tsgarch1.0.3 package

Univariate GARCH Models

AIC

Akaike's An Information Criterion

as_flextable.benchmark

Transform an object into flextable

as_flextable.summary

Transform a summary object into flextable

benchmark_fcp

FCP GARCH Benchmark

benchmark_laurent

Laurent APARCH Benchmark

BIC

Bayesian Information Criterion

bread

Bread Method

coef

Extract Model Coefficients

confint

Confidence Intervals for Model Parameters

estfun

Score Method

pit

Probability Integral Transform (PIT)

plot

News Impact Plot

plot.tsgarch.estimate

Estimated Model Plots

plus-.tsgarch.spec

Combine univariate GARCH specifications into a multi-specification obj...

predict

Model Prediction

print

Model Estimation Summary Print method

print.summary.tsgarch.profile

Profile Summary Print method

reexports

Objects exported from other packages

residuals

Extract Model Residuals

sigma

Extract Volatility (Conditional Standard Deviation)

nobs

Extract the Number of Observations

omega

Omega (Variance Equation Intercept)

persistence

Model Persistence

estimate

Estimates an GARCH model given a specification object using maximum li...

fitted

Extract Model Fitted Values

garch_modelspec

GARCH Model Specification

halflife

Half Life

logLik

Extract Log-Likelihood

newsimpact

News Impact Curve

nloptr_options

Default options for nloptr solver

simulate

Model Simulation

summary

GARCH Model Estimation Summary

summary.tsgarch.profile

GARCH Profile Summary

to_multi_estimate

Convert a list of tsgarch.estimate objects to a multi_estimate object

tsbacktest

Walk Forward Rolling Backtest

tsequation

Model Equation (LaTeX)

tsfilter

Model Filtering

tsgarch-package

tsgarch: Univariate GARCH Models

tsprofile

Model Parameter Profiling

unconditional

Unconditional Value

vcov

The Covariance Matrix of the Estimated Parameters

Multiple flavors of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model with a large choice of conditional distributions. Methods for specification, estimation, prediction, filtering, simulation, statistical testing and more. Represents a partial re-write and re-think of 'rugarch', making use of automatic differentiation for estimation.

  • Maintainer: Alexios Galanos
  • License: GPL-2
  • Last published: 2024-10-12