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The Black-Litterman model has gained popularity in applications in the area of quantitative equity portfolio management. Unfortunately, many recent applications of the Black-Litterman to novel aspects of quantitative portfolio management have neglected the rigor of the original Black-Litterman modelling. In this article, we critically examine some of these applications from a Bayesian perspective. We identify three reasons why these applications may create losses to investors. These three reasons are: (1) Using a prior without "anchoring" the prior to an equilibrium model, (2) Using a prior and an equilibrium model that conflict with one another, and (3) Ignoring the implications of the estimation error of the variance-covariance matrix. We also quantify the loss first analytically, and also numerically based on historical data on 10 major world stock market indices. Our conservative estimate of the loss is around a 1% reduction in the annualized return of the portfolio.


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