leoncuhk/awesome-quant-ai

Organizes resources across ML/AI techniques (supervised learning for return forecasting, reinforcement learning for execution optimization, generative models for stress-testing) and quantitative finance theory (stochastic processes, mean-CVaR optimization, factor analysis). Provides a structured design methodology covering alpha research, rigorous backtesting with transaction cost modeling, and portfolio risk management, alongside categorized tools, papers, and emerging topics like LLM-based sentiment extraction and multimodal market analysis.

178 stars.