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> Hi Nicolas. Thanks and that's more or less where I am. I have an
>article here from Chaitin based on the compression criterion for
>randomness. He claims that financial time series are more or less ALL
>random. 'Only one series in 1.000 can be compressed'. Meaning that in
>practice you can find only 1 non-random time series in 1.000. I just
>cannot believe this because if that's true what about technical
>analysis ? So I am missing something ...
You make a good point, if this is true, then TA would be pointless. I
would say it all depends on the timescale, at small timescales (1mn -
5mn) there are for sure recurrent patterns. The whole problem is to
find ones that are tradable despite slippage and delays : )
> Anyway, you are saying that you did some testing on the NAS100
stocks with the Lempel-Ziv algorithm (?). Do you have any code for me
or an URL where I can find it ?
Unfortunately, I cannot give the code (part of a C++ library). You may
implement one of the algorithms described in
http://www.snl-e.salk.edu/publications/Kennel-2005.pdf
The one on page 1571 (Kontoyiannis et al) is known to be good.
Alternatively, you may export your time series to a txt file and
compress it using gzip/pkzip. Then you do the same for a large number
of random time series (1000) and compute the ratio of the size of the
files (your_time_series/average_random_time_series), it will give you
a rough idea about how far you are from randomness .. but never
explain that to a physicist : ) (see for instance
http://cscs.umich.edu/~crshalizi/notebooks/cep-gzip.html
)
Regards,
Nicolas
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