An asset manager might add, to this assessment, parts of the portfolio theory. Today, in the financial markets, stock analysts usually look for “fundamentals” and then try to assess potential growth.
Furthermore, after explaining the pitfalls of the traditional Minimum-Variance optimization and providing a review of the BL framework, both theoretical and empirical results are provided in order to show how one can go from the original BL setting to the one that includes active management. These resulting active portfolios reflect the real investment insights given by the investors.
Black litterman model excel without vba portable#
Thus, focusing on the mismatch between the Sharpe ratio (SR) optimization used in the initial BL framework and the information ratio (IR) optimization that constitutes the goal of the active management, they propose a solution to fix this problem that leads to portable alpha implementation of active portfolios. Moreover, Silva, Lee and Pornrojnangkool (2009) give special attention to the fact that the straight application of the BL framework in active investment management can lead to unintended trades and risk taking, which leads to a riskier portfolio than desired. Finally, this paper adds to the previous literature the introduction of some risk management tools to assess the benefits of using the BL model in an active management setting, by adapting the method developed by Fusai and Meucci (2003). Maggiar also discusses one of the crucial points of the BL model- the covariance matrix, as previously mentioned- by presenting a “state-dependent model to try to more accurately capture the expected covariance matrix”. Over the allocation methods, the model still suffers from some constraints, namely the assumptions on the distribution of the returns, the parameters that one needs to specify and the imposed linearity of the expression of the views are all factors which limit its optimal use.
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