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I have been given a basic task designed to assess my knowledge of ARCH/GARCH modelling, which involves fitting the models on 2 lots of time-series index returns.

What are the brief steps I need to follow?

1) Identify if my data is firstly Stationary, then Hetereoskedastic and finally Autocorrelated? (How can I do this?) (ADF test? ARCH LM test?)

2) Fit the model? (what are the steps involved in doing this?) (In a book i've read there is least square approach, and maximum likelihood approach?) (What do I need to look for)

So far I have spent 3-4 days reading, I have a basic understanding of this process but I feel like my knowledge has a lot of gaps and I'm struggling to put it all together.

If someone could outline a simple procedure, what I need to look for etc It'd be of great help!

I'm using the software STATA.

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  • $\begingroup$ Have you read the following: this, this, this, this, and this? $\endgroup$ Apr 10, 2015 at 14:51
  • $\begingroup$ First link is too specific to that particular persons needs, the second link seems great, Thanks! The other links are useful in parts. I was hoping for an answer that simplifies the whole process into a rough guide I can follow and research individually (if I need to). $\endgroup$
    – Harry
    Apr 10, 2015 at 15:01
  • $\begingroup$ I see. One option is to wait until someone answers your question properly; the second is to draft a rough guide yourself, post it and ask if it looks fine. $\endgroup$ Apr 10, 2015 at 15:03
  • $\begingroup$ If anyone is reading this, I'd be grateful to learn how you would approach this task! $\endgroup$
    – Harry
    Apr 10, 2015 at 16:42
  • $\begingroup$ Chapters 7 and 8 of Sean Becketti's ITSUS book walks you through these steps. That's about as brief as it gets, but much too long to excerpt here. $\endgroup$
    – dimitriy
    Apr 10, 2015 at 18:15

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