private void UpdatePriceChart(PriceSeries priceData)
{
// Create a new series and append Open, High, Low, Close data
_ohlcDataSeries = new OhlcDataSeries <DateTime, double>();
_ohlcDataSeries.Append(priceData.TimeData, priceData.OpenData, priceData.HighData, priceData.LowData, priceData.CloseData);
PriceData = (IOhlcDataSeries <DateTime, double>)(UseDiscontinuousDateTimeAxis ? new DiscontinuousAxisFilter <double>(_ohlcDataSeries, Calendar).FilteredDataSeries : _ohlcDataSeries);
PriceData.SeriesName = priceData.Symbol;
var xyDataSeries = new XyDataSeries <DateTime, double>();
xyDataSeries.Append(priceData.TimeData, priceData.CloseData);
var discontinuousSeries = new DiscontinuousAxisFilter <double>(xyDataSeries, Calendar).FilteredDataSeries as IDataSeries <DateTime, double>;
// Create a series for the 200 period SMA which will be plotted as a line chart
Sma200Series = UseDiscontinuousDateTimeAxis ? (IXyDataSeries <DateTime, double>) new MovingAverageFilter <DateTime>(discontinuousSeries, 200).FilteredDataSeries :
(IXyDataSeries <DateTime, double>) new MovingAverageFilter <DateTime>(xyDataSeries, 200).FilteredDataSeries;
Sma200Series.SeriesName = "200 SMA";
// Create a series for the 50 period SMA which will be plotted as a line chart
Sma50Series = UseDiscontinuousDateTimeAxis ? (IXyDataSeries <DateTime, double>) new MovingAverageFilter <DateTime>(discontinuousSeries, 50).FilteredDataSeries :
(IXyDataSeries <DateTime, double>) new MovingAverageFilter <DateTime>(xyDataSeries, 50).FilteredDataSeries;
Sma50Series.SeriesName = "50 SMA";
// Update the chart type and timeframe with current settings
UpdateChartType(_chartType);
}
public PricePaneModel(PriceSeries prices) : base(PRICES, "$%.4f", true)
{
var stockPrices = new OhlcDataSeries <DateTime, double> {
SeriesName = "EUR/USD"
};
stockPrices.Append(prices.TimeData, prices.OpenData, prices.HighData, prices.LowData, prices.CloseData);
AddRenderableSeries(new SCIFastCandlestickRenderableSeries
{
DataSeries = stockPrices,
YAxisId = PRICES,
StrokeUpStyle = new SCISolidPenStyle(0xff52cc54, 1f),
FillUpBrushStyle = new SCISolidBrushStyle(0xa052cc54),
StrokeDownStyle = new SCISolidPenStyle(0xffe26565, 1f),
FillDownBrushStyle = new SCISolidBrushStyle(0xd0e26565)
});
var maLow = new XyDataSeries <DateTime, double> {
SeriesName = "Low Line"
};
maLow.Append(prices.TimeData, prices.CloseData.MovingAverage(50));
AddRenderableSeries(new SCIFastLineRenderableSeries {
DataSeries = maLow, StrokeStyle = new SCISolidPenStyle(0xFFFF3333, 1f), YAxisId = PRICES
});
var maHigh = new XyDataSeries <DateTime, double> {
SeriesName = "High Line"
};
maHigh.Append(prices.TimeData, prices.CloseData.MovingAverage(200));
AddRenderableSeries(new SCIFastLineRenderableSeries {
DataSeries = maHigh, StrokeStyle = new SCISolidPenStyle(0xFF33DD33, 1f), YAxisId = PRICES
});
var priceMarker = new SCIAxisMarkerAnnotation
{
Position = stockPrices.YValues.ValueAt(stockPrices.Count - 1).ToComparable(),
Style = { BackgroundColor = 0xFFFF3333.ToColor() },
YAxisId = PRICES
};
var maLowMarker = new SCIAxisMarkerAnnotation
{
Position = maLow.YValues.ValueAt(maLow.Count - 1).ToComparable(),
Style = { BackgroundColor = 0xFFFF3333.ToColor() },
YAxisId = PRICES
};
var maHighMarker = new SCIAxisMarkerAnnotation
{
Position = maHigh.YValues.ValueAt(maHigh.Count - 1).ToComparable(),
Style = { BackgroundColor = 0xFF33DD33.ToColor() },
YAxisId = PRICES
};
Annotations.Add(priceMarker);
Annotations.Add(maLowMarker);
Annotations.Add(maHighMarker);
}
private void UpdateVolumeChart(PriceSeries prices)
{
// Create a new series and append Open, High, Low, Close data
VolumeData = new XyDataSeries <DateTime, long>();
VolumeData.SeriesName = string.Format("{0} Volume", prices.Symbol);
VolumeData.Append(prices.TimeData, prices.VolumeData);
}
private double SyncedRankCorrelation(PriceSeries inputSeries1, SyncedDataSeries inputSeries2, int corrPeriod)
// SyncedRankCorrelation: Calculate the Spearman Rank Correlation of 2 Data Series, using only the bars which are synchronized
//
// Inputs:
// inputSeries1: 1st DataSeries, typically Closes[x]
// inputSeries2: SyncedDataSeries, synced to InputSeries1; some bars (flagged by BoolSeries "Synced") hold valid (synchronized) values
// corrPeriod: Period for Correlation calculation; there must be >= CorrPeriod synced bars in the input series, or it will throw an exception
//
{
int index1 = 0;
double[] dataArray1 = new double[corrPeriod];
double[] dataArray2 = new double[corrPeriod];
for (int counter = corrPeriod - 1; counter >= 0; counter--)
{
while (!inputSeries2.Synced[index1]) //Find next synced Bar
{
index1++;
}
dataArray1[counter] = inputSeries1[index1];
dataArray2[counter] = inputSeries2[index1];
index1++;
}
return(KDRankCorrelation(dataArray1, dataArray2, corrPeriod));
}
public VolumePaneModel(PriceSeries prices) : base(VOLUME, "", false)
{
YAxis.NumberFormatter = new NSNumberFormatter
{
MaximumIntegerDigits = 3,
NumberStyle = NSNumberFormatterStyle.Scientific,
ExponentSymbol = @"E+"
};
var volumePrices = new XyDataSeries <DateTime, double> {
SeriesName = "Volume"
};
volumePrices.Append(prices.TimeData, prices.VolumeData.Select(x => (double)x));
AddRenderableSeries(new SCIFastColumnRenderableSeries
{
DataSeries = volumePrices,
YAxisId = VOLUME,
FillBrushStyle = new SCISolidBrushStyle(UIColor.White),
StrokeStyle = new SCISolidPenStyle(UIColor.White, 1f)
});
Annotations.Add(new SCIAxisMarkerAnnotation
{
Position = volumePrices.YValues.ValueAt(volumePrices.Count - 1).ToComparable(),
YAxisId = VOLUME,
});
}
private double SyncedPctChangeCorrelation(PriceSeries inputSeries1, SyncedDataSeries inputSeries2, int corrPeriod, int changeLookback)
{
int index = 0;
double[] pctChangeArray1 = new double[corrPeriod];
double[] pctChangeArray2 = new double[corrPeriod];
while (!inputSeries2.Synced[index]) //Find most recent synced Bar
{
index++;
}
double val1 = inputSeries1[index];
double val2 = inputSeries2[index];
index++;
for (int counter = corrPeriod - 1; counter >= 0; counter--)
{
int changeIndex;
while (!inputSeries2.Synced[index]) //Find previous synced Bar
{
index++;
}
double chg2 = inputSeries2.SyncedGet(changeLookback - 1, index, out changeIndex); // this will scan back more synced bars if changeLookback > 0
double chg1 = inputSeries1[changeIndex];
pctChangeArray1[counter] = (val1 - chg1) / chg1;
pctChangeArray2[counter] = (val2 - chg2) / chg2;
val1 = inputSeries1[index];
val2 = inputSeries2[index];
index++;
}
// return(KDRankCorrelation(pctChangeArray1,pctChangeArray2,corrPeriod)); // maybe rank correlation of PctChange would be better?
return(KDCorrelation(pctChangeArray1, pctChangeArray2, corrPeriod));
}
public MacdPaneModel(Context context, PriceSeries prices) : base(context, MACD, "0.0", false)
{
var macdPoints = prices.CloseData.Macd(12, 25, 9);
var histogramSeries = new XyDataSeries <DateTime, double> {
SeriesName = "Histogram"
};
histogramSeries.Append(prices.TimeData, macdPoints.Select(x => x.Divergence));
AddRenderableSeries(new FastColumnRenderableSeries {
DataSeries = histogramSeries, YAxisId = MACD
});
var macdSeries = new XyyDataSeries <DateTime, double> {
SeriesName = "MACD"
};
macdSeries.Append(prices.TimeData, macdPoints.Select(x => x.Macd), macdPoints.Select(x => x.Signal));
AddRenderableSeries(new FastBandRenderableSeries {
DataSeries = macdSeries, YAxisId = MACD
});
Annotations.Add(new AxisMarkerAnnotation(context)
{
Y1 = (Java.Lang.IComparable)histogramSeries.YValues.Get(histogramSeries.Count - 1), YAxisId = MACD
});
Annotations.Add(new AxisMarkerAnnotation(context)
{
Y1 = (Java.Lang.IComparable)macdSeries.YValues.Get(macdSeries.Count - 1), YAxisId = MACD
});
}
public StockPriceChart( string name, StockHandle stock, IPriceSeries prices )
{
Name = name;
Stock = stock;
Prices = new PriceSeries( prices );
IndicatorPoints = new Dictionary<string, IPriceSeries>();
Signals = SignalSeries.Null;
}
public StockPriceChart(string name, StockHandle stock, IPriceSeries prices)
{
Name = name;
Stock = stock;
Prices = new PriceSeries(prices);
IndicatorPoints = new Dictionary <string, IPriceSeries>();
Signals = SignalSeries.Null;
}
public void Apply_DayMissing_DataFromDayBeforeIsTaken()
{
var op = new InterpolateMissingDatesOperator();
var monday = new SimplePrice(new DateTime(2011, 1, 10), 123);
var weddnesday = new SimplePrice(new DateTime(2011, 1, 12), 456);
var input = new PriceSeries(SeriesIdentifier.Null, new[] { monday, weddnesday });
var series = op.Apply(input);
Assert.That(series[1].Value, Is.EqualTo(123));
}
public void Apply_LessOrEqualPointsThanMax_SeriesRemainsUnchanged()
{
var op = new ReducePointsOperator(2);
var monday = new SimplePrice(new DateTime(2011, 1, 10), 12);
var thuesday = new SimplePrice(new DateTime(2011, 1, 11), 23);
var input = new PriceSeries(SeriesIdentifier.Null, new[] { monday, thuesday });
var series = op.Apply(input);
Assert.That(series, Is.EquivalentTo(input));
}
public void Apply_NoDataForWeekend_NoDataInterpolatedForWeekend()
{
var op = new InterpolateMissingDatesOperator();
var friday = new SimplePrice(new DateTime(2011, 1, 7), 0);
var monday = new SimplePrice(new DateTime(2011, 1, 10), 0);
var input = new PriceSeries(SeriesIdentifier.Null, new[] { friday, monday });
var series = op.Apply(input);
Assert.That(series, Is.EquivalentTo(input));
}
public void Apply_NoDataForWeekend_NoDataInterpolatedForWeekend()
{
var op = new InterpolateMissingDatesOperator();
var friday = new SimplePrice( new DateTime( 2011, 1, 7 ), 0 );
var monday = new SimplePrice( new DateTime( 2011, 1, 10 ), 0 );
var input = new PriceSeries( SeriesIdentifier.Null, new[] { friday, monday } );
var series = op.Apply( input );
Assert.That( series, Is.EquivalentTo( input ) );
}
public void Apply_DayMissing_DataFromDayBeforeIsTaken()
{
var op = new InterpolateMissingDatesOperator();
var monday = new SimplePrice( new DateTime( 2011, 1, 10 ), 123 );
var weddnesday = new SimplePrice( new DateTime( 2011, 1, 12 ), 456 );
var input = new PriceSeries( SeriesIdentifier.Null, new[] { monday, weddnesday } );
var series = op.Apply( input );
Assert.That( series[ 1 ].Value, Is.EqualTo( 123 ) );
}
public void Apply_LessOrEqualPointsThanMax_SeriesRemainsUnchanged()
{
var op = new ReducePointsOperator( 2 );
var monday = new SimplePrice( new DateTime( 2011, 1, 10 ), 12 );
var thuesday = new SimplePrice( new DateTime( 2011, 1, 11 ), 23 );
var input = new PriceSeries( SeriesIdentifier.Null, new[] { monday, thuesday } );
var series = op.Apply( input );
Assert.That( series, Is.EquivalentTo( input ) );
}
public PricePaneModel(Context context, PriceSeries prices) : base(context, PRICES, "$0.0000", true)
{
var stockPrices = new OhlcDataSeries <DateTime, double> {
SeriesName = "EUR/USD"
};
stockPrices.Append(prices.TimeData, prices.OpenData, prices.HighData, prices.LowData, prices.CloseData);
AddRenderableSeries(new FastCandlestickRenderableSeries {
DataSeries = stockPrices, YAxisId = PRICES
});
var maLow = new XyDataSeries <DateTime, double> {
SeriesName = "Low Line"
};
maLow.Append(prices.TimeData, prices.CloseData.MovingAverage(50));
AddRenderableSeries(new FastLineRenderableSeries {
DataSeries = maLow, StrokeStyle = new SolidPenStyle(0xFFFF3333, 1f.ToDip(context)), YAxisId = PRICES
});
var maHigh = new XyDataSeries <DateTime, double> {
SeriesName = "High Line"
};
maHigh.Append(prices.TimeData, prices.CloseData.MovingAverage(200));
AddRenderableSeries(new FastLineRenderableSeries {
DataSeries = maHigh, StrokeStyle = new SolidPenStyle(0xFF33DD33, 1f.ToDip(context)), YAxisId = PRICES
});
var priceMarker = new AxisMarkerAnnotation(context)
{
Y1 = (Java.Lang.IComparable)stockPrices.YValues.Get(stockPrices.Count - 1), YAxisId = PRICES
};
priceMarker.SetBackgroundColor(0xFFFF3333.ToColor());
var maLowMarker = new AxisMarkerAnnotation(context)
{
Y1 = (Java.Lang.IComparable)maLow.YValues.Get(maLow.Count - 1), YAxisId = PRICES
};
maLowMarker.SetBackgroundColor(0xFFFF3333.ToColor());
var maHighMarker = new AxisMarkerAnnotation(context)
{
Y1 = (Java.Lang.IComparable)maHigh.YValues.Get(maHigh.Count - 1), YAxisId = PRICES
};
maHighMarker.SetBackgroundColor(0xFF33DD33.ToColor());
Annotations.Add(priceMarker);
Annotations.Add(maLowMarker);
Annotations.Add(maHighMarker);
}
public void Apply_NoDatesMissing_SeriesRemainsUnchanged()
{
var op = new InterpolateMissingDatesOperator();
var monday = new SimplePrice(new DateTime(2011, 1, 10), 12);
var thuesday = new SimplePrice(new DateTime(2011, 1, 11), 23);
var weddnesday = new SimplePrice(new DateTime(2011, 1, 12), 34);
var input = new PriceSeries(SeriesIdentifier.Null, new[] { monday, thuesday, weddnesday });
var series = op.Apply(input);
Assert.That(series, Is.EquivalentTo(input));
}
public IPriceSeries Apply(IPriceSeries series)
{
if (!series.Any())
{
return(series);
}
var descriptor = new ObjectDescriptor("InterpolatedMissingDates");
var seriesId = series.Identifier.Modify(descriptor);
return(PriceSeries.FromSortedSet(seriesId, FillMissingDates(series)));
}
public void Apply_NoDatesMissing_SeriesRemainsUnchanged()
{
var op = new InterpolateMissingDatesOperator();
var monday = new SimplePrice( new DateTime( 2011, 1, 10 ), 12 );
var thuesday = new SimplePrice( new DateTime( 2011, 1, 11 ), 23 );
var weddnesday = new SimplePrice( new DateTime( 2011, 1, 12 ), 34 );
var input = new PriceSeries( SeriesIdentifier.Null, new[] { monday, thuesday, weddnesday } );
var series = op.Apply( input );
Assert.That( series, Is.EquivalentTo( input ) );
}
public IPriceSeries Apply(IPriceSeries series)
{
double groupInterval = (double)series.Count / (double)myMaxPoints;
if (groupInterval <= 1)
{
return(series);
}
var descriptor = new ObjectDescriptor("ThinOut", ObjectDescriptor.Param("MaxCount", myMaxPoints));
var seriesId = series.Identifier.Modify(descriptor);
return(PriceSeries.FromSortedSet(seriesId, GroupPointsByAverage(series, (int)Math.Ceiling(groupInterval))));
}
public void Apply_MorePointsThanMax_DataGroupedByAverage()
{
var op = new ReducePointsOperator( 2 );
var monday = new SimplePrice( new DateTime( 2011, 1, 10 ), 10 );
var thuesday = new SimplePrice( new DateTime( 2011, 1, 11 ), 20 );
var weddnesday = new SimplePrice( new DateTime( 2011, 1, 12 ), 30 );
var input = new PriceSeries( SeriesIdentifier.Null, new[] { monday, thuesday, weddnesday } );
var series = op.Apply( input );
Assert.That( series.Count, Is.EqualTo( 2 ) );
Assert.That( series[ 0 ].Value, Is.EqualTo( 15 ) );
Assert.That( series[ 1 ].Value, Is.EqualTo( 30 ) );
}
public void Apply_MorePointsThanMax_DataGroupedByAverage()
{
var op = new ReducePointsOperator(2);
var monday = new SimplePrice(new DateTime(2011, 1, 10), 10);
var thuesday = new SimplePrice(new DateTime(2011, 1, 11), 20);
var weddnesday = new SimplePrice(new DateTime(2011, 1, 12), 30);
var input = new PriceSeries(SeriesIdentifier.Null, new[] { monday, thuesday, weddnesday });
var series = op.Apply(input);
Assert.That(series.Count, Is.EqualTo(2));
Assert.That(series[0].Value, Is.EqualTo(15));
Assert.That(series[1].Value, Is.EqualTo(30));
}
public VolumePaneModel(Context context, PriceSeries prices) : base(context, VOLUME, "###E+0", false)
{
var volumePrices = new XyDataSeries <DateTime, double> {
SeriesName = "Volume"
};
volumePrices.Append(prices.TimeData, prices.VolumeData.Select(x => (double)x));
AddRenderableSeries(new FastColumnRenderableSeries {
DataSeries = volumePrices, YAxisId = VOLUME
});
Annotations.Add(new AxisMarkerAnnotation(context)
{
Y1 = (Java.Lang.IComparable)volumePrices.YValues.Get(volumePrices.Count - 1), YAxisId = VOLUME
});
}
public RsiPaneViewModel(CreateMultiPaneStockChartsViewModel parentViewModel, PriceSeries prices)
: base(parentViewModel)
{
var rsiSeries = new XyDataSeries <DateTime, double>()
{
SeriesName = "RSI"
};
rsiSeries.Append(prices.TimeData, prices.Rsi(14));
ChartSeriesViewModels.Add(new LineRenderableSeriesViewModel {
DataSeries = rsiSeries
});
YAxisTextFormatting = "0.0";
Height = 100;
}
public RsiPaneModel(Context context, PriceSeries prices) : base(context, RSI, "0.0", false)
{
var rsiSeries = new XyDataSeries <DateTime, double> {
SeriesName = "RSI"
};
var xData = prices.TimeData;
var yData = prices.Rsi(14);
rsiSeries.Append(xData, yData);
AddRenderableSeries(new FastLineRenderableSeries {
DataSeries = rsiSeries, YAxisId = RSI
});
Annotations.Add(new AxisMarkerAnnotation(context)
{
Y1 = (Java.Lang.IComparable)rsiSeries.YValues.Get(rsiSeries.Count - 1), YAxisId = RSI
});
}
public PriceSeries GetPriceData(string dataset)
{
if (_dataSets.ContainsKey(dataset))
{
return(_dataSets[dataset]);
}
// e.g. resource format: Abt.Controls.SciChart.Example.Resources.EURUSD_Daily.csv
var csvResource = string.Format("{0}.{1}", ResourceDirectory, Path.ChangeExtension(dataset, "csv"));
var priceSeries = new PriceSeries();
priceSeries.Symbol = dataset;
var assembly = typeof(DataManager).Assembly;
// Debug.WriteLine(string.Join(", ", assembly.GetManifestResourceNames()));
using (var stream = assembly.GetManifestResourceStream(csvResource))
using (var streamReader = new StreamReader(stream))
{
string line = streamReader.ReadLine();
while (line != null)
{
var priceBar = new PriceBar();
// Line Format:
// Date, Open, High, Low, Close, Volume
// 2007.07.02 03:30, 1.35310, 1.35310, 1.35280, 1.35310, 12
var tokens = line.Split(',');
priceBar.DateTime = DateTime.Parse(tokens[0], DateTimeFormatInfo.InvariantInfo);
priceBar.Open = double.Parse(tokens[1], NumberFormatInfo.InvariantInfo);
priceBar.High = double.Parse(tokens[2], NumberFormatInfo.InvariantInfo);
priceBar.Low = double.Parse(tokens[3], NumberFormatInfo.InvariantInfo);
priceBar.Close = double.Parse(tokens[4], NumberFormatInfo.InvariantInfo);
priceBar.Volume = long.Parse(tokens[5], NumberFormatInfo.InvariantInfo);
priceSeries.Add(priceBar);
line = streamReader.ReadLine();
}
}
_dataSets.Add(dataset, priceSeries);
return(priceSeries);
}
private void UpdatePriceChart(PriceSeries priceData)
{
// Create a new series and append Open, High, Low, Close data
_ohlcDataSeries = new OhlcDataSeries <DateTime, double>();
_ohlcDataSeries.Append(priceData.TimeData, priceData.OpenData, priceData.HighData, priceData.LowData, priceData.CloseData);
PriceData = (IOhlcDataSeries <DateTime, double>)(UseDiscontinuousDateTimeAxis ? _ohlcDataSeries.ToDiscontinuousSeries(Calendar) : _ohlcDataSeries);
PriceData.SeriesName = priceData.Symbol;
// Create a series for the 200 period SMA which will be plotted as a line chart
Sma200Series = (IXyDataSeries <DateTime, double>)PriceData.ToMovingAverage(200);
Sma200Series.SeriesName = "200 SMA";
// Create a series for the 50 period SMA which will be plotted as a line chart
Sma50Series = (IXyDataSeries <DateTime, double>)PriceData.ToMovingAverage(50);
Sma50Series.SeriesName = "50 SMA";
// Update the chart type and timeframe with current settings
UpdateChartType(_chartType);
}
public RsiPaneModel(PriceSeries prices) : base(RSI, "%.1f", false)
{
var rsiSeries = new XyDataSeries <DateTime, double> {
SeriesName = "RSI"
};
var xData = prices.TimeData;
var yData = prices.Rsi(14);
rsiSeries.Append(xData, yData);
AddRenderableSeries(new SCIFastLineRenderableSeries {
DataSeries = rsiSeries, YAxisId = RSI, StrokeStyle = new SCISolidPenStyle(0xFFC6E6FF, 1f)
});
Annotations.Add(new SCIAxisMarkerAnnotation
{
Position = rsiSeries.YValues.ValueAt(rsiSeries.Count - 1).ToComparable(),
YAxisId = RSI
});
}
private double SyncedCorrelation(PriceSeries inputSeries1, SyncedDataSeries inputSeries2, int corrPeriod)
// SyncedCorrelation: Calculates the Pearson Product Moment Correlation of 2 Data Series, using only the bars which are synchronized
// Note: Correlations may differ from Excel if NinjaTrader is set to dividend-adjust historical prices
//
// Inputs:
// inputSeries1: 1st DataSeries, typically Closes[x]
// inputSeries2: SyncedDataSeries, synced to InputSeries1; some bars (flagged by BoolSeries "Synced") hold valid (synchronized) values
// corrPeriod: Period for Correlation calculation; there must be >= CorrPeriod synced bars in the input series, or it will throw an exception
//
{
double sum1 = 0;
double sum2 = 0;
double sum3 = 0;
int index1 = 0;
double mean1, mean2, variance1, variance2, denominator;
mean1 = SyncedSMA(inputSeries1, inputSeries2.Synced, corrPeriod);
mean2 = SyncedSMA(inputSeries2, inputSeries2.Synced, corrPeriod);
for (int counter = 0; counter < corrPeriod; counter++)
{
while (!inputSeries2.Synced[index1]) //Find next synced Bar
{
index1++;
}
variance1 = inputSeries1[index1] - mean1;
variance2 = inputSeries2[index1] - mean2;
sum1 += variance1 * variance2;
sum2 += variance1 * variance1;
sum3 += variance2 * variance2;
index1++;
}
denominator = Math.Sqrt(sum2 * sum3);
if (denominator == 0)
{
return(0); // avoid divide-by-zero error; not really the correct result (actual correlation is undefined)
}
else
{
return(sum1 / denominator);
}
}
public VolumePaneModel(PriceSeries prices) : base(VOLUME, "###E+0", false)
{
var volumePrices = new XyDataSeries <DateTime, double> {
SeriesName = "Volume"
};
volumePrices.Append(prices.TimeData, prices.VolumeData.Select(x => (double)x));
AddRenderableSeries(new SCIFastColumnRenderableSeries
{
DataSeries = volumePrices,
YAxisId = VOLUME,
FillBrushStyle = new SCISolidBrushStyle(UIColor.White),
StrokeStyle = new SCISolidPenStyle(UIColor.White, 1f)
});
Annotations.Add(new SCIAxisMarkerAnnotation
{
Position = volumePrices.YValues.ValueAt(volumePrices.Count - 1).ToComparable(),
YAxisId = VOLUME,
});
}
public MacdPaneModel(PriceSeries prices) : base(MACD, "%.2f", false)
{
var macdPoints = prices.CloseData.Macd(12, 25, 9);
var histogramSeries = new XyDataSeries <DateTime, double> {
SeriesName = "Histogram"
};
histogramSeries.Append(prices.TimeData, macdPoints.Select(x => x.Divergence));
AddRenderableSeries(new SCIFastColumnRenderableSeries {
DataSeries = histogramSeries, YAxisId = MACD, StrokeStyle = new SCISolidPenStyle(UIColor.White, 1f)
});
var macdSeries = new XyyDataSeries <DateTime, double> {
SeriesName = "MACD"
};
macdSeries.Append(prices.TimeData, macdPoints.Select(x => x.Macd), macdPoints.Select(x => x.Signal));
AddRenderableSeries(new SCIFastBandRenderableSeries
{
DataSeries = macdSeries,
YAxisId = MACD,
FillBrushStyle = new SCISolidBrushStyle(UIColor.Clear),
StrokeStyle = new SCISolidPenStyle(0xffe26565, 1f),
FillY1BrushStyle = new SCISolidBrushStyle(UIColor.Clear),
StrokeY1Style = new SCISolidPenStyle(0xff52cc54, 1f)
});
Annotations.Add(new SCIAxisMarkerAnnotation
{
Position = histogramSeries.YValues.ValueAt(histogramSeries.Count - 1).ToComparable(),
YAxisId = MACD
});
Annotations.Add(new SCIAxisMarkerAnnotation
{
Position = macdSeries.YValues.ValueAt(macdSeries.Count - 1).ToComparable(),
YAxisId = MACD
});
}
private void UpdateChartData(BarStyle barStyle)
{
PriceSeries priceData = null;
switch (barStyle)
{
case BarStyle.TimeBar:
priceData = TicksAggregator.GetPriceDataByTimeFrame(_ticks, _selectedTimeFrame, _calendar, out _min, out _max);
break;
case BarStyle.VolumeBar:
priceData = TicksAggregator.GetPriceDataByVolume(_ticks, _selectedVolume, _calendar, _barTimeFrame, out _min, out _max);
break;
case BarStyle.RangeBar:
priceData = TicksAggregator.GetPriceDataByRange(_ticks, _selectedRange, _calendar, _barTimeFrame, out _min, out _max);
break;
}
UpdatePriceChart(priceData);
_priceSeries.InvalidateParentSurface(RangeMode.ZoomToFit);
}
public void SavePrices(IEnumerable <PriceParserResult> priceData)
{
var dateNow = DateTime.Now;
var priceSeries = new List <PriceSeries>();
var dbPriceDetails = priceRepository.GetPriceDetails();
foreach (var price in priceData)
{
var priceSerie = new PriceSeries();
priceSerie.CreatedDate = dateNow;
priceSerie.ParserId = price.ParserConfigId;
priceSerie.Price = price.Price;
var existingPriceDetail = dbPriceDetails
.Where(pd => pd.RetailerNo == price.ProductNo)
.OrderByDescending(pd => pd.Id)
.FirstOrDefault();
if (existingPriceDetail == null)
{
var priceDetailsItem = new PriceDetails();
priceDetailsItem.Title = price.Title;
priceDetailsItem.RetailerNo = price.ProductNo;
priceDetailsItem.CreatedDate = dateNow;
priceRepository.SavePriceDetails(priceDetailsItem);
existingPriceDetail = priceDetailsItem;
}
priceSerie.PriceDetailsId = existingPriceDetail.Id;
priceSeries.Add(priceSerie);
}
priceRepository.SavePrices(priceSeries);
}
private void UpdatePriceChart(AggregationPriceChart barStyle)
{
switch (barStyle)
{
case AggregationPriceChart.Count:
PriceSeries = (IOhlcDataSeries <DateTime, double>)_priceData.AggregateByCount(_selectedCount);
break;
case AggregationPriceChart.Time:
PriceSeries = (IOhlcDataSeries <DateTime, double>)_priceData.AggregateByTime(TimeSpan.FromMinutes(_selectedTimeFrame));
break;
case AggregationPriceChart.Volume:
PriceSeries = (IOhlcDataSeries <DateTime, double>)_priceData.AggregateByVolume(_ticks.Select(x => x.Volume.ToDouble()).ToList(), _selectedVolume);
break;
case AggregationPriceChart.Range:
PriceSeries = (IOhlcDataSeries <DateTime, double>)_priceData.AggregateByRange(_selectedRange);
break;
case AggregationPriceChart.Renko:
PriceSeries = (IOhlcDataSeries <DateTime, double>)_priceData.AggregateByRenko(_selectedBrickSize);
break;
}
PriceSeries.SeriesName = "PriceData";
// Create a series for the 200 period SMA which will be plotted as a line chart
Sma200Series = (IXyDataSeries <DateTime, double>)PriceSeries.ToMovingAverage(200);
Sma200Series.SeriesName = "200 SMA";
// Create a series for the 50 period SMA which will be plotted as a line chart
Sma50Series = (IXyDataSeries <DateTime, double>)PriceSeries.ToMovingAverage(50);
Sma50Series.SeriesName = "50 SMA";
_priceSeries.InvalidateParentSurface(RangeMode.ZoomToFit);
}
private void UpdatePriceChart(PriceSeries priceData)
{
// Create a new series and append Open, High, Low, Close data
this.PriceData = new OhlcDataSeries <DateTime, double>();
PriceData.SeriesName = priceData.Symbol;
PriceData.Append(priceData.TimeData, priceData.OpenData, priceData.HighData, priceData.LowData, priceData.CloseData);
// Create a series for the 200 period SMA which will be plotted as a line chart
Sma200Series = new XyDataSeries <DateTime, double>();
Sma200Series.SeriesName = "200 SMA";
var ma200 = DataManager.Instance.ComputeMovingAverage(priceData.CloseData, 200);
Sma200Series.Append(priceData.TimeData, ma200);
// Create a series for the 50 period SMA which will be plotted as a line chart
Sma50Series = new XyDataSeries <DateTime, double>();
Sma50Series.SeriesName = "50 SMA";
var ma50 = DataManager.Instance.ComputeMovingAverage(priceData.CloseData, 50);
Sma50Series.Append(priceData.TimeData, ma50);
// Update the chart type and timeframe with current settings
UpdateChartType(_chartType);
}
private double SyncedResidualCorrelation(PriceSeries inputSeries1, SyncedDataSeries inputSeries2, int corrPeriod)
// Correlation of residuals (residual = error = difference between actual values and linear regression line)
{
int index1 = 0;
double[] residualArray1 = new double[corrPeriod];
double[] residualArray2 = new double[corrPeriod];
double[] dataArray1 = new double[corrPeriod];
double[] dataArray2 = new double[corrPeriod];
for (int counter = corrPeriod - 1; counter >= 0; counter--)
{
while (!inputSeries2.Synced[index1]) //Find next synced Bar
{
index1++;
}
dataArray1[counter] = inputSeries1[index1];
dataArray2[counter] = inputSeries2[index1];
index1++;
}
KDResidual(dataArray1, corrPeriod, residualArray1);
KDResidual(dataArray2, corrPeriod, residualArray2);
// return(KDRankCorrelation(residualArray1,residualArray2,corrPeriod)); // maybe rank correlation of residuals would be better?
return(KDCorrelation(residualArray1, residualArray2, corrPeriod));
}
private PriceBar Next(PriceSeries priceSeries)
{
return priceSeries[_currentIndex++];
}
public PriceSeries GetRandomTrades(out List<Trade> trades, out List<NewsEvent> news)
{
var priceSeries = new PriceSeries();
trades = new List<Trade>();
news = new List<NewsEvent>();
var startDate = new DateTime(2012, 01, 01);
double randomWalk = 0.0;
// Note: Change the value below to increase or decrease the point count and trade frequency
const int Count = 1000;
const uint TradeFrequency = 14;
// Generate the X,Y data with sequential dates on the X-Axis and slightly positively biased random walk on the Y-Axis
for (int i = 0; i < Count; i++)
{
randomWalk += (_random.NextDouble() - 0.498);
priceSeries.Add(new PriceBar(startDate.AddMinutes(i*10), randomWalk, randomWalk, randomWalk, randomWalk, 0));
}
// The random walk is a truly random series, so it may contain negative values. Here we find the minimum and offset it
// so it is always positive.
double yOffset = -priceSeries.CloseData.Min() + _random.NextDouble();
for (int i = 0; i < Count; i++)
{
// Now update with the offset so it is never negative
priceSeries[i].Close += yOffset;
// Every N'th tick create a random trade
if (i % TradeFrequency == 0)
{
var trade = new Trade();
// randomize buy or sell
trade.BuySell = _random.NextDouble() > 0.48 ? BuySell.Buy : BuySell.Sell;
// Set dealprice and date
trade.DealPrice = priceSeries[i].Close;
trade.TradeDate = priceSeries[i].DateTime;
// Set instrument and quantity
trade.Instrument = Instrument.CrudeOil;
trade.Quantity = _random.Next(100, 500);
trades.Add(trade);
}
// Every N'th tick create a random news event
if (_random.Next(0, 99) > 95)
{
var newsEvent = new NewsEvent();
newsEvent.EventDate = priceSeries[i].DateTime;
newsEvent.Headline = "OPEC meeting minutes";
newsEvent.Body = "The Organization of the Petroleum Exporting Countries voted today to increase production of Crude oil from its member states";
news.Add(newsEvent);
}
}
return priceSeries;
}
public PriceSeries GetPriceData(string dataset)
{
if (_dataSets.ContainsKey(dataset))
{
return _dataSets[dataset];
}
// e.g. resource format: Abt.Controls.SciChart.Example.Resources.EURUSD_Daily.csv
var csvResource = string.Format("{0}.{1}", ResourceDirectory, Path.ChangeExtension(dataset, "csv"));
var priceSeries = new PriceSeries();
priceSeries.Symbol = dataset;
var assembly = typeof(DataManager).Assembly;
// Debug.WriteLine(string.Join(", ", assembly.GetManifestResourceNames()));
using (var stream = assembly.GetManifestResourceStream(csvResource))
using (var streamReader = new StreamReader(stream))
{
string line = streamReader.ReadLine();
while (line != null)
{
var priceBar = new PriceBar();
// Line Format:
// Date, Open, High, Low, Close, Volume
// 2007.07.02 03:30, 1.35310, 1.35310, 1.35280, 1.35310, 12
var tokens = line.Split(',');
priceBar.DateTime = DateTime.Parse(tokens[0], DateTimeFormatInfo.InvariantInfo);
priceBar.Open = double.Parse(tokens[1], NumberFormatInfo.InvariantInfo);
priceBar.High = double.Parse(tokens[2], NumberFormatInfo.InvariantInfo);
priceBar.Low = double.Parse(tokens[3], NumberFormatInfo.InvariantInfo);
priceBar.Close = double.Parse(tokens[4], NumberFormatInfo.InvariantInfo);
priceBar.Volume = long.Parse(tokens[5], NumberFormatInfo.InvariantInfo);
priceSeries.Add(priceBar);
line = streamReader.ReadLine();
}
}
_dataSets.Add(dataset, priceSeries);
return priceSeries;
}
