A machine learning model that predicts whether the S&P 500 index will go up or down the next trading day. Uses a Random Forest classifier trained on historical price data with rolling window features, evaluated through a walk-forward backtesting system to simulate real trading conditions.
feature-engineering random-forest-classifier rolling-window-features time-series-data-handling target-engineering walk-forward-backtesting precision-focused-prediction yfinance-data-fetching precision-score-evaluation pandas-time-series-operations
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Updated
May 19, 2026 - Python