LogNormalVaRDFPerc {Dowd} | R Documentation |

## 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)
```

*Dowd*version 0.12 Index]