FANPAC MT

Supported models:

• BEKK GARCH model
• Diagonal VEC multivariate models:
  • GARCH model
  • Fractionally integrated GARCH model
  • GJR GARCH model
• Multivariate constant conditional correlation models:
  • GARCH model
  • Exponential GARCH model
  • Fractionally integrated GARCH model
  • GJR GARCH model
• Multivariate dynamic conditional correlation models:
  • GARCH model
  • Exponential GARCH model
  • Fractionally integrated GARCH model
  • GJR GARCH model
• Multivariate factor GARCH model
• Generalized orthogonal GARCH model
• Univariate time series models:
  • GARCH model
  • OLS
  • ARIMA

Modeling Flexibility Provided with User-Specified Modeling Features:

• GARCH, ARCH, autoregressive, and moving average orders
• Flexible enforcement of stationarity and nonnegative conditional variance requirements
• Pre-programmed, user controlled Boxcox data transformations
• Error density functions (Normal, Student’s t, or skew t-distribution)

GAUSS FANPAC MT Output Includes:

• Estimates of model parameters
• Moment matrix of parameter estimates
• Confidence limits
• Time series and conditional variance matrices forecasts

FANPAC MT Tools Facilitate Goodness-of-Fit analysis:

• Reported Akaike and Bayesian information criterion
• Computed model residuals
• Computed roots of characteristic equations
• GARCH time series data simulation
• Andrews simulation method statistical inference
• Time series ACF and PACF computation and plotting
• Data and diagnostic plots including:
  • Standardized residuals
  • Conditional correlations, standard deviations, and variance
  • Quantile-quantile plots
• Residual diagnostics including skew, kurtosis, and Ljung-Box statistics