A Step-By-Step Guide to the Black-Litterman Model Incorporating User-specified Confidence Levels

Publisher Summary This chapter focuses on the insights of the Black–Litterman model and provides step-by-step instructions for implementation of the complex model. It details the process of developing the inputs for the Black–Litterman model, which enables investors to combine their unique views regarding the performance of various assets with the market equilibrium for generation of a new vector of expected returns. The new combined return vector leads to intuitive, well-diversified portfolios. The two parameters of the Black–Litterman model that control the relative importance placed on the equilibrium returns versus the view returns, the scalar and the uncertainty in the views, are very difficult to specify. The Black–Litterman formula with hundred percent certainty in the views enables determination of the implied confidence in a view. Using this implied confidence framework, a new method for controlling the tilts and the final portfolio weights caused by the views is introduced. The method asserts that the magnitude of the tilts should be controlled by the user- specified confidence level based on an intuitive zero percent to hundred percent confidence level. Overall, the Black–Litterman model overcomes the most-often cited weaknesses of mean-variance optimization helping users to realize the benefits of the Markowitz paradigm. Likewise, the proposed new method for incorporating user-specified confidence levels should increase the intuitiveness and the usability of the Black–Litterman model.

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