arch |
c(arg) | where arg may be “scalar”, “diag” (diagonal), “rank1” (rank one), “fullrank”, “indef” (indefinite - default), or “vt” (variance target). |
arch(n, arg) | where n indicates the order of the term, and arg may be “scalar”, “diag” (diagonal), “rank1” (rank one), “fullrank”, or “indef” (indefinite - default). |
garch(n, arg) | where n indicates the order of the term, and arg may be “scalar”, “diag” (diagonal), “rank1” (rank one), “fullrank”, or “indef” (indefinite - default). |
tarch(n, arg) | where n indicates the order of the term, and arg may be “scalar”, “diag” (diagonal), “rank1” (rank one), “fullrank”, or “indef” (indefinite - default). |
exog(series, arg) | where series indicates a series name, and arg may be “scalar”, “diag” (diagonal), “rank1” (rank one), “fullrank”, or “indef” (indefinite - default). |
c(arg) | where arg may be “scalar” (default) or “vt” (variance target). |
arch(n[, arg]) | where n indicates the order of the term, and the optional arg may be “scalar” (default). |
garch(n[, arg]) | where n indicates the order of the term, and the optional arg may be “scalar” (default). |
tarch(n[, arg]) | where n indicates the order of the term, and the optional arg may be “scalar” (default). |
exog(series, arg) | where series indicates a series name, and arg may be “indiv” (individual - default) or “common”. |
c(arg) | where arg may be “scalar”, “diag” (diagonal), “rank1” (rank one), “fullrank”, “indef” (indefinite - default), or “vt” (variance target). |
arch(n[, arg]) | where n indicates the order of the term, and the optional arg may be “diag” (diagonal - default). |
garch(n[, arg]) | where n indicates the order of the term, and the optional arg may be “diag” (diagonal - default). |
tarch(n[, arg]) | where n indicates the order of the term, and the optional arg may be “diag” (diagonal - default). |
exog(series, arg) | where series indicates a series name, and arg may be “scalar”, “diag” (diagonal), “rank1” (rank one), “fullrank”, or “indef” (indefinite - default). |
tdist | Estimate the model assuming that the residuals follow a conditional Student’s t-distribution (the default is the conditional normal distribution). |
optmethod = arg | Optimization method: “bfgs” (BFGS); “newton” (Newton-Raphson), “opg” or “bhhh” (OPG or BHHH), “legacy” (EViews legacy). “bfgs” is the default for new equations. |
optstep = arg | Step method: “marquardt” (Marquardt - default); “dogleg” (Dogleg); “linesearch” (Line search). (Applicable when “optmethod=bfgs”, “optmethod=newton” or “optmethod=opg”.) |
b | Use Berndt-Hall-Hall-Hausman (BHHH) as maximization algorithm. The default is Marquardt. (Applicable when “optmethod=legacy”.) |
cov=arg | Covariance method: “ordinary” (default method based on inverse of the estimated information matrix), “huber” or “white” (Huber-White sandwich method), “bollerslev” (Bollerslev-Wooldridge method). |
covinfo = arg | Information matrix method: “opg” (OPG); “hessian” (observed Hessian), “ (Applicable when non-legacy “optmethod=” with “cov=ordinary”.) |
h | Bollerslev-Wooldridge robust quasi-maximum likelihood (QML) covariance/standard errors. (Applicable for “optmethod=legacy” when estimating assuming normal errors.) |
m=integer | Set maximum number of iterations. |
c=scalar | Set convergence criterion. The criterion is based upon the maximum of the percentage changes in the scaled coefficients. |
s | Use the current coefficient values in “C” as starting values (see also
param). |
numericderiv / ‑numericderiv | [Do / do not] use numeric derivatives only. If omitted, EViews will follow the global default. |
fastderiv / ‑fastderiv | [Do / do not] use fast derivative computation. If omitted, EViews will follow the global default. |
showopts / ‑showopts | [Do / do not] display the starting coefficient values and estimation options in the estimation output. |
coef=arg | Specify the name of the coefficient vector of a system’s variance component; the default behavior is to use the “C” coefficient vector. |
backcast=n | Backcast weight to calculate value used as the presample conditional variance. Weight needs to be greater than 0 and less than or equal to 1; the default value is 0.7. Note that a weight of 1 is equivalent to no backcasting, i.e. using the unconditional residual variance as the presample conditional variance. |
prompt | Force the dialog to appear from within a program. |
p | Print estimation results. |