1. NCCU Academic Hub
  2. 學術產出
  3. College of Social Science
  4. Theses
  5. Item

學術產出-Theses

Article View/Open

Publication Export

Google ScholarTM

政大圖書館

Citation Infomation

  • No doi shows Citation Infomation
題名 Google搜尋趨勢與認知金融：從臺灣股票市場學到的新知
Google Trends and Cognitive Finance : Lessons Gained from the Taiwan Stock Market
作者 沈佩璇
Shen, Pei Hsuan
貢獻者 陳樹衡
Chen, Shu Heng
沈佩璇
Shen, Pei Hsuan
關鍵詞 認知金融
搜尋量指數
股票市場
投資行為
Cognitive finance
Google search volume index
Stock market
Behavior of investors
日期 2018
上傳時間 2-Feb-2018 11:35:12 (UTC+8)
摘要 
Behavioral finance is the study of the influence of psychology on the behaviors of financial practitioners and the subsequent effect on the markets. Although behavioral finance theory has been popular for many years, empirical studies only become possible recently, thanks to the advancement of technology and the availability of data and tools. This research adopts an empirical approach to investigate how investors’ attention and interview sentiments influence Taiwan stock market. In particular, we identify the psychological factors that have an impact on Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX).
In addition to TAIEX data, including TAIEX prices and trading volume, two other data sources have been used in this study: (1) Investor Confidence Index interview data provided by J.P. Morgan Asset Management, representing investors’ interview sentiments and (2) search volume data from Google Trends, symbolizing investors’ attention. We first analyzed weekly data from January 5, 2014 to November 6, 2016, and then ran regression on the data, under the Newey-West correction of standard errors method, to identify the effects of investors’ attention and interview sentiments on TAIEX.
We have found many interesting results. First, we discovered the investors in the Taiwan stock market normally use company names, not ticker symbols, to conduct Google search for information related to investment decisions. Second, investors’ attention based on the Google Search Volume Index (SVI) searched by company names is significantly and positively correlated with the average returns of TAIEX, which agrees with the attention hypothesis of Barber and Odean (2007). Third, we verified the hypothesis of Barber and Odean (2007) that the positive trend of SVI is an indication of investors’ intention of purchasing a stock. Fourth, investors’ interview sentiment of Taiwan Stock Price Index is negatively correlated with the average returns of TAIEX, which supports the overconfident hypothesis proposed by De Bondt and Thaler (1995). By contrast, their interview sentiment of Taiwan Economic Situation Index is positively correlated with the average returns of TAIEX. Finally, trading volume is positively related to the average returns of TAIEX, which aligns with that reported in Chuang, Ouyang, and Lo (2010).
參考文獻 Aouadi, A., Arouri, M., & Teulon, F. (2013). Investor attention and stock market activity: Evidence from France. Economic Modelling, 35, 674-681.
Andrade, S. C., Chang, C., & Seasholes, M. S. (2008). Trading imbalances, predictable reversals, and cross-stock price pressure. Journal of Financial Economics, 88(2), 406-423.
Andrews, D. W. (1991). Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica: Journal of the Econometric Society, 817-858.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680.
Bank, M., Larch, M., & Peter, G. (2011). Google search volume and its influence on liquidity and returns of German stocks. Financial markets and portfolio management, 25(3), 239-264.
Barber, B. M., & Odean, T. (2007). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. The Review of Financial Studies, 21(2), 785-818.
Barber, B. M., Odean, T., & Zhu, N. (2008). Do retail trades move markets?. The Review of Financial Studies, 22(1), 151-186.
Barber, B. M., Odean, T., & Zhu, N. (2009). Systematic Noise. Journal of Financial Markets, volume 12, issue 4, pages 547-569, Elsevier
Chuang, W. J., Ouyang, L. Y., & Lo, W. C. (2010). The impact of investor sentiment on excess returns a Taiwan stock market case. International Journal of Information and Management Sciences, 21(1), 13-28.
Chung, S. L., & Yeh, C. Y. (2009). Investor Sentiment, Regimes and Stock Returns.
(February 13, 2009). Available at SSRN: https://ssrn.com/abstract=1342588.
Da, Z., Engelberg, J., & Gao, P. (2009). In Search of Attention. AFA 2010 Atlanta
Meetings Paper. Available at SSRN: http://ssrn.com/abstract=1364209
Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention. The Journal of Finance, 66(5), 1461-1499.
Daniel, K., Hirshleifer, D., and Subrahmanyam, A.(1998) Investor Psychology and Security Market Under- and Over-Reactions, Journal of Finance, 53(6):1839-1885.
De Bondt, W. F. & Thaler, R. H. (1995). Financial decision-making in markets and firms: A behavioral perspective. Handbooks in operations research and management science, 9, 385-410.
Fan, M. H., Liao, E. C., & Chen, M. Y. (2014, December). A TAIEX forecasting model based on changes of keyword search volume on Google Trends. In IEEE International Symposium on Independent Computing (ISIC). IEEE.
Gallant, A. R. (2009). Nonlinear statistical models (Vol. 310). John Wiley & Sons.
Karpoff, J. M. (1987). The relation between price changes and trading volume: A survey. Journal of Financial and quantitative Analysis, 22(1), 109-126.
KUAN, C. M. (2008). LECTURE ON Robust Tests with and without Consistent Estimation of Asymptotic Covariance Matrix. Institute of Economics Academia Sinica. Retrieved from http://homepage.ntu.edu.tw/~ckuan/pdf/Lec-HAC_0802.pdf
Lee, C., and Swaminathan, B. (2000), Price momentum and trading volume, Journal of Finance, Vol. 55, pp.2017-2069.
Litterman, R. B. (1983). A random walk, Markov model for the distribution of time series. Journal of Business & Economic Statistics, 1(2), 169-173.
Miller, E. M. (1977). Risk, uncertainty, and divergence of opinion. The Journal of finance, 32(4), 1151-1168.
McCall, J. J. (1970). Economics of information and job search. The Quarterly Journal of Economics, 113-126.
Russo, J. E. (1974). More information is better: A reevaluation of Jacoby, Speller and Kohn. Journal of Consumer Research, 1(3), 68-72.
描述 碩士
國立政治大學
經濟學系
104258021
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0104258021
資料類型 thesis
dc.contributor.advisor 陳樹衡zh_TW
dc.contributor.advisor Chen, Shu Hengen_US
dc.contributor.author (Authors) 沈佩璇zh_TW
dc.contributor.author (Authors) Shen, Pei Hsuanen_US
dc.creator (作者) 沈佩璇zh_TW
dc.creator (作者) Shen, Pei Hsuanen_US
dc.date (日期) 2018en_US
dc.date.accessioned 2-Feb-2018 11:35:12 (UTC+8)-
dc.date.available 2-Feb-2018 11:35:12 (UTC+8)-
dc.date.issued (上傳時間) 2-Feb-2018 11:35:12 (UTC+8)-
dc.identifier (Other Identifiers) G0104258021en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/115755-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經濟學系zh_TW
dc.description (描述) 104258021zh_TW
dc.description.abstract (摘要) zh_TW
dc.description.abstract (摘要) Behavioral finance is the study of the influence of psychology on the behaviors of financial practitioners and the subsequent effect on the markets. Although behavioral finance theory has been popular for many years, empirical studies only become possible recently, thanks to the advancement of technology and the availability of data and tools. This research adopts an empirical approach to investigate how investors’ attention and interview sentiments influence Taiwan stock market. In particular, we identify the psychological factors that have an impact on Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX).
In addition to TAIEX data, including TAIEX prices and trading volume, two other data sources have been used in this study: (1) Investor Confidence Index interview data provided by J.P. Morgan Asset Management, representing investors’ interview sentiments and (2) search volume data from Google Trends, symbolizing investors’ attention. We first analyzed weekly data from January 5, 2014 to November 6, 2016, and then ran regression on the data, under the Newey-West correction of standard errors method, to identify the effects of investors’ attention and interview sentiments on TAIEX.
We have found many interesting results. First, we discovered the investors in the Taiwan stock market normally use company names, not ticker symbols, to conduct Google search for information related to investment decisions. Second, investors’ attention based on the Google Search Volume Index (SVI) searched by company names is significantly and positively correlated with the average returns of TAIEX, which agrees with the attention hypothesis of Barber and Odean (2007). Third, we verified the hypothesis of Barber and Odean (2007) that the positive trend of SVI is an indication of investors’ intention of purchasing a stock. Fourth, investors’ interview sentiment of Taiwan Stock Price Index is negatively correlated with the average returns of TAIEX, which supports the overconfident hypothesis proposed by De Bondt and Thaler (1995). By contrast, their interview sentiment of Taiwan Economic Situation Index is positively correlated with the average returns of TAIEX. Finally, trading volume is positively related to the average returns of TAIEX, which aligns with that reported in Chuang, Ouyang, and Lo (2010).		en_US
dc.description.tableofcontents 1. Abstract i
2. Introduction 1
1. Research Motivation 1
2. Contributions 2
3. Organizations 4
3. Background and Related Works 5
1. Investors’ Psychology and Behaviours 5
2. Related Works 7
3. Summary 11
4. Research Methods 13
1. Taiwan Economic Journal Data 13
2. J. P. Morgan Asset Management Confidence Indexes 13
3. Google Trends Data 16
4. Newey-West Correction of Standard Errors 18
5. Summary 20
5. Research Results and Analysis 21
1. Variables with a Significant Impact on Average Stock Returns 22
2. Ticker Symbols vs. Company Names: SVIs for Investors Attention 25
3. Analysis of Investors’ Behaviours 30
4. Verification of Investors Buying Attention 33
5. Short-Term Average Returns Prediction. 37
6. Summary 39
6. Conclusions and Outlooks 40
1. Review of Research Findings 40
2. Applications of the Study 42
3. Limitations of the Study 42
4. Recommendations for Future Research 43
7. Appendix 45
1. Newey-West Correction of Standard Errors Method Explained 45
2. Code 49
8. References 51		zh_TW
dc.format.extent 730048 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0104258021en_US
dc.subject (關鍵詞) 認知金融zh_TW
dc.subject (關鍵詞) 搜尋量指數zh_TW
dc.subject (關鍵詞) 股票市場zh_TW
dc.subject (關鍵詞) 投資行為zh_TW
dc.subject (關鍵詞) Cognitive financeen_US
dc.subject (關鍵詞) Google search volume indexen_US
dc.subject (關鍵詞) Stock marketen_US
dc.subject (關鍵詞) Behavior of investorsen_US
dc.title (題名) Google搜尋趨勢與認知金融：從臺灣股票市場學到的新知zh_TW
dc.title (題名) Google Trends and Cognitive Finance : Lessons Gained from the Taiwan Stock Marketen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Aouadi, A., Arouri, M., & Teulon, F. (2013). Investor attention and stock market activity: Evidence from France. Economic Modelling, 35, 674-681.
Andrade, S. C., Chang, C., & Seasholes, M. S. (2008). Trading imbalances, predictable reversals, and cross-stock price pressure. Journal of Financial Economics, 88(2), 406-423.
Andrews, D. W. (1991). Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica: Journal of the Econometric Society, 817-858.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680.
Bank, M., Larch, M., & Peter, G. (2011). Google search volume and its influence on liquidity and returns of German stocks. Financial markets and portfolio management, 25(3), 239-264.
Barber, B. M., & Odean, T. (2007). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. The Review of Financial Studies, 21(2), 785-818.
Barber, B. M., Odean, T., & Zhu, N. (2008). Do retail trades move markets?. The Review of Financial Studies, 22(1), 151-186.
Barber, B. M., Odean, T., & Zhu, N. (2009). Systematic Noise. Journal of Financial Markets, volume 12, issue 4, pages 547-569, Elsevier
Chuang, W. J., Ouyang, L. Y., & Lo, W. C. (2010). The impact of investor sentiment on excess returns a Taiwan stock market case. International Journal of Information and Management Sciences, 21(1), 13-28.
Chung, S. L., & Yeh, C. Y. (2009). Investor Sentiment, Regimes and Stock Returns.
(February 13, 2009). Available at SSRN: https://ssrn.com/abstract=1342588.
Da, Z., Engelberg, J., & Gao, P. (2009). In Search of Attention. AFA 2010 Atlanta
Meetings Paper. Available at SSRN: http://ssrn.com/abstract=1364209
Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention. The Journal of Finance, 66(5), 1461-1499.
Daniel, K., Hirshleifer, D., and Subrahmanyam, A.(1998) Investor Psychology and Security Market Under- and Over-Reactions, Journal of Finance, 53(6):1839-1885.
De Bondt, W. F. & Thaler, R. H. (1995). Financial decision-making in markets and firms: A behavioral perspective. Handbooks in operations research and management science, 9, 385-410.
Fan, M. H., Liao, E. C., & Chen, M. Y. (2014, December). A TAIEX forecasting model based on changes of keyword search volume on Google Trends. In IEEE International Symposium on Independent Computing (ISIC). IEEE.
Gallant, A. R. (2009). Nonlinear statistical models (Vol. 310). John Wiley & Sons.
Karpoff, J. M. (1987). The relation between price changes and trading volume: A survey. Journal of Financial and quantitative Analysis, 22(1), 109-126.
KUAN, C. M. (2008). LECTURE ON Robust Tests with and without Consistent Estimation of Asymptotic Covariance Matrix. Institute of Economics Academia Sinica. Retrieved from http://homepage.ntu.edu.tw/~ckuan/pdf/Lec-HAC_0802.pdf
Lee, C., and Swaminathan, B. (2000), Price momentum and trading volume, Journal of Finance, Vol. 55, pp.2017-2069.
Litterman, R. B. (1983). A random walk, Markov model for the distribution of time series. Journal of Business & Economic Statistics, 1(2), 169-173.
Miller, E. M. (1977). Risk, uncertainty, and divergence of opinion. The Journal of finance, 32(4), 1151-1168.
McCall, J. J. (1970). Economics of information and job search. The Quarterly Journal of Economics, 113-126.
Russo, J. E. (1974). More information is better: A reevaluation of Jacoby, Speller and Kohn. Journal of Consumer Research, 1(3), 68-72.		zh_TW