Predicting firm profitability in post-COVID India: A machine learning approach using fundamental financial ratios

FINANCIAL DISTRESS PREDICTION USING THE DECISION TREE METHOD IN MANUFACTURING COMPANIES IN INDONESIA

This study aims to predict financial distress in Indonesian manufacturing companies using the Decision Tree method. A quantitative predictive design was applied to secondary data from the annual financial statements of manufacturing companies listed on the Indonesia Stock Exchange during 2020–2024, yielding 612 firm-ye...

Financial Modelling and Forecasting of Selected Information Technology Companies Listed in India

-Financial modelling and forecasting translate a company's historical accounting record into a forward-looking view of its earning power and value, which matters greatly for a sector such as Indian information technology (IT) whose revenues are shaped by currency movements, global demand cycles and rapid technological...

Machine Learning Applications in Credit Risk Prediction

EARLY PREDICTION OF FINANCIAL DISTRESS RISK IN VIETNAMESE LISTED INDUSTRIAL FIRMS USING MACHINE LEARNING

Early prediction of financial distress risk is important for providing timely warning signals to investors, creditors, and regulators. This study examines 91 Vietnamese listed industrial firms over the period 2015–2024 and compares a traditional Logistic Regression model with three machine learning algorithms: Random F...

Working Capital Management and Corporate Profitability: An Empirical Study Based on Secondary Financial Data

This paper is an analysis of the working-capital management and its relationship with corporate profitability in five major consumer goods companies in India - Hindustan Unilever Limited, ITC Limited, Nestlé India Limited, Dabur India Limited and Britannia Industries Limited. The key working capital measure is the cash...

FORECASTING CORPORATE CASH HOLDINGS IN VIETNAM: COMPARING MACHINE LEARNING MODELS AND THE IMPACT OF THE WORLD UNCERTAINTY INDEX

This study forecasts the cash holdings (CASH) of listed companies in Vietnam based on data from 2018-2025 using a machine learning approach and identifies HistGradientBoosting as the optimal model, demonstrating strong non-linearity in liquidity management behavior in the Vietnamese market.