static void Main(string[] args)
{
string symbol = YSQSymbol.YSQIndex.SNP;
DateTime begin = new DateTime(2003, 12, 1);
DateTime end = new DateTime(2004, 2, 1);
ISamplePackage samplePackage = new YSQProvider().GetHistory(new Asset(symbol, AssetType.Index), begin, end, null);
IBarPackage barPackage = (IBarPackage)samplePackage;
List <IBar> bars = barPackage.Samples;
TaResult ema13 = bars.EMA(13);
BullPower bullPower = new BullPower(bars, 13);
//var sampleValues = new List<IInstantValue<double>>();
//sampleValues.Add(new InstantValue<double>(new DateTime(2004, 1, 1), 1.0));
//sampleValues.Add(new InstantValue<double>(new DateTime(2004, 1, 2), -1.0));
//sampleValues.Add(new InstantValue<double>(new DateTime(2004, 1, 3), 1.0));
//sampleValues.Add(new InstantValue<double>(new DateTime(2004, 1, 4), -1.0));
ChartPool.CreateChart();
ChartPool.ClearSeries();
ChartPool.AddSeries(
new List <Series> {
new Series("Prices", ChartType.Lines, Colors.Black, bars.Select(x => new Sample(x.DateTime, (double)x.Close))),
new Series("EMA(13)", ChartType.Lines, Colors.Red, ema13.InstantValues.Select(x => new Sample(x.DateTime, x.Value))),
new Series("BullPower(13)", ChartType.Columns, Colors.Blue, bullPower.InstantValues.Select(x => new Sample(x.DateTime, x.Value))),
}
);
Console.WriteLine("Press a key to exit...");
Console.ReadKey(true);
}
public void AddSerie(string name, TaResult serie)
{
if (serie.Count != _bars.Count)
{
throw new Exception("Wrong samples qty.");
}
_series[name] = serie;
}
static void Main(string[] args)
{
string symbol = YSQSymbol.YSQIndex.SNP;
DateTime begin = new DateTime(2013, 1, 1);
DateTime end = new DateTime(2014, 1, 1);
ISamplePackage samplePackage = new YSQProvider().GetHistory(new Asset(symbol, AssetType.Index), begin, end, null);
IBarPackage barPackage = (IBarPackage)samplePackage;
List <IBar> bars = barPackage.Samples;
// simulation
ISimulation bestSimulation = default(ISimulation);
TaResult bestSimulationSmallEma = default(TaResult);
TaResult bestSimulationBigEma = default(TaResult);
ChartPool.CreateChart();
int configurationsCount = 0;
DateTime simulationsBegin = DateTime.Now;
for (int small = 2; small < 14; small += 1)
{
for (int big = 30; big < 80; big += 1)
{
for (int take = 10; take < 50; take += 2)
{
for (int stop = 10; stop < 50; stop += 2)
{
configurationsCount++;
var simulation = SmaSimulation.CreateLongOnly(2, take, stop);
simulation.SimulationInfo = string
.Format("EMA_SMALL: {0}, EMA_BIG: {1}, TakeProfit: {2}, StopLoss: {3}",
small, big, take, stop);
SimulationRunner simulationRunner = new SimulationRunner(bars, simulation);
var smallEma = bars.EMA(small);
var bigEma = bars.EMA(big);
simulationRunner.AddSerie("EMA_SMALL", smallEma);
simulationRunner.AddSerie("EMA_BIG", bigEma);
simulationRunner.Execute();
Console.WriteLine(simulation.GetReport());
if (bestSimulation == default(ISimulation) || simulation.Earnings > bestSimulation.Earnings)
{
bestSimulation = simulation;
bestSimulationSmallEma = smallEma;
bestSimulationBigEma = bigEma;
}
//ShowSimulation(simulation, bars, smallEma, bigEma);
//Console.ReadKey(true);
}
}
}
}
Console.WriteLine("{0} configurations tested in {1}", configurationsCount, DateTime.Now - simulationsBegin);
Console.WriteLine("Best simulation");
ShowSimulation(bestSimulation, bars, bestSimulationSmallEma, bestSimulationBigEma);
Console.ReadKey(true);
}
static void ShowSimulation(ISimulation simulation, List <IBar> bars, TaResult smallEma, TaResult bigEma)
{
Console.WriteLine(simulation.GetReport());
ChartPool.ClearSeries();
ChartPool.AddSeries(
new List <Series> {
new Series("Prices", ChartType.Lines, Colors.Black, bars.Select(x => new Sample(x.DateTime, (double)x.Close))),
new Series("EMA Small", ChartType.Lines, Colors.Blue, smallEma.InstantValues.Select(x => new Sample(x.DateTime, x.Value))),
new Series("EMA Big", ChartType.Lines, Colors.DarkGreen, bigEma.InstantValues.Select(x => new Sample(x.DateTime, x.Value))),
new Series("Trades", ChartType.Trades, Colors.Purple, simulation.ClosedPositions.Select(x => new Trade(x.OpenDateTime, x.CloseDateTime, x.Side, (double)x.OpenPrice, (double)x.ClosePrice))),
}
);
}
static void ShowSimulation(ISimulation simulation, List <IBar> bars, TaResult indicator0, TaResult indicator1, TaResult indicator2, TaResult indicator3)
{
Console.WriteLine(simulation.GetReport());
ChartPool.ClearSeries();
ChartPool.AddSeries(
new List <Series> {
new Series("Prices", ChartType.Lines, Colors.Black, bars.Select(x => new Sample(x.DateTime, (double)x.Close))),
new Series("indicator0", ChartType.Lines, Colors.Blue, indicator0.InstantValues.Select(x => new Sample(x.DateTime, x.Value))),
new Series("indicator1", ChartType.Lines, Colors.DarkGreen, indicator1.InstantValues.Select(x => new Sample(x.DateTime, x.Value))),
new Series("indicator2", ChartType.Lines, Colors.DarkGreen, indicator2.InstantValues.Select(x => new Sample(x.DateTime, x.Value))),
new Series("indicator3", ChartType.Lines, Colors.DarkGreen, indicator3.InstantValues.Select(x => new Sample(x.DateTime, x.Value))),
new Series("Trades", ChartType.Trades, Colors.Purple, simulation.ClosedPositions.Select(x => new Trade(x.OpenDateTime, x.CloseDateTime, x.Side, (double)x.OpenPrice, (double)x.ClosePrice))),
}
);
}
private Dictionary <string, IInstantValue <double> > GetSeriesValues(int index)
{
Dictionary <string, IInstantValue <double> > seriesValues = new Dictionary <string, IInstantValue <double> >();
foreach (KeyValuePair <string, TaResult> serie in _series)
{
if (serie.Value.FirstValidSample > index)
{
return(null);
}
string serieKey = serie.Key;
TaResult serieValue = serie.Value;
seriesValues[serieKey] = serieValue.InstantValues[index];
}
return(seriesValues);
}
public BullPower(List <IBar> bars, int period)
{
InstantValues = new List <IInstantValue <double> >();
TaResult ema = bars.EMA(period);
int count = ema.Count;
if (count != bars.Count)
{
throw new Exception("Samples count can't be different");
}
FirstValidSample = ema.FirstValidSample;
for (int i = 0; i < count; i++)
{
DateTime dateTime = bars[i].DateTime;
double bullPower = 0;
if (i >= FirstValidSample)
{
double high = (double)bars[i].High;
double emaValue = ema.InstantValues[i].Value;
bullPower = high - emaValue;
}
InstantValues.Add(new InstantValue <double>(dateTime, bullPower));
}
}
static void TrainWithIndexData()
{
List <double[]> data = new List <double[]>();
var symbol = YSQSymbol.YSQIndex.SNP;
var begin = new DateTime(2004, 1, 1);
var end = new DateTime(2008, 1, 1);
var samplePackage = new YSQProvider().GetHistory(new Asset(symbol, AssetType.Index), begin, end, null);
var barPackage = (IBarPackage)samplePackage;
var bars = barPackage.Samples;
TaResult indicator0 = bars.SMA(7);
TaResult indicator1 = bars.SMA(14);
TaResult indicator2 = bars.SMA(24);
TaResult indicator3 = bars.SMA(60);
List <TaResult> indicatorsList = new List <TaResult> {
indicator0, indicator1, indicator2, indicator3
};
// discard bars and indicators previous to valid series
int firstValidSampleOnSeries = TaResult.GetFirstValidSample(indicatorsList);
Console.WriteLine("First valid sample on series: {0}", firstValidSampleOnSeries);
bars.RemoveRange(0, firstValidSampleOnSeries);
TaResult.DiscardFirstSamples(indicatorsList, firstValidSampleOnSeries);
Console.WriteLine("Invalid samples removed");
// possible answers
var stay = new double[] { 1, 0, 0 };
var goLong = new double[] { 0, 1, 0 };
var goShort = new double[] { 0, 0, 1 };
var deltaPrices = bars.Select(x => x.Close - x.Open).ToList();
var action = deltaPrices.Select(deltaPrice => {
var abs = Math.Abs(deltaPrice);
if (abs < 5)
{
return(stay);
}
if (deltaPrice < 0)
{
return(goShort);
}
return(goLong);
}).ToList();
Console.WriteLine("Times to stay: {0}", action.Count(x => x == stay));
Console.WriteLine("Times to go long: {0}", action.Count(x => x == goLong));
Console.WriteLine("Times to go short: {0}", action.Count(x => x == goShort));
int samplesCount = bars.Count;
for (int i = 0; i < samplesCount; i++)
{
var entry = new double[] {
indicator0.InstantValues[i].Value,
indicator1.InstantValues[i].Value,
indicator2.InstantValues[i].Value,
indicator3.InstantValues[i].Value,
action[i][0],
action[i][1],
action[i][2]
};
data.Add(entry);
}
NeuralNetwork neuralNetwork = Trainer.Execute(data);
ChartPool.CreateChart();
int takeProfitPoints = 15;
int stopLossPoints = 10;
decimal intensityThreshold = 0.0m;
indicator0.Normalize();
indicator1.Normalize();
indicator2.Normalize();
indicator3.Normalize();
var simulation = new NNSimulation(neuralNetwork, intensityThreshold, takeProfitPoints, stopLossPoints, true);
SimulationRunner simulationRunner = new SimulationRunner(bars, simulation);
simulationRunner.AddSerie("INDICATOR_0", indicator0);
simulationRunner.AddSerie("INDICATOR_1", indicator1);
simulationRunner.AddSerie("INDICATOR_2", indicator2);
simulationRunner.AddSerie("INDICATOR_3", indicator3);
simulationRunner.Execute();
ShowSimulation(simulation, bars, indicator0, indicator1, indicator2, indicator3);
}
