arch.univariate.base.ARCHModelFixedResult¶

class arch.univariate.base.ARCHModelFixedResult(params: ndarray[tuple[int], dtype[float64]], resid: ndarray[tuple[int], dtype[float64]], volatility: ndarray[tuple[int], dtype[float64]], dep_var: Series, names: list[str], loglikelihood: float, is_pandas: bool, model: ARCHModel)[source]¶

Results for fixed parameters for an ARCHModel model

Parameters:¶

params: ndarray[tuple[int], dtype[float64]]¶

Estimated parameters

resid: ndarray[tuple[int], dtype[float64]]¶

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

volatility: ndarray[tuple[int], dtype[float64]]¶

Conditional volatility from model

dep_var: 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