Utilizing Technical Data to Discover Similar Companies in Dhaka Stock Exchange

TL;DR

This paper explores how technical data can be used to identify groups of similar companies in the Dhaka Stock Exchange, aiding investors in analyzing multiple companies efficiently.

Contribution

It introduces a method to find company clusters based solely on technical data, revealing domain-specific relations without using fundamental data.

Findings

Successfully identified company groups with similar movement patterns

Discovered a correlation between technical and fundamental data

Provided a scalable approach for analyzing large stock markets

Abstract

Stock market investment have been an ideal form of investment for many years. Investing capitals smartly in stock market yields high profit returns. But there are many companies available in a market. Currently there are more than $345$ active companies who have stocks in Dhaka Stock Exchange (DSE). Analyzing all these companies is quite impossible. However, many companies tend to move together. This study aims at finding which companies in DSE have a close connection and move alongside each other. By analyzing this relation, the investors and traders will be able to analyze a lot of companies' statistics from a calculating just a handful number of companies. The conducted experiment yielded promising results. It was found that though the system was not given anything other than technical data, it was able to identify companies that show domain specific outcomes. In other words, a relation between technical data and fundamental data was discovered from the conducted experiment.