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%.
Highlights
We are living in a world where data is generated from all domains of life
The real question is how we can convert this data into meaningful information for decision making such as to predict stock market behavior
Stock market prediction is a domain of challenging factors which is based on many important aspects and collective thinking of the financial experts
Summary
We are living in a world where data is generated from all domains of life. The real question is how we can convert this data into meaningful information for decision making such as to predict stock market behavior. Stock market prediction is a domain of challenging factors which is based on many important aspects and collective thinking of the financial experts. Stock Market data can be acquired from different sources. Its impact has generated considerable scientific attention due to its complexity and size. Despite its huge size, such data sets capture only the final action taken at the end of a decisionmaking process. No insight is provided into earlier stages of this process, where traders may use this information to determine what consequences of various actions and factors may be
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
