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  3. GARCH Analysis

GARCH Analysis

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This reference manual section covers NumXL's GARCH-family model functions, including parameter validation and calibration, sample data fitting, goodness-of-fit measures, residual diagnosis, model-based volatility forecasts (locality and term structure), and simulation.

  • Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Model
  • GARCH - Defining a GARCH Model
  • GARCH_CHECK - Check Parameters' Values for Model Stability
  • GARCH_LLF - GARCH Model's Log-Likelihood Function
  • GARCH_AIC - Akaike's Information Criterion (AIC) of a GARCH Model
  • GARCH_FORE - Forecasting for GARCH Model
  • GARCH_FORECI - Forecasting Confidence Interval of GARCH Model
  • GARCH_FORESD - Volatility Forecast of GARCH Model
  • GARCH_GUESS - Initial Values for Model's Parameters
  • GARCH_CALIBRATE - Optimal Values for Model's Parameters
  • GARCH_ERRORS - Estimated Errors of the Parameters Values
  • GARCH_RESID - GARCH Fitted Values of Standardized Residuals
  • GARCH_VOL - GARCH Fitted Values of Conditional Volatility
  • GARCH_SIM - Simulated Values of a GARCH Model
  • GARCH_VL - Long-run Volatility of the GARCH Model
  • GARCH-in Mean (GARCH-M) Model
  • GARCHM - Defining a GARCH-M Model
  • GARCHM_AIC - Akaike's Information Criterion (AIC) for GARCH-M
  • GARCHM_CALIBRATE - Optimal Values for Model's Parameters
  • GARCHM_CHECK - Check Parameters' Values for Model Stability
  • GARCHM_ERRORS - Estimated Errors of the Parameters Values
  • GARCHM_FORE - Forecasting for GARCH-M Model
  • GARCHM_FORECI - Forecasting Confidence Interval of GARCH-M Model
  • GARCHM_FORESD - Volatility Forecast of GARCH-M Model
  • GARCHM_GUESS - Initial Values for Model's Parameters
  • GARCHM_LLF – Log-Likelihood Function of a GARCH-M Model
  • GARCHM_MEAN - GARCH-M Model Fitted Values
  • GARCHM_RESID - GARCH-M Fitted Standardized Residuals.
  • GARCHM_SIM - Simulated Values of a GARCH-M Model
  • GARCHM_VL - Long-Run Volatility of the GARCH-M Model
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