private ChartPointsPredition Predict(TimeFrame TFrame, string product, int deep, int ahead, int position, List <ChartPoint> LCPoints)
{
int iDeep = deep;
int iAhead = ahead;
if (position < iDeep)
{
return(null);
}
int iDecimals = int.Parse(OSBlotter.Get(product).DecimalPlaces);
int iMinMatches = 1;
double dMinResolution = 1;
List <ChartPoint> LCPSub = LCPoints.GetRange(0, position);
List <ChartPoint> LCPSubSpecified = LCPoints.GetRange(position - iDeep, iDeep);
//List<ChartPoint> LCPSubPredicted = LCPoints.GetRange(position, iAhead);//TODO comment
ChartPointsPredition CPsP = ANALYSIS.PredictNextSpecified(product, LCPSub, LCPSubSpecified, TFrame, iDecimals, iMinMatches, dMinResolution, iAhead, new double[] { 0, 0, 0, 0, 0 });
CPsP.Prognosis(0);
CPsP.Position = position;
return(CPsP);
}
public double WeightFactor(Rates RATE, int position, int deep, int ahead, bool averange, double step, double range, int setID) //symilarity must be above 60%
{
string product = RATE.CCY_Pair;
TimeFrame TFrame = TimeFrame.ONE_MINUTE;
int iDecimals = RATE.Decimals;
double dPipValue = Math.Pow(10, -iDecimals);
List <ChartPoint> LCPoints = ARCHIVE.GetDATA(TFrame, product, 0, position);
List <ChartPoint> LCPointsSpecified = ARCHIVE.GetDATA(TFrame, product, position - deep, deep);
List <ChartPoint> LCPointsAll = ARCHIVE.GetDATA(TFrame, product, 0, position + ahead);
List <double> LDSetChange = (from CP in LCPointsAll select Math.Round(CP.Change, iDecimals)).ToList();
List <double> LDSetPeak = (from CP in LCPointsAll select Math.Round(CP.Peak, iDecimals)).ToList();
List <double> LDSetBase = (from CP in LCPointsAll select Math.Round(CP.Base, iDecimals)).ToList();
//double dTopSubSim = 0;
//
List <double> LDWFactors = new List <double>();
List <double> LDSymilarities = new List <double>();
double[] DAWeightFactor = new double[5];
for (double dWF = -step * range; dWF <= step * range; dWF += step)
{
DAWeightFactor[setID] = dWF;
ChartPointsPredition CPsPrediction = new ChartPointsPredition();
ChartPointsPredition CPsPredictionNow = new ChartPointsPredition();
double dSymilMax = 90;
double dSymilMin = 50;
do
{
double dSymil = (dSymilMax + dSymilMin) / 2;
ChartPointsPredition CPsP = null;// this.PredictNextSpecified(product, LCPoints, LCPointsSpecified, TFrame, iDecimals, dSymil, ahead, DAWeightFactor);
if (CPsP.Prognosis(1) != ChartPointsPredition.Kind.Uncertain)
{
CPsPredictionNow = CPsP;
}
if (CPsP.Matches < 10)
{
dSymilMax = dSymil;
}
else
{
dSymilMin = dSymil;
}
if ((dSymilMax - dSymilMin <= 1) || (CPsPredictionNow.Matches >= 10 && CPsPredictionNow.Matches < 50 && CPsPredictionNow.Analised))
{
CPsPrediction = CPsPredictionNow;
break;
}
} while (true);
if (CPsPrediction.Matches == 0)
{
continue;
}
double dSimChange = this.Compare(LDSetChange, CPsPrediction.LDChange, position);
double dSimPeak = this.Compare(LDSetPeak, CPsPrediction.LDPeak, position);
double dSimBase = this.Compare(LDSetBase, CPsPrediction.LDBase, position);
double dSubSim = (dSimChange * dSimPeak * dSimBase) / (100 * 100);
LDWFactors.Add(dWF);
LDSymilarities.Add(dSubSim);
}
double dLESum = 0;
double dGESum = 0;
int iGECount = 0;
int iLECount = 0;
for (int i = 0; i < LDWFactors.Count; i++)
{
if (LDWFactors[i] > 0)
{
dGESum += LDSymilarities[i];
++iGECount;
}
else if (LDWFactors[i] < 0)
{
dLESum += LDSymilarities[i];
++iLECount;
}
}
double dGES = dGESum / iGECount;
double dLES = dLESum / iLECount;
double dTobWF = 0;
double dTopSubSim = 0;
if (!averange)
{
for (int i = 0; i < LDWFactors.Count; i++)
{
if (((dGES > dLES) && LDWFactors[i] > 0 && LDSymilarities[i] > dTopSubSim) ||
((dGES < dLES) && LDWFactors[i] < 0 && LDSymilarities[i] > dTopSubSim))
{
dTopSubSim = LDSymilarities[i];
dTobWF = LDWFactors[i];
}
}
}
else
{
double dSumWF = 0;
double dSumWeightWF = 0;
for (int i = 0; i < LDWFactors.Count; i++)
{
if ((dGES > dLES && LDWFactors[i] > 0) || (dGES < dLES && LDWFactors[i] < 0))
{
dSumWF += LDWFactors[i] * LDSymilarities[i];
dSumWeightWF += LDSymilarities[i];
dTobWF = dSumWF / dSumWeightWF;
}
}
}
return(dTobWF);
}
public double CheckSimilarity(Rates RATE, int position, int deep, int ahead, double[] DAWeightFacotrs) //symilarity must be above 60%
{
string product = RATE.CCY_Pair;
TimeFrame TFrame = TimeFrame.ONE_MINUTE;
int iDecimals = RATE.Decimals;
double dPipValue = Math.Pow(10, -iDecimals);
List <ChartPoint> LCPoints = ARCHIVE.GetDATA(TFrame, product, 0, position);
List <ChartPoint> LCPointsSpecified = ARCHIVE.GetDATA(TFrame, product, position - deep, deep);
List <ChartPoint> LCPointsAll = ARCHIVE.GetDATA(TFrame, product, 0, position + ahead);
List <double> LDSetChange = (from CP in LCPointsAll select Math.Round(CP.Change, iDecimals)).ToList();
List <double> LDSetPeak = (from CP in LCPointsAll select Math.Round(CP.Peak, iDecimals)).ToList();
List <double> LDSetBase = (from CP in LCPointsAll select Math.Round(CP.Base, iDecimals)).ToList();
ChartPointsPredition CPsPrediction = new ChartPointsPredition();
ChartPointsPredition CPsPredictionNow = new ChartPointsPredition();
double dSymilMax = 90;
double dSymilMin = 50;
do
{
double dSymil = (dSymilMax + dSymilMin) / 2;
ChartPointsPredition CPsP = null; // this.PredictNextSpecified(product, LCPoints, LCPointsSpecified, TFrame, iDecimals, dSymil, ahead, DAWeightFacotrs);
if (CPsP.Prognosis(1) != ChartPointsPredition.Kind.Uncertain)
{
CPsPredictionNow = CPsP;
}
if (CPsP.Matches < 10)
{
dSymilMax = dSymil;
}
else
{
dSymilMin = dSymil;
}
if ((dSymilMax - dSymilMin <= 1) || (CPsPredictionNow.Matches >= 10 && CPsPredictionNow.Matches < 50 && CPsPredictionNow.Analised))
{
CPsPrediction = CPsPredictionNow;
break;
}
} while (true);
if (CPsPrediction.Matches == 0)
{
return(0);
}
double dSimChange = this.Compare(LDSetChange, CPsPrediction.LDChange, position);
double dSimPeak = this.Compare(LDSetPeak, CPsPrediction.LDPeak, position);
double dSimBase = this.Compare(LDSetBase, CPsPrediction.LDBase, position);
double dSubSim = (dSimChange * dSimPeak * dSimBase) / (100 * 100);
return(dSubSim);
}
