# LogtVaRPlot2DCL: Plots log-t VaR against confidence level In Dowd: Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's Book Measuring Market Risk

## 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` ```LogtVaRPlot2DCL(...) ```

## Arguments

 `...` The input arguments contain either return data or else mean and standard deviation data. Accordingly, number of input arguments is either 5 or 6. In case there 5 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 investment Size of investment df Number of degrees of freedom in the t distribution cl VaR confidence level and must be a vector hp VaR holding period and must be a scalar

Dinesh Acharya

## References

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

## Examples

 ```1 2 3 4 5 6``` ```# Plots VaR against confidene level given geometric return data data <- runif(5, min = 0, max = .2) LogtVaRPlot2DCL(returns = data, investment = 5, df = 6, cl = seq(.85,.99,.01), hp = 60) # Computes VaR against confidence level given mean and standard deviation of return data LogtVaRPlot2DCL(mu = .012, sigma = .03, investment = 5, df = 6, cl = seq(.85,.99,.01), hp = 40) ```

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