tvgarch (version 2.4.3)

coef.tvgarchTest: Extraction functions for univarate 'tvgarchTest' objects

Description

Extraction functions for objects of class 'tvgarchTest'. Results from the estimation of the model under the null hypothesis, i.e., a GARCH(1,1) model, can be extracted similar to an object of class 'tvgarch' with the exception of functions print.tvgarchTest() and summary.tvgarchTest().

Usage

# S3 method for tvgarchTest
coef(object, ...)
  # S3 method for tvgarchTest
fitted(object, 
  as.zoo = TRUE, ...)
  # S3 method for tvgarchTest
logLik(object, ...)
  # S3 method for tvgarchTest
nobs(object, ...)
  # S3 method for tvgarchTest
plot(x, ...)                           
  # S3 method for tvgarchTest
predict(object, n.ahead = 10, newxreg = NULL, 
                                 newindex = NULL, n.sim = 5000,
                                 as.zoo = TRUE, verbose = FALSE, ...)
  # S3 method for tvgarchTest
print(x, ...)
  # S3 method for tvgarchTest
quantile(x, probs = 0.025, names = TRUE, type = 7, 
                                  as.zoo = TRUE, ...)
  # S3 method for tvgarchTest
residuals(object, as.zoo = TRUE, ...)
  # S3 method for tvgarchTest
summary(object, ...)
  # S3 method for tvgarchTest
toLatex(object, digits = 4, ...)
  # S3 method for tvgarchTest
vcov(object, ...)

Value

coef:

parameter estimates.

fitted:

fitted conditional variance.

logLik:

optimised log-likelihood (normal density) value.

nobs:

the number of observations used in the estimation.

plot:

plot of the fitted conditional volatility.

predict:

variance predictions.

quantile:

fitted quantiles, i.e. the conditional standard deviation times the empirical quantile of the standardised innovations.

residuals:

volatility standardised residuals.

summary:

summary of test result.

vcov:

coefficient variance-covariance matrix.

Arguments

object

an object of class 'tvgarchTest'.

x

an object of class 'tvgarchTest'.

as.zoo

logical. If TRUE, then the returned result is of class zoo.

n.ahead

integer that determines how many steps ahead predictions should be generated.

newxreg

vector or matrix with the out-of-sample regressor values.

newindex

a zoo-index for the out-of-sample predictions. If NULL (default), then 1:n.ahead is used.

n.sim

integer, the number of simulations.

verbose

logical. If TRUE, then the simulations - in addition to the predictions - are returned.

probs

vector of probabilities.

names

logical, whether to return names or not.

type

integer that determines the algorithm used to compute the quantile, see quantile.

digits

integer, the number of digits in the printed LaTeX code.

...

additional arguments.

Author

Susana Campos-Martins

References

Cristina Amado and Timo Terasvirta (2013) Modelling volatility by variance decomposition, Journal of Econometrics 175, 142-153.

Cristina Amado and Timo Terasvirta (2014) Modelling changes in the unconditional variance of long stock return series, Journal of Empirical Finance 25, 15-35.

Susana Campos-Martins and Genaro Sucarrat (2024) Modeling Nonstationary Financial Volatility with the R Package tvgarch, Journal of Statistical Software 108, 1-38.

See Also

tvgarchTest, tvgarchSim, tvgarch, zoo

Examples

set.seed(123)

## Simulate from a TV(1)-GARCH(1,1) model (default):
ySim <- tvgarchSim(n = 1500)

## Test a GARCH(1,1) model against a TV(1)-GARCH(1,1) model:
yTest <- tvgarchTest(y = ySim)

## Print test and estimation results:
print(yTest)

## Estimated number of locations
summary(yTest)

## Extract and plot estimation results for GARCH(1,1) used in the test:
sigma2Test <- fitted(yTest)
plot(yTest)

## Estimate a TV(s)-GARCH(1,1) model:
s <- summary(yTest)
yEst <- tvgarch(y = ySim, order.g  = s)