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NEUROSHELL TRADER
Hans Uhlig’s nearest neighbor prediction (NNP) trading
system presented in his article in this issue works by finding
near neighbors of the reference pattern, and then averaging
the next moves of the neighbors to get an estimate of the next
move of the reference pattern. In the article, under the
heading “Refinements,” Uhlig outlines a method of improving
the performance, wherein each neighbor is weighted in
proportion to its distance. A further refinement he describes
would be to apply different weights to individual elements of
the pattern.
Here’s how to implement the NNP in NeuroShell Trader.
Ward Systems offers an add-on for NeuroShell Trader called
Adaptive Net Indicators (ANI). This add-on was designed to
do exactly the near neighbor prediction as described by
Uhlig, including both refinements. This will save you from
having to do the spreadsheet manipulations that Uhlig calls
“laborious and time-intensive.” The ANI add-on will not only
make a prediction of a coming move, but it is also capable of
classifying patterns as well (for example, buy or don’t buy,
sell or don’t sell).
Adaptive Net Indicators will work with any type of pattern
information, not just previous price values. You can choose
almost anything for your patterns, including stochastics,
moving averages, or any of hundreds of other indicators. You
can choose your own “lookback” period (the amount of
history to include), or allow the genetic algorithm optimizer
in our professional versions to find the lookback period that
makes the most profit at the same time it finds the best
indicators and indicator parameters.
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