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The share market, or stock market, nowadays is one of the typical ways of investing and earning money. All the different earning sectors in India, viz. Education, agriculture, defense sector, IT sector, pharmaceutical sector, etc., depend upon the share market movement. It is very difficult for an individual to predict the stock market. However, our paper proposes to use different machine learning and deep learning algorithms for predicting future stock prices and their trends using the Python libraries. We compare and contrast the methods of prediction. Our work effectively utilizes both sequence modeling and statistical approaches for prediction and analysis, distinguishing it from current research in the field.

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Forecasting Stock Prices: A Comparative Analysis of Machine Learning, Deep Learning, and Statistical Approaches

  • 会议论文

  • 发表日期：

    2025年

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  • Kimi Gajjar,
  • Ami Tusharkant Choksi

摘要

The share market, or stock market, nowadays is one of the typical ways of investing and earning money. All the different earning sectors in India, viz. Education, agriculture, defense sector, IT sector, pharmaceutical sector, etc., depend upon the share market movement. It is very difficult for an individual to predict the stock market. However, our paper proposes to use different machine learning and deep learning algorithms for predicting future stock prices and their trends using the Python libraries. We compare and contrast the methods of prediction. Our work effectively utilizes both sequence modeling and statistical approaches for prediction and analysis, distinguishing it from current research in the field.