Probabilistic Portfolio Optimization with Uncertainty Quantification

Develop a sophisticated portfolio optimization framework that goes beyond traditional mean-variance analysis by incorporating comprehensive uncertainty quantification. Create a probabilistic model that can dynamically assess asset allocation strategies considering multiple risk dimensions, including tail risk, correlation instability, and macroeconomic scenario dependencies. Implement Monte Carlo simulation techniques with advanced resampling methods to generate robust, adaptive investment recommendations.