V. 19:11 (98-99): Traders’ Tips
Product Description
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.
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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