Description Usage Arguments Author(s) References Examples

View source: R/LogtVaRDFPerc.R

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

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`...` |
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 |

Dinesh Acharya

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

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# 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)
``` |

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