Dynamic Risk Assessment Database with Machine Learning Integration

Create a sophisticated PostgreSQL database schema in Python that dynamically tracks financial instrument risk profiles using machine learning predictions. Develop a system that can ingest historical trading data, calculate real-time risk metrics, and automatically adjust risk coefficients using scikit-learn's predictive models. Implement a flexible indexing strategy that supports both historical analysis and near-instantaneous risk calculations for complex derivative instruments.