garchMFit

Purpose

Estimates GARCH-in-mean model.

Format

out1 = garchMFit(y, p[, c0])
out1 = garchMFit(y, p[, q, c0])
out1 = garchMFit(dataset, formula, p[, c0])
out1 = garchMFit(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.

Library

tsmt

Source

tsgarch.src