public void TestCalculateRealData()
{
TickerBLL tbll = new TickerBLL(_unit);
List <Ticker> tList = tbll.GetTickerListByShareDB(1585, null, 21100000);
double[] inputData = new double[tList.Count];
double[] h = new double[tList.Count];
double[] lo = new double[tList.Count];
double?[] k = new double?[tList.Count];
double?[] d = new double?[tList.Count];
var i = 0;
foreach (var t in tList)
{
inputData[i] = t.Close;
h[i] = t.High;
lo[i] = t.Low;
i++;
}
Result res = Stochastic.CalculateSlow(inputData, h, lo, 14, 3, k, d);
}
/// <summary>
/// Реализация эксперимента
/// </summary>
public void CalcExper()
{
double minI = 0.2, maxI = 1.2;
double minQ = 3, maxQ = 10;
int step = 3, nExp = 100;
TextWriter tw = new StreamWriter("res.txt");
for (double i = minI; i <= maxI; i += (maxI - minI) / step)
{
for (double q = minQ; q <= maxQ; q += (maxQ - minQ) / step)
{
for (int j = 0; j < nExp; j++)
{
this.sI = new Stochastic(dl: 2, scl: i);
this.sQ = new Stochastic(dl: 1, loc: q, scl: q / 5);
double[] sc = new double[4];
while (sc[0] <= 0 || double.IsPositiveInfinity(sc[0]))
{
sc = simplexCoeffs();
}
tw.WriteLine("{0}\t{1}\t{2}\t{3}\t{4}", i, q, sc[0], sc[1], sc[3]);
//tw.WriteLine("{0}\t{1}\t{2}", i, q, SimulateTS());
}
}
}
tw.Close();
}
public void TestCalculate()
{
double[] high = new double[] {
127.01, 127.62, 126.59, 127.35, 128.17,
128.43, 127.37, 126.42, 126.90, 126.85,
125.65, 125.72, 127.16, 127.72, 127.69,
128.22, 128.27, 128.09, 128.27, 127.74,
128.77, 129.29, 130.06, 129.12, 129.29,
128.47, 128.09, 128.65, 129.14, 128.64
};
double[] low = new double[] {
125.36, 126.16, 124.93, 126.09, 126.82,
126.48, 126.03, 124.83, 126.39, 125.72,
124.56, 124.57, 125.07, 126.86, 126.63,
126.80, 126.71, 126.80, 126.13, 125.92,
126.99, 127.81, 128.47, 128.06, 127.61,
127.60, 127.00, 126.90, 127.49, 127.40
};
double[] close = new double[] {
0, 0, 0, 0, 0,
0, 0, 0, 0, 0,
0, 0, 0, 127.29, 127.18,
128.01, 127.11, 127.73, 127.06, 127.33,
128.71, 127.87, 128.58, 128.60, 127.93,
128.11, 127.60, 127.60, 128.69, 128.27
};
double?[] k = new double?[close.Length];
double?[] d = new double?[close.Length];
Stochastic.CalculateSlow(close, high, low, 14, 3, k, d);
}
public override void GetAll(IIndicatorValues Ind)
{
int period = (int)this.IndicatorParameters.List[0];
int firstSmoothingPeriod = (int)this.IndicatorParameters.List[1];
int secondSmoothingPeriod = (int)this.IndicatorParameters.List[2];
decimal thresholdPercentage = (decimal)this.IndicatorParameters.List[3];
if (!Ind.SlowStochastic(period, firstSmoothingPeriod, secondSmoothingPeriod, thresholdPercentage).IsPopulated)
{
int oldCurrentBar = Ind.Bar.CurrentBar;
for (int i = 1; i <= Ind.Bar.MaxBar; i++)
{
Ind.Bar.CurrentBar = i;
object prototype = null;
if (i == 1)
{
prototype = new Stochastic(thresholdPercentage);
}
else
{
prototype = (Stochastic)Ind.SlowStochastic(period, firstSmoothingPeriod, secondSmoothingPeriod, thresholdPercentage)[1].Clone();
}
Get(ref prototype, Ind);
Ind.SlowStochastic(period, firstSmoothingPeriod, secondSmoothingPeriod, thresholdPercentage)[0] = (Stochastic)prototype;
Ind.SlowStochastic(period, firstSmoothingPeriod, secondSmoothingPeriod, thresholdPercentage).IsPopulated = true; // set here so instance is guaranteed to exits
}
Ind.Bar.CurrentBar = oldCurrentBar;
}
}
public void PrimaryOutputIsFastStochProperty()
{
var stochastics = new Stochastic("sto", 12, 3, 5);
TestHelper.TestIndicator(stochastics, "spy_with_stoch12k3.txt", "Stochastics 12 %K 3",
(ind, expected) => Assert.Equal(((Stochastic)ind).FastStoch.Current.Price, ind.Current.Price));
}
public async Task<IndStochasticEntity[]> GetStochastic(string code, int period = 14, int slow =3, int start = 0, int end = 0, string type = "day")
{
TickerEntity[] tickers = await base.getTickerEntityArray(code, start, end, type);
List<IndStochasticEntity> outList = new List<IndStochasticEntity>();
int len = tickers.Length;
double[] close = tickers.Select(t => (double)t.C).ToArray();
double[] high = tickers.Select(t => (double)t.H).ToArray();
double[] low = tickers.Select(t => (double)t.L).ToArray();
double?[] outK = new double?[len];
double?[] outD = new double?[len];
Stochastic.CalculateSlow(close, high, low, period, slow, outK, outD);
for (int i = 0; i < len; i++)
{
outList.Add(new IndStochasticEntity
{
T = tickers[i].T,
P = tickers[i].P,
K = outK[i],
D = outD[i]
});
}
return outList.Where(r => (start == 0 || r.P >= start) && (end == 0 || r.P <= end)).ToArray();
}
/// <summary>
/// Creates a new Stochastic indicator.
/// </summary>
/// <param name="symbol">The symbol whose stochastic we seek</param>
/// <param name="resolution">The resolution.</param>
/// <param name="period">The period of the stochastic. Normally 14</param>
/// <param name="kPeriod">The sum period of the stochastic. Normally 14</param>
/// <param name="dPeriod">The sum period of the stochastic. Normally 3</param>
/// <returns>Stochastic indicator for the requested symbol.</returns>
public Stochastic STO(string symbol, int period, int kPeriod, int dPeriod, Resolution?resolution = null)
{
string name = CreateIndicatorName(symbol, "STO", resolution);
var stoch = new Stochastic(name, period, kPeriod, dPeriod);
RegisterIndicator(symbol, stoch, resolution);
return(stoch);
}
public void ComparesAgainstExternalDataOnStochasticsK()
{
var stochastics = new Stochastic("sto", 12, 3, 5);
const double epsilon = 1e-3;
TestHelper.TestIndicator(stochastics, "spy_with_stoch12k3.txt", "Stochastics 12 %K 3",
(ind, expected) => ((double)((Stochastic)ind).StochK.Current.Price).Should()
.BeApproximately(expected, epsilon));
}
protected override void Create()
{
m_Stochastic = new Stochastic(this);
m_oFastK = new VariableSeries <Double>(this);
m_oFastD = new VariableSeries <Double>(this);
m_oSlowK = new VariableSeries <Double>(this);
m_oSlowD = new VariableSeries <Double>(this);
m_StochLE =
OrderCreator.MarketNextBar(new SOrderParameters(Contracts.Default, "StochLE", EOrderAction.Buy));
}
public void ComparesAgainstExternalDataOnStochasticsD()
{
var stochastics = new Stochastic("sto", 12, 3, 5);
const double epsilon = 1e-3;
TestHelper.TestIndicator(stochastics, "spy_with_stoch12k3.txt", "%D 5",
(ind, expected) => Assert.AreEqual(expected, (double)((Stochastic)ind).StochD.Current.Value, epsilon)
);
}
public void D_Single_SimpleValues_Calculated()
{
//Given
double[] data = { 1, 2, 3, 4, 5, 6, 5, 8, 4, 7 };
//When
var result = Stochastic.D_Single(data, period: 5, k_period: 3);
//Then
Assert.Equal(88.89D, Math.Round(result.Value, 2));
}
public void K_Single_SimpleValues_Calculated()
{
//Given
double[] data = { 1, 2, 3, 4, 5, 6, 5, 8, 4, 7 };
//When
var result = Stochastic.K_Single(data, period: 5);
//Then
Assert.Equal(75D, result);
}
public void D_Single_DataLengthLessThanPeriod_ReturnZero()
{
//Given
double[] data = { 1, 2, 3, 4, 5, 6, 5, 8, 4, 7 };
//When
var result = Stochastic.D_Single(data, period: 11);
//Then
Assert.Equal(0, result);
}
public void D_simplevalues_calculated()
{
//Given
double[] data = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
//When
double?[] result = Stochastic.D(data, period: 5, k_period: 3);
double?[] expected = { null, null, null, null, 100, 100, 100, 100, 100, 100 };
//Then
Assert.Equal(expected, result);
}
private void BuildTexure(List <Vector2> samples)
{
if (texturePixels == null || texturePixels.Length != IMAGE_LENGTH * IMAGE_LENGTH || lights == null || sampleWeights == null || sampleWeights.Length != IMAGE_LENGTH * IMAGE_LENGTH)
{
Initialize();
}
Vector2 center = new Vector2(.5f, .5f);
int samplesAAexp = aaQuality;
float pixelLength = 1f / IMAGE_LENGTH;
foreach (Vector2 sample in samples)
{
int x = Mathf.Clamp((int)(sample.x * IMAGE_LENGTH), 0, IMAGE_LENGTH - 1);
int y = Mathf.Clamp((int)(sample.y * IMAGE_LENGTH), 0, IMAGE_LENGTH - 1);;
List <Vector2> aaSamples = Stochastic.GetStratifiedUniformGrid(samplesAAexp, samplesAAexp);
Color pixel = Color.black;
foreach (Vector2 aa in aaSamples)
{
Vector2 p = sample + aa * pixelLength;
if ((p - center).magnitude < .5f)
{
pixel += RenderPixel((p - center) / .5f) / aaSamples.Count;
}
else
{
// Background pixel
Vector2 dirToPoint = p - center;
Vector2 edge = dirToPoint.normalized;
//pixel += RenderPixel(edge *.999f) / aaSamples.Count;
}
}
Color previousColor = texturePixels[y * IMAGE_LENGTH + x];
float previousWeight = sampleWeights[y * IMAGE_LENGTH + x];
sampleWeights[y * IMAGE_LENGTH + x] += 1f;
if (previousWeight > 0.0001f)
{
texturePixels[y * IMAGE_LENGTH + x] = ((previousColor * previousWeight) + pixel) / (previousWeight + 1f);
}
else
{
texturePixels[y * IMAGE_LENGTH + x] = pixel;
}
}
}
public void HandlesEqualMinAndMax()
{
var reference = DateTime.Now;
var stochastics = new Stochastic("sto", 2, 2, 2);
for (var i = 0; i < 4; i++)
{
var bar = new TradeBar(reference.AddSeconds(i), Symbols.SPY, 1, 1, 1, 1, 1);
stochastics.Update(bar);
Assert.AreEqual(0m, stochastics.Current.Value);
}
}
protected override string GetPresentDetail(IOutputInstant Instant, IIndicatorValues Data, IndicatorParameters IndicatorParameters)
{
Stochastic stochastic = Data.SlowStochastic(IndicatorParameters)[Instant.ExposureDate];
if (stochastic != null)
{
return(String.Format("{0}|{1}|{2}|{3}|", stochastic.PercentageK, stochastic.PercentageD, (int)stochastic.Oscillation, stochastic.Oscillation));
}
else
{
return(String.Format("{0}|{1}|{2}|{3}|", "", "", "", ""));
}
}
public SuperSmoothedDoubleStochastic(string name, int period, int kPeriod, int dPeriod)
: base(name)
{
_maximum = new Maximum(name + "_Max", period);
_mininum = new Minimum(name + "_Min", period);
_stochastic = new Stochastic(name + "_Stoch", period, kPeriod, dPeriod);
_firstSmoothing = new SimpleMovingAverage(3);
Smoothed = new FunctionalIndicator <TradeBar>(name + "_Smoothed",
input => ComputeSmoothed(period, input),
smoothed => _maximum.IsReady,
() => _maximum.Reset()
);
}
public void HandlesEqualMinAndMax()
{
var reference = new DateTime(2015, 09, 01);
var stochastics = new Stochastic("sto", 2, 2, 2);
for (int i = 0; i < 4; i++)
{
var bar = new TradeBar {
Time = reference.AddSeconds(i)
};
bar.Open = bar.Close = bar.High = bar.Low = bar.Volume = 1;
stochastics.Update(bar);
Assert.AreEqual(0m, stochastics.Current.Value);
}
}
public void Run(string downloadTime)
{
DateTime date = DateTime.Now;
DownloadEngine download = new DownloadEngine();
Formatting formatting = new Formatting();
PeregrineOperation peregrine = new PeregrineOperation();
MACD macd = new MACD();
Stochastic stochastic = new Stochastic();
TechnicalIndicators indicators = new TechnicalIndicators();
Transactions transactions = new Transactions();
WebClient web = new WebClient(); // provides the ability to download from the internet
WebURIs uRIs = new WebURIs(); // refers to an instance of the Wall Street Journal URL
DownloadTimer(download, formatting, peregrine, macd, stochastic, indicators, transactions, web, uRIs, Database, downloadTime);
}
public void Update()
{
if (previewMode)
{
int previewSamples = (int)(IMAGE_LENGTH);
BuildTexure(Stochastic.GetStratifiedUniformGrid(previewSamples, previewSamples));
updateCounter++;
if (updateCounter > 1)
{
sphereMap.SetPixels(texturePixels);
sphereMap.Apply();
updateCounter = 0;
}
}
}
protected override void Create()
{
m_stochastic1 = new Stochastic(this);
m_ofastk = new VariableSeries <Double>(this);
m_ofastd = new VariableSeries <Double>(this);
m_oslowk = new VariableSeries <Double>(this);
m_oslowd = new VariableSeries <Double>(this);
Plot1 =
AddPlot(new PlotAttributes("SlowK", 0, Color.Yellow,
Color.Empty, 0, 0, true));
Plot2 =
AddPlot(new PlotAttributes("SlowD", 0, Color.Blue,
Color.Empty, 0, 0, true));
Plot3 =
AddPlot(new PlotAttributes("OverBot", 0, Color.Green,
Color.Empty, 0, 0, true));
Plot4 =
AddPlot(new PlotAttributes("OverSld", 0, Color.Green,
Color.Empty, 0, 0, true));
}
public void ResetsProperly()
{
var stochastics = new Stochastic("sto", 12, 3, 5);
foreach (var bar in TestHelper.GetTradeBarStream("spy_with_stoch12k3.txt", false))
{
stochastics.Update(bar);
}
Assert.IsTrue(stochastics.IsReady);
Assert.IsTrue(stochastics.FastStoch.IsReady);
Assert.IsTrue(stochastics.StochK.IsReady);
Assert.IsTrue(stochastics.StochD.IsReady);
stochastics.Reset();
TestHelper.AssertIndicatorIsInDefaultState(stochastics);
TestHelper.AssertIndicatorIsInDefaultState(stochastics.FastStoch);
TestHelper.AssertIndicatorIsInDefaultState(stochastics.StochK);
TestHelper.AssertIndicatorIsInDefaultState(stochastics.StochD);
}
/// <summary>
/// Rolls a start and end point--wrapping allowed--and scrambles the elements between.
/// </summary>
/// <typeparam name="T">The array data type.</typeparam>
/// <param name="arry"></param>
/// <returns>The scrambled array.</returns>
protected T[] Scramble <T>(T[] arry)
{
var N = arry.Count();
var newArry = new T[N];
Array.Copy(arry, newArry, N);
var start = Stochastic.Next(N);
var end = Stochastic.Next(N);
while (end != start)
{
end = Stochastic.Next(N);
}
var isWrapped = start > end;
var offset = isWrapped ? end + 1 : 0;
//If isWrapped (N-start) count back end & (start+1) counts front end.
var len = end - start + 1 + (isWrapped ? N : 0);
var scrambled = new T[len];
for (var i = 0; i < len; i++)
{
scrambled[i] = arry[(start + i) % N];
}
scrambled = Stochastic.Shuffle(scrambled);
for (var i = 0; i < len; i++)
{
newArry[(start + i) % N] = scrambled[i];
}
return(newArry);
}
public StochasticSeries(C1FlexChart chart, string plotAreaName) : base()
{
Chart = chart;
Chart.BeginUpdate();
AxisY.TitleStyle = new ChartStyle();
AxisY.TitleStyle.FontWeight = Windows.UI.Text.FontWeights.Bold;
AxisY.Position = C1.Chart.Position.Right;
AxisY.PlotAreaName = plotAreaName;
AxisY.Title = "Stoc";
AxisY.Labels = false;
AxisY.MajorTickMarks = AxisY.MinorTickMarks = C1.Chart.TickMark.None;
series = new Stochastic();
series.DLineStyle = new ChartStyle();
series.DLineStyle.StrokeThickness = 1;
series.KLineStyle = new ChartStyle();
series.KLineStyle.StrokeThickness = 1;
series.ChartType = C1.Chart.Finance.FinancialChartType.Line;
series.Style = new ChartStyle();
series.Style.Stroke = new SolidColorBrush(Color.FromArgb(255, 51, 103, 214));
series.Style.Fill = new SolidColorBrush(Color.FromArgb(128, 66, 133, 244));
series.Style.StrokeThickness = 1;
series.BindingX = "Date";
series.Binding = "High,Low,Close";
series.AxisY = AxisY;
Chart.Series.Add(series);
ThresholdSeries overBought = new ThresholdSeries();
overBought.ChartType = C1.Chart.Finance.FinancialChartType.Line;
overBought.Style = new ChartStyle();
overBought.Style.Stroke = new SolidColorBrush(ViewModel.IndicatorPalettes.StockGreen);
overBought.Style.StrokeThickness = 1;
overBought.AxisY = AxisY;
Chart.Series.Add(overBought);
ThresholdSeries overSold = new ThresholdSeries();
overSold.ChartType = C1.Chart.Finance.FinancialChartType.Line;
overSold.Style = new ChartStyle();
overSold.Style.Stroke = new SolidColorBrush(ViewModel.IndicatorPalettes.StockRed);
overSold.Style.StrokeThickness = 1;
overSold.AxisY = AxisY;
Chart.Series.Add(overSold);
Utilities.Helper.BindingSettingsParams(chart, this, typeof(StochasticSeries), "Stochastic",
new Data.PropertyParam[]
{
new Data.PropertyParam("StochasticType", typeof(StochasticPresetType)),
},
() =>
{
this.OnSettingParamsChanged();
}
);
Utilities.Helper.BindingSettingsParams(chart, series, typeof(Stochastic), "Stochastic",
new Data.PropertyParam[]
{
new Data.PropertyParam("KPeriod", typeof(int)),
new Data.PropertyParam("DPeriod", typeof(int)),
new Data.PropertyParam("SmoothingPeriod", typeof(int)),
new Data.PropertyParam("DLineStyle.Stroke", typeof(Brush)),
new Data.PropertyParam("KLineStyle.Stroke", typeof(Brush))
},
() =>
{
this.OnSettingParamsChanged();
}
);
Utilities.Helper.BindingSettingsParams(chart, overBought, typeof(ThresholdSeries), "Stochastic",
new Data.PropertyParam[]
{
new Data.PropertyParam("ZonesVisibility", typeof(bool)),
new Data.PropertyParam("Threshold", typeof(int), "OverBought"),
},
() =>
{
this.OnSettingParamsChanged();
}
);
Utilities.Helper.BindingSettingsParams(chart, overSold, typeof(ThresholdSeries), "Stochastic",
new Data.PropertyParam[]
{
new Data.PropertyParam("ZonesVisibility", typeof(bool)),
new Data.PropertyParam("Threshold", typeof(int), "OverSold"),
},
() =>
{
this.OnSettingParamsChanged();
}
);
overBought.OnThesholdChanged += (o, e) =>
{
this.OnSettingParamsChanged();
};
overSold.OnThesholdChanged += (o, e) =>
{
this.OnSettingParamsChanged();
};
//binding series color to axis title.
Binding binding = new Binding();
binding.Path = new Windows.UI.Xaml.PropertyPath("Stroke");
binding.Source = series.Style;
BindingOperations.SetBinding(AxisY.TitleStyle, ChartStyle.StrokeProperty, binding);
Chart.EndUpdate();
this.Series = new FinancialSeries[] { series, overBought, overSold };
}
/// Prediction Algo via Technical Indicators
public List <Results> MathPredictsTheFuture(DownloadEngine download, MACD macd, Stochastic stochastic,
Transactions transactions, TechnicalIndicators indicators, string stock)
{
DateTime date = transactions.DatabaseDateQuery(database, stock)[0];
// 50 Day Average - queries database and calculates the 50 day average
double FiftyDayAverage = indicators.FiftyDayAvg(stock, transactions);
// MACD - determines if a stock is bearish or bullish. Uses 12 and 26 period exponental moving average
List <MACD> todaysMACD = macd.TodaysMACD(stock, transactions);
// Stochastic
List <Stochastic> todayStoch = stochastic.StochasticToday(Database, stock);
List <Results> results = new List <Results>()
{
new Results
{
Date = date,
CIK = download.DatabaseCIKQuery(Database, stock),
Symbol = stock,
LastClose = transactions.CloseQuery(Database, stock),
FiftyDayAvg = FiftyDayAverage,
mACD = todaysMACD[0].MACDValue,
MACDSignal = todaysMACD[0].MACDSignal,
EMA12 = todaysMACD[0].EMA12,
EMA26 = todaysMACD[0].EMA26,
StochasticFast = todayStoch[0].Fast,
StochasticSlow = todayStoch[0].Slow,
StochasticSignal = todayStoch[0].Signal
}
};
return(results);
}
public SVMBaselineSignalWIP(
QuoteBarConsolidator consolidator,
Stochastic stoch,
ExponentialMovingAverage stochMA,
RollingWindow <IndicatorDataPoint> rollingStochMA,
LeastSquaresMovingAverage stochEmaLSMA,
RollingWindow <IndicatorDataPoint> rollingStochEmaSlope,
ExponentialMovingAverage ema,
LeastSquaresMovingAverage emaMA,
RollingWindow <IndicatorDataPoint> rollingEmaSlope,
ExponentialMovingAverage shortTermMA,
LeastSquaresMovingAverage dailyEmaLSMA,
RollingWindow <IndicatorDataPoint> rollingDailyEmaSlope,
SecurityHolding securityHolding,
Security security,
SVMBaselineStrategyWIP qcAlgorithm)
{
_consolidator = consolidator;
_stoch = stoch;
_stochMA = stochMA;
_rollingStochMA = rollingStochMA;
_stochEmaLSMA = stochEmaLSMA;
_rollingStochEmaSlope = rollingStochEmaSlope;
_ema = ema;
_emaMA = emaMA;
_rollingEmaSlope = rollingEmaSlope;
_shortTermMA = shortTermMA;
_dailyEmaLSMA = dailyEmaLSMA;
_rollingDailyEmaSlope = rollingDailyEmaSlope;
_securityHolding = securityHolding;
_security = security;
_minimumPriceVariation = (1m / _security.SymbolProperties.MinimumPriceVariation) / 10m;
_qcAlgorithm = qcAlgorithm;
_stochMA.Updated += (sender, args) =>
{
try
{
var currentQuote = (QuoteBar)_consolidator.Consolidated;
var aboveEma = currentQuote.Close - _ema.Current.Value > 4m / _minimumPriceVariation;
var belowEma = _ema.Current.Value - currentQuote.Close > 4m / _minimumPriceVariation;
var aboveEmaExit = (currentQuote.Close - _ema.Current.Value > 10m / _minimumPriceVariation) || _rollingDailyEmaSlope[0] > 0.0005m;
var belowEmaExit = (_ema.Current.Value - currentQuote.Close > 10m / _minimumPriceVariation) || _rollingDailyEmaSlope[0] < -0.0005m;
var longCondition = _rollingStochMA[0] > _rollingStochMA[1] &&
_stochMA > 55 &&
aboveEma &&
//_rollingDailyEmaSlope[0] > _rollingDailyEmaSlope[1] &&
_dailyEmaLSMA.Slope > 0 &&
//_rollingStochEmaSlope[0] < 2 &&
//_rollingStochEmaSlope[0] > _rollingStochEmaSlope[1] &&
//_rollingStochMA[0] > 45 &&
_rollingEmaSlope[0] > 0.00001m;
var shortCondition = _rollingStochMA[0] < _rollingStochMA[1] &&
_stochMA < 45 &&
belowEma &&
//_rollingDailyEmaSlope[0] < _rollingDailyEmaSlope[1] &&
_dailyEmaLSMA.Slope < 0 &&
//_rollingStochEmaSlope[0] > -2 &&
//_rollingStochEmaSlope[0] < _rollingStochEmaSlope[1] &&
//_rollingStochMA[0] < 55 &&
_rollingEmaSlope[0] < -0.00001m;
var prediction = longCondition ? 1 : shortCondition ? -1 : 0;
/*var prediction = _rollingStochMA[0] > _rollingStochMA[1] && aboveEma && _stochEmaLSMA.Slope > 0.5 && _rollingEmaSlope[0] > 0
* ? 1
* : _rollingStochMA[0] < _rollingStochMA[1] && belowEma && _stochEmaLSMA.Slope < -0.5 && _rollingEmaSlope[0] < 0
* ? -1
* : 0;*/
var probability = 1d;
var logLikelihood = 1d;
_qcAlgorithm.PlotSignal((QuoteBar)_consolidator.Consolidated, prediction, logLikelihood);
var longExit = Signal == SignalType.Long && belowEmaExit && _rollingEmaSlope[0] < 0;
var shortExit = Signal == SignalType.Short && aboveEmaExit && _rollingEmaSlope[0] > 0;
/*var longExit = Signal == SignalType.Long && _stochEmaLSMA.Slope < -0.5;
* var shortExit = Signal == SignalType.Short && _stochEmaLSMA.Slope > 0.5;*/
if (!_securityHolding.Invested && prediction == 1)
{
if (true)//if (!_shortOnly.Contains(_securityHolding.Symbol))
{
Signal = Signal != SignalType.PendingLong ? SignalType.Long : SignalType.Long;
}
else
{
Signal = SignalType.NoSignal;
}
//Signal = Signal != SignalType.PendingLong ? SignalType.Long : SignalType.Long;
//Signal = SignalType.NoSignal;
if (_debug)
{
Console.WriteLine("Long Signal: {0} Probability: {1} Log Likelihood: {2}", Signal, probability, logLikelihood);
Console.WriteLine("Long STO: {0} STO MA: {1}", _stoch.Current.Value, args.Value);
Console.WriteLine("Long Time: {0} Price: {1}", _consolidator.Consolidated.Time, _consolidator.Consolidated.Value);
}
}
else if (!_securityHolding.Invested && prediction == -1)
{
if (true) //if (_shortable.Contains(_securityHolding.Symbol))
{
Signal = Signal != SignalType.PendingShort ? SignalType.Short : SignalType.Short;
}
else
{
Signal = SignalType.NoSignal;
}
//Signal = Signal != SignalType.PendingShort ? SignalType.Short : SignalType.Short;
//Signal = SignalType.NoSignal;
if (_debug)
{
Console.WriteLine("Short Signal: {0} Probability: {1} Log Likelihood: {2}", Signal, probability, logLikelihood);
Console.WriteLine("Short STO: {0} STO MA: {1}", _stoch.Current.Value, args.Value);
Console.WriteLine("Short Time: {0} Price: {1}", _consolidator.Consolidated.Time, _consolidator.Consolidated.Value);
}
}
else if ((_securityHolding.Invested && longExit) || (_securityHolding.Invested && shortExit))
{
if (_debug)
{
Console.WriteLine("Exit Signal: {0} Probability: {1} Log Likelihood: {2}", Signal, probability, logLikelihood);
Console.WriteLine("Exit STO: {0} STO MA: {1}", _stoch.Current.Value, args.Value);
Console.WriteLine("Exit Time: {0} Price: {1}", _consolidator.Consolidated.Time, _consolidator.Consolidated.Value);
}
Signal = SignalType.Exit;
}
else if (!_securityHolding.Invested && (Signal == SignalType.PendingLong || Signal == SignalType.PendingShort))
{
Signal = SignalType.NoSignal;
}
else
{
//Signal = SignalType.NoSignal;
}
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
Signal = SignalType.NoSignal;
}
};
}
/// <inheritdoc />
public void Iteration()
{
_network.NetworkTraining = true;
// alert the layers that a new batch is starting.
foreach (var layer in _network.Layers)
{
layer.TrainingBatch(Stochastic);
}
// begin the iteration
_gradients.Reset();
_errorCalc.Clear();
var iterationSize = BatchSize == 0
? _training.Count
: Math.Min(BatchSize, _training.Count);
for (var i = 0; i < iterationSize; i++)
{
BasicData element;
if (IsOnlineTraining)
{
if (Stochastic != null)
{
var stochasticIndex = Stochastic.NextInt(0, _training.Count);
element = _training[stochasticIndex];
}
else
{
element = _training[_currentIndex++];
}
}
else
{
element = _training[i];
}
_gradients.Process(_errorCalc, element.Input, element.Ideal);
}
if (_currentIndex > _training.Count || BatchSize == 0)
{
_currentIndex = 0;
}
_currentError = _errorCalc.Calculate();
for (var i = 0; i < _network.Weights.Length; i++)
{
double delta;
if (NesterovUpdate)
{
var prevNesterov = _lastDelta[i];
_lastDelta[i] = Momentum * prevNesterov
+ _gradients.Gradients[i] * LearningRate;
delta = Momentum * prevNesterov - (1 + Momentum) * _lastDelta[i];
}
else
{
delta = _gradients.Gradients[i] * -LearningRate + _lastDelta[i] * Momentum;
_lastDelta[i] = delta;
}
_network.Weights[i] += delta;
}
_network.NetworkTraining = false;
}
private void DownloadTimer(DownloadEngine download, Formatting formatting, PeregrineOperation peregrine, MACD macd, Stochastic stochastic,
TechnicalIndicators indicators, Transactions transactions, WebClient web, WebURIs uRIs, string Database, string downloadTime)
{
var DailyTime = downloadTime; //Time when method needs to be called
var timeParts = DailyTime.Split(new char[1] {
':'
});
var dateNow = DateTime.Now;
var date = new DateTime(dateNow.Year, dateNow.Month, dateNow.Day,
int.Parse(timeParts[0]), int.Parse(timeParts[1]), int.Parse(timeParts[2]));
TimeSpan ts;
if (date > dateNow)
{
ts = date - dateNow;
}
else
{
date = date.AddDays(1);
ts = date - dateNow;
}
while (date != dateNow)
{
Console.WriteLine($"Waiting for {downloadTime}");
//waits certan time and run the code
Task.Delay(ts).ContinueWith((x) => Download(date, download, formatting, peregrine, macd, stochastic, indicators, transactions, web, uRIs, Database));
Console.Read();
}
}
/// Download and save to Database
private void Download(DateTime date, DownloadEngine download, Formatting formatting, PeregrineOperation peregrine, MACD macd, Stochastic stochastic, TechnicalIndicators indicators, Transactions transactions, WebClient web, WebURIs uRIs, string Database)
{
List <string> Symbols = transactions.DatabaseSymbolListQuery(Database, stocks);
transactions.TruncateStockTable(Database, "Clean Data"); // clears data from the clean data table.
int count = 1;
foreach (var stock in Symbols)
{
Console.Clear();
Console.WriteLine($"Downloading {stock} || {count} of {Symbols.Count}");
download.ToDatabase(date, formatting, peregrine, transactions, web, uRIs, stock, Database);
count++;
}
Console.WriteLine("I'm Done");
//count = 1;
//calls the list of stocks that have been data verified
//List<string> CleanData = transactions.DatabaseSymbolListQuery(Database, stocks);
//foreach (var stock in CleanData)
//{
// Console.Clear();
// Console.WriteLine($"Doing Math {stock} || {count} of {CleanData.Count}");
// List<Results> results = MathPredictsTheFuture(download, macd, stochastic, transactions, indicators, stock);
// transactions.SaveToTableResult(Database, results); // saves the calculations to the Results table in the database
// count++;
//}
//// calls the stocks from the results list
//List<PeregrineResults> todaysResults = transactions.DailyResultsQuery(peregrine.Database);
//transactions.TruncateStockTable(database, peregrineresults); // clears the web results table. This table feeds the model for the ASP.Net interface.
//transactions.SaveToTableWebResult(peregrine.Database, todaysResults);
//Console.WriteLine("Peregrine Results Updated");
}
protected override void Create(){
m_Stochastic = new Stochastic(this);
m_oFastK = new VariableSeries<Double>(this);
m_oFastD = new VariableSeries<Double>(this);
m_oSlowK = new VariableSeries<Double>(this);
m_oSlowD = new VariableSeries<Double>(this);
m_StochLE =
OrderCreator.MarketNextBar(new SOrderParameters(Contracts.Default, "StochLE", EOrderAction.Buy));
}
protected override void Create(){
m_stochastic1 = new Stochastic(this);
m_ofastk = new VariableSeries<Double>(this);
m_ofastd = new VariableSeries<Double>(this);
m_oslowk = new VariableObject<Double>(this);
m_oslowd = new VariableObject<Double>(this);
Plot1 =
AddPlot(new PlotAttributes("FastK", 0, Color.Yellow,
Color.Empty, 0, 0, true));
Plot2 =
AddPlot(new PlotAttributes("FastD", 0, Color.Blue,
Color.Empty, 0, 0, true));
Plot3 =
AddPlot(new PlotAttributes("OverBot", 0, Color.Green,
Color.Empty, 0, 0, true));
Plot4 =
AddPlot(new PlotAttributes("OverSld", 0, Color.Green,
Color.Empty, 0, 0, true));
}
