few-shot-learning-finance

What problem does it solve?

This Skill enables rapid adaptation of trading models to new market regimes with limited data by leveraging episodic, context-based meta-learning.

Core Features & Use Cases

• Episodic training that mirrors test-time usage to improve generalization.
• Context set construction methods: random, time-equivalent, and CPD-segmented with causality guarantees.
• Cross-attention-based transfer of patterns from context to target for rapid adaptation.
• Joint optimization of forecasting accuracy and trading performance using a single loss.

Quick Start

Run an episodic training loop using your asset data and evaluate predictions with a context set that precedes each target.