arch.univariate.RiskMetrics2006¶

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

RiskMetrics 2006 Variance process

Parameters:¶

tau0: float = 1560¶

Length of long cycle. Default is 1560.

tau1: float = 4¶

Length of short cycle. Default is 4.

kmax: int = 14¶

Number of components. Default is 14.

rho: float = 1.4142135623730951¶

Relative scale of adjacent cycles. Default is sqrt(2)

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
update(index, parameters, resids, sigma2, ...)	Compute the variance for a single observation
variance_bounds(resids[, power])	Construct loose bounds for conditional variances.

Properties

name	The name of the volatility process
num_params	The number of parameters in the model
start	Index to use to start variance subarray selection
stop	Index to use to stop variance subarray selection
updateable	Flag indicating that the volatility process supports update
volatility_updater	Get the volatility updater associated with the volatility process