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政大機構典藏 > 商學院 > 財務管理學系 > 學位論文 > Item 140.119/152072

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/152072

Title:	樂透股的GOOGLE搜尋量指數與股票報酬之關係 The Relationship Between Google Search Volume Index for Lottery-Like Stocks and Stock Returns
Authors:	吳祐誠 Wu, You-Cheng
Contributors:	周冠男 Chou, Robin K. 吳祐誠 Wu, You-Cheng
Keywords:	行為財務投資人情緒關注度 SVI 樂透股 Behavioral Finance Investor Sentiment Attention SVI Lottery Stocks
Date:	2024
Issue Date:	2024-07-01 12:40:46 (UTC+8)
Abstract:	本研究調查了台灣股市中較少被探討的樂透型股票及搜尋量指數（SVI）在理解這些股票動態中的應用。台灣關於樂透型股票的研究相對稀少，本研究旨在填補這一缺口，而使用SVI作為投資者注意力的衡量工具更近期，本研究假設認為SVI與這些高風險、高回報投資的出現和交易量有內在聯繫，希望可以看到相關的數據證明此事。研究方法涉及從台灣股市中選取樂透型股票的過程，這些股票的特徵是高波動、偏度與低股價。為捕捉投資者注意力的細微變化，構建了異常搜尋量指數（ASVI）和綜合情緒指標。本研究採用了分位數回歸分析數據，以處理樂透型股票回報中典型的不對稱性和極端值。我們的研究發現顯示，ASVI的變化與台灣股市樂透型股票的回報顯著相關，證實了假設：即投資者注意力對股票表現有明顯影響。結果不僅強調了將Google趨勢等數字軌跡數據整合到樂透股中的相關性，還突顯了這類非傳統數據在預測受投資者情緒影響的市場環境中市場行為的潛力。 This research investigates the underexplored area of lottery-like stocks in the Taiwan stock market and the application of the Search Volume Index (SVI) in understanding the dynamics of these stocks. Research on lottery-like stocks in Taiwan is relatively scarce, and this study aims to fill this gap. Using SVI as a measure of investor attention is a recent development; this study hypothesizes that SVI is linked to the appearance and trading volumes of these high-risk, high-return investments. We expect to find data supporting this link. The methodology involves selecting lottery-like stocks characterized by high volatility, skewness and low-price. An Abnormal Search Volume Index (ASVI) and a composite sentiment index are developed to capture shifts in investor attention. Quantile regression is used to manage the asymmetries and extreme values in the returns of these stocks. Our findings indicate that changes in ASVI significantly correlate with the returns of lottery-like stocks in the Taiwan stock market. This confirms the hypothesis that investor attention impacts stock performance. The results highlight the importance of integrating digital trace data such as Google Trends into the analysis of lottery stocks. We also show the potential of such non-traditional data in predicting market behaviors in environments influenced by investor sentiment.
Reference:	Baker, M. and Wurgler, J. (2006). Investor Sentiment and the Cross-Section of Stock Returns, Journal of Finance, 61(4): 1645-1680. Baker, M. and Wurgler, J. (2007). Investor Sentiment in the Stock Market, Journal of Economic Perspectives, 21(2): 129-151. Barber, B. M. and Odean, T. (2000). Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors, Journal of Finance, 55(2): 773-806. Barber, B. M. and 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. Brown, G. W. and Cliff, M. T. (2004). Investor Sentiment and the Near-Term Stock Market, Journal of Empirical Finance, 11(1): 1-27. Campos, I., Cortazar, G., and Reyes, T. (2017). Modeling and predicting oil VIX: Internet search volume versus traditional variables, Energy Economics, 66: 194-204. Chai, D., Dai, M., Gharghori, P. and Hong, B. (2021), Internet Search Intensity and Its Relation with Trading Activity and Stock Returns† . International Review of Finance, 21: 282-311. Chou, R. Y., Lin, J.-L. and Wu, C.-S. (1999). Modeling the Taiwan Stock Market and International Linkages, Pacific Economic Review, 4(3): 305-320. Chou, B.-H., Chang, Y.-C., & Lin, M.-C. (2019). Investor Sentiment and Stock Return Interaction. Quarterly Journal of Securities Markets Development, Special Issue on Behavioral Finance, 153-190. Da, Z., Engelberg, J. and Gao, P. (2011). In Search of Attention, Journal of Finance, 66(5): 1461-1499. Eraker, B. and Ready, M. J. (2015). Do Investors Overpay for Stocks with Lottery-Like Payoffs? An Examination of the Returns of OTC Stocks, Journal of Financial Economics, 115(3): 486–504 Fisher, K. L. and Statman, M. (2000). Investor Sentiment and Stock Returns, Financial Analysts Journal, 56(2): 16-23. Audrino, F., Sigrist, F., and Ballinari, D. (2020). The impact of sentiment and attention measures on stock market volatility, International Journal of Forecasting, 36(2): 334-357. Kahneman, D. and Tversky, A. (1979). Prospect Theory: An analysis of Decision under Risk, Econometrica, 47(2): 263-292. Kahneman, D. 1973. Attention and Effort (Englewood Cliffs, New Jersey: Prentice-Hall). Ko, C.-R. and Chang, H.-T. (2021). LSTM-based sentiment analysis for stock price forecast, PeerJ Computer Science, 7:e408. Koenker, R., & Bassett, G. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. Kumar, A. (2009). Who Gambles in the Stock Market?, Journal of Finance, 64(4): 1889-1933. Kuo, Yu-Hsiang. (2020). “Study of the lottery-type stocks for Taiwan stock markets” (Master’s thesis, Tamkang University) Meng, H. (2023). A Brief Analysis of The Impact of Investor Sentiment on Stock Prices in The Chinese Stock Market, Frontiers in Business, Economics and Management, 11(2): 61-64. Preis, T., Moat, H. S. and Stanley, H. E. (2013). Quantifying Trading Behavior in Financial Markets Using Google Trends, Nature Scientific Reports, 3: 1684. Shiller, R. J. (1981). Do Stock Prices Move Too Much to Be Justified by Subsequent Changes in Dividends?, American Economic Review, 71(3): 421-436. Vozlyublennaia, N. (2014). Investor Attention, Index Performance, and Return Predictability, Journal of Banking & Finance, 41: 17-35. Wang, Yun-Sheng. (2019). “Can we predict the future return of lottery-like stocks?” (Master’s thesis, National University of Kaohsiung)
Description:	碩士國立政治大學財務管理學系 111357038
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0111357038
Data Type:	thesis
Appears in Collections:	[財務管理學系] 學位論文

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