PCAES: Estimates ES by principal components analysis

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

Description

Estimates the ES of a multi position portfolio by principal components analysis, using chosen number of principal components and a specified confidence level or range of confidence levels.

Usage

PCAES(Ra, position.data, number.of.principal.components, cl)

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
number.of.principal.components	Chosen number of principal components
cl	Chosen confidence level

Value

ES

Author(s)

Dinesh Acharya

References

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

Examples

# Computes PCA ES
   Ra <- matrix(rnorm(4*6),4,6)
   position.data <- rnorm(6)
   PCAES(Ra, position.data, 2, .95)

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