Knowledge Base
Financial Machine Learning
pragmatic & bite sized

Discoveries and Best Practices

How to avoid Overfitting on Noisy Data
Overfitting in finance occurs when models, highly accurate on historical data, fail with new data due to high complexity. Strategies to combat this include simpler models, cross-validation, feature selection, and out-of-sample testing to ensure real-world adaptability.
February 21, 2019
Differentiating Between Luck and Skill
Explore the fine line between luck and skill in time series financial forecasting. Learn how walk-forward cross-validation and z-score analysis help differentiate model success due to skill from mere chance, ensuring reliable and accurate market predictions.
February 21, 2019