I. Introduction
The stock market is known for being erratic, lively and nonlinear. Because of several variables (macro and micro) including politics, international economic conditions, unforeseen occurrences, company’s financial performance and others, accurately predicting stock prices is very difficult [1]. But all these also means that there is lot of data to look into for patterns. As a result, to identify stock market patterns, financial analysts, researchers and data scientists continue to explore analytics tools. The idea of algorithmic trading, which employs automated, pre-programmed trading techniques to execute orders was born as a result of this [2].