addBLViews: Create or add to a BLViews object
In BLCOP: Black-Litterman and Copula Opinion Pooling Frameworks

Description Usage Arguments Value Author(s) See Also Examples

BLViews and COPViews are "constructors" for BLViews and COPViews objects respectively. addBLViews and addCOPViews allow one to easily add more views to a pre-existing views objects. newPMatrix is a utility function for creating pick matrices.

	
addBLViews(pickMatrix, q, confidences, views)
addCOPViews(pickMatrix, viewDist, confidences, views) 
BLViews(P, q, confidences, assetNames)
COPViews(pickMatrix, viewDist, confidences, assetNames) 
newPMatrix(assetNames, numViews, defaultValue = 0)

`P`	"Pick" matrix with columns named after assets to which views correspond
`pickMatrix`	"Pick" matrix with columns named after assets to which views correspond
`q`	"q" vector of views
`confidences`	Vector of confidences in views. Note that confidences are recipricols of standard deviations
`viewDist`	A list of marginal distributions of the views
`views`	A BLViews object
`assetNames`	Names of the assets in the universe
`numViews`	Number of views in the pick matrix
`defaultValue`	Default value to use to fill the new pick matrix

A BLViews or COPViews class object as appropriate. newPMatrix creates a matrix.

Francisco Gochez

createBLViews, updateBLViews

    ### example from T. M. Idzorek's paper "A STEP-BY-STEP GUIDE TO THE 
	### BLACK-LITTERMAN MODEL"
 	## Not run: 
	    pick <- newPMatrix(letters[1:8], 3)
	    pick[1,7] <- 1
	    pick[2,1] <- -1 
	    pick[2,2] <- 1
	    pick[3, 3:6] <- c(0.9, -0.9, .1, -.1)
	    confidences <- 1 / c(0.00709, 0.000141, 0.000866)
	    myViews <- BLViews(pick, q = c(0.0525, 0.0025, 0.02), confidences, letters[1:8])
	    myViews
	    
	    ### Modified COP example from Meucci's "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 <- newPMatrix(c("SP", "FTSE", "CAC", "DAX"), 1)
	    pick[1,4] <- 1
	    vdist <- list(distribution("unif", min = -0.02, max = 0))
	    views <- COPViews(pick, vdist, 0.2, c("SP", "FTSE", "CAC", "DAX"))
    
## End(Not run)