Application of machine learning algorithm to measure a firm's performance.

Abstract

Machine learning techniques are an emerging field in today’s world. The objective of this thesis was to use machine learning methodology to measure a company’s per-formance by using forecasting techniques in financial statements. This information can be useful for investors, managers, and analysts. The financial statement data collected were from 250 companies from the United States of America. The method-ology that was applied was Long Short-Term Memory. The forecasting method used was time-series forecasting. The software used for running the code was Juypter. The conclusion of the study shows that machine learning algorithms can be applied for forecasting firm performance. The program shows the results for the future predic-tion of the performance of companies.