Big Data and AI

  In the ever-evolving world of portfolio management, the classic Mean-Variance Optimization (MVO) model developed by Harry Markowitz laid the foundation for constructing efficient portfolios. But despite its elegance, MVO suffers from serious flaws— instability, unintuitive asset weights, and extreme sensitivity to input assumptions. Enter the Black-Litterman Model , developed in 1990 by Fischer Black and Robert Litterman of Goldman Sachs. This model elegantly blends market equilibrium with investor views, solving many of the practical issues inherent in traditional MVO.  What Is the Black-Litterman Model? The Black-Litterman Model (BLM) is a Bayesian approach to portfolio optimization that combines a prior (the market equilibrium) with subjective views to generate more robust, stable expected returns and asset weights. Rather than relying solely on historical data or volatile forecasts, the BLM starts from the implied returns of the market (reverse-optimized) an...