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Google Trends and Cognitive Finance: Lessons Gained from the Taiwan Stock Market

  • Pei-Hsuan Shen
  • Shu-Heng ChenEmail author
  • Tina Yu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 805)

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.

Keywords

Google Trends Investors attention TAIEX Cognitive finance Search volume index Attention hypothesis Stock returns 

Notes

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.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.National Chengchi University AI-ECON Research CenterTaipeiRepublic of China

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