LogtVaRDFPerc: Percentiles of VaR distribution function for Student-t

Description Usage Arguments Author(s) References Examples

View source: R/LogtVaRDFPerc.R

Description

Plots the VaR of a portfolio against confidence level assuming that geometric returns are Student t distributed, for specified confidence level and holding period.

Usage

1

Arguments

...

The input arguments contain either return data or else mean and standard deviation data. Accordingly, number of input arguments is either 6 or 8. In case there 6 input arguments, the mean, standard deviation and number of observations of the 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

investment Size of investment

perc Desired percentile

df Number of degrees of freedom in the t distribution

cl VaR confidence level and must be a scalar

hp VaR holding period and must be a a scalar

Percentiles of VaR distribution function

Author(s)

Dinesh Acharya

References

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

Examples

1
2
3
4
5
6
7
8
# Estimates Percentiles of VaR distribution
   data <- runif(5, min = 0, max = .2)
   LogtVaRDFPerc(returns = data, investment = 5, perc = .7,
                 df = 6, cl = .95, hp = 60)

   # Computes v given mean and standard deviation of return data
   LogtVaRDFPerc(mu = .012, sigma = .03, n= 10, investment = 5,
                 perc = .8, df = 6, cl = .99, hp = 40)

Dowd documentation built on May 30, 2017, 1:30 a.m.