# LogtESDFPerc: Percentiles of ES distribution function for Student-t In Dowd: Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's Book Measuring Market Risk

## Description

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

## Usage

 `1` ```LogtESDFPerc(...) ```

## 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 and standard deviation 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 investment Size of investment 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

Dinesh Acharya

## References

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

## Examples

 ```1 2 3 4 5 6``` ```# Estimates Percentiles of ES distribution data <- runif(5, min = 0, max = .2) LogtESDFPerc(returns = data, investment = 5, perc = .7, df = 6, cl = .95, hp = 60) # Computes v given mean and standard deviation of return data LogtESDFPerc(mu = .012, sigma = .03, n= 10, investment = 5, perc = .8, df = 6, cl = .99, hp = 40) ```

Dowd documentation built on May 31, 2017, 4:46 a.m.