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    政大典藏 > College of Commerce > Department of Finance > Theses >  Item 140.119/152070


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/152070


    Title: 投資人關注度對台灣50指數之股票報酬率的影響
    The Impact of Aggregate Investor Attention on Stock Returns of the Taiwan 50 Index
    Authors: 陳盈錡
    Chen, Ying-Chi
    Contributors: 周冠男
    Chou, Robin K.
    陳盈錡
    Chen, Ying-Chi
    Keywords: 投資人關注度
    主成分分析
    報酬率
    偏最小平方法
    Investor attention
    Principal component analysis
    Returns
    Partial least squares
    Date: 2024
    Issue Date: 2024-07-01 12:40:23 (UTC+8)
    Abstract: 本論文希望建立一個綜合性的投資者關注度指數，以探討其對台灣50指數報酬率的影響。透過主成分分析 (PCA) 和偏最小平方法 (PLS)，我們將7個單獨的投資人關注度代理變數整合為綜合指數，以預測報酬率。實證結果顯示，採用PLS方法建構的投資者關注度綜合指數，在3、6及12個月的時間範圍內，無論是否調整極端值，對台灣50指數報酬率均展現出強大的預測能力，尤其在調整極端值後，其效果更為突出；而採用PCA方法建構的投資者關注度綜合指數則未顯示出顯著的預測能力。在單獨的代理變數中，異常交易量以及過去報酬率與台灣50指數報酬率之間呈現出顯著相關性。
    This study examines how aggregate investor attention indexes affect returns for the Taiwan 50 Index. Using Principal Component Analysis (PCA) and Partial Least Squares (PLS) methods, the research builds comprehensive aggregate investor attention indexes based on seven well-known individual proxies. The empirical results showed that the aggregate investor attention index constructed by the PLS method had strong predictive power over 3, 6, and 12-month periods, regardless of whether extreme values were adjusted, and notably strengthened after such adjustments. In contrast, the aggregate investor attention index constructed by the PCA method generally lacks significant predictive ability. Among the individual attention proxies, abnormal trading volume and past return demonstrated significant correlations with Taiwan 50 Index returns.
    Reference: Chinese Literature
    李永隆、杜玉振、王瑋瑄 (2017)。Google 搜尋量指數對臺灣股票報酬與成交量之影響。管理與系統，24(4)，565-590。[Li, Du, and Wang (2017)]
    何怡滿、陳雯琪 (2019)。投資人關注度對台灣50指數成分股之股票報酬與公司績效的影響。屏東大學學報管理類，(2)，73-103。[He and Chen (2019)]

    English Literature
    Barber, B. M., & 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.
    Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. Journal of Finance, 61(4), 1645-1680.
    Ben-Rephael, A., Da, Z., & Israelsen, R. D. (2017). It depends on where you search: Institutional investor attention and underreaction to news. Review of Financial Studies, 30(9), 3009-3047.
    Chen, J., Tang, G., Yao, J., & Zhou, G. (2022). Investor attention and stock returns. Journal of Financial and Quantitative Analysis, 57(2), 455-484.
    Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention. Journal of Finance, 66(5), 1461-1499.
    Dellavigna, S., & Pollet, J. M. (2009). Investor inattention and Friday earnings announcements. Journal of Finance, 64(2), 709-749.
    Fang, L., & Peress, J. (2009). Media coverage and the cross-section of stock returns. Journal of Finance, 64(5), 2023-2052.
    Gervais, S., Kaniel, R., & Mingelgrin, D. H. (2001). The high-volume return premium. Journal of Finance, 56(3), 877-919.
    Huang, T. L., Chen, M. L., Kuo, H. J., & Lai, K. L. (2016). How do web search activity and financial media coverage affect asset pricing?. Journal of Financial Studies, 24(1), 25.
    Jondeau, E., Zhang, Q., & Zhu, X. (2019). Average skewness matters. Journal of Financial Economics, 134(1), 29-47.
    Kahneman, D. (1973). Attention and Effort. Englewood Cliffs, NJ: Prentice-Hall.
    Kelly, B., & Pruitt, S. (2013). Market expectations in the cross-section of present values. Journal of Finance, 68(5), 1721-1756.
    Kelly, B., & Pruitt, S. (2015). The three-pass regression filter: A new approach to forecasting using many predictors. Journal of Econometrics, 186(2), 294-316.
    Li, J., & Yu, J. (2012). Investor attention, psychological anchors, and stock return predictability. Journal of Financial Economics, 104(2), 401-419.
    Light, N., Maslov, D., & Rytchkov, O. (2017). Aggregation of information about the cross section of stock returns: A latent variable approach. Review of Financial Studies, 30(4), 1339-1381.
    Ludvigson, S. C., & Ng, S. (2007). The empirical risk-return relation: A factor analysis approach. Journal of Financial Economics, 83(1), 171-222.
    Neely, C. J., Rapach, D. E., Tu, J., & Zhou, G. (2014). Forecasting the equity risk premium: The role of technical indicators. Management Science, 60(7), 1772-1791.
    Rapach, D. E., Ringgenberg, M. C., & Zhou, G. (2016). Short interest and aggregate stock returns. Journal of Financial Economics, 121(1), 46-65.
    Vozlyublennaia, N. (2014). Investor attention, index performance, and return predictability. Journal of Banking & Finance, 41, 17-35.
    Wold, H. (1966). Estimation of principal components and related models by iterative least squares. Multivariate analysis, 391-420.
    Description: 碩士
    國立政治大學
    財務管理學系
    111357027
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0111357027
    Data Type: thesis
    Appears in Collections:[Department of Finance] Theses

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