blacklitterman.org

Comparison of Author's Methods

Headlines

MATLAB and SciLAB implementations of the model

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My paper on the Black-Litterman Model (Updated 16 February 2009)

An applet which implements the Black-Litterman model

The table below attempts to summarize some of the differences between the various authors on several dimensions where the author's tend to disagree.

Author(s) τ View Uncertainty Posterior Variance
Fuasi and Meucci Ignores (1) αPΣP, α ≥ 1 Use prior variance
He and Litterman Close to 0 diag(τPΣP) Updated
Idzorek Close to 0 Specified as % Use prior variance
Satchell and Scowcroft Usually 1 ? Use prior variance

Description of the various attributes in the table

τ  -  The authors either expect that τ = 1, or else it is a small number. In general an investor will have τ << 1 if they are going to update the variamce, and will use τ = 1 if they are not going to update the variance. Some authors (not included in the references on this site) also discuss using values of τ > 1. Given what τ&SIGMA; represents (uncertainty in our estimate of the mean) and the fact that τ greater than 1 does not make sense in this context, I've not added those views to the table. See or my paper for further information

View Uncertainty - The authors use various expressions to specify the uncertainty of the views. Fusasi and Meucci specify that the uncertainty of the views will be a multiple of the uncertainty of the prior distribution. He and Litterman specify the view uncertainty as a diagonal matrix, with on-diagonal elements equal to the uncertainty of the prior distribution.

Posterior Variance - The authors either update the variance based on the variance of the posterior distribution, or else they just use the prior variance of returns.

For a more thorough discussion see my paper on the Black-Litterman model.

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