Percentiles of ES distribution function for Student-t

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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

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Arguments

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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 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

Author(s)

Dinesh Acharya

References

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

Examples

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# 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)

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