VaR plot

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Description

Estimates VaR plot using principal components analysis

Usage

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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

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

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