[Quantproject-developers] QuantProject/b7_Scripts/EvaluatingOptimizationTechnique/EfficientPortfolio RunTestingOptimizationCloseToOpen.cs, 1.3, 1.4 RunTestingOptimizationOpenToClose.cs, 1.9, 1.10 RunTestingOptimizationOpenToCloseFitnessCombined.cs, 1.3, 1.4

[Glauco S. <gla...@us...>]

Update of /cvsroot/quantproject/QuantProject/b7_Scripts/EvaluatingOptimizationTechnique/EfficientPortfolio
In directory sc8-pr-cvs16.sourceforge.net:/tmp/cvs-serv3611/b7_Scripts/EvaluatingOptimizationTechnique/EfficientPortfolio

Modified Files:
	RunTestingOptimizationCloseToOpen.cs 
	RunTestingOptimizationOpenToClose.cs 
	RunTestingOptimizationOpenToCloseFitnessCombined.cs 
Log Message:
- the code has been cleaned up to avoid warnings
- standard indentation has been applied

Index: RunTestingOptimizationOpenToClose.cs
===================================================================
RCS file: /cvsroot/quantproject/QuantProject/b7_Scripts/EvaluatingOptimizationTechnique/EfficientPortfolio/RunTestingOptimizationOpenToClose.cs,v
retrieving revision 1.9
retrieving revision 1.10
diff -C2 -d -r1.9 -r1.10
*** RunTestingOptimizationOpenToClose.cs	14 Jan 2008 23:28:58 -0000	1.9
--- RunTestingOptimizationOpenToClose.cs	19 Aug 2008 17:13:11 -0000	1.10
***************
*** 3,7 ****
  
  RunTestingOptimizationOpenToClose.cs
! Copyright (C) 2003 
  Marco Milletti
  
--- 3,7 ----
  
  RunTestingOptimizationOpenToClose.cs
! Copyright (C) 2003
  Marco Milletti
  
***************
*** 19,23 ****
  along with this program; if not, write to the Free Software
  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
! */
  
  using System;
--- 19,23 ----
  along with this program; if not, write to the Free Software
  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
!  */
  
  using System;
***************
*** 38,91 ****
  	/// for the efficient open to close portfolio
  	/// </summary>
!   [Serializable]
!   public class RunTestingOptimizationOpenToClose
!   {
!   	private double[] fitnessesInSample;
!   	private double[] fitnessesOutOfSample;
!   	private string tickerGroupID;
!     private int numberOfEligibleTickers;
!     private int numberOfTickersToBeChosen;
!     private int numDaysForOptimization;
!     private int populationSizeForGeneticOptimizer;
!     private int generationNumberForGeneticOptimizer;
!   	private string benchmark;
!   	private DateTime marketDate;
!   	private double targetReturn;
!   	private PortfolioType portfolioType;
!   	private int numDaysAfterLastOptimizationDay;
!   	private int numberOfSubsets;
!   	private Genome[] genomesToTestOutOfSample;
!   	private int numberOfGenomesToTest;
!       	
!     public RunTestingOptimizationOpenToClose(string tickerGroupID, int numberOfEligibleTickers,
!       				int numberOfTickersToBeChosen, int numDaysForOptimization,
!       				int generationNumberForGeneticOptimizer, int populationSizeForGeneticOptimizer, 
!       				string benchmark,
!       				DateTime marketDate, double targetReturn,
!       				PortfolioType portfolioType, int numDaysAfterLastOptimizationDay,
!       				int numberOfSubsets, int numberOfGenomesToTest)
!     {
!   		this.numberOfGenomesToTest = numberOfGenomesToTest;
!   		this.genomesToTestOutOfSample = new Genome[numberOfGenomesToTest];
!   		this.fitnessesInSample = new double[numberOfGenomesToTest];
!   		this.fitnessesOutOfSample = new double[numberOfGenomesToTest];
!   		this.tickerGroupID = tickerGroupID;
!   		this.numberOfEligibleTickers = numberOfEligibleTickers;
!   		this.numberOfTickersToBeChosen = numberOfTickersToBeChosen;
!   		this.numDaysForOptimization = numDaysForOptimization;
!   		this.populationSizeForGeneticOptimizer = populationSizeForGeneticOptimizer;
!   		this.generationNumberForGeneticOptimizer = generationNumberForGeneticOptimizer;
!   		this.benchmark = benchmark;
!   		this.marketDate = marketDate;
!   		this.targetReturn = targetReturn;
!   		this.portfolioType = portfolioType;
!   		this.numDaysAfterLastOptimizationDay = numDaysAfterLastOptimizationDay;
!   		this.numberOfSubsets = numberOfSubsets;
!    	}
!     
!   	private DataTable getSetOfTickersToBeOptimized(DateTime date)
!     {
!       /*
!       SelectorByAverageRawOpenPrice selectorByOpenPrice = 
                    new SelectorByAverageRawOpenPrice(this.tickerGroupID, false,
                            currentDate.AddDays(-this.numDaysForOptimization), currentDate,
--- 38,91 ----
  	/// for the efficient open to close portfolio
  	/// </summary>
! 	[Serializable]
! 	public class RunTestingOptimizationOpenToClose
! 	{
! 		private double[] fitnessesInSample;
! 		private double[] fitnessesOutOfSample;
! 		private string tickerGroupID;
! 		private int numberOfEligibleTickers;
! 		private int numberOfTickersToBeChosen;
! 		private int numDaysForOptimization;
! 		private int populationSizeForGeneticOptimizer;
! 		private int generationNumberForGeneticOptimizer;
! 		private string benchmark;
! 		private DateTime marketDate;
! 		private double targetReturn;
! 		private PortfolioType portfolioType;
! 		private int numDaysAfterLastOptimizationDay;
! 		private int numberOfSubsets;
! 		private Genome[] genomesToTestOutOfSample;
! 		private int numberOfGenomesToTest;
! 		
! 		public RunTestingOptimizationOpenToClose(string tickerGroupID, int numberOfEligibleTickers,
! 		                                         int numberOfTickersToBeChosen, int numDaysForOptimization,
! 		                                         int generationNumberForGeneticOptimizer, int populationSizeForGeneticOptimizer,
! 		                                         string benchmark,
! 		                                         DateTime marketDate, double targetReturn,
! 		                                         PortfolioType portfolioType, int numDaysAfterLastOptimizationDay,
! 		                                         int numberOfSubsets, int numberOfGenomesToTest)
! 		{
! 			this.numberOfGenomesToTest = numberOfGenomesToTest;
! 			this.genomesToTestOutOfSample = new Genome[numberOfGenomesToTest];
! 			this.fitnessesInSample = new double[numberOfGenomesToTest];
! 			this.fitnessesOutOfSample = new double[numberOfGenomesToTest];
! 			this.tickerGroupID = tickerGroupID;
! 			this.numberOfEligibleTickers = numberOfEligibleTickers;
! 			this.numberOfTickersToBeChosen = numberOfTickersToBeChosen;
! 			this.numDaysForOptimization = numDaysForOptimization;
! 			this.populationSizeForGeneticOptimizer = populationSizeForGeneticOptimizer;
! 			this.generationNumberForGeneticOptimizer = generationNumberForGeneticOptimizer;
! 			this.benchmark = benchmark;
! 			this.marketDate = marketDate;
! 			this.targetReturn = targetReturn;
! 			this.portfolioType = portfolioType;
! 			this.numDaysAfterLastOptimizationDay = numDaysAfterLastOptimizationDay;
! 			this.numberOfSubsets = numberOfSubsets;
! 		}
! 		
! 		private DataTable getSetOfTickersToBeOptimized(DateTime date)
! 		{
! 			/*
!       SelectorByAverageRawOpenPrice selectorByOpenPrice =
                    new SelectorByAverageRawOpenPrice(this.tickerGroupID, false,
                            currentDate.AddDays(-this.numDaysForOptimization), currentDate,
***************
*** 93,350 ****
                            this.maxPriceForMinimumCommission, 0, 2);
        DataTable tickersByPrice = selectorByOpenPrice.GetTableOfSelectedTickers();
!       */
!      	
!      	SelectorByGroup temporizedGroup = new SelectorByGroup(this.tickerGroupID,
!       	                                                    date);
!       
!       SelectorByOpenCloseCorrelationToBenchmark lessCorrelatedFromTemporizedGroup = 
!         new SelectorByOpenCloseCorrelationToBenchmark(temporizedGroup.GetTableOfSelectedTickers(),
!                                           this.benchmark,true,
!                                           date.AddDays(-this.numDaysForOptimization ),
!                                           date,
!                                          this.numberOfEligibleTickers);
!       
!       DataTable eligibleTickers;
!       eligibleTickers = lessCorrelatedFromTemporizedGroup.GetTableOfSelectedTickers();
!       //eligibleTickers = temporizedGroup.GetTableOfSelectedTickers();
!       SelectorByQuotationAtEachMarketDay quotedAtEachMarketDayFromEligible = 
!         new SelectorByQuotationAtEachMarketDay( eligibleTickers,
!                                    false, date.AddDays(-this.numDaysForOptimization),
!                                     date, this.numberOfEligibleTickers, this.benchmark);
!       //SelectorByWinningOpenToClose winners =
!       	//new SelectorByWinningOpenToClose(quotedAtEachMarketDayFromEligible.GetTableOfSelectedTickers(),
!       	  //                               false, date.AddDays(-1),
!       	    //                             date.AddDays(-1), this.numberOfEligibleTickers/2,
!               //                            true);      	                                 
!       //return winners.GetTableOfSelectedTickers();
!      
!       return quotedAtEachMarketDayFromEligible.GetTableOfSelectedTickers();
!       //return lessCorrelated.GetTableOfSelectedTickers();
!     }
!   	
!     private double setFitnesses_setFitnessesActually_getFitnessOutOfSample(Genome genome)
!   		
!     {
!       double returnValue = 0;
!       foreach(string tickerCode in ((GenomeMeaning)genome.Meaning).Tickers)
!       {
!         double coefficient = 1.0;
!         string ticker = tickerCode;
!         if(ticker.StartsWith("-"))
!         {
!           ticker = ticker.Substring(1,ticker.Length -1);
!           coefficient = -1.0;
!         }
!         DateTime dateOutOfSample = this.marketDate.AddDays(this.numDaysAfterLastOptimizationDay);
!         //returnValue is the single return for the numDaysAfterLastOptimizationDay - th day
!         //after the given market date
!         
!         //Quotes tickerQuotes = new Quotes(ticker, dateOutOfSample,
!         //  															 dateOutOfSample);
!         //returnValue +=
!         //  (tickerQuotes.GetFirstValidRawClose(dateOutOfSample)/
!         //  tickerQuotes.GetFirstValidRawOpen(dateOutOfSample) - 1.0)*coefficient;
! 	 			
!         //returnValue is the average return for the interval between
! 	 			//the given market date and the numDaysAfterLastOptimizationDay - th
! 	 			//day after the given market date
! 	 			//Quotes tickerQuotes = new Quotes(ticker, this.marketDate,
!         //  															 dateOutOfSample);
!         //double close, open;
! 	 			//for(int i = 0; i<this.numDaysAfterLastOptimizationDay; i++)
! 	 			//{
! 		      //close = tickerQuotes.GetFirstValidRawClose(this.marketDate.AddDays(i));
! 		      //open = tickerQuotes.GetFirstValidRawOpen(this.marketDate.AddDays(i));
! 	 				//returnValue +=
! 		      //(close/open - 1.0)*coefficient/this.numDaysAfterLastOptimizationDay;
! 		      	
! 	 			//}
!         
!         //returnValue is the sharpe ratio for the interval between
!         //the given market date and the numDaysAfterLastOptimizationDay - th
!         //day after the given market date
!         Quotes tickerQuotes = new Quotes(ticker, this.marketDate,
!           															 dateOutOfSample);
!         double close, open;
!         double[] returns = new double[this.numDaysAfterLastOptimizationDay];
!         for(int i = 0; i<this.numDaysAfterLastOptimizationDay; i++)
!         {
!           close = tickerQuotes.GetFirstValidRawClose(this.marketDate.AddDays(i));
!           open = tickerQuotes.GetFirstValidRawOpen(this.marketDate.AddDays(i));
!           returns[i] = (close/open - 1.0)*coefficient;
!         }
!         returnValue += BasicFunctions.SimpleAverage(returns) / BasicFunctions.StdDev(returns);
!       }
  
!       return returnValue/genome.Size;
!       
!     }
!     
!     private bool setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes_sharesNoGeneWithGenomesAlreadyAdded(Genome genomeToBeAdded,
!                                                                                                                               bool addWorstGenomes)
!   		
!     {
!       bool returnValue = true;
!       if(addWorstGenomes)
!       //the first half containing the worst genomes has to be checked
!       {
!         for(int i = 0; i<this.numberOfGenomesToTest/2; i++)
!         {
!           if(this.genomesToTestOutOfSample[i]==null)
!             return true;
!           if(!genomeToBeAdded.SharesNoGeneWith(this.genomesToTestOutOfSample[i]))
!             return false;
!         }
!       }
!       else
!       //the second half containing the best genomes has to be checked
!       {
!         for(int i = 0; i<this.numberOfGenomesToTest/2; i++)
!         {
!           if(this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-i]==null)
!             return true;
!           if(!genomeToBeAdded.SharesNoGeneWith(this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-i]))
!             return false;
!         }
!       }
!       return returnValue;
!     }
!     private void setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(GeneticOptimizer optimizer,
!                                                                                       bool addWorstGenomes)
!   		
!     {
!       Genome currentGenome;
!       Genome previousGenome = null;
!       int numOfDifferentGenomesFound = 0;
!       for(int j = 0;
!         j<this.populationSizeForGeneticOptimizer && numOfDifferentGenomesFound<this.numberOfGenomesToTest/2;
!         j++)
!       {
!         if(addWorstGenomes == true)
!           currentGenome = (Genome)optimizer.CurrentGeneration[j];
!         else
!           currentGenome = (Genome)optimizer.CurrentGeneration[this.populationSizeForGeneticOptimizer-j-1];
  
!         if(this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes_sharesNoGeneWithGenomesAlreadyAdded(currentGenome, addWorstGenomes))
!         //no genes of the current genome are present in the relative half
!         {
!           if(this.genomesToTestOutOfSample[numOfDifferentGenomesFound]!= null)
!           //the first half of the array has already been filled
!             this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-numOfDifferentGenomesFound]=currentGenome;
!           else//the first half is still empty
!             this.genomesToTestOutOfSample[numOfDifferentGenomesFound] = currentGenome;
!           previousGenome = currentGenome;
!           numOfDifferentGenomesFound++;
!         }
!         
!       }
!      
!     }
!   	
!     private void setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample(IGenomeManager genomeManager)
!   		
!     {
!       GeneticOptimizer optimizer = new GeneticOptimizer(genomeManager,
!                                               this.populationSizeForGeneticOptimizer,
!                                               this.generationNumberForGeneticOptimizer,
!                                               ConstantsProvider.SeedForRandomGenerator);
!       optimizer.Run(false);
!       this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(optimizer,
!                                                                                  true);
!       this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(optimizer,
!                                                                                 false);
!       Array.Sort(this.genomesToTestOutOfSample);
!     }
!     
!     private void setFitnesses_setFitnessesActually(IGenomeManager genomeManager)
!   		
!     {
!       this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample(genomeManager);
!       for(int i = 0; i<this.numberOfGenomesToTest; i++)
!       {
!         this.fitnessesInSample[i]=(this.genomesToTestOutOfSample[i]).Fitness;
!         this.fitnessesOutOfSample[i]= 
!           this.setFitnesses_setFitnessesActually_getFitnessOutOfSample(this.genomesToTestOutOfSample[i]);
!       }
!       
!     }
  
!     private void setFitnesses()
!   		
!     {
!       
!       DataTable setOfTickersToBeOptimized = 
!       	this.getSetOfTickersToBeOptimized(this.marketDate);
!        IGenomeManager genManEfficientOTC = 
!         new GenomeManagerForEfficientOTCPortfolio(setOfTickersToBeOptimized,
!       	                                          this.marketDate.AddDays(-this.numDaysForOptimization),
!       	                                          this.marketDate,
!       	                                          this.numberOfTickersToBeChosen,
!       	                                          this.targetReturn,
!       	                                         	this.portfolioType,
! 																									this.benchmark);
!     
!       this.setFitnesses_setFitnessesActually(genManEfficientOTC);
!       
!     }
!   	
!     public void Run()
!     {
!       try
!       {
!         this.setFitnesses();
!         OptimizationTechniqueEvaluator evaluator = 
!           new OptimizationTechniqueEvaluator(this.fitnessesInSample,
!           this.fitnessesOutOfSample);
!         this.run_writeToLogFile(evaluator);
!       }
!       catch(Exception ex)
!       {
!         ex = ex;
!       }
!     }
!     
!     private void run_writeToLogFile(OptimizationTechniqueEvaluator evaluator)
!     {
!     	double[] averagesInSample = 
!     		evaluator.GetAveragesOfSubsetsInSample(this.numberOfSubsets);
!     	double[] averagesOutOfSample = 
!     		evaluator.GetAveragesOfSubsetsOutOfSample(this.numberOfSubsets);
!     	double r = evaluator.GetCorrelationBetweenFitnesses();
!     	GenomeCounter genomeCounter = new GenomeCounter(this.genomesToTestOutOfSample);
!     	int differentEvaluatedGenomes = genomeCounter.TotalEvaluatedGenomes;
!      	string pathFile = System.Configuration.ConfigurationSettings.AppSettings["GenericArchive"] +
!                     "\\OptimizationEvaluation.txt";
!   	  StreamWriter w = File.AppendText(pathFile);
!   	  w.WriteLine ("\n----------------------------------------------\r\n");
!   	  w.Write("\r\nNew Test for Evaluation of Open To Close Optimization {0}\r", DateTime.Now.ToLongDateString()+ " " +DateTime.Now.ToLongTimeString());
!   	  w.Write("\r\nNum days for optimization {0}\r", this.numDaysForOptimization.ToString());
!       w.Write("\r\nOptimizing market date {0}\r", this.marketDate.ToLongDateString());
!       w.Write("\r\nMarket date for test out of sample (sharpe ratio as fitness OS){0}\r",
!                         this.marketDate.AddDays(this.numDaysAfterLastOptimizationDay).ToLongDateString());
!       w.Write("\r\nNumber of tickers: {0}\r", this.numberOfTickersToBeChosen.ToString());
!       w.WriteLine ("\n----------------------------------------------");
!   	  w.Write("\r\nFitnesses compared (sharpe r. OTC): {0}\r", this.fitnessesInSample.Length.ToString());
!   	  w.Write("\r\nDifferent evaluated genomes: {0}\r", differentEvaluatedGenomes.ToString());
!       w.Write("\r\nAverages of the {0} sub sets of fitnesses In Sample:\r",
!   	          this.numberOfSubsets);
!       //
!       for(int i = 0; i<averagesInSample.Length; i++)
!         	w.WriteLine("\n{0}-->{1}", i.ToString(), averagesInSample[i].ToString());
!       
!       w.WriteLine ("\n\n----------------------------------------------");
!       w.Write("\r\nAverages of the {0} sub sets of fitnesses Out of Sample:\r",
!   	          this.numberOfSubsets);
!       //
!       for(int i = 0; i<averagesOutOfSample.Length; i++)
!         	w.WriteLine("\n{0}-->{1}", i.ToString(), averagesOutOfSample[i].ToString());	
!       w.WriteLine ("\n\n----------------------------------------------");
!       //
!       w.Write("\r\nCorrelation coefficient between fitnesses: {0}\r", r.ToString());
!       w.WriteLine ("\n-----------------End of Test------------------\r\n");
!       // Update the underlying file.
!       w.Flush();
!       w.Close();
!     }	
  	}
  }
--- 93,351 ----
                            this.maxPriceForMinimumCommission, 0, 2);
        DataTable tickersByPrice = selectorByOpenPrice.GetTableOfSelectedTickers();
! 			 */
! 			
! 			SelectorByGroup temporizedGroup = new SelectorByGroup(this.tickerGroupID,
! 			                                                      date);
! 			
! 			SelectorByOpenCloseCorrelationToBenchmark lessCorrelatedFromTemporizedGroup =
! 				new SelectorByOpenCloseCorrelationToBenchmark(temporizedGroup.GetTableOfSelectedTickers(),
! 				                                              this.benchmark,true,
! 				                                              date.AddDays(-this.numDaysForOptimization ),
! 				                                              date,
! 				                                              this.numberOfEligibleTickers);
! 			
! 			DataTable eligibleTickers;
! 			eligibleTickers = lessCorrelatedFromTemporizedGroup.GetTableOfSelectedTickers();
! 			//eligibleTickers = temporizedGroup.GetTableOfSelectedTickers();
! 			SelectorByQuotationAtEachMarketDay quotedAtEachMarketDayFromEligible =
! 				new SelectorByQuotationAtEachMarketDay( eligibleTickers,
! 				                                       false, date.AddDays(-this.numDaysForOptimization),
! 				                                       date, this.numberOfEligibleTickers, this.benchmark);
! 			//SelectorByWinningOpenToClose winners =
! 			//new SelectorByWinningOpenToClose(quotedAtEachMarketDayFromEligible.GetTableOfSelectedTickers(),
! 			//                               false, date.AddDays(-1),
! 			//                             date.AddDays(-1), this.numberOfEligibleTickers/2,
! 			//                            true);
! 			//return winners.GetTableOfSelectedTickers();
! 			
! 			return quotedAtEachMarketDayFromEligible.GetTableOfSelectedTickers();
! 			//return lessCorrelated.GetTableOfSelectedTickers();
! 		}
! 		
! 		private double setFitnesses_setFitnessesActually_getFitnessOutOfSample(Genome genome)
! 			
! 		{
! 			double returnValue = 0;
! 			foreach(string tickerCode in ((GenomeMeaning)genome.Meaning).Tickers)
! 			{
! 				double coefficient = 1.0;
! 				string ticker = tickerCode;
! 				if(ticker.StartsWith("-"))
! 				{
! 					ticker = ticker.Substring(1,ticker.Length -1);
! 					coefficient = -1.0;
! 				}
! 				DateTime dateOutOfSample = this.marketDate.AddDays(this.numDaysAfterLastOptimizationDay);
! 				//returnValue is the single return for the numDaysAfterLastOptimizationDay - th day
! 				//after the given market date
! 				
! 				//Quotes tickerQuotes = new Quotes(ticker, dateOutOfSample,
! 				//  															 dateOutOfSample);
! 				//returnValue +=
! 				//  (tickerQuotes.GetFirstValidRawClose(dateOutOfSample)/
! 				//  tickerQuotes.GetFirstValidRawOpen(dateOutOfSample) - 1.0)*coefficient;
! 				
! 				//returnValue is the average return for the interval between
! 				//the given market date and the numDaysAfterLastOptimizationDay - th
! 				//day after the given market date
! 				//Quotes tickerQuotes = new Quotes(ticker, this.marketDate,
! 				//  															 dateOutOfSample);
! 				//double close, open;
! 				//for(int i = 0; i<this.numDaysAfterLastOptimizationDay; i++)
! 				//{
! 				//close = tickerQuotes.GetFirstValidRawClose(this.marketDate.AddDays(i));
! 				//open = tickerQuotes.GetFirstValidRawOpen(this.marketDate.AddDays(i));
! 				//returnValue +=
! 				//(close/open - 1.0)*coefficient/this.numDaysAfterLastOptimizationDay;
! 				
! 				//}
! 				
! 				//returnValue is the sharpe ratio for the interval between
! 				//the given market date and the numDaysAfterLastOptimizationDay - th
! 				//day after the given market date
! 				Quotes tickerQuotes = new Quotes(ticker, this.marketDate,
! 				                                 dateOutOfSample);
! 				double close, open;
! 				double[] returns = new double[this.numDaysAfterLastOptimizationDay];
! 				for(int i = 0; i<this.numDaysAfterLastOptimizationDay; i++)
! 				{
! 					close = tickerQuotes.GetFirstValidRawClose(this.marketDate.AddDays(i));
! 					open = tickerQuotes.GetFirstValidRawOpen(this.marketDate.AddDays(i));
! 					returns[i] = (close/open - 1.0)*coefficient;
! 				}
! 				returnValue += BasicFunctions.SimpleAverage(returns) / BasicFunctions.StdDev(returns);
! 			}
  
! 			return returnValue/genome.Size;
! 			
! 		}
! 		
! 		private bool setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes_sharesNoGeneWithGenomesAlreadyAdded(Genome genomeToBeAdded,
! 		                                                                                                                          bool addWorstGenomes)
! 			
! 		{
! 			bool returnValue = true;
! 			if(addWorstGenomes)
! 				//the first half containing the worst genomes has to be checked
! 			{
! 				for(int i = 0; i<this.numberOfGenomesToTest/2; i++)
! 				{
! 					if(this.genomesToTestOutOfSample[i]==null)
! 						return true;
! 					if(!genomeToBeAdded.SharesNoGeneWith(this.genomesToTestOutOfSample[i]))
! 						return false;
! 				}
! 			}
! 			else
! 				//the second half containing the best genomes has to be checked
! 			{
! 				for(int i = 0; i<this.numberOfGenomesToTest/2; i++)
! 				{
! 					if(this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-i]==null)
! 						return true;
! 					if(!genomeToBeAdded.SharesNoGeneWith(this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-i]))
! 						return false;
! 				}
! 			}
! 			return returnValue;
! 		}
! 		private void setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(GeneticOptimizer optimizer,
! 		                                                                                      bool addWorstGenomes)
! 			
! 		{
! 			Genome currentGenome;
! 			Genome previousGenome = null;
! 			int numOfDifferentGenomesFound = 0;
! 			for(int j = 0;
! 			    j<this.populationSizeForGeneticOptimizer && numOfDifferentGenomesFound<this.numberOfGenomesToTest/2;
! 			    j++)
! 			{
! 				if(addWorstGenomes == true)
! 					currentGenome = (Genome)optimizer.CurrentGeneration[j];
! 				else
! 					currentGenome = (Genome)optimizer.CurrentGeneration[this.populationSizeForGeneticOptimizer-j-1];
  
! 				if(this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes_sharesNoGeneWithGenomesAlreadyAdded(currentGenome, addWorstGenomes))
! 					//no genes of the current genome are present in the relative half
! 				{
! 					if(this.genomesToTestOutOfSample[numOfDifferentGenomesFound]!= null)
! 						//the first half of the array has already been filled
! 						this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-numOfDifferentGenomesFound]=currentGenome;
! 					else//the first half is still empty
! 						this.genomesToTestOutOfSample[numOfDifferentGenomesFound] = currentGenome;
! 					previousGenome = currentGenome;
! 					numOfDifferentGenomesFound++;
! 				}
! 				
! 			}
! 			
! 		}
! 		
! 		private void setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample(IGenomeManager genomeManager)
! 			
! 		{
! 			GeneticOptimizer optimizer = new GeneticOptimizer(genomeManager,
! 			                                                  this.populationSizeForGeneticOptimizer,
! 			                                                  this.generationNumberForGeneticOptimizer,
! 			                                                  ConstantsProvider.SeedForRandomGenerator);
! 			optimizer.Run(false);
! 			this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(optimizer,
! 			                                                                              true);
! 			this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(optimizer,
! 			                                                                              false);
! 			Array.Sort(this.genomesToTestOutOfSample);
! 		}
! 		
! 		private void setFitnesses_setFitnessesActually(IGenomeManager genomeManager)
! 			
! 		{
! 			this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample(genomeManager);
! 			for(int i = 0; i<this.numberOfGenomesToTest; i++)
! 			{
! 				this.fitnessesInSample[i]=(this.genomesToTestOutOfSample[i]).Fitness;
! 				this.fitnessesOutOfSample[i]=
! 					this.setFitnesses_setFitnessesActually_getFitnessOutOfSample(this.genomesToTestOutOfSample[i]);
! 			}
! 			
! 		}
  
! 		private void setFitnesses()
! 			
! 		{
! 			
! 			DataTable setOfTickersToBeOptimized =
! 				this.getSetOfTickersToBeOptimized(this.marketDate);
! 			IGenomeManager genManEfficientOTC =
! 				new GenomeManagerForEfficientOTCPortfolio(setOfTickersToBeOptimized,
! 				                                          this.marketDate.AddDays(-this.numDaysForOptimization),
! 				                                          this.marketDate,
! 				                                          this.numberOfTickersToBeChosen,
! 				                                          this.targetReturn,
! 				                                          this.portfolioType,
! 				                                          this.benchmark);
! 			
! 			this.setFitnesses_setFitnessesActually(genManEfficientOTC);
! 			
! 		}
! 		
! 		public void Run()
! 		{
! 			try
! 			{
! 				this.setFitnesses();
! 				OptimizationTechniqueEvaluator evaluator =
! 					new OptimizationTechniqueEvaluator(this.fitnessesInSample,
! 					                                   this.fitnessesOutOfSample);
! 				this.run_writeToLogFile(evaluator);
! 			}
! 			catch(Exception ex)
! 			{
! 				string forBreakpoint = ex.Message; forBreakpoint = forBreakpoint + "";
! 			}
! 		}
! 		
! 		private void run_writeToLogFile(OptimizationTechniqueEvaluator evaluator)
! 		{
! 			double[] averagesInSample =
! 				evaluator.GetAveragesOfSubsetsInSample(this.numberOfSubsets);
! 			double[] averagesOutOfSample =
! 				evaluator.GetAveragesOfSubsetsOutOfSample(this.numberOfSubsets);
! 			double r = evaluator.GetCorrelationBetweenFitnesses();
! 			GenomeCounter genomeCounter = new GenomeCounter(this.genomesToTestOutOfSample);
! 			int differentEvaluatedGenomes = genomeCounter.TotalEvaluatedGenomes;
! 			string pathFile =
! 				System.Configuration.ConfigurationManager.AppSettings["GenericArchive"] +
! 				"\\OptimizationEvaluation.txt";
! 			StreamWriter w = File.AppendText(pathFile);
! 			w.WriteLine ("\n----------------------------------------------\r\n");
! 			w.Write("\r\nNew Test for Evaluation of Open To Close Optimization {0}\r", DateTime.Now.ToLongDateString()+ " " +DateTime.Now.ToLongTimeString());
! 			w.Write("\r\nNum days for optimization {0}\r", this.numDaysForOptimization.ToString());
! 			w.Write("\r\nOptimizing market date {0}\r", this.marketDate.ToLongDateString());
! 			w.Write("\r\nMarket date for test out of sample (sharpe ratio as fitness OS){0}\r",
! 			        this.marketDate.AddDays(this.numDaysAfterLastOptimizationDay).ToLongDateString());
! 			w.Write("\r\nNumber of tickers: {0}\r", this.numberOfTickersToBeChosen.ToString());
! 			w.WriteLine ("\n----------------------------------------------");
! 			w.Write("\r\nFitnesses compared (sharpe r. OTC): {0}\r", this.fitnessesInSample.Length.ToString());
! 			w.Write("\r\nDifferent evaluated genomes: {0}\r", differentEvaluatedGenomes.ToString());
! 			w.Write("\r\nAverages of the {0} sub sets of fitnesses In Sample:\r",
! 			        this.numberOfSubsets);
! 			//
! 			for(int i = 0; i<averagesInSample.Length; i++)
! 				w.WriteLine("\n{0}-->{1}", i.ToString(), averagesInSample[i].ToString());
! 			
! 			w.WriteLine ("\n\n----------------------------------------------");
! 			w.Write("\r\nAverages of the {0} sub sets of fitnesses Out of Sample:\r",
! 			        this.numberOfSubsets);
! 			//
! 			for(int i = 0; i<averagesOutOfSample.Length; i++)
! 				w.WriteLine("\n{0}-->{1}", i.ToString(), averagesOutOfSample[i].ToString());
! 			w.WriteLine ("\n\n----------------------------------------------");
! 			//
! 			w.Write("\r\nCorrelation coefficient between fitnesses: {0}\r", r.ToString());
! 			w.WriteLine ("\n-----------------End of Test------------------\r\n");
! 			// Update the underlying file.
! 			w.Flush();
! 			w.Close();
! 		}
  	}
  }

Index: RunTestingOptimizationCloseToOpen.cs
===================================================================
RCS file: /cvsroot/quantproject/QuantProject/b7_Scripts/EvaluatingOptimizationTechnique/EfficientPortfolio/RunTestingOptimizationCloseToOpen.cs,v
retrieving revision 1.3
retrieving revision 1.4
diff -C2 -d -r1.3 -r1.4
*** RunTestingOptimizationCloseToOpen.cs	14 Jan 2008 23:28:58 -0000	1.3
--- RunTestingOptimizationCloseToOpen.cs	19 Aug 2008 17:13:11 -0000	1.4
***************
*** 3,7 ****
  
  RunTestingOptimizationCloseToOpen.cs
! Copyright (C) 2003 
  Marco Milletti
  
--- 3,7 ----
  
  RunTestingOptimizationCloseToOpen.cs
! Copyright (C) 2003
  Marco Milletti
  
***************
*** 19,23 ****
  along with this program; if not, write to the Free Software
  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
! */
  
  using System;
--- 19,23 ----
  along with this program; if not, write to the Free Software
  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
!  */
  
  using System;
***************
*** 38,321 ****
  	/// for the efficient close to open portfolio
  	/// </summary>
!   [Serializable]
!   public class RunTestingOptimizationCloseToOpen
!   {
!   	private double[] fitnessesInSample;
!   	private double[] fitnessesOutOfSample;
!   	private string tickerGroupID;
!     private int numberOfEligibleTickers;
!     private int numberOfTickersToBeChosen;
!     private int numDaysForOptimization;
!     private int populationSizeForGeneticOptimizer;
!     private int generationNumberForGeneticOptimizer;
!   	private string benchmark;
!   	private DateTime marketDate;
!   	private double targetReturn;
!   	private PortfolioType portfolioType;
!   	private int numDaysAfterLastOptimizationDay;
!   	private int numberOfSubsets;
!   	private Genome[] genomesToTestOutOfSample;
!   	private int numberOfGenomesToTest;
!       	
!     public RunTestingOptimizationCloseToOpen(string tickerGroupID, int numberOfEligibleTickers,
!       				int numberOfTickersToBeChosen, int numDaysForOptimization,
!       				int generationNumberForGeneticOptimizer, int populationSizeForGeneticOptimizer, 
!       				string benchmark,
!       				DateTime marketDate, double targetReturn,
!       				PortfolioType portfolioType, int numDaysAfterLastOptimizationDay,
!       				int numberOfSubsets, int numberOfGenomesToTest)
!     {
!   		this.numberOfGenomesToTest = numberOfGenomesToTest;
!   		this.genomesToTestOutOfSample = new Genome[numberOfGenomesToTest];
!   		this.fitnessesInSample = new double[numberOfGenomesToTest];
!   		this.fitnessesOutOfSample = new double[numberOfGenomesToTest];
!   		this.tickerGroupID = tickerGroupID;
!   		this.numberOfEligibleTickers = numberOfEligibleTickers;
!   		this.numberOfTickersToBeChosen = numberOfTickersToBeChosen;
!   		this.numDaysForOptimization = numDaysForOptimization;
!   		this.populationSizeForGeneticOptimizer = populationSizeForGeneticOptimizer;
!   		this.generationNumberForGeneticOptimizer = generationNumberForGeneticOptimizer;
!   		this.benchmark = benchmark;
!   		this.marketDate = marketDate;
!   		this.targetReturn = targetReturn;
!   		this.portfolioType = portfolioType;
!   		this.numDaysAfterLastOptimizationDay = numDaysAfterLastOptimizationDay;
!   		this.numberOfSubsets = numberOfSubsets;
!    	}
!     
!     private DataTable getSetOfTickersToBeOptimized(DateTime date)
!     {
!       SelectorByGroup temporizedGroup = new SelectorByGroup(this.tickerGroupID, date);
!       SelectorByQuotationAtEachMarketDay quotedAtEachMarketDayFromEligible = 
!         new SelectorByQuotationAtEachMarketDay( temporizedGroup.GetTableOfSelectedTickers(),
!         false, date.AddDays(-this.numDaysForOptimization),
!         date, this.numberOfEligibleTickers, this.benchmark);
  
!       return quotedAtEachMarketDayFromEligible.GetTableOfSelectedTickers();
!     }
!     private double setFitnesses_setFitnessesActually_getFitnessOutOfSample(Genome genome)
!   		
!     {
!       double returnValue = 0;
!       foreach(string tickerCode in ((GenomeMeaning)genome.Meaning).Tickers)
!       {
!         double coefficient = 1.0;
!         string ticker = tickerCode;
!         if(ticker.StartsWith("-"))
!         {
!           ticker = ticker.Substring(1,ticker.Length -1);
!           coefficient = -1.0;
!         }
!         DateTime dateOutOfSample = this.marketDate.AddDays(this.numDaysAfterLastOptimizationDay);
!         //returnValue is the single return for the numDaysAfterLastOptimizationDay - th day
!         //after the given market date
!         
!         //Quotes tickerQuotes = new Quotes(ticker, dateOutOfSample,
!         //  															 dateOutOfSample);
!         
!         //returnValue +=
! //          (tickerQuotes.GetFirstValidAdjustedOpen(dateOutOfSample.AddDays(1))/
!         //  tickerQuotes.GetFirstValidAdjustedClose(dateOutOfSample) - 1.0)*coefficient;
! 	 			//
!         //returnValue is the average return for the interval between
! 	 			//the given market date and the numDaysAfterLastOptimizationDay - th
! 	 			//day after the given market date
! 	 			//Quotes tickerQuotes = new Quotes(ticker, this.marketDate,
!         //  															 dateOutOfSample);
!         //double close, open;
! 	 			//for(int i = 0; i<this.numDaysAfterLastOptimizationDay; i++)
! 	 			//{
! 		      //close = tickerQuotes.GetFirstValidAdjustedClose(this.marketDate.AddDays(i));
! 		      //open = tickerQuotes.GetFirstValidAdjustedOpen(this.marketDate.AddDays(i+1));
! 	 				//returnValue +=
! 		      	//(open/close - 1.0)*coefficient/this.numDaysAfterLastOptimizationDay;
! 		      	
! 	 			//}
!         
!         //returnValue is the sharpe ratio for the interval between
!         //the given market date and the numDaysAfterLastOptimizationDay - th
!         //day after the given market date
!         Quotes tickerQuotes = new Quotes(ticker, this.marketDate,
!           dateOutOfSample);
!         double close, open;
!         double[] returns = new double[this.numDaysAfterLastOptimizationDay];
!         for(int i = 0; i<this.numDaysAfterLastOptimizationDay; i++)
!         {
!           close = tickerQuotes.GetFirstValidAdjustedClose(this.marketDate.AddDays(i));
!           open = tickerQuotes.GetFirstValidAdjustedOpen(this.marketDate.AddDays(i+1));
!           returns[i] = (open/close - 1.0)*coefficient;
!         }
!         returnValue += BasicFunctions.SimpleAverage(returns) / BasicFunctions.StdDev(returns);
!       }
!       return returnValue/genome.Size;
!       
!     }
!     
!     private bool setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes_sharesNoGeneWithGenomesAlreadyAdded(Genome genomeToBeAdded,
!                                                                                                                               bool addWorstGenomes)
!   		
!     {
!       bool returnValue = true;
!       if(addWorstGenomes)
!       //the first half containing the worst genomes has to be checked
!       {
!         for(int i = 0; i<this.numberOfGenomesToTest/2; i++)
!         {
!           if(this.genomesToTestOutOfSample[i]==null)
!             return true;
!           if(!genomeToBeAdded.SharesNoGeneWith(this.genomesToTestOutOfSample[i]))
!             return false;
!         }
!       }
!       else
!       //the second half containing the best genomes has to be checked
!       {
!         for(int i = 0; i<this.numberOfGenomesToTest/2; i++)
!         {
!           if(this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-i]==null)
!             return true;
!           if(!genomeToBeAdded.SharesNoGeneWith(this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-i]))
!             return false;
!         }
!       }
!       return returnValue;
!     }
!     private void setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(GeneticOptimizer optimizer,
!                                                                                       bool addWorstGenomes)
!   		
!     {
!       Genome currentGenome;
!       Genome previousGenome = null;
!       int numOfDifferentGenomesFound = 0;
!       for(int j = 0;
!         j<this.populationSizeForGeneticOptimizer && numOfDifferentGenomesFound<this.numberOfGenomesToTest/2;
!         j++)
!       {
!         if(addWorstGenomes == true)
!           currentGenome = (Genome)optimizer.CurrentGeneration[j];
!         else
!           currentGenome = (Genome)optimizer.CurrentGeneration[this.populationSizeForGeneticOptimizer-j-1];
  
!         if(this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes_sharesNoGeneWithGenomesAlreadyAdded(currentGenome, addWorstGenomes))
!         //no genes of the current genome are present in the relative half
!         {
!           if(this.genomesToTestOutOfSample[numOfDifferentGenomesFound]!= null)
!           //the first half of the array has already been filled
!             this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-numOfDifferentGenomesFound]=currentGenome;
!           else//the first half is still empty
!             this.genomesToTestOutOfSample[numOfDifferentGenomesFound] = currentGenome;
!           previousGenome = currentGenome;
!           numOfDifferentGenomesFound++;
!         }
!         
!       }
!      
!     }
!   	
!     private void setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample(IGenomeManager genomeManager)
!   		
!     {
!       GeneticOptimizer optimizer = new GeneticOptimizer(genomeManager,
!                                               this.populationSizeForGeneticOptimizer,
!                                               this.generationNumberForGeneticOptimizer,
!                                               ConstantsProvider.SeedForRandomGenerator);
!       optimizer.Run(false);
!       this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(optimizer,
!                                                                                  true);
!       this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(optimizer,
!                                                                                 false);
!       Array.Sort(this.genomesToTestOutOfSample);
!     }
!     
!     private void setFitnesses_setFitnessesActually(IGenomeManager genomeManager)
!   		
!     {
!       this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample(genomeManager);
!       for(int i = 0; i<this.numberOfGenomesToTest; i++)
!       {
!         this.fitnessesInSample[i]=(this.genomesToTestOutOfSample[i]).Fitness;
!         this.fitnessesOutOfSample[i]= 
!           this.setFitnesses_setFitnessesActually_getFitnessOutOfSample(this.genomesToTestOutOfSample[i]);
!       }
!       
!     }
  
!     private void setFitnesses()
!   		
!     {
!       
!       DataTable setOfTickersToBeOptimized = 
!       	this.getSetOfTickersToBeOptimized(this.marketDate);
!        IGenomeManager genManEfficientCTOPortfolio = 
!         new GenomeManagerForEfficientCTOPortfolio(setOfTickersToBeOptimized,
!       	                                          this.marketDate.AddDays(-this.numDaysForOptimization),
!       	                                          this.marketDate,
!       	                                          this.numberOfTickersToBeChosen,
!       	                                          this.targetReturn,
!       	                                         	this.portfolioType,
! 																									this.benchmark);
!     
!       this.setFitnesses_setFitnessesActually(genManEfficientCTOPortfolio);
!       
!     }
!   	
!     public void Run()
!     {
!       try
!       {
!         this.setFitnesses();
!         OptimizationTechniqueEvaluator evaluator = 
!           new OptimizationTechniqueEvaluator(this.fitnessesInSample,
!           this.fitnessesOutOfSample);
!         this.run_writeToLogFile(evaluator);
!       }
!       catch(Exception ex)
!       {
!         ex = ex;
!       }
!     }
!     
!     private void run_writeToLogFile(OptimizationTechniqueEvaluator evaluator)
!     {
!     	double[] averagesInSample = 
!     		evaluator.GetAveragesOfSubsetsInSample(this.numberOfSubsets);
!     	double[] averagesOutOfSample = 
!     		evaluator.GetAveragesOfSubsetsOutOfSample(this.numberOfSubsets);
!     	double r = evaluator.GetCorrelationBetweenFitnesses();
!     	GenomeCounter genomeCounter = new GenomeCounter(this.genomesToTestOutOfSample);
!     	int differentEvaluatedGenomes = genomeCounter.TotalEvaluatedGenomes;
!      	string pathFile = System.Configuration.ConfigurationSettings.AppSettings["GenericArchive"] +
!                     "\\OptimizationEvaluation.txt";
!   	  StreamWriter w = File.AppendText(pathFile);
!   	  w.WriteLine ("\n----------------------------------------------\r\n");
!   	  w.Write("\r\nNew Test for Evaluation of Close To Open Optimization {0}\r", DateTime.Now.ToLongDateString()+ " " +DateTime.Now.ToLongTimeString());
!   	  w.Write("\r\nNum days for optimization {0}\r", this.numDaysForOptimization.ToString());
!       w.Write("\r\nOptimizing market date {0}\r", this.marketDate.ToLongDateString());
!       w.Write("\r\nMarket date for test out of sample (sharpe ratio as fitness OS){0}\r",
!                         this.marketDate.AddDays(this.numDaysAfterLastOptimizationDay).ToLongDateString());
!       w.Write("\r\nNumber of tickers: {0}\r", this.numberOfTickersToBeChosen.ToString());
!       w.WriteLine ("\n----------------------------------------------");
!   	  w.Write("\r\nFitnesses compared (sharpe ratio CTO): {0}\r", this.fitnessesInSample.Length.ToString());
!   	  w.Write("\r\nDifferent evaluated genomes: {0}\r", differentEvaluatedGenomes.ToString());
!       w.Write("\r\nAverages of the {0} sub sets of fitnesses In Sample:\r",
!   	          this.numberOfSubsets);
!       //
!       for(int i = 0; i<averagesInSample.Length; i++)
!         	w.WriteLine("\n{0}-->{1}", i.ToString(), averagesInSample[i].ToString());
!       
!       w.WriteLine ("\n\n----------------------------------------------");
!       w.Write("\r\nAverages of the {0} sub sets of fitnesses Out of Sample:\r",
!   	          this.numberOfSubsets);
!       //
!       for(int i = 0; i<averagesOutOfSample.Length; i++)
!         	w.WriteLine("\n{0}-->{1}", i.ToString(), averagesOutOfSample[i].ToString());	
!       w.WriteLine ("\n\n----------------------------------------------");
!       //
!       w.Write("\r\nCorrelation coefficient between fitnesses: {0}\r", r.ToString());
!       w.WriteLine ("\n-----------------End of Test------------------\r\n");
!       // Update the underlying file.
!       w.Flush();
!       w.Close();
!     }	
  	}
  }
--- 38,322 ----
  	/// for the efficient close to open portfolio
  	/// </summary>
! 	[Serializable]
! 	public class RunTestingOptimizationCloseToOpen
! 	{
! 		private double[] fitnessesInSample;
! 		private double[] fitnessesOutOfSample;
! 		private string tickerGroupID;
! 		private int numberOfEligibleTickers;
! 		private int numberOfTickersToBeChosen;
! 		private int numDaysForOptimization;
! 		private int populationSizeForGeneticOptimizer;
! 		private int generationNumberForGeneticOptimizer;
! 		private string benchmark;
! 		private DateTime marketDate;
! 		private double targetReturn;
! 		private PortfolioType portfolioType;
! 		private int numDaysAfterLastOptimizationDay;
! 		private int numberOfSubsets;
! 		private Genome[] genomesToTestOutOfSample;
! 		private int numberOfGenomesToTest;
! 		
! 		public RunTestingOptimizationCloseToOpen(string tickerGroupID, int numberOfEligibleTickers,
! 		                                         int numberOfTickersToBeChosen, int numDaysForOptimization,
! 		                                         int generationNumberForGeneticOptimizer, int populationSizeForGeneticOptimizer,
! 		                                         string benchmark,
! 		                                         DateTime marketDate, double targetReturn,
! 		                                         PortfolioType portfolioType, int numDaysAfterLastOptimizationDay,
! 		                                         int numberOfSubsets, int numberOfGenomesToTest)
! 		{
! 			this.numberOfGenomesToTest = numberOfGenomesToTest;
! 			this.genomesToTestOutOfSample = new Genome[numberOfGenomesToTest];
! 			this.fitnessesInSample = new double[numberOfGenomesToTest];
! 			this.fitnessesOutOfSample = new double[numberOfGenomesToTest];
! 			this.tickerGroupID = tickerGroupID;
! 			this.numberOfEligibleTickers = numberOfEligibleTickers;
! 			this.numberOfTickersToBeChosen = numberOfTickersToBeChosen;
! 			this.numDaysForOptimization = numDaysForOptimization;
! 			this.populationSizeForGeneticOptimizer = populationSizeForGeneticOptimizer;
! 			this.generationNumberForGeneticOptimizer = generationNumberForGeneticOptimizer;
! 			this.benchmark = benchmark;
! 			this.marketDate = marketDate;
! 			this.targetReturn = targetReturn;
! 			this.portfolioType = portfolioType;
! 			this.numDaysAfterLastOptimizationDay = numDaysAfterLastOptimizationDay;
! 			this.numberOfSubsets = numberOfSubsets;
! 		}
! 		
! 		private DataTable getSetOfTickersToBeOptimized(DateTime date)
! 		{
! 			SelectorByGroup temporizedGroup = new SelectorByGroup(this.tickerGroupID, date);
! 			SelectorByQuotationAtEachMarketDay quotedAtEachMarketDayFromEligible =
! 				new SelectorByQuotationAtEachMarketDay( temporizedGroup.GetTableOfSelectedTickers(),
! 				                                       false, date.AddDays(-this.numDaysForOptimization),
! 				                                       date, this.numberOfEligibleTickers, this.benchmark);
  
! 			return quotedAtEachMarketDayFromEligible.GetTableOfSelectedTickers();
! 		}
! 		private double setFitnesses_setFitnessesActually_getFitnessOutOfSample(Genome genome)
! 			
! 		{
! 			double returnValue = 0;
! 			foreach(string tickerCode in ((GenomeMeaning)genome.Meaning).Tickers)
! 			{
! 				double coefficient = 1.0;
! 				string ticker = tickerCode;
! 				if(ticker.StartsWith("-"))
! 				{
! 					ticker = ticker.Substring(1,ticker.Length -1);
! 					coefficient = -1.0;
! 				}
! 				DateTime dateOutOfSample = this.marketDate.AddDays(this.numDaysAfterLastOptimizationDay);
! 				//returnValue is the single return for the numDaysAfterLastOptimizationDay - th day
! 				//after the given market date
! 				
! 				//Quotes tickerQuotes = new Quotes(ticker, dateOutOfSample,
! 				//  															 dateOutOfSample);
! 				
! 				//returnValue +=
! 				//          (tickerQuotes.GetFirstValidAdjustedOpen(dateOutOfSample.AddDays(1))/
! 				//  tickerQuotes.GetFirstValidAdjustedClose(dateOutOfSample) - 1.0)*coefficient;
! 				//
! 				//returnValue is the average return for the interval between
! 				//the given market date and the numDaysAfterLastOptimizationDay - th
! 				//day after the given market date
! 				//Quotes tickerQuotes = new Quotes(ticker, this.marketDate,
! 				//  															 dateOutOfSample);
! 				//double close, open;
! 				//for(int i = 0; i<this.numDaysAfterLastOptimizationDay; i++)
! 				//{
! 				//close = tickerQuotes.GetFirstValidAdjustedClose(this.marketDate.AddDays(i));
! 				//open = tickerQuotes.GetFirstValidAdjustedOpen(this.marketDate.AddDays(i+1));
! 				//returnValue +=
! 				//(open/close - 1.0)*coefficient/this.numDaysAfterLastOptimizationDay;
! 				
! 				//}
! 				
! 				//returnValue is the sharpe ratio for the interval between
! 				//the given market date and the numDaysAfterLastOptimizationDay - th
! 				//day after the given market date
! 				Quotes tickerQuotes = new Quotes(ticker, this.marketDate,
! 				                                 dateOutOfSample);
! 				double close, open;
! 				double[] returns = new double[this.numDaysAfterLastOptimizationDay];
! 				for(int i = 0; i<this.numDaysAfterLastOptimizationDay; i++)
! 				{
! 					close = tickerQuotes.GetFirstValidAdjustedClose(this.marketDate.AddDays(i));
! 					open = tickerQuotes.GetFirstValidAdjustedOpen(this.marketDate.AddDays(i+1));
! 					returns[i] = (open/close - 1.0)*coefficient;
! 				}
! 				returnValue += BasicFunctions.SimpleAverage(returns) / BasicFunctions.StdDev(returns);
! 			}
! 			return returnValue/genome.Size;
! 			
! 		}
! 		
! 		private bool setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes_sharesNoGeneWithGenomesAlreadyAdded(Genome genomeToBeAdded,
! 		                                                                                                                          bool addWorstGenomes)
! 			
! 		{
! 			bool returnValue = true;
! 			if(addWorstGenomes)
! 				//the first half containing the worst genomes has to be checked
! 			{
! 				for(int i = 0; i<this.numberOfGenomesToTest/2; i++)
! 				{
! 					if(this.genomesToTestOutOfSample[i]==null)
! 						return true;
! 					if(!genomeToBeAdded.SharesNoGeneWith(this.genomesToTestOutOfSample[i]))
! 						return false;
! 				}
! 			}
! 			else
! 				//the second half containing the best genomes has to be checked
! 			{
! 				for(int i = 0; i<this.numberOfGenomesToTest/2; i++)
! 				{
! 					if(this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-i]==null)
! 						return true;
! 					if(!genomeToBeAdded.SharesNoGeneWith(this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-i]))
! 						return false;
! 				}
! 			}
! 			return returnValue;
! 		}
! 		private void setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(GeneticOptimizer optimizer,
! 		                                                                                      bool addWorstGenomes)
! 			
! 		{
! 			Genome currentGenome;
! 			Genome previousGenome = null;
! 			int numOfDifferentGenomesFound = 0;
! 			for(int j = 0;
! 			    j<this.populationSizeForGeneticOptimizer && numOfDifferentGenomesFound<this.numberOfGenomesToTest/2;
! 			    j++)
! 			{
! 				if(addWorstGenomes == true)
! 					currentGenome = (Genome)optimizer.CurrentGeneration[j];
! 				else
! 					currentGenome = (Genome)optimizer.CurrentGeneration[this.populationSizeForGeneticOptimizer-j-1];
  
! 				if(this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes_sharesNoGeneWithGenomesAlreadyAdded(currentGenome, addWorstGenomes))
! 					//no genes of the current genome are present in the relative half
! 				{
! 					if(this.genomesToTestOutOfSample[numOfDifferentGenomesFound]!= null)
! 						//the first half of the array has already been filled
! 						this.genomesToTestOutOfSample[this.numberOfGenomesToTest-1-numOfDifferentGenomesFound]=currentGenome;
! 					else//the first half is still empty
! 						this.genomesToTestOutOfSample[numOfDifferentGenomesFound] = currentGenome;
! 					previousGenome = currentGenome;
! 					numOfDifferentGenomesFound++;
! 				}
! 				
! 			}
! 			
! 		}
! 		
! 		private void setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample(IGenomeManager genomeManager)
! 			
! 		{
! 			GeneticOptimizer optimizer = new GeneticOptimizer(genomeManager,
! 			                                                  this.populationSizeForGeneticOptimizer,
! 			                                                  this.generationNumberForGeneticOptimizer,
! 			                                                  ConstantsProvider.SeedForRandomGenerator);
! 			optimizer.Run(false);
! 			this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(optimizer,
! 			                                                                              true);
! 			this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample_addGenomes(optimizer,
! 			                                                                              false);
! 			Array.Sort(this.genomesToTestOutOfSample);
! 		}
! 		
! 		private void setFitnesses_setFitnessesActually(IGenomeManager genomeManager)
! 			
! 		{
! 			this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample(genomeManager);
! 			for(int i = 0; i<this.numberOfGenomesToTest; i++)
! 			{
! 				this.fitnessesInSample[i]=(this.genomesToTestOutOfSample[i]).Fitness;
! 				this.fitnessesOutOfSample[i]=
! 					this.setFitnesses_setFitnessesActually_getFitnessOutOfSample(this.genomesToTestOutOfSample[i]);
! 			}
! 			
! 		}
  
! 		private void setFitnesses()
! 			
! 		{
! 			
! 			DataTable setOfTickersToBeOptimized =
! 				this.getSetOfTickersToBeOptimized(this.marketDate);
! 			IGenomeManager genManEfficientCTOPortfolio =
! 				new GenomeManagerForEfficientCTOPortfolio(setOfTickersToBeOptimized,
! 				                                          this.marketDate.AddDays(-this.numDaysForOptimization),
! 				                                          this.marketDate,
! 				                                          this.numberOfTickersToBeChosen,
! 				                                          this.targetReturn,
! 				                                          this.portfolioType,
! 				                                          this.benchmark);
! 			
! 			this.setFitnesses_setFitnessesActually(genManEfficientCTOPortfolio);
! 			
! 		}
! 		
! 		public void Run()
! 		{
! 			try
! 			{
! 				this.setFitnesses();
! 				OptimizationTechniqueEvaluator evaluator =
! 					new OptimizationTechniqueEvaluator(this.fitnessesInSample,
! 					                                   this.fitnessesOutOfSample);
! 				this.run_writeToLogFile(evaluator);
! 			}
! 			catch(Exception ex)
! 			{
! 				string forBreakpoint = ex.Message; forBreakpoint = forBreakpoint + "";
! 			}
! 		}
! 		
! 		private void run_writeToLogFile(OptimizationTechniqueEvaluator evaluator)
! 		{
! 			double[] averagesInSample =
! 				evaluator.GetAveragesOfSubsetsInSample(this.numberOfSubsets);
! 			double[] averagesOutOfSample =
! 				evaluator.GetAveragesOfSubsetsOutOfSample(this.numberOfSubsets);
! 			double r = evaluator.GetCorrelationBetweenFitnesses();
! 			GenomeCounter genomeCounter = new GenomeCounter(this.genomesToTestOutOfSample);
! 			int differentEvaluatedGenomes = genomeCounter.TotalEvaluatedGenomes;
! 			string pathFile =
! 				System.Configuration.ConfigurationManager.AppSettings["GenericArchive"] +
! 				"\\OptimizationEvaluation.txt";
! 			StreamWriter w = File.AppendText(pathFile);
! 			w.WriteLine ("\n----------------------------------------------\r\n");
! 			w.Write("\r\nNew Test for Evaluation of Close To Open Optimization {0}\r", DateTime.Now.ToLongDateString()+ " " +DateTime.Now.ToLongTimeString());
! 			w.Write("\r\nNum days for optimization {0}\r", this.numDaysForOptimization.ToString());
! 			w.Write("\r\nOptimizing market date {0}\r", this.marketDate.ToLongDateString());
! 			w.Write("\r\nMarket date for test out of sample (sharpe ratio as fitness OS){0}\r",
! 			        this.marketDate.AddDays(this.numDaysAfterLastOptimizationDay).ToLongDateString());
! 			w.Write("\r\nNumber of tickers: {0}\r", this.numberOfTickersToBeChosen.ToString());
! 			w.WriteLine ("\n----------------------------------------------");
! 			w.Write("\r\nFitnesses compared (sharpe ratio CTO): {0}\r", this.fitnessesInSample.Length.ToString());
! 			w.Write("\r\nDifferent evaluated genomes: {0}\r", differentEvaluatedGenomes.ToString());
! 			w.Write("\r\nAverages of the {0} sub sets of fitnesses In Sample:\r",
! 			        this.numberOfSubsets);
! 			//
! 			for(int i = 0; i<averagesInSample.Length; i++)
! 				w.WriteLine("\n{0}-->{1}", i.ToString(), averagesInSample[i].ToString());
! 			
! 			w.WriteLine ("\n\n----------------------------------------------");
! 			w.Write("\r\nAverages of the {0} sub sets of fitnesses Out of Sample:\r",
! 			        this.numberOfSubsets);
! 			//
! 			for(int i = 0; i<averagesOutOfSample.Length; i++)
! 				w.WriteLine("\n{0}-->{1}", i.ToString(), averagesOutOfSample[i].ToString());
! 			w.WriteLine ("\n\n----------------------------------------------");
! 			//
! 			w.Write("\r\nCorrelation coefficient between fitnesses: {0}\r", r.ToString());
! 			w.WriteLine ("\n-----------------End of Test------------------\r\n");
! 			// Update the underlying file.
! 			w.Flush();
! 			w.Close();
! 		}
  	}
  }

Index: RunTestingOptimizationOpenToCloseFitnessCombined.cs
===================================================================
RCS file: /cvsroot/quantproject/QuantProject/b7_Scripts/EvaluatingOptimizationTechnique/EfficientPortfolio/RunTestingOptimizationOpenToCloseFitnessCombined.cs,v
retrieving revision 1.3
retrieving revision 1.4
diff -C2 -d -r1.3 -r1.4
*** RunTestingOptimizationOpenToCloseFitnessCombined.cs	14 Jan 2008 23:28:58 -0000	1.3
--- RunTestingOptimizationOpenToCloseFitnessCombined.cs	19 Aug 2008 17:13:11 -0000	1.4
***************
*** 3,7 ****
  
  RunTestingOptimizationOpenToCloseFitnessCombined.cs
! Copyright (C) 2003 
  Marco Milletti
  
--- 3,7 ----
  
  RunTestingOptimizationOpenToCloseFitnessCombined.cs
! Copyright (C) 2003
  Marco Milletti
  
***************
*** 19,23 ****
  along with this program; if not, ...
 
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