What is the GARCH model used for?
GARCH is a statistical model that can be used to analyze a number of different types of financial data, for instance, macroeconomic data. Financial institutions typically use this model to estimate the volatility of returns for stocks, bonds, and market indices.
Which GARCH model is the best?
In general, for the normal period (pre and post-crisis), symmetric GARCH model perform better than the asymmetric GARCH but for fluctuation period (crisis period), asymmetric GARCH model is preferred.
Why GARCH is better than ARIMA?
The GARCH (1,1) was found to be a better model in forecasting spot price of Gram. The values for RMSE, MAE and MAPE obtained were smaller than those in ARIMA (0,1,1) model. The AIC and SIC values from GARCH model were smaller than that from ARIMA model.
Why is GARCH more parsimonious?
Thus GARCH is more parsimonious as it uses just a couple of (or a few) parameters to achieve what the ARCH model would need an infinite number of parameters for. The argument is also very similar (essentially the same) to how an ARMA model is more parsimonious than an AR or an MA model. References: Bollerslev, T.
What is multivariate GARCH?
MGARCH stands for multivariate GARCH, or multivariate generalized autoregressive conditional heteroskedasticity. MGARCH allows the conditional-on-past-history covariance matrix of the dependent variables to follow a flexible dynamic structure.
What is a BEKK model?
The BEKK model is a commonly applied multivariate volatility model frequently used in modelling and forecasting volatilities in financial applications. Our results suggest that it is subject to considerable bias and this should be considered by potential users.
What is Omega in a GARCH model?
In a garch(1,1) model if you know alpha, beta and the asymptotic variance (the value of the prediction at infinite horizon), then omega (the variance intercept) is determined. Variance targeting is the act of specifying the asymptotic variance in order not to have to estimate omega.
What is multivariate GARCH model?
What is DCC GARCH?
A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations.