observ_normal: Example of distribution of views - normal distribution

In BLModel: Black-Litterman Posterior Distribution

Description

Function observ_normal computes density of normal distribution of views using the formula
f(x) = c_k*\exp(-((x-q)^{T}*covmat^{-1}*(x-q))/2),
where c_k is a normalization constant (depends on the dimension of x and q).

Usage

observ_normal(x, q, covmat)

Arguments

x	Data points matrix which collects in rows coordinates of points in which distribution density is computed.
q	Vector of investor's views.
covmat	Covariance matrix of the distribution.

Value

function returns a vector of distribution densities in data points x.

References

Palczewski, J., Palczewski, A., Black-Litterman Model for Continuous Distributions (2016). Available at SSRN: https://ssrn.com/abstract=2744621.

Examples

k =3
observ_normal (x = matrix(c(rep(0.5,k),rep(0.2,k)),k,2), q = matrix(0,k,1), 
               covmat = diag(k)) 

BLModel documentation built on May 2, 2019, 5:11 a.m.