Modern information gathering: Using search trends in Google as a predictor of the Philippine Stock Exchange index for the years 2004-2013

First, this research paper tries to study the correlational relationship between search volume queries in Google of Philippine Stock Exchange index-related search terms and the main index of the Philippine stock market., which is the Philippine Stock Exchange index or PSEi. To reduce the biasness of the researchers, the researchers have gathered the relevant search terms from a survey that was done for Philippine Stock Exchange investors. Second, we provide thorough details on why such a relationship exists between the selected variables. This means the proposed relationship and a-priori expectations of the model in the study are supplemented by numerous related journals. Third, in coming up with the final model, we used different data analysis methods to check if the proposed model is more or less adequate. The researchers constructed two econometric models, which are bivariate regression model and multivariate regression model using dummy variables, to determine the final model. Lastly, the researchers propose a hypothetical investment strategy based on our final model and check its effectiveness by computing for its cumulative returns of the hypothetical investment strategy is higher that the cumulative returns of a simple buy-and-hold strategy for the same period.That being said, we found out that the search volume of the search term Philippine stock exchange has the best predictive power over PSEi movements with major positive search volume changes having greater impact than major negative search volume changes. Also, the hypothetical investment strategy using Google trends data garnered 291.01% cumulative returns while the buy-and-hold strategy only gained 218.06%, which yields a 72.95% difference. Hence, we conclude that the strategy is indeed effective.