Volatility Processes

A volatility process is added to a mean model to capture time-varying volatility.

ConstantVariance()

Constant volatility process

GARCH([p, o, q, power])

GARCH and related model estimation

FIGARCH([p, q, power, truncation])

FIGARCH model

EGARCH([p, o, q])

EGARCH model estimation

HARCH([lags])

Heterogeneous ARCH process

MIDASHyperbolic([m, asym])

MIDAS Hyperbolic ARCH process

ARCH([p])

ARCH process

APARCH([p, o, q, delta, common_asym])

Asymmetric Power ARCH (APARCH) volatility process

Parameterless Variance Processes

Some volatility processes use fixed parameters and so have no parameters that are estimable.

EWMAVariance([lam])

Exponentially Weighted Moving-Average (RiskMetrics) Variance process

RiskMetrics2006([tau0, tau1, kmax, rho])

RiskMetrics 2006 Variance process

FixedVariance

The FixedVariance class is a special-purpose volatility process that allows the so-called zig-zag algorithm to be used. See the example for usage.

FixedVariance(variance[, unit_scale])

Fixed volatility process

Writing New Volatility Processes

All volatility processes must inherit from :class:VolatilityProcess and provide all public methods.

VolatilityProcess()

Abstract base class for ARCH models.