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

Author

Listed:
  • Zhao, Chencheng
  • Yuan, Xianghui
  • Long, Jun
  • Jin, Liwei
  • Guan, Bowen

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.

Suggested Citation

  • Zhao, Chencheng & Yuan, Xianghui & Long, Jun & Jin, Liwei & Guan, Bowen, 2023. "Financial indicators analysis using machine learning: Evidence from Chinese stock market," Finance Research Letters, Elsevier, vol. 58(PD).
    • Handle: RePEc:eee:finlet:v:58:y:2023:i:pd:s1544612323009625
    DOI: 10.1016/j.frl.2023.104590
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    More about this item

    Keywords

    Financial indicators; Machine learning; Return prediction;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G39 - Financial Economics - - Corporate Finance and Governance - - - Other
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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