Global Portfolio Optiomization Revisted: A Least Discrimination Alternative to Black-Litterman

Global portfolio optimization models rank among the proudest achievements of modern finance theory, but practitioners are still struggling to put them to work. In 1992, Black and Litterman put the problem down to difficulties portfolio managers have in extrapolating views about some expected asset returns into full probabilistic forecasts about all asset returns and proposed a method to alleviate this problem. We propose a more general method based on a least discrimination (LD) principle. It produces a probabilistic forecast that remains true to personal views but is otherwise as close as possible to the forecast implied by a reference portfolio. The LD method produces optimal portfolios for a variety of views, including views on volatility and correlation, in which case optimal portfolios include option-like pay-offs. It also justifies a simple linear interpolation between market and personal forecasts, should a compromise be reached.