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題名 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
作者 陳盈錡
Chen, Ying-Chi
貢獻者 周冠男
Chou, Robin K.
陳盈錡
Chen, Ying-Chi
關鍵詞 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
日期 2024
上傳時間 1-Jul-2024 12:40:23 (UTC+8)
摘要 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.
參考文獻 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.
描述 碩士
國立政治大學
財務管理學系
111357027
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0111357027
資料類型 thesis
dc.contributor.advisor 周冠男zh_TW
dc.contributor.advisor Chou, Robin K.en_US
dc.contributor.author (Authors) 陳盈錡zh_TW
dc.contributor.author (Authors) Chen, Ying-Chien_US
dc.creator (作者) 陳盈錡zh_TW
dc.creator (作者) Chen, Ying-Chien_US
dc.date (日期) 2024en_US
dc.date.accessioned 1-Jul-2024 12:40:23 (UTC+8)-
dc.date.available 1-Jul-2024 12:40:23 (UTC+8)-
dc.date.issued (上傳時間) 1-Jul-2024 12:40:23 (UTC+8)-
dc.identifier (Other Identifiers) G0111357027en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/152070-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 財務管理學系zh_TW
dc.description (描述) 111357027zh_TW
dc.description.abstract (摘要) 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。zh_TW
dc.description.abstract (摘要) 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.en_US
dc.description.tableofcontents 1. Introduction 1 1.1 Motivation 1 1.2 Chapter Outlines 2 2. Literature Review 3 3. Data and Methodology 6 3.1 Sample Selection 6 3.2 Data Description 6 3.3 Methodology 9 4. Empirical Results 12 4.1 Descriptive Summary of Individual Attention Proxies 12 4.2 Aggregate Attention Indexes with PCA and PLS Methods 14 4.3 The Regression Result of the Aggregate Attention Index 16 4.4 The Regression Result for All Individual Attention Proxies 19 5. Conclusion 23 6. References 24zh_TW
dc.format.extent 1376380 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0111357027en_US
dc.subject (關鍵詞) 投資人關注度zh_TW
dc.subject (關鍵詞) 主成分分析zh_TW
dc.subject (關鍵詞) 報酬率zh_TW
dc.subject (關鍵詞) 偏最小平方法zh_TW
dc.subject (關鍵詞) Investor attentionen_US
dc.subject (關鍵詞) Principal component analysisen_US
dc.subject (關鍵詞) Returnsen_US
dc.subject (關鍵詞) Partial least squaresen_US
dc.title (題名) 投資人關注度對台灣50指數之股票報酬率的影響zh_TW
dc.title (題名) The Impact of Aggregate Investor Attention on Stock Returns of the Taiwan 50 Indexen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 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.zh_TW