Financial indicators analysis using machine learning: Evidence from Chinese stock market

Abstract

This study employs machine learning models to explore the predictive power of 10 categories of financial indicators on the Chinese stock market. We examine whether influential financial indicators fall into distinct categories of greater importance for predicting stock returns. The findings demonstrate that financial indicators across 10 categories hold predictive power for stock returns on Chinese market, with neural network models outperforming linear ones. Profitability and growth indicators are among the most influential indicators. This study contributes to a better understanding of financial indicators and demonstrates the effectiveness of machine learning models in the Chinese stock market.