igarchFit#

Purpose#

Estimates integrated GARCH model, i.e., a model containing a unit root.

out1 = igarchFit(y, p[, c0])#

out1 = igarchFit(y, p[, q, c0])

out1 = igarchFit(dataset, formula, p[, c0])

out1 = igarchFit(dataset, formula, p[, q, c0])

Parameters:

y (Matrix) – dependent variables.
x (Matrix) – independent variables.
dataset (string) – name of data set or null string.
formula (string) – formula string of the model. E.g. “y ~ X1 + X2” ‘y’ is the name of dependent variable, ‘X1’ and ‘X2’ are names of independent variables; E.g. “y ~ .” , ‘.’ means including all variables except dependent variable ‘y’;
p (scalar) – order of the GARCH parameters.
q (scalar) – Optional input, order of the ARCH parameters.

c0 (struct) –

Optional input, garchControl structure.

c0.density	scalar, density of error term: 0 - Normal 1 - Student’s t 3 - skew generalized t.
c0.asymmetry	scalar, if nonzero assymetry terms are added.
c0.inmean	scalar, GARCH-in-mean, square root of conditional variance is included in the mean equation.
c0.stConstraintsType	scalar, type of enforcement of stationarity requirements: 1 - roots of characteristic polynomial constrained outside unit circle 2 - arch, GARCH parameters constrained to sum to less than one and greater than zero 3 - none.
c0.cvConstraintsType	scalar, type of enforcement of nonnegative conditional variances: 0 - direct constraints 1 - Nelson & Cao constraints.
c0.covType	scalar, type of covariance matrix of parameters: 1 - ML 2 - QML 3 - none.

Returns:

out1 (struct) –

garchEstimation structure.

out1.aic	scalar, Akiake criterion.
out1.bic	scalar, Bayesian information criterion.
out1.lrs	scalar, likelihood ratio statistic.
out1.numObs	scalar, number of observations.
out1.df	scalar, degrees of freedom.
out1.par	instance of PV structure containing parameter estimates.
out1.retcode	scalar, return code. out1.moment KxK matrix, moment m?atrix of parameter estimates. 1: normal convergence. 2: forced exit. 3: function calculation failed. 4: gradient calculation failed. 5: Hessian calculation failed. 6: line search failed. 7: error with constraints. 8: function complex.
out1.moment	KxK matrix, moment matrix of parameter estimates.
out1.climits	Kx2 matrix, confidence limits.

new;
cls;
library tsmt;

y = loadd( getGAUSSHome() $+ "pkgs/tsmt/examples/igarch.dat");

struct garchEstimation f0;
f0 = igarchFit(y, 1, 1);

tsmt

tsgarch.src