Cross-Temporal Credit Default Probability Prediction Model

Develop a probabilistic machine learning pipeline that predicts credit default probabilities using multi-dimensional time series data. The model should integrate macroeconomic indicators, historical default rates, company-specific financial statements, and market sentiment signals. Create a robust feature engineering approach that handles missing data, performs advanced feature selection, and generates confidence intervals for default predictions.