Abstract
We investigate the relationship between Google Trends Search Volume Index (SVI) and the average returns of Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). In particular, we used the aggregate SVI searched by a company’s abbreviated name and by its ticker symbol to conduct our research. The results are very different. While the aggregate SVI of abbreviated names is significantly and positively correlated to the average returns of TAIEX, the aggregate SVI of ticker symbols is not. This gives strong evidence that investors in the Taiwan stock market normally use abbreviated names, not ticker symbols, to conduct Google search for stock information. Additionally, we found the aggregate SVI of small–cap companies has a higher degree of impact on the TAIEX average returns than that of the mid–cap and large–cap companies. Finally, we found the aggregate SVI with an increasing trend also has a stronger positive influence on the TAIEX average returns than that of the overall aggregate SVI, while the aggregate SVI with a decreasing trend has no influence on the TAIEX average returns. This supports the attention hypothesis of Odean [12] in that the increased investors attention, which is measured by the Google SVI, is a sign of their buying intention, hence caused the stock prices to increase while decreased investors attention is not connected to their selling intention or the decrease of stock prices.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Aouadi, A., Arouri, M., Teulon, F.: Investor attention and stock market activity: evidence from France. Econ. Modell. 35, 674–681 (2013)
Bank, M., Larch, M., Peter, G.: Google search volume and its influence on liquidity and returns of German stocks. Financ. Mark. Portf. Manag. 25(3), 239–264 (2011)
Barber, B.M., Odean, T.: All that glitters: the effect of attention and news on the buying behavior of individual and institutional investors. Rev. Financ. Stud. 21(2), 785–818 (2008)
Bulut, L.: Google Trends and forecasting performance of exchange rate models. IPEK Working Papers 1505, Ipek University, Department of Economics (2015)
Choi, H., Varian, H.: Predicting the present with Google Trends. Econ. Rec. 88, 2–9 (2012)
Challet, D., Ayed, A.B.H.: Do Google Trend data contain more predictability than price returns? J. Invest. Strat. (2015)
Da, Z., Engelberg, J., Gao, P.: In search of attention. J. Financ. 66(5), 1461–1499 (2011)
Joseph, K., Wintoki, M.B., Zhang, Z.: Forecasting abnormal stock returns and trading volume using investor sentiment: evidence from online search. Int. J. Forecast. 27(4), 1116–1127 (2011)
Kri\(\check{s}\)toufek, L.: BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Reports 3 (2013). Article number 3415
Latoeiro, P., Ramos, S.B., Veiga, H.: Predictability of stock market activity using Google search queries. Working Paper 13-06. Universidad Carlos III de Madrid (2013)
Merton, R.C.: A simple model of capital market equilibrium with incomplete information. J. Financ. 42(3), 483–510 (1987)
Odean, T.: Do investors trade too much? Am. Econ. Rev. 89(5), 1279–1298 (1999)
Preis, T., Moat, H. S., Stanley, H. E.: Quantifying trading behavior in financial markets using Google Trends, Science Report 3 (2013)
Simon, H.A.: A behavioral model of rational choice. Q. J. Econ. 69(1), 99–118 (1955)
Taiwan Stock Exchange: TWSE Publishes the SmallCap 300 Sub-Index (2015). (Press Release). http://www.twse.com.tw/en/news/newsDetail/72DAE07E05F945A8953D40A303F418B7
Takeda, F., Wakao, T.: Google search intensity and its relationship with returns and trading volume of Japanese stocks. Pac.-Basin Financ. J. 27, 1–18 (2014)
Turan, S.S.: Internet search volume and stock return volatility: the case of Turkish companies. Inf. Manag. Bus. Rev. 6(6), 317–328 (2014)
Vlastakis, N., Markellos, R.N.: Information demand and stock market volatility. J. Bank. Financ. 36(6), 1808–1821 (2012)
Vozlyublennaia, N.: Investor attention, index performance, and return predictability. J. Bank. Financ. 41, 17–35 (2014)
Acknowledgement
The authors are grateful for the research support in the form of Ministry of Science and Technology (MOST) Grants, MOST 106-2410-H-004-006-MY2.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Shen, PH., Chen, SH., Yu, T. (2019). Google Trends and Cognitive Finance: Lessons Gained from the Taiwan Stock Market. In: Bucciarelli, E., Chen, SH., Corchado, J. (eds) Decision Economics. Designs, Models, and Techniques for Boundedly Rational Decisions. DCAI 2018. Advances in Intelligent Systems and Computing, vol 805. Springer, Cham. https://doi.org/10.1007/978-3-319-99698-1_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-99698-1_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-99697-4
Online ISBN: 978-3-319-99698-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)