BLCOP (version 0.3.3)

Build Views: Create or add to a BLViews object

Description

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.

Usage

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)

Arguments

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

Value

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

See Also

createBLViews, updateBLViews

Examples

# NOT RUN {
    ### 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 <!-- %*% caps -->
	    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"))
    
# }