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This research tests whether Benjamin Graham's classical value investing rules can act as a mathematical 'low-pass filter' to prevent modern machine learning models (XGBoost, AutoGluon) from overfitting to market noise. Using 20 years of S&P 500 data, the authors find that Graham's rules combined with Random Forest achieve high returns with lower risk than complex AI models alone.