SimpleHistroricalSimulation.java

/*
 * (c) Copyright Christian P. Fries, Germany. All rights reserved. Contact: email@christian-fries.de.
 * 
 * Created on 15.07.2012
 */


package net.finmath.timeseries.models.parametric;

import java.util.HashMap;
import java.util.Map;

import net.finmath.timeseries.HistoricalSimulationModel;

/**
 * Implementation of standard historical simulation.
 * 
 * @author Christian Fries, Norman Seeger
 */

public class SimpleHistroricalSimulation implements HistoricalSimulationModel {

	private double[] values;	

	private int windowIndexStart;
	private int windowIndexEnd;

	public SimpleHistroricalSimulation(double[] values) {
		this.values = values;
		this.windowIndexStart	= 0;
		this.windowIndexEnd		= values.length-1;

	}

	public SimpleHistroricalSimulation(double[] values, int windowIndexStart, int windowIndexEnd) {
		this.values = values;
		this.windowIndexStart	= windowIndexStart;
		this.windowIndexEnd		= windowIndexEnd;

	}


	/* (non-Javadoc)
	 * @see net.finmath.timeseries.HistoricalSimulationModel#getCloneWithWindow(int, int)
	 */
	@Override
	public HistoricalSimulationModel getCloneWithWindow(int windowIndexStart, int windowIndexEnd) {
		return new SimpleHistroricalSimulation(this.values, windowIndexStart, windowIndexEnd);
	}

	public double[] getSzenarios(int relAbsFlag) {
		double[] szenarios = new double[windowIndexEnd-windowIndexStart+1-1];
		
		double y;
		
		for (int i = windowIndexStart+1; i <= windowIndexEnd; i++) {
			
			if (relAbsFlag==1) {
				y = Math.log(values[i]/values[i-1]);
				//double y = (values[i]-values[i-1]))/values[i-1]);
			} else {
				y = values[i] - values[i-1];
			}

			szenarios[i-windowIndexStart-1]	= y;
		}
		java.util.Arrays.sort(szenarios);
		
		return szenarios;
	}
	public double[] getQuantilPredictions(int relAbsFlag,  double[] quantiles) {
		double[] szenarios = this.getSzenarios(relAbsFlag);

		double[] quantileValues = new double[quantiles.length];
		for(int i=0; i<quantiles.length; i++) {
			double quantile = quantiles[i];
			double quantileIndex = szenarios.length * quantile  - 1;
			int quantileIndexLo = (int)quantileIndex;
			int quantileIndexHi = quantileIndexLo+1;

			double evalLo = szenarios[Math.max(quantileIndexLo,0               )];
			double evalHi = szenarios[Math.max(quantileIndexHi,0               )];
			
			if (relAbsFlag==1) {
				double szenarioChange =
						(quantileIndexHi-quantileIndex) * Math.exp(evalLo)  // ?????????????????????
						+ (quantileIndex-quantileIndexLo) * Math.exp(evalHi);
				
				double quantileValue = values[windowIndexEnd] * szenarioChange;
				quantileValues[i] = quantileValue;
				
			} else {
				double szenarioChange =
						(quantileIndexHi-quantileIndex) * evalLo  // ?????????????????????
						+ (quantileIndex-quantileIndexLo) * evalHi;
				
				double quantileValue = values[windowIndexEnd] + szenarioChange;
				quantileValues[i] = quantileValue;

			}
			
		}

		return quantileValues;
	}
	

	/* (non-Javadoc)
	 * @see net.finmath.timeseries.HistoricalSimulationModel#getBestParameters()
	 */
	@Override
	public Map<String, Object> getBestParameters() {
		return getBestParameters(null);
	}

	
	@Override
	public Map<String, Object> getBestParameters(Map<String, Object> guess) {
		int relAbsFlag = 1;
		double[] quantiles = {0.01, 0.05, 0.5};
		double[] quantileValues = this.getQuantilPredictions(relAbsFlag, quantiles);

		Map<String, Object> results = new HashMap<String, Object>();
		results.put("Szenarios", this.getSzenarios(relAbsFlag));
		results.put("Quantile=1%", quantileValues[0]);
		results.put("Quantile=5%", quantileValues[1]);
		results.put("Quantile=50%", quantileValues[2]);
		return results;
	}

}