Added some standard indicators
This commit is contained in:
Michael Schimmel
@@ -2,10 +2,10 @@ unit Myc.Trade.DataArray;
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interface
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uses
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Myc.Trade.DataPoint;
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type
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// A series is an array of values with the newest ite at index=0. Each series counts the total of added items since creation, but
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// it actually may contain less items, because the array size is limited by the lookback parameter, when adding items.
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// Series are immutable.
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TMycDataArray<T> = record
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private
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const
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@@ -21,7 +21,9 @@ type
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function GetItems(Idx: Int64): T; inline;
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public
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constructor Create(const AChunks: TArray<TChunk>; ACount, ATotalCount: Int64);
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// Add a singe item
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function Add(const Data: T; Lookback: Int64): TMycDataArray<T>; overload;
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// Add a ranmge of items
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function Add(const Data: array of T; First, Count, Lookback: Int64): TMycDataArray<T>; overload;
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class function CreateEmpty: TMycDataArray<T>; static;
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// Helper to create a data array from a raw TArray.
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@@ -0,0 +1,355 @@
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unit Myc.Trade.Indicators;
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interface
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uses
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System.SysUtils,
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System.Math,
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Myc.Trade.DataArray,
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Myc.Trade.DataPoint;
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type
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// Result for the Moving Average Convergence Divergence (MACD) indicator.
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TMacdResult = record
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MacdLine: Double;
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SignalLine: Double;
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Histogram: Double;
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end;
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// Result for the Stochastic Oscillator indicator.
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TStochasticResult = record
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K: Double; // %K line
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D: Double; // %D line (signal line)
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end;
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// Result for the Bollinger Bands indicator.
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TBollingerBandsResult = record
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UpperBand: Double;
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MiddleBand: Double;
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LowerBand: Double;
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end;
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TIndicators = record
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private
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class function CalculateSMA(const Series: TMycDataArray<Double>; const Period: Integer): Double; static;
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class function CalculateStdDev(const Series: TMycDataArray<Double>; const Period: Integer): Double; static;
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class function CalculateWMA(const Series: TMycDataArray<Double>; const Period: Integer): Double; static;
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public
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// Simple Moving Average
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class function CreateSMA(Period: Integer): TFunc<Double, Double>; static;
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// Exponential Moving Average
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class function CreateEMA(Period: Integer): TFunc<Double, Double>; static;
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// Hull Moving Average
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class function CreateHMA(Period: Integer): TFunc<Double, Double>; static;
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// Relative Strength Index
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class function CreateRSI(Period: Integer): TFunc<Double, Double>; static;
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// Moving Average Convergence Divergence
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class function CreateMACD(FastPeriod, SlowPeriod, SignalPeriod: Integer): TFunc<Double, TMacdResult>; static;
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// Stochastic Oscillator
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class function CreateStochastic(KPeriod, DPeriod: Integer): TFunc<TOhlcItem, TStochasticResult>; static;
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// Bollinger Bands
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class function CreateBollingerBands(Period: Integer; Multiplier: Double): TFunc<Double, TBollingerBandsResult>; static;
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end;
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implementation
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{ TIndicators }
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class function TIndicators.CalculateSMA(const Series: TMycDataArray<Double>; const Period: Integer): Double;
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var
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i: Integer;
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sum: Double;
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begin
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if (Series.Count < Period) or (Period <= 0) then
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Exit(0.0);
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sum := 0;
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for i := 0 to Period - 1 do
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sum := sum + Series[i];
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Result := sum / Period;
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end;
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class function TIndicators.CalculateStdDev(const Series: TMycDataArray<Double>; const Period: Integer): Double;
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var
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i: Integer;
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mean, sumOfSquares: Double;
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begin
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if (Series.Count < Period) or (Period <= 0) then
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Exit(0.0);
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mean := CalculateSMA(Series, Period);
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sumOfSquares := 0;
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for i := 0 to Period - 1 do
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sumOfSquares := sumOfSquares + Power(Series[i] - mean, 2);
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Result := Sqrt(sumOfSquares / Period);
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end;
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class function TIndicators.CalculateWMA(const Series: TMycDataArray<Double>; const Period: Integer): Double;
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var
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i: Integer;
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numerator: Double;
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denominator: Int64;
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begin
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// Ensure there is enough data to calculate the WMA
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if (Series.Count < Period) or (Period <= 0) then
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Exit(0.0);
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numerator := 0;
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// The sum of weights (1 + 2 + ... + Period)
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denominator := Period * (Period + 1) div 2;
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if (denominator = 0) then
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Exit(0.0);
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for i := 0 to Period - 1 do
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begin
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// Newest data (index 0) gets the highest weight (Period)
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numerator := numerator + Series[i] * (Period - i);
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end;
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Result := numerator / denominator;
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end;
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class function TIndicators.CreateBollingerBands(Period: Integer; Multiplier: Double): TFunc<Double, TBollingerBandsResult>;
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begin
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var sourceData := TMycDataArray<Double>.CreateEmpty;
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Result :=
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function(Value: Double): TBollingerBandsResult
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var
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stdDev: Double;
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begin
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sourceData := sourceData.Add(Value, Period);
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Result.MiddleBand := Double.NaN;
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Result.UpperBand := Double.NaN;
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Result.LowerBand := Double.NaN;
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if (sourceData.Count >= Period) then
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begin
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Result.MiddleBand := CalculateSMA(sourceData, Period);
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stdDev := CalculateStdDev(sourceData, Period);
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Result.UpperBand := Result.MiddleBand + (stdDev * Multiplier);
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Result.LowerBand := Result.MiddleBand - (stdDev * Multiplier);
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end;
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end;
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end;
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class function TIndicators.CreateEMA(Period: Integer): TFunc<Double, Double>;
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begin
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var lastEma: Double := Double.NaN;
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var sourceData := TMycDataArray<Double>.CreateEmpty;
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var multiplier := 2 / (Period + 1);
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Result :=
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function(Value: Double): Double
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begin
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sourceData := sourceData.Add(Value, Period);
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if (sourceData.Count < Period) then
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begin
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Result := Double.NaN;
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Exit;
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end;
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if not IsNan(lastEma) then
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begin
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// Subsequent EMA calculation
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lastEma := (Value - lastEma) * multiplier + lastEma;
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end
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else
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begin
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// First EMA is a SMA of the initial period
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lastEma := CalculateSMA(sourceData, Period);
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end;
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Result := lastEma;
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end;
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end;
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class function TIndicators.CreateHMA(Period: Integer): TFunc<Double, Double>;
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begin
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var periodHalf := Period div 2;
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var periodSqrt := Round(Sqrt(Period));
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var sourceData := TMycDataArray<Double>.CreateEmpty;
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var diffSeries := TMycDataArray<Double>.CreateEmpty;
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Result :=
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function(Value: Double): Double
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var
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price: Double;
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wmaHalf, wmaFull, diff: Double;
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begin
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price := Value;
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// Default HMA to NaN for the warm-up period.
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Result := Double.NaN;
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// Add new price to the source data array, respecting the lookback period.
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sourceData := sourceData.Add(price, Period);
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// Check if there is enough data to start the first stage of calculation.
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if (sourceData.Count >= Period) then
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begin
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// Calculate the two WMAs for the first step.
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wmaHalf := CalculateWMA(sourceData, periodHalf);
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wmaFull := CalculateWMA(sourceData, Period);
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// Calculate the difference and add to the intermediate series.
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diff := 2 * wmaHalf - wmaFull;
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diffSeries := diffSeries.Add(diff, periodSqrt);
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// Check if there is enough intermediate data for the final calculation.
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if (diffSeries.Count >= periodSqrt) then
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begin
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// Calculate the final HMA value
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Result := CalculateWMA(diffSeries, periodSqrt);
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end;
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end;
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end;
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end;
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class function TIndicators.CreateMACD(FastPeriod, SlowPeriod, SignalPeriod: Integer): TFunc<Double, TMacdResult>;
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begin
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var emaFast := CreateEMA(FastPeriod);
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var emaSlow := CreateEMA(SlowPeriod);
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var emaSignal := CreateEMA(SignalPeriod);
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Result :=
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function(Value: Double): TMacdResult
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var
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fastVal, slowVal: Double;
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begin
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fastVal := emaFast(Value);
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slowVal := emaSlow(Value);
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if IsNan(slowVal) then // slowVal will be the last one to become non-NaN
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begin
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Result.MacdLine := Double.NaN;
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Result.SignalLine := Double.NaN;
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Result.Histogram := Double.NaN;
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end
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else
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begin
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Result.MacdLine := fastVal - slowVal;
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Result.SignalLine := emaSignal(Result.MacdLine);
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if not IsNan(Result.SignalLine) then
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Result.Histogram := Result.MacdLine - Result.SignalLine
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else
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Result.Histogram := Double.NaN;
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end;
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end;
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end;
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class function TIndicators.CreateRSI(Period: Integer): TFunc<Double, Double>;
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begin
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var avgGain: Double := Double.NaN;
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var avgLoss: Double := Double.NaN;
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var sourceData := TMycDataArray<Double>.CreateEmpty;
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Result :=
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function(Value: Double): Double
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var
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change, gain, loss, rs: Double;
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gainSum, lossSum: Double;
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i: Integer;
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begin
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sourceData := sourceData.Add(Value, Period + 1);
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Result := Double.NaN;
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if (sourceData.Count <= Period) then
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Exit;
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// Initial calculation for the first full period
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if IsNan(avgGain) then
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begin
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gainSum := 0;
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lossSum := 0;
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for i := 0 to Period - 1 do
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begin
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change := sourceData[i] - sourceData[i + 1];
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if (change > 0) then
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gainSum := gainSum + change
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else
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lossSum := lossSum - change;
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end;
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avgGain := gainSum / Period;
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avgLoss := lossSum / Period;
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end
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else // Smoothed calculation for subsequent values
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begin
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change := sourceData[0] - sourceData[1];
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gain := 0;
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loss := 0;
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if (change > 0) then
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gain := change
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else
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loss := -change;
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avgGain := (avgGain * (Period - 1) + gain) / Period;
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avgLoss := (avgLoss * (Period - 1) + loss) / Period;
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end;
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if (avgLoss = 0) then
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Result := 100
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else
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begin
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rs := avgGain / avgLoss;
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Result := 100 - (100 / (1 + rs));
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end;
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end;
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end;
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class function TIndicators.CreateSMA(Period: Integer): TFunc<Double, Double>;
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begin
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var sourceData := TMycDataArray<Double>.CreateEmpty;
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Result :=
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function(Value: Double): Double
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begin
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sourceData := sourceData.Add(Value, Period);
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if (sourceData.Count >= Period) then
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Result := CalculateSMA(sourceData, Period)
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else
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Result := Double.NaN;
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end;
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end;
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class function TIndicators.CreateStochastic(KPeriod, DPeriod: Integer): TFunc<TOhlcItem, TStochasticResult>;
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begin
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var sourceData := TMycDataArray<TOhlcItem>.CreateEmpty;
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var smaD := CreateSMA(DPeriod);
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Result :=
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function(Value: TOhlcItem): TStochasticResult
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var
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i: Integer;
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highestHigh, lowestLow: Double;
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begin
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sourceData := sourceData.Add(Value, KPeriod);
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Result.K := Double.NaN;
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Result.D := Double.NaN;
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if (sourceData.Count >= KPeriod) then
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begin
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highestHigh := -MaxDouble;
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lowestLow := MaxDouble;
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for i := 0 to KPeriod - 1 do
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begin
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// Correctly use High and Low fields
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if (sourceData[i].High > highestHigh) then
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highestHigh := sourceData[i].High;
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if (sourceData[i].Low < lowestLow) then
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lowestLow := sourceData[i].Low;
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end;
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if (highestHigh > lowestLow) then
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// Correctly use the current Close
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Result.K := 100 * (sourceData[0].Close - lowestLow) / (highestHigh - lowestLow)
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else
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Result.K := 100; // Or 50, depends on convention
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Result.D := smaD(Result.K);
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end;
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end;
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end;
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end.
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