garchGJRFit#
Purpose#
Estimates asymmetric GJR-GARCH model.
Library#
tsmt
Format#
- out1 = garchGJRFit(y, p [, q, c0]);
- out1 = garchGJRFit(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 –
Optional input.
garchControl
structure.- type c0:
Optional input
- return out1:
garchEstimation structure containing the following members:
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:
- 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.
- rtype out1:
struct
Example#
new;
cls,;
library tsmt;
y = loadd( getGAUSSHome() $+ "pkgs/tsmt/examples/gjrgarch.dat");
// GARCH control structure
struct garchControl c0;
c0 = garchControlCreate;
c0.cmlmtControlproc = &prc;
// Covariance type
c0.covtype = 2;
// Control cmlmt estimation
proc prc(struct cmlmtControl c0);
c0.printiters = 10;
c0.switch = 0;
c0.algorithm = 1;
retp(c0);
endp;
// GARCH order
p = 1;
// ARCH order
q = 1;
// Estimate model
struct garchEstimation f0;
f0 = garchgjrFit(y, p, q, c0);
Source#
tsgarch.src
See also
Functions garchFit()
, garchMFit()