ml-for-finance

What problem does it solve?

This skill provides a structured approach to applying supervised machine learning to finance, addressing the challenge of building robust models for trading signals, regime detection, and risk assessment.

Core Features & Use Cases

• Supervised modeling for returns and regime detection in financial markets
• Time-series cross-validation with purging and embargo to avoid look-ahead bias
• Feature importance analysis using SHAP and permutation methods for model interpretability
• Backtesting-ready evaluation and monitoring of model decay and performance

Quick Start

Train a baseline model on a finance dataset to predict next-day returns.