Estimates VaR plot using principal components analysis
PCAVaRPlot(Ra, position.data)
Arguments
Ra: Matrix return data set where each row is interpreted as a set of daily observations, and each column as the returns to each position in a portfolio
position.data: Position-size vector, giving amount invested in each position
Examples
# Computes PCA VaR Ra <- matrix(rnorm(15*20),15,20) position.data <- rnorm(20) PCAVaRPlot(Ra, position.data)