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Pattern Recognition / Classification in R for Financial Time Series

3 messages · Ian Seow, Dirk Eddelbuettel, stefano iacus

#
Hi I was wondering if there are any good packages in R that would be
useful in Time Series Pattern Recognition (3rd party software
suggestions are also welcome!) .

My search problem description is this: Given a specific 5 day OHLC
sequence in a particular stock A, I want to scan through a list of
stocks B, C, etc... and return another 5 day OHLC sequence which
closely 'matches' my given sequence.

The basic brute force algorithm which I'm working on currently is to
normalize all 5 day sequences in my search universe and to calculate
the differential in HL and return the top N patterns with the lowest
differential value. If there are any elegant / intelligent ways to
solve my problem, I would love to hear it! Thanks...

Rgds
Ian
#
On 31 October 2008 at 11:17, Ian Seow wrote:
| Hi I was wondering if there are any good packages in R that would be
| useful in Time Series Pattern Recognition (3rd party software
| suggestions are also welcome!) .

Well, one could remember this:

      Zeileis' Law:  For any given open question in R, start with
      the Task Views page at http://cran.r-project.org/web/views/

Now, I just made that law up, but seriously -- look at at least the Machine
Learning one. 

Dirk
#
Hi all,
we have recently developed a new dissimilarity measure which works  
under the assumption that the underlying data follow a discretely  
observed diffusion process
The paper is still under review, so the R code is not yet released,  
but I can share the code with the ones interested.

here is the reference

De Gregorio, A.,   Iacus, S.M. (2008) Clustering of discretely  
observed diffusion processes.
Available at http://arxiv.org/abs/0809.3902


stefano
On 31/ott/08, at 04:47, Dirk Eddelbuettel wrote:

            
-----------------------------------
Stefano M. Iacus
Department of Economics,
Business and Statistics
University of Milan
Via Conservatorio, 7
I-20123 Milan - Italy
Ph.: +39 02 50321 461
Fax: +39 02 50321 505
http://www.economia.unimi.it/iacus
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