Portfolio Optimization Based on Transformer-GAN Enhanced Black–Litterman Framework for Quantitative Analysis
A Transformer-GAN enhanced Black–Litterman framework that integrates temporal representation learning, uncertainty-aware scenario generation, and Bayesian portfolio optimization is proposed that improves risk-adjusted portfolio performance while maintaining robustness against market uncertainty.