Baillie, Bollerslev, Mikkelson(1996) FIGARCH
Baillie, Bollerslev, Mikkelson(1996) FIGARCH
bailliebw1996.zip is a replication for Baillie, Bollerslev and Mikkelson(1996), "Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity", Journal of Econometrics, vol 74, pp 3-30, which introduced the FIGARCH model. The more complicated FIEGARCH model is shown at Bollerslev and Mikkelson(1996).
Detailed description
Detailed description
running bbmjoe1996-Unknown source for "diagnostic" procedur
Dear
Thank you for your help. It works just fine (as I said, I’m not familiar with rats …)
However, the code does not estimate the FIGARCH (1,d,1) – that is, the 4th column of table 4 in Baillie et al. (1996).
Indeed, the entitled “FIGARCH (1,1) “ in the bbmjoe1996.dat file corresponds to the FIGARCH(1,d,0), presented in the last column of table 4.
I’ve already tried to adjust the code in “bbmjoe1996.dat” to get FIGARCH (1,d,1) but I've been unable to succeed (as I said I’m really new in rats…).
Therefore, I would be extremely grateful if I could have your help .
José Manuel
Thank you for your help. It works just fine (as I said, I’m not familiar with rats …)
However, the code does not estimate the FIGARCH (1,d,1) – that is, the 4th column of table 4 in Baillie et al. (1996).
Indeed, the entitled “FIGARCH (1,1) “ in the bbmjoe1996.dat file corresponds to the FIGARCH(1,d,0), presented in the last column of table 4.
I’ve already tried to adjust the code in “bbmjoe1996.dat” to get FIGARCH (1,d,1) but I've been unable to succeed (as I said I’m really new in rats…).
Therefore, I would be extremely grateful if I could have your help .
José Manuel
Re: Baillie, Bollerslev, Mikkelson(1996) FIGARCH
Add this to the end of the other program. (The zip above has now been edited to include this).
Note that you have to be more careful with this model than with the simpler ones—it's possible to get guess values which produce negative variances for some data points. Starting at phi=0 from the converged estimates of the FIGARCH(1,d,0) model (which is the value of phi which nests the simpler model) will avoid any problems with that.
Note that you have to be more careful with this model than with the simpler ones—it's possible to get guess values which produce negative variances for some data points. Starting at phi=0 from the converged estimates of the FIGARCH(1,d,0) model (which is the value of phi which nests the simpler model) will avoid any problems with that.
Code: Select all
*
* FIGARCH(1,d,1) model. Add phi to the previous parmset and start it at phi=0.
*
nonlin(parmset=garchparms) c b phi d
compute phi=0.0
frml varf = c+b*h{1}+uu-b*uu{1}-(uufilter-phi*uufilter{1})
frml logl = (h(t)=varf(t)),%logdensity(h,u)
maximize(startup=%uufilter(d),parmset=meanparms+garchparms,$
title="FIGARCH(1,d,1)") logl gstart *
set ustd gstart * = u/sqrt(h)
@Diagnostics(title="FIGARCH(1,d,1) model") ustd
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Arife Ozdemir
- Posts: 5
- Joined: Thu Apr 13, 2017 8:54 am
Re: Baillie, Bollerslev, Mikkelson(1996) FIGARCH
Hello Tom,
I am quite new to the use of the rats program. When I look at the work of Baillie, Bollerslev, Mikkelson(1996) FIGARCH model, I only have FIGARCH (1,d,1) and (1,d,0) codes. How can I do if I want to do (2,d,1) or (2,d,2) or (2,d,0) in GARCH, IGARCH and FIGARCH analysis. I am very happy to help. Thanks for your help
I am quite new to the use of the rats program. When I look at the work of Baillie, Bollerslev, Mikkelson(1996) FIGARCH model, I only have FIGARCH (1,d,1) and (1,d,0) codes. How can I do if I want to do (2,d,1) or (2,d,2) or (2,d,0) in GARCH, IGARCH and FIGARCH analysis. I am very happy to help. Thanks for your help
Re: Baillie, Bollerslev, Mikkelson(1996) FIGARCH
If d=0, those aren't FIGARCH models; they're just GARCH and you can do them with P and Q options. Why do you think adding parameters to a (1,d,1) FIGARCH would be a good idea? The 1,d,1 already allows for more flexibility than the typical GARCH model. If you read the comments above, you'll see that you have to be very careful just to get anywhere on estimating a 1,d,1 model. A 2,d,1 is probably close to hopeless in practice.
Last bumped by TomDoan on Thu Nov 07, 2024 10:28 am.