[R-SIG-Finance] Splitting time series into blocks/regimes?
sethy.anmol at gmail.com
Thu Mar 1 01:25:47 CET 2012
It is a difficult task and results will invariably do not match with what one's intuition might be suggesting.
You can have a look at strucchange package as well and explore topics related to distance measurements in correlation matrices.
On 29 Feb, 2012, at 20:55, Whit Armstrong <armstrong.whit at gmail.com> wrote:
> It's not easy to do this.
> Most people use gibbs sampling or other mcmc methods.
> as it happens, I have some software you can use if you don't mind
> getting your hands dirty.
> or you can just use BUGS/JAGS.
> also, some code is here:
> On Wed, Feb 29, 2012 at 7:24 AM, R. Michael Weylandt
> <michael.weylandt at gmail.com> wrote:
>> I find this idea methodologically iffy, but perhaps you could do a
>> little bit to make it a well posed question:
>> i) Are you picking these periods as relatively equal divisions or time
>> or as ex-post artifacts of "all that mess"
>> ii) What is "the clustering algorithm"? Aren't there quite a few?
>> iii) What does this mean: "the 3 big blocks/regimes need to be
>> contiguous within each block/regime itself..."
>> Perhaps you should look into reformulating your idea in terms of
>> regime switching models.
>> Michael Weylandt
>> On Tue, Feb 28, 2012 at 12:55 PM, Michael <comtech.usa at gmail.com> wrote:
>>> Hi all,
>>> I have a time series of historical SP500 returns.
>>> How do I split it into a few non-overlapping blocks(regimes) in time in an
>>> automated fashion?
>>> For example, given a prespecified number N which is the number of
>>> blocks/regimes, lets say 3.
>>> And given 5 year history of SP500 time series and returns.
>>> Manually, the period before Sept. 2008 is one regime. The period in-between
>>> Sept. 2008 and arguably May 2010 is the 2nd regime.
>>> Then the third regime is from May 2010 until today.
>>> So then we have three blocks/regimes splitted.
>>> Is there a way to split automatically?
>>> I have been thinking about using clustering algorithm on the returns.
>>> However, what is needed is a constrained version of the clustering
>>> algorithm, i.e. the 3 big blocks/regimes need to be contiguous within each
>>> block/regime itself...
>>> I am looking for a way to do this in R...
>>> Any thoughts are highly appreciated!
>>> Thanks a lot!
>>> FYI: I have asked a similar question before on this list but somehow I felt
>>> it's probably better to renew the question with my newer and more concrete
>>> examples. Also I've listed my question here so the answers to my question
>>> could be reference for fellow statisticians in the future...
>>> [[alternative HTML version deleted]]
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