estimate.tsgarch.spec {tsgarch}

Estimates an GARCH model given a specification object using maximum likelihood and autodiff

Description

Estimates an GARCH model given a specification object using maximum likelihood and autodiff

Usage

## S3 method for class 'tsgarch.spec'
estimate(
  object,
  solver = "nloptr",
  control = NULL,
  stationarity_constraint = 0.999,
  ...
)

Arguments

object

an object of class tsgarch.spec.

solver

only “nloptr” is currently supported (see nloptr).

control

solver control parameters.

stationarity_constraint

the bound on the inequality constraint for ensuring the stationary of the GARCH process (see details).

...

not currently used.

Details

The underlying code is written using the TMB framework which uses automatic differentiation and hence allows the generation of analytic derivatives. Stationarity is usually based on the condition that the persistence of the model is less than 1. The argument “stationarity_constraint” allows to fine tune this. For example, setting it to a very high value will effectively render this constraint inactive. The default of 0.999 has been found to be a reasonable bound since values close to one may lead to problems. Since the nloptr solver make use of analytic Jacobians for the inequality constraint, these are either provided in closed form or calculated as part of the automatic differentiation algorithms implemented in the package. The estimation makes 2 passes to the solver. The first pass uses no parameter scaling, whilst in the second pass the parameters (as well as bounds) are scaled making use of the estimated hessian from the first pass in order to generate a hopefully more robust solution.

Value

An object of class “tsgarch.estimate”.

Author(s)

Alexios Galanos