org.joone.util

Class DeltaNormPlugIn

java.lang.Object

org.joone.util.AbstractConverterPlugIn

org.joone.util.ConverterPlugIn

org.joone.util.DeltaNormPlugIn

All Implemented Interfaces:

java.io.Serializable, PlugInListener

public class DeltaNormPlugIn
extends ConverterPlugIn

This plugin calculates the Delta Normalization on a time series. the Delta Normalization technique permits to feed a neural network with the delta values instead of the absolute values of the series, permitting in this manner to avoid the problems correlated with both ascending and descending trends. The normalization is obtained by dividing the delta value by the dynamic range (named Probability Volatility Windows) calculated on the given period. This plugin is very useful for financial predictions when used in combination with the MinMaxExtractorPlugin. To learn more on this technique read the excellent book: "Financial Prediction Using Neural Networks" by Joseph S. Zirilli (you can buy it in electronic format at http://www.mjfutures.com/Book.htm)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
DeltaNormPlugIn() Creates a new instance of DeltaNormPlugin

Method Summary

Methods inherited from class org.joone.util.ConverterPlugIn

isApplyEveryCycle, newCycle, setApplyEveryCycle

Methods inherited from class org.joone.util.AbstractConverterPlugIn

addPlugIn, addPlugInListener, check, convertPatterns, dataChanged, getAdvancedSerieSelector, getName, getNextPlugIn, isConnected, removeAllPlugIns, removePlugInListener, setAdvancedSerieSelector, setConnected, setInputVector, setName, setNextPlugin, setNextPlugIn

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

DeltaNormPlugIn

public DeltaNormPlugIn()

Creates a new instance of DeltaNormPlugin