arch.univariate.base.ARCHModelFixedResult

class arch.univariate.base.ARCHModelFixedResult(params: ndarray, resid: ndarray, volatility: ndarray, dep_var: pandas.Series, names: list[str], loglikelihood: float, is_pandas: bool, model: ARCHModel)[source]

Results for fixed parameters for an ARCHModel model

Parameters:
params: ndarray

Estimated parameters

resid: ndarray

Residuals from model. Residuals have same shape as original data and contain nan-values in locations not used in estimation

volatility: ndarray

Conditional volatility from model

dep_var: pandas.Series

Dependent variable

names: list[str]

Model parameter names

loglikelihood: float

Loglikelihood at specified parameters

is_pandas: bool

Whether the original input was pandas

model: ARCHModel

The model object used to estimate the parameters

Methods

arch_lm_test([lags, standardized])

ARCH LM test for conditional heteroskedasticity

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

Construct forecasts from estimated model

hedgehog_plot([params, horizon, step, ...])

Plot forecasts from estimated model

plot([annualize, scale])

Plot standardized residuals and conditional volatility

summary()

Constructs a summary of the results from a fit model.

Properties

aic

Akaike Information Criteria

bic

Schwarz/Bayesian Information Criteria

conditional_volatility

Estimated conditional volatility

loglikelihood

Model loglikelihood

model

Model instance used to produce the fit

nobs

Number of data points used to estimate model

num_params

Number of parameters in model

params

Model Parameters

resid

Model residuals

std_resid

Residuals standardized by conditional volatility