Nothing

```
## factorModelCovariance.r
##
## purpose: compute covariance matrix from estimated factor model
## author: Eric Zivot
## created: November 25, 2008
## revised: July 20, 2009
factorModelCovariance <- function(beta.mat, factor.cov, sig.e) {
## Inputs:
## beta.mat n x k matrix of factor betas
## factor.cov k x k factor excess return covariance matrix
## sig.e n x 1 vector of residual variances from factor model
## Output:
## cov.fm n x n excess return covariance matrix based on
## estimated factor model
beta.mat = as.matrix(beta.mat)
factor.cov = as.matrix(factor.cov)
sig.e = as.vector(sig.e)
if (length(sig.e) > 1) {
D.e = diag(as.vector(sig.e))
} else {
D.e = as.matrix(sig.e)
}
if (ncol(beta.mat) != ncol(factor.cov))
stop("beta.mat and factor.cov must have same number of columns")
if (nrow(D.e) != nrow(beta.mat))
stop("beta.mat and D.e must have same number of rows")
cov.fm = beta.mat %*% factor.cov %*% t(beta.mat) + D.e
if (any(diag(chol(cov.fm)) == 0))
warning("Covariance matrix is not positive definite")
return(cov.fm)
}
```

**Any scripts or data that you put into this service are public.**

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.