PCAVaRPlot: VaR plot

In Dowd: Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's Book Measuring Market Risk

Description

Estimates VaR plot using principal components analysis

Usage

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

Author(s)

Dinesh Acharya

References

Dowd, K. Measuring Market Risk, Wiley, 2007.

Examples

# Computes PCA VaR
   Ra <- matrix(rnorm(15*20),15,20)
   position.data <- rnorm(20)
   PCAVaRPlot(Ra, position.data)

Dowd documentation built on May 2, 2019, 6:15 p.m.