[R-SIG-Finance] Changing (seasonal) conditional distribution

Francis X. Diebold fdiebold at sas.upenn.edu
Tue May 20 18:50:08 CEST 2014


Just add seasonals as "exogenous" variables in the GARCH equation.  Use of
Fourier terms can achieve significant economy relative to a full set of
dummies.  See http://www.ssc.upenn.edu/~fdiebold/papers/paper53/reprint.pdf.

--

Francis X. Diebold

Paul F. and Warren S. Miller Professor of Economics  
Professor of Finance and Statistics  
University of Pennsylvania 
www.ssc.upenn.edu/~fdiebold/     
@FrancisDiebold
No Hesitations: www.fxdiebold.blogspot.com    

  
  


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Today's Topics:

   1. Changing (seasonal) conditional distribution in a	fGarch
      model (PoddyOne)
   2. Re: Changing (seasonal) conditional distribution in	a fGarch
      model (alexios ghalanos)
   3. Re: Changing (seasonal) conditional distribution in	a fGarch
      model (PoddyOne)
   4. Re: Changing (seasonal) conditional distribution in	a fGarch
      model (PoddyOne)
   5. Re: Changing (seasonal) conditional distribution in	a fGarch
      model (Alexios Ghalanos)


----------------------------------------------------------------------

Message: 1
Date: Mon, 19 May 2014 15:10:52 -0700 (PDT)
From: PoddyOne <padarn at gmail.com>
To: r-sig-finance at r-project.org
Subject: [R-SIG-Finance] Changing (seasonal) conditional distribution
	in a	fGarch model
Message-ID: <1400537452329-4690850.post at n4.nabble.com>
Content-Type: text/plain; charset=us-ascii

Hi there, 

I'm working with a time series that has a clear seasonal component in it's
conditional distribution. Not only does the variance increase at certain
parts of the seasonal cycle, but also the distribution becomes skewed.

I would like to fit an fGarch model to this time series, but with a
conditional distribution which depends on a dummy variable. I was wondering
if anyone knew if this was possible in fGarch or any of the similar
packages?

/(As an aside, I recognise that this may not be the easiest way to go about
modelling this. For a little more detail: This is a time series with a
strong diurnal cycle in it. The series has been 'detrended' and is
stationary at least under the usual metrics. However, still clearly during
the midnight hours, the residuals are strongly positively skewed. I have
tried transforming the series, but the large disparity in both the skew and
scale see to prohibit this working nicely.

Any other suggestions are welcome)/



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------------------------------

Message: 2
Date: Mon, 19 May 2014 23:34:31 +0100
From: alexios ghalanos <alexios at 4dscape.com>
To: PoddyOne <padarn at gmail.com>
Cc: r-sig-finance at r-project.org
Subject: Re: [R-SIG-Finance] Changing (seasonal) conditional
	distribution in	a fGarch model
Message-ID: <4A68E0AD-6B2F-4B31-9D6E-7487F38C8DCA at 4dscape.com>
Content-Type: text/plain; charset=windows-1252

Hi,

Try reading this:
http://www.unstarched.net/2013/03/20/high-frequency-garch-the-multiplicative
-component-garch-mcsgarch-model/
You?ll have to switch to using rugarch, but hopefully it should not be too
much of a sacrifice...

Alexios

On 19 May 2014, at 23:10, PoddyOne <padarn at gmail.com> wrote:

> Hi there,
> 
> I'm working with a time series that has a clear seasonal component in 
> it's conditional distribution. Not only does the variance increase at 
> certain parts of the seasonal cycle, but also the distribution becomes
skewed.
> 
> I would like to fit an fGarch model to this time series, but with a 
> conditional distribution which depends on a dummy variable. I was 
> wondering if anyone knew if this was possible in fGarch or any of the 
> similar packages?
> 
> /(As an aside, I recognise that this may not be the easiest way to go 
> about modelling this. For a little more detail: This is a time series 
> with a strong diurnal cycle in it. The series has been 'detrended' and 
> is stationary at least under the usual metrics. However, still clearly 
> during the midnight hours, the residuals are strongly positively 
> skewed. I have tried transforming the series, but the large disparity 
> in both the skew and scale see to prohibit this working nicely.
> 
> Any other suggestions are welcome)/
> 
> 
> 
> --
> View this message in context: 
> http://r.789695.n4.nabble.com/Changing-seasonal-conditional-distributi
> on-in-a-fGarch-model-tp4690850.html
> Sent from the Rmetrics mailing list archive at Nabble.com.
> 
> _______________________________________________
> R-SIG-Finance at r-project.org mailing list 
> https://stat.ethz.ch/mailman/listinfo/r-sig-finance
> -- Subscriber-posting only. If you want to post, subscribe first.
> -- Also note that this is not the r-help list where general R questions
should go.
> 



------------------------------

Message: 3
Date: Mon, 19 May 2014 17:17:15 -0700 (PDT)
From: PoddyOne <padarn at gmail.com>
To: r-sig-finance at r-project.org
Subject: Re: [R-SIG-Finance] Changing (seasonal) conditional
	distribution in	a fGarch model
Message-ID: <1400545035633-4690853.post at n4.nabble.com>
Content-Type: text/plain; charset=us-ascii

Great! Thanks for that, this looks like pretty much exactly what I am
looking for.



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------------------------------

Message: 4
Date: Mon, 19 May 2014 18:36:38 -0700 (PDT)
From: PoddyOne <padarn at gmail.com>
To: r-sig-finance at r-project.org
Subject: Re: [R-SIG-Finance] Changing (seasonal) conditional
	distribution in	a fGarch model
Message-ID: <1400549798601-4690858.post at n4.nabble.com>
Content-Type: text/plain; charset=us-ascii

Hi Alexios 

After having (somewhat) digested the link you sent me to the seasonal
variance models in your package, I'm under the impression that the
conditional distribution is still restricted to being normally distributed
(with varying variance)? I was hoping to use a skewed-normal as the
conditional distribution at certain times of day.

Another thing is that at the bottom of the page you say:

" Another possible direction for expansion would be to treat the diurnal
effect separately for each day of the week."

This is an interesting idea, and is something I thought about, but was a
little uneasy about the ideas that popped into my head about how to go about
this. For example, one simple approach might be (at least in my case) to
transform each hour of the diurnal cycle separately to try and match the
conditional distributions as closely as possible. However, this seems like
it would leave to an overly complicated model.

Cheers



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View this message in context:
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a-fGarch-model-tp4690850p4690858.html
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------------------------------

Message: 5
Date: Tue, 20 May 2014 03:18:52 -0500
From: Alexios Ghalanos <alexios at 4dscape.com>
To: PoddyOne <padarn at gmail.com>
Cc: "r-sig-finance at r-project.org" <r-sig-finance at r-project.org>
Subject: Re: [R-SIG-Finance] Changing (seasonal) conditional
	distribution in	a fGarch model
Message-ID: <8531EA42-C8AD-4F0A-810B-A551E6BDA916 at 4dscape.com>
Content-Type: text/plain;	charset=us-ascii

Hi,

Yes, you have a wide choice of skewed and shaped distributions which are
covered in detail in the vignette.

As to the expansion, I'm a little busy right now to look at this but feel
free to contribute an enhancement if you are able to.

Best,

Alexios

> On 19 May 2014, at 20:36, PoddyOne <padarn at gmail.com> wrote:
> 
> Hi Alexios
> 
> After having (somewhat) digested the link you sent me to the seasonal 
> variance models in your package, I'm under the impression that the 
> conditional distribution is still restricted to being normally 
> distributed (with varying variance)? I was hoping to use a 
> skewed-normal as the conditional distribution at certain times of day.
> 
> Another thing is that at the bottom of the page you say:
> 
> " Another possible direction for expansion would be to treat the 
> diurnal effect separately for each day of the week."
> 
> This is an interesting idea, and is something I thought about, but was 
> a little uneasy about the ideas that popped into my head about how to 
> go about this. For example, one simple approach might be (at least in 
> my case) to transform each hour of the diurnal cycle separately to try 
> and match the conditional distributions as closely as possible. 
> However, this seems like it would leave to an overly complicated model.
> 
> Cheers
> 
> 
> 
> --
> View this message in context: 
> http://r.789695.n4.nabble.com/Changing-seasonal-conditional-distributi
> on-in-a-fGarch-model-tp4690850p4690858.html
> Sent from the Rmetrics mailing list archive at Nabble.com.
> 
> _______________________________________________
> R-SIG-Finance at r-project.org mailing list 
> https://stat.ethz.ch/mailman/listinfo/r-sig-finance
> -- Subscriber-posting only. If you want to post, subscribe first.
> -- Also note that this is not the r-help list where general R questions
should go.
> 



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