Nonstationary Generalised Autoregressive Conditional Heteroskedasticity Modelling for Fitting Higher Order Moments of Financial Series within Moving Time Windows

Figure 6

The phase diagrams for (, ) space for GARCH-double-normal (1,1) models corresponding to different parameters given in Table 2. We overlay the empirical data for Bank of America, truncated from to of the length of the time series, incremented in one percent steps, for the period of 6 October 2000 to 6 October 2018. To highlight the ability of the GARCH-double-normal model to fit higher order moments for specific lengths of time windows, we present three regions for the space that allow the fitting of the fourth- and sixth-order standardised moments by a GARCH-double-normal model. Each has a different time window that it can fit, shown by the letter, associated with Table 2.