The Firm Life Cycle Forecasting Model Using Machine Learning Based on News Articles

Abstract

The determination of the firm life cycle has been carried out in relation to the establishment of corporate strategy in the field of accounting or management. The life cycle prediction based on financial information is long because it is determined based on the financial performance of the entity over a year. This study sought to lay the foundation for overcoming this by using news articles to predict the life cycle of a company. In the process of quantifying news article data and predicting the firm life cycle, the method of selecting keywords that can represent the firm life cycle is presented, and the life cycle prediction model is verified with four machine learning techniques using selected candidate keywords. In this study, all four machine learning techniques showed a predicted static classification rate of nearly 60%, demonstrating the availability of news articles, which are unstructured text data, in predicting the corporate life cycle.

Keywords

• Firm life cycle prediction
• news analysis
• machine learning
• text feature selection