arch.univariate.MIDASHyperbolic.variance_bounds

MIDASHyperbolic.variance_bounds(resids: ndarray, power: float = 2.0) ndarray

Construct loose bounds for conditional variances.

These bounds are used in parameter estimation to ensure that the log-likelihood does not produce NaN values.

Parameters:
resids: ndarray

Approximate residuals to use to compute the lower and upper bounds on the conditional variance

power: float = 2.0

Power used in the model. 2.0, the default corresponds to standard ARCH models that evolve in squares.

Returns:

var_bounds – Array containing columns of lower and upper bounds with the same number of elements as resids

Return type:

numpy.ndarray