PCAES: Estimates ES by principal components analysis

Description Usage Arguments Value Author(s) References Examples

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

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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

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# 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.