Taming the Noise with Regularization and Hyperparameter Tuning Keywords: Ridge, Lasso, Elastic-net Introduction In last part, we built a linear regression model to predict stock returns. We discovered a fundamental truth: simple models often underfit (fail to capture signal), while complex models (like high-degree polynomials) overfit (memorize noise). In Finance, the “signal-to-noise” ratio is incredibly … Continue reading Machine Learning for Quants (Part 2)