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NEW:
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TRADESTATION TECHNIQUE

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Technical
Description


Forthcoming Releases:

Fuzzy Logic:
sFLC3
DLL & API


Neural Net:
Release of NXL3
DLL & API



 

The Standard GPF is no longer available, and upgrading to the GPF Pro is recommended.  Only a few of you have been using the Standard GPF anyway.  Here are the specific features of the GPF Pro:

  • Possibility to have a custom objective.  This can be used to gear the genetic algorithm to use your parameters.  You can for instance create your own Excel formulas to calculate the profit & loss potential using stop losses, profit caps, ...   A more interesting use which has been requested by users consists in  applying a profit & loss objective from another (dependent) stock so that a causality be detected in patterns, for instance, using pattern data from Intel to maximize P&L in Compaq.
    For simplicity, all data must be present in the same workbook.
  • Adding your own Boolean indicators to filter patterns.  This will force the G.P.F. to skip bars if your indicator says so.  It is a simple way to jack-knife your data set.
  • Pattern Topology:  Although this should be used with much care, it can be interesting to better extract consistencies in winning patterns in specific market configurations.  It is possible to ask the G.P.F. to focus on reversal or follow-through patterns.  A pattern strength has even been added to make sure mild signals are ignored.
    This must used with caution though.  For each bar, the Rate of Change over the n last bars, with n being your maximum search space or bars back (default: 5) is first calculated.  Then the pattern strength is calculated as the profit potential (according to your optimization objective) multiplied by that RoC. As this uses the profit potential, it obviously peeks into the future.  This would make it a very unsuitable neural net entry. But for genetic algorithms, as long as you know what you are doing, you may do so.  You must not be fooled by the beautiful equity curve, which will obviously look great, but this is the best way to determine whether a pattern has consistently revealed a turn-around or a run-away rally.
  • Full Out-Of-Sample Analysis
    Data at the end of your sample set can be held out and reserved for out of sample analysis.  While this is not a requirement like in neural nets, we believe this gives more credit to your patterns.
  • For intraday traders, it is now possible to focus on a particular time frame.
  • Intraday features have been moved to the G.P.F. Pro, and are no longer part of the standard G.P.F.
 
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Today: - Page last modified: December 08, 2007
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