So far we have treated the sample mean vector and covariance matrix as fixed when considering the risk of a portfolio. Stated differently, estimation risk has been ignored. A methodology for taking...

So far we have treated the sample mean vector and covariance matrix as fixed when considering the risk of a portfolio. Stated differently, estimation risk has been ignored. A methodology for taking risk due to estimation error into account was proposed by Greyserman, Jones, and Strawderman (2006). Assume that the vector of returns R is N(μ, Σ) distributed. Let (μ(k) , Σ(k) ), k = 1,...,K, be an MCMC sample from the posterior distribution of (μ, Σ). For each k, let R(k) be N(μ(k) , Σ(k) ) distributed. Then