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 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();
}
