Transfer Learning for Cross-Market Financial Prediction

Develop an advanced transfer learning approach for financial prediction that can effectively leverage knowledge across different market domains and asset classes. Create a modular machine learning framework capable of transferring learned representations between seemingly unrelated financial time series while maintaining predictive performance and interpretability. Implement techniques to quantify and mitigate negative transfer effects.