COPPosterior {BLCOP} | R Documentation |
COPPosteior
uses Attilio Meucci's copula opinion pooling method to incorporate an analyst's subjective
views with a prior "official" market distribution. Both the views and the market may have an arbitrary distribution
as long as it can be sampled in R.
Calculations are done with monte-carlo simulation, and the object returned will hold samples drawn from the market
posterior distribution.
COPPosterior(marketDist, views, numSimulations = BLCOPOptions("numSimulations"))
marketDist |
An object of class mvdistribution which describes the prior "official" distribution of the market. |
views |
An object of class COPViews which describe the subjective views on the market distribution |
numSimulations |
The number of monte carlo samples to draw during calculations. Each asset in one's universe will have numSimulations samples from the posterior. |
An object of class COPResult.
Francisco Gochez <fgochez@mango-solutions.com>
Attilio Meucci, "Beyond Black-Litterman:Views on Non-normal Markets". See also Attilio Meucci, "Beyond Black-Litterman in Practice: a Five-Step Recipe to Input Views on non-Normal Markets."
## Not run: # An example based on one found in "Beyond Black-Litterman:Views on Non-normal Markets" dispersion <- c(.376,.253,.360,.333,.360,.600,.397,.396,.578,.775) / 1000 sigma <- BLCOP:::.symmetricMatrix(dispersion, dim = 4) caps <- rep(1/4, 4) mu <- 2.5 * sigma dim(mu) <- NULL marketDistribution <- mvdistribution("mt", mean = mu, S = sigma, df = 5 ) pick <- matrix(0, ncol = 4, nrow = 1, dimnames = list(NULL, c("SP", "FTSE", "CAC", "DAX"))) pick[1,4] <- 1 vdist <- list(distribution("unif", min = -0.02, max = 0)) views <- COPViews(pick, vdist, 0.2, c("SP", "FTSE", "CAC", "DAX")) posterior <- COPPosterior(marketDistribution, views) ## End(Not run)