Text Analytics to Assist Financial Research

Abstract

The amount of data is increasing in the financial domain as in every field. It is humanly impossible to analyse all these data efficiently, so we need optimised computational techniques to achieve this. In this work, We aim to figure out an efficient technique to collect relevant news articles from web sources and extract valuable pieces of information from them. We started by focusing on extracting six important financial events from news articles. We devised a method that could achieve a fair accuracy in these six event types. More work is to be done to integrate additional financial events and enhance accuracy. We believe that this work can serve as a foundation for future developments and research.