arch.univariate.RiskMetrics2006

class arch.univariate.RiskMetrics2006(tau0=1560, tau1=4, kmax=14, rho=1.4142135623730951)[source]

RiskMetrics 2006 Variance process

Parameters
  • tau0 ({int, float}, optional) – Length of long cycle. Default is 1560.

  • tau1 ({int, float}, optional) – Length of short cycle. Default is 4.

  • kmax (int, optional) – Number of components. Default is 14.

  • rho (float, optional) – Relative scale of adjacent cycles. Default is sqrt(2)

num_params

The number of parameters in the model

Type

int

Examples

Daily RiskMetrics 2006 process

>>> from arch.univariate import RiskMetrics2006
>>> rm = RiskMetrics2006()

Notes

The variance dynamics of the model are given as a weighted average of kmax EWMA variance processes where the smoothing parameters and weights are determined by tau0, tau1 and rho.

This model has no parameters since the smoothing parameter is fixed.

Methods

backcast(resids)

Construct values for backcasting to start the recursion

backcast_transform(backcast)

Transformation to apply to user-provided backcast values

bounds(resids)

Returns bounds for parameters

compute_variance(parameters, resids, sigma2, …)

Compute the variance for the ARCH model

constraints()

Construct parameter constraints arrays for parameter estimation

forecast(parameters, resids, backcast, …)

Forecast volatility from the model

parameter_names()

Names of model parameters

simulate(parameters, nobs, rng[, burn, …])

Simulate data from the model

starting_values(resids)

Returns starting values for the ARCH model

variance_bounds(resids[, power])

Construct loose bounds for conditional variances.

Properties

name

The name of the volatilty process

start

Index to use to start variance subarray selection

stop

Index to use to stop variance subarray selection