arch.univariate.base.ARCHModel

class arch.univariate.base.ARCHModel(y=None, volatility=None, distribution=None, hold_back=None, rescale=None)[source]

Abstract base class for mean models in ARCH processes. Specifies the conditional mean process.

All public methods that raise NotImplementedError should be overridden by any subclass. Private methods that raise NotImplementedError are optional to override but recommended where applicable.

Methods

bounds()

Construct bounds for parameters to use in non-linear optimization

compute_param_cov(params[, backcast, robust])

Computes parameter covariances using numerical derivatives.

constraints()

Construct linear constraint arrays for use in non-linear optimization

fit([update_freq, disp, starting_values, …])

Fits the model given a nobs by 1 vector of sigma2 values

fix(params[, first_obs, last_obs])

Allows an ARCHModelFixedResult to be constructed from fixed parameters.

forecast(params[, horizon, start, align, …])

Construct forecasts from estimated model

parameter_names()

List of parameters names

resids(params[, y, regressors])

Compute model residuals

simulate(params, nobs[, burn, …])

rtype

DataFrame

starting_values()

Returns starting values for the mean model, often the same as the values returned from fit

Properties

distribution

Set or gets the error distribution

name

The name of the model.

num_params

Number of parameters in the model

volatility

Set or gets the volatility process

y

Returns the dependent variable