Squares (OLS) regression, incorporating five sentiment indices as independent variables: the American Association of Individual Investors (AAII) Sentiment Index, representing U.S. retail investor sentiment; the CBSI Gold Sentiment Index, reflecting sentiment toward traditional safe-haven assets; the CBSI Equity Market Sentiment Index, capturing institutional sentiment toward the stock market; the CBSI U.S. Dollar Sentiment Index, indicating sentiment toward the U.S. dollar; and the Nasdaq Composite Index, which serves as a proxy to examine the interaction between Bitcoin returns and the traditional technology equity market.

    The empirical findings are summarized as follows:
    1. Changes in the CBSI Equity Market Sentiment Index have a significantly positive impact on Bitcoin returns, suggesting that institutional sentiment toward the stock market possesses predictive power over Bitcoin price movements. In contrast, sentiment changes in the AAII and CBSI Gold Sentiment Indexes show limited statistical significance.
    2. Institutional sentiment toward the U.S. dollar exhibits a negative relationship with Bitcoin returns, indicating a potential substitution effect between Bitcoin and the dollar.
    3. The CBSI Gold Sentiment Index shows no significant correlation with Bitcoin returns, highlighting a decoupling between Bitcoin and traditional safe-haven assets.

    Overall, this study contributes to a deeper understanding of how different investor sentiments, particularly those of institutional participants, influence the volatility and dynamics of Bitcoin returns, and enriches the literature on the interaction between cryptocurrency markets and sentiment indicators.

    目錄 摘要 ........................................................... i Abstract ...................................................... ii 致謝 .......................................................... iii 目錄 .......................................................... iv 圖目錄 ........................................................ vi 表目錄 ........................................................ vii 第一章 緒論 ..................................................... 1 第一節 研究背景與動機 .......................................... 1 第二節 研究目的 ............................................... 2 第二章 文獻回顧 ................................................. 4 第一節 比特幣相關文獻 .......................................... 4 第二節 情緒指數相關文獻 ........................................ 5 第三章 研究方法 ................................................. 7 第一節 研究架構 ............................................... 7 第二節 資料來源及研究期間 ...................................... 8 第三節 變數定義 ............................................... 9 第四節 研究方法與敘述性統計 .................................... 12 第四章 實證結果與分析 ........................................... 15 第一節 各情緒指數的情緒變化對比特幣報酬率的關聯性分析 ............ 15 第二節 各情緒指數的情緒變化組合模型對比特幣報酬率的關聯性分析 ..... 17 第三節 景氣循環下的穩定性測試 .................................. 20 第四節 小結 .................................................. 23 第五章 結論與建議 .............................................. 24 第一節 研究結論 .............................................. 24 第二節 研究限制與未來研究建議 .................................. 25 參考文獻 ....................................................... 27

    中文部分
    1. 周賓凰、張宇志、林美珍(2007),『投資人情緒與股票報酬互動關係』,證券市場發展季刊,19,153-190
    2. 周賓凰(2023),「計量經濟學:理論、觀念與應用」,二版,新陸書局
    3. 楊奇樺(2024),「金屬商品情緒能預測股市嗎?」,國立中央大學碩士論文
    4. 維基百科,比特幣,擷取自維基百科,自由的百科全書,https:// zh.wikipedia.org/zh-tw/比特幣

    英文部分
    1. Bukovina, J., & Martiček, M. (2016). Sentiment and bitcoin volatility. Kybernetes, 45(7), 1265–1280.
    2. Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21(2), 129–151.
    3. Baur, D. G., Hong, K., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money, 54, 177–189.
    4. Baur, D. G., Dimpfl, T., & Kuck, K. (2018). Bitcoin, gold and the US dollar—A replication and extension. Finance Research Letters, 25, 103–110.
    5. Chou, P.-H., Hsieh, C.-H., & Shen, C. H.-H. (2016). What explains the orange juice puzzle: Sentiment, smart money, or fundamentals? Journal of Financial Markets, 29, 47-65.
    6. Corbet, S., Lucey, B., Urquhart, A., & Yarovaya, L. (2018). Cryptocurrencies as a financial asset: A systematic analysis. International Review of Financial Analysis, 62, 182–199.
    7. Fang, Y., Liu, Y., & Zhang, Y. (2022). Institutional sentiment and cryptocurrency returns. Journal of Behavioral and Experimental Finance, 33, 100678.
    8. Garcia, D., Tessone, C. J., Mavrodiev, P., & Perony, N. (2014). The digital traces of bubbles. Journal of the Royal Society Interface, 11(99), 20140623.
    9. Kristoufek, L. (2013). Bitcoin meets Google Trends and Wikipedia. Scientific Reports, 3, 3415.
    10. Mai, F., Shan, Z., Bai, Q., Wang, X. S., & Chiang, R. H. L. (2018). How Does Social Media Impact Bitcoin Value? Journal of Management Information Systems, 35(1), 19–52.
    11. Qadan, M., & Aharon, D. Y. (2019). Sentiment and the cryptocurrency market. Journal of Behavioral and Experimental Finance, 22, 1–9.
    12. Shiller, R. J. (2019). Narrative Economics. Princeton University Press.
    13. Shiller, R. J. (2003). From efficient markets theory to behavioral finance. Journal of Economic Perspectives, 17(1), 83–104.

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