Volatility clusters

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Volatility clusters

Dzidas
Dear all,
what would you propose for volatility clusters identification?
K-mean doesn't fit because it requires to fix length of clusters. SOM doesn't look good as well.
I found one paper, where the author refers to F. Laurini works:

F. Laurini, J.A. Tawn (2003), ‘New Estimators for the Extremal Index and Other Cluster
Characteristics,’ Extremes, Vol 6, 3, 189-211.

F. Laurini, 2004, ‘Clusters of Extreme Observations and Extremal Index Estimate in
Garch Processes,” Studies in Nonlinear Dynamics & Econometrics, Vol 8, Issue
2, 1-21.

What would be your recommendation?
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Re: Volatility clusters

Patrick Burns-2
I don't understand the question.

What are you ultimately trying to do?

On 19/07/2010 11:39, kafkaz wrote:

>
> Dear all,
> what would you propose for volatility clusters identification?
> K-mean doesn't fit because it requires to fix length of clusters. SOM
> doesn't look good as well.
> I found one paper, where the author refers to F. Laurini works:
>
> F. Laurini, J.A. Tawn (2003), ‘New Estimators for the Extremal Index and
> Other Cluster
> Characteristics,’ Extremes, Vol 6, 3, 189-211.
>
> F. Laurini, 2004, ‘Clusters of Extreme Observations and Extremal Index
> Estimate in
> Garch Processes,” Studies in Nonlinear Dynamics&  Econometrics, Vol 8, Issue
> 2, 1-21.
>
> What would be your recommendation?

--
Patrick Burns
[hidden email]
http://www.burns-stat.com

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Re: Volatility clusters

kafkaz2
The fact is that volatility moves in clusters - high movements are followed by high movements and low by low. My goal is to identify existing volatility regime based on historical data. My question is what statistical methods can I use to map historical volatility data into clusters.

I would expect something like this:
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Re: Volatility clusters

Patrick Burns-2
Have a look at the finance task view where
you will find packages that do GARCH estimation
and stochastic volatility.

On 21/07/2010 07:42, kafkaz2 wrote:
>
> The fact is that volatility moves in clusters - high movements are followed
> by high movements and low by low. My goal is to identify existing volatility
> regime based on historical data. My question is what statistical methods can
> I use to map historical volatility data into clusters.
>
> I would expect something like this:
>

--
Patrick Burns
[hidden email]
http://www.burns-stat.com

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Re: Volatility clusters

kafkaz2
Dear Patrick,
thank you for the replay.
Actually the graph above was generated by using garch estimation. I have a broad understanding how garch estimation is done, but I can't understand how can it identify volatility clusters. The output of this methodology is predicted variance, but it doesn't say to which volatility regime it belongs.
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Re: Volatility clusters

Patrick Burns-2
Regimes are artificial additions -- they have
no objective reality.  That doesn't mean they
can't sometimes be useful.

This gets us back to the question I asked yesterday:
what are you trying to do, and why do you think
that imposing regimes would help you?

On 21/07/2010 09:29, kafkaz2 wrote:
>
> Dear Patrick,
> thank you for the replay.
> Actually the graph above was generated by using garch estimation. I have a
> broad understanding how garch estimation is done, but I can't understand how
> can it identify volatility clusters. The output of this methodology is
> predicted variance, but it doesn't say to which volatility regime it
> belongs.

--
Patrick Burns
[hidden email]
http://www.burns-stat.com

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Re: Volatility clusters

kafkaz2
I'm trying to test a claim, that mean reverting strategies work best, then volatility is high. So far, I improved the results on the strategy by applying simple volatility filter.
If 5 days volatility is below 2 years 0.35 quantile is stops trading.
So, my question is - can the filter be more sophisticated?
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Re: Volatility clusters

Whit Armstrong-3
You should look at the Kim/Nelson book:
http://www.amazon.com/State-Space-Models-Regime-Switching-Gibbs-Sampling/dp/0262112388/ref=sr_1_1?ie=UTF8&s=books&qid=1279726296&sr=8-1

There are also a ton of papers on this topic.

-Whit


On Wed, Jul 21, 2010 at 10:36 AM, kafkaz2 <[hidden email]> wrote:

>
> I'm trying to test a claim, that mean reverting strategies work best, then
> volatility is high. So far, I improved the results on the strategy by
> applying simple volatility filter.
> If 5 days volatility is below 2 years 0.35 quantile is stops trading.
> So, my question is - can the filter be more sophisticated?
>
> --
> View this message in context: http://r.789695.n4.nabble.com/Volatility-clusters-tp2293786p2297196.html
> Sent from the Rmetrics mailing list archive at Nabble.com.
>
> _______________________________________________
> [hidden email] 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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