Using Popular Search Terms in Stock Price Prediction

Web portals are key gateways to many companies for products search, customer services, and many more services. The volume of searching for a particular company, and its website through the Internet and search engines can be a metric on its web popularity. Our goal in this paper is to study, the relationship, if any, between the change in volume of searches for companies through the Internet and the change in the companies stock prices. We expect to see different types of levels of impacts/correlations between those two factors for different reasons. For example stock prices can change for many different reasons where some of those reasons may have nothing to do with customers at all. Second is that same factors can have different impact on the different companies. For example, while in some IT or technology related companies web popularity can be a significant factor or indicator, in many other companies, such popularity is not significant at all. In this paper, we studied historical stock prices for a selected dataset of companies(S&P 500) along with the search or interest in those companies (based on Google search queries). We created and evaluated a dataset of search terms and their correlations with stock price change of S&P 500 companies. Results showed that different companies can be influenced by popular search terms at different weights. We distinguished also in our work between negative or positive influence where keywords can be correlated to the decrease or increase of stock prices.