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John,
if you could define such a function, why run a Neural Net on it at all? You
could derive anything worth knowing directly from the definition of the
function.
Regards,
Michael Suesserott
-----Ursprungliche Nachricht-----
Von: John Nelson [mailto:trader@xxxxxxxxxxxxxxx]
Gesendet: Monday, December 18, 2000 20:14
An: pierre.orphelin
Cc: omega-list@xxxxxxxxxx
Betreff: Re: The Yats Group
This posting provides some food for thought. If one could devise a
function which accurately simulates the random and non-random aspects of
markets using convenient data measures (price, volume, volatility) then it
would be possible to train a neural net using other than historical data.
Simulated data would provide a much more extensive training data set thus
improving the NN's predictive power and avoiding curve-fitting on limited
data.
I don't believe that there is any point training a neural net, or any
predictive system on random data since by definition, there is no
relationship between the training data and future data.
But then I don't believe that markets are entirely random.
-- John
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John T. Nelson | John's Trading Journal
trader@xxxxxxxxxxxxxxx | http://trader.computation.org/
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