hs: Nonparametric calculation of univariate Value at Risk and...

In quarks: Simple Methods for Calculating and Backtesting Value at Risk and Expected Shortfall

Nonparametric calculation of univariate Value at Risk and Expected Shortfall

Description

Computes Value at Risk and Expected Shortfall (Conditional Value at Risk) by means of plain and age-weighted historical simulation.

Usage

hs(x, p = 0.975, method = c("age", "plain"), lambda = 0.98)

Arguments

x	a numeric vector of asset returns
p	confidence level for VaR calculation; default is 0.975
method	method to be used for calculation; default is 'plain'
lambda	decay factor for the calculation of weights; default is 0.98

Value

Returns a list with the following elements:

VaR

Calculated Value at Risk

ES

Calculated Expected Shortfall (Conditional Value at Risk)

p

Confidence level for VaR calculation

Examples

prices <- DAX$price_close
returns <- diff(log(prices))
hs(x = returns, p = 0.975, method = 'plain')
hs(x = returns, p = 0.975, method = 'age', lambda = 0.98)

quarks documentation built on June 22, 2024, 10:03 a.m.