Assessing Financial Performance of Tech Enterprises Blending Machine Learning Techniques

Abstract

In this study, the objective is developing a holistic research model for evaluating Tech business performance by blending machine learning techniques with well-known financial instruments such as Dupont Analysis. Systematic literature review of high-quality journals has helped formed the backbone of this research work. The dependent variable are Return on Equity and Return on Assets. The technique used will be a Machine Learning model using financial data from esteemed databases such as Eikon Refinitiv. The objective is to develop a predictive model utilizing machine learning approach that can analyse and visualize financial performance of tech companies from similar domains using Cluster Analysis. The design of our research model would be such that it is more practical in scope.  The proposed model would be put forth as a decision support system for investors wishing to understand the companies better before investing.