If the variance of two correlated variables is: $$Var(r_1+r_2)=\sigma^2_1+\sigma^2_2+2\textrm{cov}(r_1,r_2)=\sigma^2_1+\sigma^2_2+2\rho\sigma_1\sigma_2$$ where $r_1$ and $r_2$ are vectors, then what is the multivariate representation of this.
So, if $R_1$ and $R_2$ both denote a matrix we get $$Var(R_1+R_2)=\Sigma_1+\Sigma_2+…$$ where $\Sigma_i$ denotes the covariance matrix for $R_i$.
Anyone knows how to fill in the dots?
Best Answer
$R_1$ and $R_2$ should be vectors.
Then $Var(R_1+R_2)=\Sigma_1+\Sigma_2+2\rho_{12}\sqrt{\Sigma_1} \sqrt{ \Sigma_2}$
where $\Sigma_i$ denotes the variance matrix of $R_1$ and $R_2$ respectively.