/predict_stock_market

Primary LanguageJupyter Notebook

Project Overview

This project aims to predict the price of the S&P 500 stock market index using machine learning techniques.

Project Steps

  1. Data Acquisition

    • Utilize the yfinance package to download historical data of the S&P 500 stock market index.

  2. Initial Model Creation and Evaluation

    • Build an initial machine-learning model using the acquired data.
    • Estimate the model's accuracy and performance metrics.

  3. Backtesting Engine Development

    • Develop a robust backtesting engine to more accurately evaluate the model's performance.
    • Employ the engine to measure accuracy, considering various periods and potential market conditions.

  4. Model Enhancement for Improved Accuracy

    • Refine and enhance the machine learning model based on insights from the backtesting results.
    • Implement feature engineering, parameter tuning, or model selection techniques to improve predictive accuracy.