A Study on the Relationship between Internet Search Trends and Company’s Stock Price and Trading Volume

Pyunghoi Koo, Minsoo Kim

Abstract


In this paper, we investigate the relationship between Internet search trends and stock market. Under the assumption that investors may use Internet search engine to obtain information for companies of their interests before taking actual investment actions, the relationship between the changes on Internet search volume and the fluctuation of trading volume as well as stock price of a company is analyzed with actual market data. A search trend investment strategy that reflects the changes on Internet search volume is applied to large enterprises’ group and to small and medium enterprises’ (SMEs) group, and the correlation between profit rate and trading volume is analyzed for each company group. Our search trend investment strategy has outperformed average stock market returns in both KOSPI and KOSDAQ markets during the seven-year study period (2007~2013). It is also shown that search trend investment strategy is more effective to SMEs than to large enterprises. The relationship between changes on Internet search volume and stock trading volume is stronger at SMEs than at large enterprises.


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References


Biswas, S., Yoo, J. H., and Jung, C. Y., “A Study on Priorities of the Components of Big Data Information Security Service by AHP,” Journal of Society for e-Business Studies, Vol. 18, No. 4, 2013.

Bollen, J., Mao, H., and Zeng, X. J., “Twitter mood predicts the stock market,” Journal of Computational Science, Vol. 2, No. 1 pp. 1-8, 2011.

Bordino, I., Battiston, S., Caldarelli, G., Cristelli, M., Ukkonen, A., and Weber, I., “Web search queries can predict stock market volumes,” PLOS One, Vol. 7, No. 7, pp. 1-17, 2012.

Choi, H. and Varian, H., “Predicting Initial Claims for Unemployment Insurance Using Google Trends,” Technical Report, Google, 2009.

Choi, H. and Varian, H., “Predicting the present with Google Trends,” The Economic Record, Vol. 88, pp. 2-9, 2012.

Choi, S. and Kwon, O., “The Study of Developing Korean SentiWordNet for Big Data Analytics: Focusing on Anger Emotion,” Journal of Society for e-Business Studies, Vol. 19, No. 4, pp. 1-19, 2014.

Cooper, C., Mallon, K., Leadbetter, S., Pollack, L., and Peipins, L., “Cancer Internet Search Activity on a Major Search Engine, United States 2001-2003,” Journal of Medical Internet Research, Vol. 7, No. 3, 2005.

Ettredge, M., Gerdes, J., and Karuga, G., “Using Web-based search data to predict macroeconomic statistics,” Communications of the ACM, Vol. 48, No. 11, pp. 87-92, 2005.

Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., and Brilliant, L., “Detecting influenza epidemics using search engine query data,” Nature, Vol. 457, pp. 1012-1014, 2009.

Goel, S., Hofman, J. M., Lahaie, S., Pennock, D. M., and Watts, D. J., “Predicting consumer behavior with Web search,” Proceedings of the National Academy of Sciences, Vol. 7, No. 41, pp. 17486-17490, 2010.

Kim, M. and Koo, P., “A Study on Big Data Based Investment Strategy Using Internet Search Trends,” Journal of the Korean Operations Research and Management Science Society, Vol. 38, No. 4, pp. 53-63, 2013.

McLaren, L. and Shanbhogue, R., “Using internet search data as economic indicator,” Quarterly Bulletin, Q2, pp. 134-140, 2011.

Min, G. Y. and Jeong, D. H., “Research on Assessment of Impact of Big Data Attributes to Disaster Response Decision-Making Process,” Journal of Society for e-Business Studies, Vol. 18, No. 3, 2013.

Moat, H. S., Curme, C., Avakian, A., Kenett, D. Y., Stanley, E., and Preis, T., “Quantifying Wikipedia usage patterns before stock market moves,” Scientific Report, Vol. 3, pp. 01801:1-5, 2013.

National Information Society Agency (Korea), New Value-Creation Engine, Big Data’s New Possibility and Response Strategy, IT & Future Strategy, Vol. 18, 2011.

Parikh, P., VALUE INVESTING and BEHAVIORAL FINANCE: Insights into Indian Stock Market Realities, Tata McGraw-Hill Education, 2009.

Polgreen, P. M., Chen, Y., Pennock, D. M., and Nelson, F. D., “Using Internet Searches for Influenza Surveillance,” Healthcare Epidemiology, Vol. 47, pp. 1443-1448, 2008.

Preis, T., Moat, H. S., and Stanley, H. E., “Quantifying trading behavior in financial markets using Google Trends,” Scientific Report, Vol. 3, pp. 01684:1-5, 2013.

Preis, T., Moat, H. S., Stanley, H. E., and Bishop, S. R., “Quantifying the Advantage of Looking Forward,” Scientific Report, Vol. 2, pp. 00350:1-2, 2012.

Preis, T., Reith, D., and Stanley, H. E., “Complex dynamics of our economic life on different scales: insights from search engine query data,” Philosophical Transactions of the Royal Society, Vol. 368, pp. 5707-5719, 2010.

Song, M., Business Future Map That Big Data Builds, Hans Media, 2012.

Suzuki, R., The Age of Big Data Business, The Soup, 2012.

Yoon, H., Now Its Big Data Era, eBiz Books, 2012.


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