black.litterman

Compute the Black Litterman estimate of moments for the posterior normal.

Portfolio optimization and analysis routines and graphics.

Brian G Peterson

PortfolioAnalytics

Portfolio Analysis, Including Numerical Methods for Optimization
of Portfolios

Peter Carl

Ross Bennett

Kris Boudt

Xinran Zhao

R. Douglas Martin

Guy Yollin

Hezky Varon

Xiaokang Feng

Yifu Kang

black.litterman function

<dl><dt>R</dt>
<dd>returns</dd>
<dt>P</dt>
<dd>a K x N pick matrix</dd>
<dt>Mu</dt>
<dd>vector of length N of the prior expected values. The sample mean
is used if <code>Mu=NULL</code>.</dd>
<dt>Sigma</dt>
<dd>an N x N matrix of the prior covariance matrix. The sample 
covariance is used if <code>Sigma=NULL</code>.</dd>
<dt>Views</dt>
<dd>a vector of length K of the views</dd></dl>

Arguments

Author

Black Litterman Estimates — black.litterman

<dl>

<dt>R</dt>
<dd>returns</dd>


<dt>P</dt>
<dd>a K x N pick matrix</dd>


<dt>Mu</dt>
<dd>vector of length N of the prior expected values. The sample mean
is used if <code>Mu=NULL</code>.</dd>


<dt>Sigma</dt>
<dd>an N x N matrix of the prior covariance matrix. The sample 
covariance is used if <code>Sigma=NULL</code>.</dd>


<dt>Views</dt>
<dd>a vector of length K of the views</dd>

</dl>

Black Litterman Estimates

black.litterman: Black Litterman Estimates

Description

Usage

Value

Arguments

Author

References

See Also