The Role of AI Recommendations in Extending the Black-Litterman Portfolio

This study explores the role of AI recommendations in portfolio optimization by extending the Black-Litterman (BL) model using consensus analyst opinions generated by ChatGPT. The aim is to assess if AI recommendations can improve portfolio diversification and risk-adjusted returns compared to traditional investment strategies.
We conducted a quantitative analysis using weekly historical price data across equities, commodities, fixed-income securities, and cryptocurrencies from January 2018 to May 2024. Portfolios constructed with the extended BL model were tested against standard benchmarks, including the S&P500 index and various mean-variance portfolios. Out-of-sample performance and robustness were evaluated through 100 random resampling procedures.
Results indicate that integrating AI-generated analyst consensus significantly improves the BL portfolio’s risk-adjusted returns. The AI-enhanced model consistently outperformed traditional mean-variance portfolios, the unadjusted BL model, and market benchmarks. Robustness tests confirmed the method’s stability and practical feasibility in real-world investing.