LogNormalVaRDFPerc {Dowd}

Percentiles of VaR distribution function for normally distributed geometric returns

Description

Estimates the percentile of VaR distribution function for normally distributed geometric returns, using the theory of order statistics.

Usage

LogNormalVaRDFPerc(...)

Arguments

...

The input arguments contain either return data or else mean and standard deviation data. Accordingly, number of input arguments is either 5 or 7. In case there 5 input arguments, the mean, standard deviation and number of observations of data are computed from returns data. See examples for details.

returns Vector of daily geometric return data

mu Mean of daily geometric return data

sigma Standard deviation of daily geometric return data

n Sample size

investment Size of investment

perc Desired percentile

cl VaR confidence level and must be a scalar

hp VaR holding period and must be a a scalar

Percentiles of VaR distribution function and is scalar

Author(s)

Dinesh Acharya

References

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

Examples

# Estimates Percentiles of VaR distribution
   data <- runif(5, min = 0, max = .2)
   LogNormalVaRDFPerc(returns = data, investment = 5, perc = .7, cl = .95, hp = 60)

   # Computes v given mean and standard deviation of return data
   LogNormalVaRDFPerc(mu = .012, sigma = .03, n= 10, investment = 5, perc = .8, cl = .99, hp = 40)