private void PrepDataForStrategies() { int maxN = 0; List <Quantum> data = new List <Quantum>(); foreach (AbstractStrategy s in _strategies) { foreach (AbstractIndicator i in s.indicatorList.Values) { if (i.Period > maxN) { maxN = i.Period; } } foreach (AbstractChannel i in s.channelList.Values) { if (i.Period > maxN) { maxN = i.Period; } } } foreach (Symbol s in _symbolList) { _priceEngine.GetLongHistoricPrices(s.SymbolString, TradeTimeframe, 2 * maxN); data.Add(_priceEngine.Data); _priceEngine.Reset(); } MultiQuantum m = MultiQuantum.OrganizeMultiQuantum(data); foreach (List <Tick> ticks in m) { foreach (AbstractStrategy s in _strategies) { s.OnTick(ticks.ToArray()); } } foreach (AbstractStrategy s in _strategies) { s.IsLive = true; } }
public void OrganizeData() { _multiQuantum = MultiQuantum.OrganizeMultiQuantum(_dataSet); }
public static void TestMultiSymbolGraph(this AbstractMultiSymbolIndicator ind, string[] filename, int length) { List <Quantum> lq = new List <Quantum>(); foreach (string s in filename) { lq.Add(Quantum.ExcelToQuantum(s, s, 0)); } MultiQuantum multiQuantum = MultiQuantum.OrganizeMultiQuantum(lq); var dz = new DenseMatrix(4 + 1 + ind.SubIndicatorSize, multiQuantum.Length); List <string> names = new List <string>(); names.Add("symbol"); names.Add(ind.ToString()); foreach (var indicator in ind.SubIndicators) { names.Add(indicator.Key); } //chartoptions ChartOption[] chartOptions = new ChartOption[names.Count]; chartOptions[0] = new ChartOption() { Height = 400, YPosition = 0 }; chartOptions[1] = new ChartOption() { Height = 200, YPosition = 1 }; for (int i = 2; i < chartOptions.Length; i++) { chartOptions[i] = new ChartOption() { Height = 0, YPosition = 1, Layover = true } } ; int counter = 0; foreach (List <Tick> t in multiQuantum) { dz[0, counter] = t[0].BidOpen; dz[1, counter] = t[0].BidHigh; dz[2, counter] = t[0].BidLow; dz[3, counter] = t[0].BidClose; dz[4, counter] = ind.HandleNextTicks(t.ToArray()); int icounter = 5; foreach (var subind in ind.SubIndicators.Values) { dz[icounter, counter] = subind[0]; icounter++; } counter++; } Visualize.GenerateMultiPaneGraph(names.ToArray(), multiQuantum.Keys.ToArray(), dz, QSConstants.DEFAULT_DATA_FILEPATH + @"results.html", chartOptions); Console.WriteLine("Done Generating Graph for " + ind.ToString()); }
private static void Main() { //TestLiveCointegration.Run(); /* * IndicatorMatrix im = new IndicatorMatrix("EUR/USD"); * im.LoadData(); * im.Execute(); */ //TestIndicator.TestMA(QSConstants.DEFAULT_DATA_FILEPATH + "GBPUSD15M.xml", 14000, new QSPolyMA(40), new ZLEMA(40)); //TestIndicator.TestChannelLive(new QSPolyChannel(), "EUR/USD", "m5", 5000 ); //TestIndicator.TestChannel(new KirshenbaumBands(20), QSConstants.DEFAULT_DATA_FILEPATH + "EURUSD15M.xml", 10000); //TestIndicator.TestMA(QSConstants.DEFAULT_DATA_FILEPATH + "EURUSD1H.xml", 15000, new SMA(25), new DWT(25, 5)); //TestIndicator.TestGraph(new ReversalGenesis(50), QSConstants.DEFAULT_DATA_FILEPATH + "AUDUSD1H.xml", 15000); //TestIndicator.TestGraph(new HurstIndicator(256), QSConstants.DEFAULT_DATA_FILEPATH + "AUDUSD1H.xml", 15000); //TestIndicator.TestGraphLive(new Genesis(30), "m30", "EUR/USD", 10000); //TestIndicator.TestGraphLive(new PercentileRank(250, new SMA(200)), "H1", "EUR/USD", 1000); //TestIndicator.TestGraphLive(new PercentileRank(250, new SMA(200,new HistoricalVol(50))), "H1", "EUR/USD", 100000); //TestIndicator.TestGraphLive(new WilliamsR(), "H1", "EUR/USD", 100000); //TestIndicator.TestGraph(new PercentileRank(252, new SMA(251)), QSConstants.DEFAULT_DATA_FILEPATH + "EURUSD1H.xml", 10000); Quantum q1 = Quantum.ExcelToQuantum(QSConstants.DEFAULT_DATA_FILEPATH + "EURUSD1H.xml", "EUR/USD"); Quantum q2 = Quantum.ExcelToQuantum(QSConstants.DEFAULT_DATA_FILEPATH + "GBPUSD1H.xml", "GBP/USD"); Quantum q3 = Quantum.ExcelToQuantum(QSConstants.DEFAULT_DATA_FILEPATH + "AUDUSD1H.xml", "AUD/USD"); List <Quantum> lq = new List <Quantum>(); lq.Add(q1); lq.Add(q2); lq.Add(q3); MultiQuantum mq = MultiQuantum.OrganizeMultiQuantum(lq); List <List <Tick> > list = mq.RevertToList(); double[] dat1 = list[0].ToArray().Select(x => x.BidClose).ToArray().NormalizeZScore(); double[] dat2 = list[1].ToArray().Select(x => x.BidClose).ToArray().NormalizeZScore(); double[] dat3 = list[2].ToArray().Select(x => x.BidClose).ToArray().NormalizeZScore(); DenseVector d11 = new DenseVector(dat1); DenseVector d12 = new DenseVector(dat2); DenseVector d13 = new DenseVector(dat3); DenseVector fe = ((.48 * d11) + (-0.22 * d12) + (-.46 * d13)); Visualize.GenerateSimpleGraph(fe, "result.html"); Console.Read(); Func <Chromosome, double> fitnessFunc = new Func <Chromosome, double>( chromosome => { double weight1 = ((RealCodedGene)chromosome[0]).GeneValue; double weight2 = ((RealCodedGene)chromosome[1]).GeneValue; double weight3 = ((RealCodedGene)chromosome[2]).GeneValue; double w1mod = weight1 / (weight1 + weight2 + weight3); double w2mod = weight2 / (weight1 + weight2 + weight3); double w3mod = weight3 / (weight1 + weight2 + weight3); DenseVector d1 = new DenseVector(dat1); DenseVector d2 = new DenseVector(dat2); DenseVector d3 = new DenseVector(dat3); double stdev = ((w1mod * d1) + (w2mod * d2) + (w3mod * d3)).StandardDeviation(); return((stdev > 0) ? (1 / stdev) : 0.000001); } ); Random r = new Random(); Gene g1 = new RealCodedGene(0, r, new GeneConstraint((x => (double)x <1.0 && (double)x> -1.0)) { HI = 1.0, LOW = -1.0 }); Gene g2 = new RealCodedGene(0, r, new GeneConstraint((x => (double)x <1.0 && (double)x> -1.0)) { HI = 1.0, LOW = -1.0 }); Gene g3 = new RealCodedGene(0, r, new GeneConstraint((x => (double)x <1.0 && (double)x> -1.0)) { HI = 1.0, LOW = -1.0 }); List <Gene> cfootprint = new List <Gene>(); cfootprint.Add(g1); cfootprint.Add(g2); cfootprint.Add(g3); GeneticAlgorithm ga = new GeneticAlgorithm( fitnessFunc, cfootprint, 30, 200, 10 ); ga.Run(); Console.Read(); var ba1 = new BacktestEngine(0, 3010, true); ba1.LoadData(QSConstants.DEFAULT_DATA_FILEPATH + "EURUSD1H.xml", "EUR/USD"); ba1.LoadData(QSConstants.DEFAULT_DATA_FILEPATH + "GBPUSD1H.xml", "GBP/USD"); //ba.LoadDataLive("EUR/USD", "m5", 200000); //ba.LoadDataLive("GBP/USD", "m5", 20000); ba1.OrganizeData(); ba1.LoadStrategy(new Cointegration()); ba1.Execute(); Console.Read(); object[,] denseMatrix; ExcelUtil.Open(QSConstants.DEFAULT_DATA_FILEPATH + @"GBPUSD1H.xml", out denseMatrix); var mData = new List <double>(); var predictor = new AC(60); for (int i = denseMatrix.GetLength(0); i > 1; i--) { DateTime dateTime = (DateTime)denseMatrix[i, 1]; var t = new Tick( 0, (double)denseMatrix[i, 6], (double)denseMatrix[i, 7], (double)denseMatrix[i, 8], (double)denseMatrix[i, 9], 0, (double)denseMatrix[i, 2], (double)denseMatrix[i, 3], (double)denseMatrix[i, 4], (double)denseMatrix[i, 5], (double)denseMatrix[i, 10], dateTime ); double d = predictor.HandleNextTick(t); if (!d.Equals(double.NaN)) { mData.Add(d); } } int windowSize = 5; int iterations = 10000; int trainLength = 5000; int validateLength = 1000; double[] trainData = mData.ToArray().Take(trainLength).ToArray(); double[] validateData = mData.ToArray().Skip(trainLength).ToArray().Take(validateLength).ToArray(); Stage1NeuralNetwork nn = new Stage1NeuralNetwork(windowSize, iterations, trainData, validateData); nn.Execute(1); NeuralNetworkStrategy nns = new NeuralNetworkStrategy(windowSize) { NeuralNetwork = nn }; var ba = new BacktestEngine(5000, 9200, true); //ba.LoadData(QSConstants.DEFAULT_DATA_FILEPATH + "GBPUSD15M.xml", "EUR/USD"); ba.LoadData(QSConstants.DEFAULT_DATA_FILEPATH + "NZDUSD1H.xml", "GBP/USD"); //ba.LoadDataLive("EUR/USD", "m5", 200000); //ba.LoadDataLive("GBP/USD", "m5", 20000); ba.OrganizeData(); ba.LoadStrategy(nns); ba.Execute(); Console.Read(); /* * Func<Chromosome, double> function = (chromosome => * { * double fitness = 0.001; * * ba.ResetAccount(); * ba.ResetStrategies(); * ba.LoadStrategy(new CustomStrategy( * (int)(double)chromosome[0].GeneValue, * (int)(double)chromosome[1].GeneValue, * (int)(double)chromosome[2].GeneValue, * (int)(double)chromosome[3].GeneValue, * (int)(double)chromosome[4].GeneValue, * (int)(double)chromosome[5].GeneValue, * (int)(double)chromosome[6].GeneValue, * (int)(double)chromosome[7].GeneValue, * (int)(double)chromosome[8].GeneValue * )); * ba.Execute(); * * * fitness += ba.ret; * * return (fitness > 0) ? fitness : 0.001; * } * ); * * var GA = new GeneticAlgorithm(function, * new List<Gene> * { * new Gene(50, new Gene.Constraint(5,200)), * new Gene(50, new Gene.Constraint(5,200)), * new Gene(50, new Gene.Constraint(5,200)), * new Gene(50, new Gene.Constraint(5,500)), * new Gene(50, new Gene.Constraint(1,100)), * new Gene(50, new Gene.Constraint(1,100)), * new Gene(50, new Gene.Constraint(5,500)), * new Gene(50, new Gene.Constraint(5,500)), * new Gene(50, new Gene.Constraint(1,100)) * }) { Generations = 1000, Trials = 10 } * ; * * GA.InitializePopulation(); * GA.Run(); * * Console.Read(); */ /* * object[,] denseMatrix; * ExcelUtil.Open(Constants.DEFAULT_DATA_FILEPATH + @"EURUSD1H.xml", out denseMatrix); * * var mData = new List<double>(); * * var predictor = new RSI(40); * * for (int i = denseMatrix.GetLength(0); i > 1; i--) * { * DateTime dateTime = (DateTime) denseMatrix[i, 1]; * var t = new Tick( * 0, * (double) denseMatrix[i, 6], * (double) denseMatrix[i, 7], * (double) denseMatrix[i, 8], * (double) denseMatrix[i, 9], * 0, * (double) denseMatrix[i, 2], * (double) denseMatrix[i, 3], * (double) denseMatrix[i, 4], * (double) denseMatrix[i, 5], * (double) denseMatrix[i, 10], * dateTime * ); * * double d = predictor.HandleNextTick(t); * if (!d.Equals(double.NaN)) * mData.Add(d); * } * * int windowSize = 5; * int iterations = 5000; * int trainLength = 5000; * int validateLength = 1000; * double[] trainData = mData.ToArray().Take(trainLength).ToArray(); * double[] validateData = mData.ToArray().Skip(trainLength).ToArray().Take(validateLength).ToArray(); * * Stage1NeuralNetwork nn = new Stage1NeuralNetwork(windowSize, iterations, trainData, validateData); * nn.Execute(1); * * NeuralNetworkStrategy nns = new NeuralNetworkStrategy(windowSize){NeuralNetwork = nn}; */ /* * bool seao = true; * if (seao) * { * * var ba = new BacktestEngine(0, 50000, true); * ba.LoadDataLive("EUR/USD", "m30", 80000); * * //ba.LoadStrategy(nns); * ba.LoadStrategy(new RSIEntry(50){LongEntry = 60, ShortEntry = 40}); * ba.LoadStrategy(new RSIExit(50){ LongExit = 70, ShortExit = 30 }); * * //ba.LoadStrategy(new Pyramid(.1, .05, .001)); * ba.Execute(); * * Console.Read(); * } * * BacktestEngine[] barray = new BacktestEngine[2]; * * Func<Chromosome, double> function = (chromosome => * { * double fitness = 0.001; * foreach (BacktestEngine bx in barray) * { * bx.ResetAccount(); * bx.ResetStrategies(); * bx.LoadStrategy(new CustomStrategy()); * bx.LoadStrategy(new Pyramid((double) chromosome[0].GeneValue, * (double) chromosome[1].GeneValue, * (double) chromosome[2].GeneValue)); * bx.Execute(); * * if (bx.ret > 100) * fitness += 100; * else * fitness += bx.ret; * } * * return (fitness > 0) ? fitness/5 : 0.001; * } * ); * * var GA = new GeneticAlgorithm(function, * new List<Gene> * { * new Gene(5, new Gene.Constraint(0,1.0)), * new Gene(5, new Gene.Constraint(0,1.0)), * new Gene(5, new Gene.Constraint(0,1.0/100.0)) * }) {Generations = 1000, Trials = 1} * ; * * GA.InitializePopulation(); * GA.Run(); * * Console.Read(); * * /* * b.Output = true; * b.ResetAccount(); * b.ResetStrategies(); * b.LoadStrategy(new RSIEntry() * { * EntryTarget1 = (double)GA.maxC[0].GeneValue, * EntryTarget2 = (double)GA.maxC[1].GeneValue * }); * b.LoadStrategy(new RSIExit() * { * ExitTarget1 = (double)GA.maxC[2].GeneValue, * ExitTarget2 = (double)GA.maxC[3].GeneValue * }); * * * b.Execute(); */ //Console.Read(); //object[,] data; /* * ExcelUtil.Open("C:\\Users\\EL65628\\Work\\QuantSys\\data\\UCUM.xls", out data); * DenseMatrix d = ExcelUtil.ToMatrix(data, 2, 1283, 1, 2, true); * * DenseVector normchf = Statistics.NormalizeZScore(d.Column(0).ToArray()); * DenseVector normmxn = Statistics.NormalizeZScore(d.Column(1).ToArray()); * * DenseVector kurtmxn = new DenseVector(Statistics.AggregateWindow(d.Column(1).ToArray(), * Statistics.Kurtosis, 50, false, false)); * * DenseVector corre = new DenseVector((Statistics.AggregateWindow( * Statistics.RawRateOfReturn(d.Column(0).ToArray()), * Statistics.RawRateOfReturn(d.Column(1).ToArray()), * Statistics.Correlation, * 80, false, true))); * * //DenseMatrix dNew = new DenseMatrix(3, 1282); * //dNew.SetRow(0, (DenseVector)d.Column(0).Normalize(100)); * //dNew.SetRow(1, (DenseVector)d.Column(1).Normalize(100)); * //dNew.SetRow(2, corre); * * Visualize.GenerateGraph(corre, "C:\\Users\\EL65628\\Work\\QuantSys\\data\\correlation.html"); * Visualize.GenerateGraph(kurtmxn, "C:\\Users\\EL65628\\Work\\QuantSys\\data\\kurtosis.html"); * //Visualize.GenerateGraph(normmxn, "C:\\Users\\EL65628\\Work\\QuantSys\\data\\diff2.html"); * Visualize.GenerateGraph((DenseVector)(Statistics.NormalizeZScore((-1.5 * normmxn + .9 * normchf).ToArray())), "C:\\Users\\EL65628\\Work\\QuantSys\\data\\diff3.html"); * * string[] symbols = { "usd/chf", "usd/mxn" ,"correlation"}; * //Visualize.GenerateMultiSymbolGraph(symbols, dNew, new DateTime(), new TimeSpan(1, 0, 0), "C:\\Users\\EL65628\\Work\\QuantSys\\data\\diff.html"); * * * int[] vectors = { 5, 3, 2, 4, 6, 7, 8, 9, 10, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54 }; * * string vecstring = "1 0 0 0 1 0 1 1 0 0 0 0 1 0 1 0 1 1 1 1 1 0 1 1 1 0 0 0 1 1 1 0 0 0 1 0 0 0 0 1 1 1 1 0 0 0 1 1 0"; * * * string[] vectemp = vecstring.Split(' '); * List<int> vec = new List<int>(); * * for (int i = 0; i < vectors.Length; i++) * { * if (vectemp[i]=="1") vec.Add(vectors[i]); * } * * //int[] vect = {13, 19, 25, 27 }; * int[] vect = { 17, 18, 22, 27, 40, 49}; * * ExcelUtil.Open("C:\\Users\\EL65628\\Work\\QuantSys\\data\\EURUSD1D.xml", out data); * TwoStageNN twoStageNn = new TwoStageNN(50, 200, data, vect); * twoStageNn.Execute(); * * * //GeneticAlgorithm g = new GeneticAlgorithm(); * //g.Run(); * * Console.ReadLine(); * * PortfolioOptimizer.Run(); */ /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// string[] currencies = { "EUR/USD", "GBP/USD", "USD/CAD", "USD/CHF", "AUD/USD", "NZD/USD", "USD/JPY", "USD/MXN", "USD/ZAR", "USD/PLN", "USD/TRY", "USD/DKK", "USD/SEK", "USD/NOK" }; var currencypairs = new List <string[]>(); for (int i = 0; i < currencies.Length; i++) { for (int j = 0; j < i; j++) { if (currencies[i] != currencies[j]) { string[] temp = { currencies[i], currencies[j] }; currencypairs.Add(temp); Console.WriteLine(currencies[i] + " " + currencies[j]); } } } ///////////////////////////////////////////////////////// /* * FXSession fxsession1 = new FXSession(); * * string[] tempgroup = { "AUD/USD", "NZD/USD" }; * * Thread oThread1 = new Thread(new ThreadStart(fxsession1.InitializeSession)); * oThread1.Start(); * * while (fxsession1.LoginStatus.Equals(FXSession.LOGIN_STATUS.NOT_LOGGED_IN)) * { * Thread.Sleep(1000); * Console.Write("."); * } * * if (fxsession1.LoginStatus.Equals(FXSession.LOGIN_STATUS.LOGGED_IN)) * { * //Job_SymbolSet job = new Job_SymbolSet(ex, "H1", 150, new EMA(14)); * //Job_CorrelationMatrix job = new Job_CorrelationMatrix(currencies, "D1", 300, Job_CorrelationMatrix.CovarianceType.RawReturn); * * Job_Cointegration job = new Job_Cointegration(tempgroup, "m30", 300); * fxsession1.PlaceJob(job); * job.RunJob(fxsession1); * Thread.Sleep(1000); * } * * Console.ReadLine(); * */ ////////////////////////////////////////////////////////////////// while (true) { try { var fxsession = new FXSession(); var oThread = new Thread(fxsession.InitializeSession); oThread.Start(); while (!fxsession.LoggedIn) { Thread.Sleep(1000); Console.Write("."); } if (fxsession.LoggedIn) { //Job_SymbolSet job = new Job_SymbolSet(ex, "H1", 150, new EMA(14)); //Job_CorrelationMatrix job = new Job_CorrelationMatrix(currencies, "D1", 300, Job_CorrelationMatrix.CovarianceType.RawReturn); //Job_Cointegration.Process(fxsession, "USD/DKK", "USD/CHF", "m30", 3000); //Console.Read(); foreach (var group in currencypairs) { if ((!group[0].Substring(0, 3).Equals("USD") && !group[1].Substring(0, 3).Equals("USD")) || (group[0].Substring(0, 3).Equals("USD") && group[1].Substring(0, 3).Equals("USD"))) { try { Job_Cointegration.Process(fxsession, group[0], group[1], "m30", 3000); Thread.Sleep(1000); } catch (Exception e) { Console.WriteLine(e.Message); } } } } fxsession.EndSession(); oThread.Abort(); } catch (Exception e) { Console.WriteLine(e.Message); } Console.WriteLine(DateTime.Now.ToString()); Thread.Sleep(1000 * 60 * 30); } Console.ReadLine(); }