Dowd (version 0.12)

tESDFPerc: Percentiles of ES distribution function for t-distributed P/L

Description

Estimates percentiles of ES distribution function for t-distributed P/L, using the theory of order statistics

Usage

tESDFPerc(...)

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 assumed sampel size of data is computed from return 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

df Degrees of freedom

perc Desired percentile

df Number of degrees of freedom in the t distribution

cl ES confidence level and must be a scalar

hp ES holding period and must be a a scalar

Value

Percentiles of ES distribution function

References

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

Examples

# Estimates Percentiles of ES distribution given P/L data
   data <- runif(5, min = 0, max = .2)
   tESDFPerc(returns = data, perc = .7, df = 6, cl = .95, hp = 60)

   # Estimates Percentiles of ES distribution given mean, std. deviation and sample size
   tESDFPerc(mu = .012, sigma = .03, n= 10, perc = .8, df = 6, cl = .99, hp = 40)