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Randall,
> I have found that I seem to accomplish fairly good smoothing with a
> limited amount of lag using a Kalman filter.
> Comments?
I have had very limited success with the univariate Kalman filter so
far. I wanted to use it as a data-filter before feeding it into other
indicators. I could not find that it improves the data. I get the
impression that the "noise" IS the real thing and filtering does not
help.
Graham send me recently this URL for some multivariate code. I would
love to test it but so far did not have the time to do so.
www.cms.dmu.ac.uk/~cph/Public/kalman++.code
Somehow I doubt that prefiltering helps with financial data.
Important are the indicators and no amount of filters can improve
them. I have found that the more I filter and I mean even go away
from 1 tick data or even time-based data (which is somehow a filter
as well) I get worse results.
This effect is sometimes not obvious because one has to distinguish
between the analysis of the data and the trading strategy. Because of
your reaction time, transaction costs it might be worthwhile to see
the trading based on a different time frame then the analysis.
So sometimes one gets better TRADING (simulation) results because the
filters produce less trades which results in less transaction cost.
Gerrit
Gerrit Jacobsen
http://www.tickscape.com
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