Skip to content
logo
arch 7.2.0
arch.univariate.HARCH.starting_values
Initializing search
    arch
    arch
    • Univariate Volatility Models
      • Introduction
      • Examples
      • Forecasting
      • Volatility Forecasting
      • Value-at-Risk Forecasting
      • Forecasting Scenarios
      • Forecasting with Exogenous Variables
      • Mean Models
      • Volatility Processes
        • arch.univariate.ConstantVariance
        • arch.univariate.GARCH
        • arch.univariate.FIGARCH
        • arch.univariate.EGARCH
        • arch.univariate.HARCH
          • Carch.univariate.HARCH
            • arch.univariate.HARCH.backcast
            • arch.univariate.HARCH.backcast_transform
            • arch.univariate.HARCH.bounds
            • arch.univariate.HARCH.compute_variance
            • arch.univariate.HARCH.constraints
            • arch.univariate.HARCH.forecast
            • arch.univariate.HARCH.parameter_names
            • arch.univariate.HARCH.simulate
            • arch.univariate.HARCH.starting_values
              • MHARCH.starting_values
                • Parameters
                  • presids
                • Returns
                • Return type
            • arch.univariate.HARCH.update
            • arch.univariate.HARCH.variance_bounds
            • arch.univariate.HARCH.name
            • arch.univariate.HARCH.num_params
            • arch.univariate.HARCH.start
            • arch.univariate.HARCH.stop
            • arch.univariate.HARCH.updateable
            • arch.univariate.HARCH.volatility_updater
        • arch.univariate.MIDASHyperbolic
        • arch.univariate.ARCH
        • arch.univariate.APARCH
        • Parameterless Variance Processes
        • FixedVariance
        • Writing New Volatility Processes
      • Using the Fixed Variance Process
      • Distributions
      • Results
      • Utilities
      • Background and References
    • Bootstrapping
    • Multiple Comparison Problems
    • Unit Root Testing
    • Cointegration Analysis
    • Long-run Covariance Estimation
    • API Reference
    • Common Type Definitions
    • Change Log
    • MHARCH.starting_values
      • Parameters
        • presids
      • Returns
      • Return type

    arch.univariate.HARCH.starting_values¶

    HARCH.starting_values(resids: ndarray[Any, dtype[float64]]) → ndarray[Any, dtype[float64]][source]¶

    Returns starting values for the ARCH model

    Parameters:¶
    resids: ndarray[Any, dtype[float64]]¶

    Array of (approximate) residuals to use when computing starting values

    Returns:¶

    sv – Array of starting values

    Return type:¶

    numpy.ndarray

    Previous arch.univariate.HARCH.simulate
    Next arch.univariate.HARCH.update
    © Copyright 2021, Kevin Sheppard.
    Created using Sphinx 8.1.3. and Sphinx-Immaterial