## Prior distribution ## Fitting of skewed Student's t distribution MSTfit <- mvFit(R, method = "st") mu <- c(MSTfit@fit$estimated[["beta"]]) S <- MSTfit@fit$estimated[["Omega"]] skew <- c(MSTfit@fit$estimated[["alpha"]]) df <- MSTfit@fit$estimated[["nu"]] CopPrior <- mvdistribution("mvst", dim = NAssets, mu = mu, Omega = S, alpha = skew, df = df) ## Pick matrix and view distributions for last forecast RetEstCop <- ReturnEst[[27]] RetEstCop PCop <- matrix(0, ncol = NAssets, nrow = 3) colnames(PCop) <- ANames PCop[1, ANames[1]] <- 1 PCop[2, ANames[2]] <- 1 PCop[3, ANames[4]] <- 1 Sds <- apply(R, 2, sd) RetViews <- list(distribution("norm", mean = RetEstCop[1], sd = Sds[1]), distribution("norm", mean = RetEstCop[2], sd = Sds[2]), distribution("norm", mean = RetEstCop[4], sd = Sds[4]) ) CopViews <- COPViews(pick = PCop, viewDist = RetViews, confidences = rep(0.5, 3), assetNames = ANames) ## Simulation of posterior NumSim <- 10000 CopPost <- COPPosterior(CopPrior, CopViews, numSimulations = NumSim) slotNames(CopPost)