Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.080752
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 7, 2017.
Abstract: Financial decisions are among the most significant life-changing decisions that individuals make. There is a strong correlation between financial decision making and human behavior. In this research the relationship between what people think and how stock market moves is investigated. The data from 2010 to 2015 of some of business, political and financial events which directly impact the local stock market in Pakistan is analyzed. The data was collected from search engine Google via Google trends. The association between internet searches regarding the political or business events and how the subsequent stock market moves is established. It was found that increase in search of these topics may lead to stock market fall or rise. The overall objective of this research is to predict Karachi Stock Exchange (now known as Pakistan stock exchange) 100 index by quantifying the semantics of international market. In addition to that, the relation between what an individual thinks while searching on Google which affects the local market is also investigated. The collected data has been mined by Multiclass Neural Network and Multiclass Decision Trees. The result shows that Multiclass Decision Trees performed best with an accuracy of 94%.
Farrukh Ahmed, Dr. Raheela Asif, Dr. Saman Hina and Muhammad Muzammil, “Financial Market Prediction using Google Trends” International Journal of Advanced Computer Science and Applications(IJACSA), 8(7), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080752