Timeline for Correct procedure for modelling GARCH for forecasting volatility of stock Index returns
Current License: CC BY-SA 3.0
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| Apr 13, 2017 at 12:46 | history | edited | CommunityBot |
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| Apr 3, 2017 at 12:15 | comment | added | Richard Hardy | Malick, from a statistical point of view, direct approach is nicer as it is more efficient, while the two-step approach can be even inconsistent (at least I have not seen a proof it would always be consistent). However, direct approach will be more computationally demanding. @Albe, "model hypothesis" should be "model assumptions" in this case. | |
| Apr 1, 2017 at 10:09 | vote | accept | Albe | ||
| Mar 25, 2017 at 21:05 | comment | added | Albe | Ok thank you I understood everything, could you please clarify what you meant by the last line though? The part about the "model's hypothesis are fulfilled (IID standardized errors )".....How would I go ensuring this? Happy to accept the answer after this reply. Thanks. | |
| Mar 21, 2017 at 14:43 | comment | added | Malick | Second comment: If you fit the ARMA part alone and then you include the GARCH term (two steps methods), you'll indeed see that ARMA coefficients changes, that's why I think it is more efficient to fit directly the model with the GARCH term included (direct approach). At the end you still may get some coefficient not being significant must it is, per se, not a serious concern. The important parts are : that you are able to justify you choice of lags (AIC method for instance) and that model's hypothesis are fulfilled ( IID standardized errors ) | |
| Mar 21, 2017 at 14:37 | comment | added | Malick | First comment , yes 1-5 paragraphs are the two step approach. I have no references, I haven't read papers that explicitly mention this methodological issue, usually researches just employ one method without more details. Note that the "terminology" direct vs two step methods is my own and is not recognized by the community. | |
| Mar 20, 2017 at 21:30 | comment | added | Albe | In the other link you provided with an example "Example: I fit all ARMA(p,q) to the series with (p,q)=0:2 and select the most parsimonious one. Let’s say the best model is p=1 and q=2. Second step : if fit all ARMA(1,2)-GARCH(s,t) models to the serie with (s,t)=0:2 and I select the "best" s,t parameters using rule A again.".......The difference with what I'm doing and the example you provided is that I keep s,t fixed as I wish to do a GARCH(1,1) rather than using rule A. However using the same AR and MA terms for my GARCH estimation leads to some of the AR and MA terms not being significant. | |
| Mar 20, 2017 at 21:20 | comment | added | Albe | Thanks for replying. Just to clarify, the two step approach would be similar to what I described in my original post from paragraphs 1-5 correct?.....Whereas the direct approach would be what I describe in my second last paragraph, correct?.......Could you kindly provide literature/links to references where both of these methodologies are employed, as I'm doing a paper, and would like to read, analyse and then cite. Thank you. | |
| Mar 20, 2017 at 15:33 | history | answered | Malick | CC BY-SA 3.0 |