I am currently attempting to model and forecast volatility of bitcoin but have not been able to find a GARCH model that fits the data appropriately. I've used tick data sampled at 1 hour intervals over a 2 year period and converted it into hourly returns. The best model i have been able to produce so far is an asymmetric garch (3,3) model.
The portmanteau stat is 198.4**
I have tried GARCH-M,EGARCH,TGARCH all up to (3,3). For some reason I cannot specify (p,q) to be any higher than 3? What steps can I take to improve the model further?
Would it be beneficial to account for seasonality or jumps similair to todrov (2011) and andersen and bollerslev(2005)?
Note: limited programming knowledge so would prefer to avoid R, output produced by PCGIVE10.