PCAVaR function

Estimates VaR by principal components analysis

Estimates the VaR 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.

PCAVaR(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

Returns

VaR

Examples

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

Author(s)

Dinesh Acharya

References

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