fExtremes

Rmetrics - Modelling Extreme Events in Finance

The fExtremes package provides functions for analysing and modelling extreme events in financial time Series. The topics include: (i) data pre-processing, (ii) explorative data analysis, (iii) peak over threshold modelling, (iv) block maxima modelling, (v) estimation of VaR and CVaR, and (vi) the computation of the extreme index. It is part of the Rmetrics software project.

An example

The following code simulates data from a GEV distribution, fits a GEV distribution to these data and creates model diagnostic plots.

library(fExtremes)
# Simulate GEV Data, use default length n=1000
x <- gevSim(model = list(xi = 0.25, mu = 0 , beta = 1), n = 1000)

# Fit GEV data using maximum likelihood estimation
fit <- gevFit(x, type = "mle") 
fit
#> 
#> Title:
#>  GEV Parameter Estimation 
#> 
#> Call:
#>  gevFit(x = x, type = "mle")
#> 
#> Estimation Type:
#>   gev mle 
#> 
#> Estimated Parameters:
#>         xi         mu       beta 
#> 0.18304217 0.04548892 0.99014748 
#> 
#> Description
#>   Fri Aug  5 17:30:44 2022

Installation

To get the current released version from CRAN:

install.packages("fExtremes")