Class Garch11

java.lang.Object
com.quantfinlib.volatility.Garch11
public final class Garch11 extends Object
GARCH(1,1) volatility model with Gaussian maximum-likelihood fitting: h_t = ω + α r_{t-1}² + β h_{t-1}.

Estimation uses variance targeting (ω = σ̄²(1-α-β), which pins the unconditional variance to the sample variance) and a coarse-to-fine grid search over (α, β) — derivative-free, deterministic, and robust for a two-parameter surface.

  • Nested Class Summary

    Nested Classes
    Modifier and Type
    Class
    Description
    static final record 
    Garch11.Params
     

  • Method Summary

    Modifier and Type
    Method
    Description
    static double[]
    conditionalVariances(double[] returns, Garch11.Params params)
    Conditional variance series under the fitted parameters (seeded at sample variance).
    static Garch11.Params
    fit(double[] returns)
    Fits GARCH(1,1) to (demeaned) returns by MLE with variance targeting.
    static double
    forecastVariance(double[] returns, Garch11.Params params, int horizon)
    k-step-ahead variance forecast: h_{T+k} = σ̄² + (α+β)^{k-1} (h_{T+1} - σ̄²) — mean-reverts to the unconditional variance at the persistence rate.

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

  • Method Details

    • fit

      public static Garch11.Params fit(double[] returns)
      Fits GARCH(1,1) to (demeaned) returns by MLE with variance targeting.

    • conditionalVariances

      public static double[] conditionalVariances(double[] returns, Garch11.Params params)
      Conditional variance series under the fitted parameters (seeded at sample variance).

    • forecastVariance

      public static double forecastVariance(double[] returns, Garch11.Params params, int horizon)
      k-step-ahead variance forecast: h_{T+k} = σ̄² + (α+β)^{k-1} (h_{T+1} - σ̄²) — mean-reverts to the unconditional variance at the persistence rate.