Mean Models¶
All ARCH models start by specifying a mean model.
| Model with zero conditional mean estimation and simulation |
| Constant mean model estimation and simulation. |
| Autoregressive model with optional exogenous regressors estimation and simulation |
| Heterogeneous Autoregression (HAR), with optional exogenous regressors, model estimation and simulation |
| Least squares model estimation and simulation |
(G)ARCH-in-mean Models¶
(G)ARCH-in-mean models allow the conditional variance (or a transformation of it) to enter the conditional mean.
| (G)ARCH-in-mean model and simulation |
Special Requirements¶
Not all volatility processes support application to AIM modeling. Specifically, the property updateable
must be True
.
In [1]: from arch.univariate import GARCH, EGARCH
In [2]: GARCH().updateable
Out[2]: True
In [3]: EGARCH().updateable
Out[3]: True
Writing New Mean Models¶
All mean models must inherit from :class:ARCHModel and provide all public methods. There are two optional private methods that should be provided if applicable.
| Abstract base class for mean models in ARCH processes. |