MycLib/Src/Myc.Trade.Indicators.Common.pas

unit Myc.Trade.Indicators.Common;

interface

uses
    System.SysUtils,
    System.Math,
    System.Generics.Collections,
    System.Rtti,
    Myc.Data.Records,
    Myc.Data.Pipeline,
    Myc.Data.Series,
    Myc.Trade.Types;

type
    // Result for the Moving Average Convergence Divergence (MACD) indicator.
    TMacdResult = record
        MacdLine: Double;
        SignalLine: Double;
        Histogram: Double;
    end;

    // Result for the Stochastic Oscillator indicator.
    TStochasticResult = record
        K: Double; // %K line
        D: Double; // %D line (signal line)
    end;

    // Result for the Bollinger Bands indicator.
    TBollingerBandsResult = record
        UpperBand: Double;
        MiddleBand: Double;
        LowerBand: Double;
    end;

    // Result for the Keltner Channels indicator.
    TKeltnerChannelsResult = record
        UpperBand: Double;
        MiddleBand: Double;
        LowerBand: Double;
    end;

    TIndicators = record
    private
        class function CalculateSMA(const Series: TSeries<Double>; const Period: Integer): Double; static;
        class function CalculateStdDev(const Series: TSeries<Double>; const Period: Integer): Double; static;
        class function CalculateWMA(const Series: TSeries<Double>; const Period: Integer): Double; static;
    public
        // Simple Moving Average
        class function CreateSMA(Period: Integer): TConvertFunc<Double, Double>; static;
        // Exponential Moving Average
        class function CreateEMA(Period: Integer): TConvertFunc<Double, Double>; static;
        // Hull Moving Average
        class function CreateHMA(Period: Integer): TConvertFunc<Double, Double>; static;
        // Relative Strength Index
        class function CreateRSI(Period: Integer): TConvertFunc<Double, Double>; static;
        // Moving Average Convergence Divergence
        class function CreateMACD(FastPeriod, SlowPeriod, SignalPeriod: Integer): TConvertFunc<Double, TMacdResult>; overload; static;
        class function CreateMACD(
            const EmaFast,
            EmaSlow,
            EmaSignal: TConvertFunc<Double, Double>
        ): TConvertFunc<Double, TMacdResult>; overload; static;
        // Stochastic Oscillator
        class function CreateStochastic(KPeriod, DPeriod: Integer): TConvertFunc<TOhlcItem, TStochasticResult>; overload; static;
        class function CreateStochastic(
            KPeriod: Integer;
            const SmaD: TConvertFunc<Double, Double>
        ): TConvertFunc<TOhlcItem, TStochasticResult>; overload; static;
        // Bollinger Bands
        class function CreateBollingerBands(Period: Integer; Multiplier: Double): TConvertFunc<Double, TBollingerBandsResult>; static;
        // Average True Range
        class function CreateATR(Period: Integer): TConvertFunc<TOhlcItem, Double>; overload; static;
        class function CreateATR(const MovAvgTR: TConvertFunc<Double, Double>): TConvertFunc<TOhlcItem, Double>; overload; static;
        // Keltner Channels
        class function CreateKeltnerChannels(
            Period: Integer;
            Multiplier: Double
        ): TConvertFunc<TOhlcItem, TKeltnerChannelsResult>; overload; static;
        class function CreateKeltnerChannels(
            const MovAvgMiddle: TConvertFunc<Double, Double>;
            const AtrFunc: TConvertFunc<TOhlcItem, Double>;
            Multiplier: Double
        ): TConvertFunc<TOhlcItem, TKeltnerChannelsResult>; overload; static;

        class function CreateMean: TConvertFunc<TArray<Double>, Double>; static;
    end;

implementation

{ TIndicators }

class function TIndicators.CalculateSMA(const Series: TSeries<Double>; const Period: Integer): Double;
var
    i: Integer;
    sum: Double;
begin
    if (Series.Count < Period) or (Period <= 0) then
        Exit(0.0);

    sum := 0;
    for i := 0 to Period - 1 do
        sum := sum + Series[i];

    Result := sum / Period;
end;

class function TIndicators.CalculateStdDev(const Series: TSeries<Double>; const Period: Integer): Double;
var
    i: Integer;
    mean, sumOfSquares: Double;
begin
    if (Series.Count < Period) or (Period <= 0) then
        Exit(0.0);

    mean := CalculateSMA(Series, Period);
    sumOfSquares := 0;
    for i := 0 to Period - 1 do
        sumOfSquares := sumOfSquares + Power(Series[i] - mean, 2);

    Result := Sqrt(sumOfSquares / Period);
end;

class function TIndicators.CalculateWMA(const Series: TSeries<Double>; const Period: Integer): Double;
var
    i: Integer;
    numerator: Double;
    denominator: Int64;
begin
    // Ensure there is enough data to calculate the WMA
    if (Series.Count < Period) or (Period <= 0) then
        Exit(0.0);

    numerator := 0;
    // The sum of weights (1 + 2 + ... + Period)
    denominator := Period * (Period + 1) div 2;

    if (denominator = 0) then
        Exit(0.0);

    for i := 0 to Period - 1 do
    begin
        // Newest data (index 0) gets the highest weight (Period)
        numerator := numerator + Series[i] * (Period - i);
    end;

    Result := numerator / denominator;
end;

class function TIndicators.CreateBollingerBands(Period: Integer; Multiplier: Double): TConvertFunc<Double, TBollingerBandsResult>;
begin
    var sourceData: TSeries<Double>;
    Result :=
        function(const Value: Double): TBollingerBandsResult
        var
            stdDev: Double;
        begin
            sourceData.Add(Value, Period);
            Result.MiddleBand := Double.NaN;
            Result.UpperBand := Double.NaN;
            Result.LowerBand := Double.NaN;

            if (sourceData.Count >= Period) then
            begin
                Result.MiddleBand := CalculateSMA(sourceData, Period);
                stdDev := CalculateStdDev(sourceData, Period);
                Result.UpperBand := Result.MiddleBand + (stdDev * Multiplier);
                Result.LowerBand := Result.MiddleBand - (stdDev * Multiplier);
            end;
        end;
end;

class function TIndicators.CreateEMA(Period: Integer): TConvertFunc<Double, Double>;
begin
    var lastEma: Double := Double.NaN;
    var sourceData: TSeries<Double>;
    var multiplier := 2 / (Period + 1);

    Result :=
        function(const Value: Double): Double
        begin
            sourceData.Add(Value, Period);

            if (sourceData.Count < Period) then
            begin
                Result := Double.NaN;
                Exit;
            end;

            if not IsNan(lastEma) then
            begin
                // Subsequent EMA calculation
                lastEma := (Value - lastEma) * multiplier + lastEma;
            end
            else
            begin
                // First EMA is a SMA of the initial period
                lastEma := CalculateSMA(sourceData, Period);
            end;
            Result := lastEma;
        end;
end;

class function TIndicators.CreateHMA(Period: Integer): TConvertFunc<Double, Double>;
begin
    var periodHalf := Period div 2;
    var periodSqrt := Round(Sqrt(Period));
    var sourceData: TSeries<Double>;
    var diffSeries: TSeries<Double>;

    Result :=
        function(const Value: Double): Double
        var
            price: Double;
            wmaHalf, wmaFull, diff: Double;
        begin
            price := Value;

            // Default HMA to NaN for the warm-up period.
            Result := Double.NaN;

            // Add new price to the source data array, respecting the lookback period.
            sourceData.Add(price, Period);

            // Check if there is enough data to start the first stage of calculation.
            if (sourceData.Count >= Period) then
            begin
                // Calculate the two WMAs for the first step.
                wmaHalf := CalculateWMA(sourceData, periodHalf);
                wmaFull := CalculateWMA(sourceData, Period);

                // Calculate the difference and add to the intermediate series.
                diff := 2 * wmaHalf - wmaFull;
                diffSeries.Add(diff, periodSqrt);

                // Check if there is enough intermediate data for the final calculation.
                if (diffSeries.Count >= periodSqrt) then
                begin
                    // Calculate the final HMA value
                    Result := CalculateWMA(diffSeries, periodSqrt);
                end;
            end;
        end;
end;

// Standard MACD using EMAs.
class function TIndicators.CreateMACD(FastPeriod, SlowPeriod, SignalPeriod: Integer): TConvertFunc<Double, TMacdResult>;
begin
    Result := CreateMACD(CreateEMA(FastPeriod), CreateEMA(SlowPeriod), CreateEMA(SignalPeriod));
end;

// Creates a MACD indicator from three provided moving average functions.
class function TIndicators.CreateMACD(const EmaFast, EmaSlow, EmaSignal: TConvertFunc<Double, Double>): TConvertFunc<Double, TMacdResult>;
begin
    Result :=
        function(const Value: Double): TMacdResult
        var
            fastVal, slowVal: Double;
        begin
            fastVal := EmaFast(Value);
            slowVal := EmaSlow(Value);

            if IsNan(slowVal) then // slowVal will be the last one to become non-NaN
            begin
                Result.MacdLine := Double.NaN;
                Result.SignalLine := Double.NaN;
                Result.Histogram := Double.NaN;
            end
            else
            begin
                Result.MacdLine := fastVal - slowVal;
                Result.SignalLine := EmaSignal(Result.MacdLine);
                if not IsNan(Result.SignalLine) then
                    Result.Histogram := Result.MacdLine - Result.SignalLine
                else
                    Result.Histogram := Double.NaN;
            end;
        end;
end;

class function TIndicators.CreateRSI(Period: Integer): TConvertFunc<Double, Double>;
begin
    var avgGain: Double := Double.NaN;
    var avgLoss: Double := Double.NaN;
    var sourceData: TSeries<Double>;

    Result :=
        function(const Value: Double): Double
        var
            change, gain, loss, rs: Double;
            gainSum, lossSum: Double;
            i: Integer;
        begin
            sourceData.Add(Value, Period + 1);
            Result := Double.NaN;

            if (sourceData.Count <= Period) then
                Exit;

            // Initial calculation for the first full period
            if IsNan(avgGain) then
            begin
                gainSum := 0;
                lossSum := 0;
                for i := 0 to Period - 1 do
                begin
                    change := sourceData[i] - sourceData[i + 1];
                    if (change > 0) then
                        gainSum := gainSum + change
                    else
                        lossSum := lossSum - change;
                end;
                avgGain := gainSum / Period;
                avgLoss := lossSum / Period;
            end
            else // Smoothed calculation for subsequent values
            begin
                change := sourceData[0] - sourceData[1];
                gain := 0;
                loss := 0;
                if (change > 0) then
                    gain := change
                else
                    loss := -change;

                avgGain := (avgGain * (Period - 1) + gain) / Period;
                avgLoss := (avgLoss * (Period - 1) + loss) / Period;
            end;

            if (avgLoss = 0) then
                Result := 100
            else
            begin
                rs := avgGain / avgLoss;
                Result := 100 - (100 / (1 + rs));
            end;
        end;
end;

class function TIndicators.CreateSMA(Period: Integer): TConvertFunc<Double, Double>;
begin
    var sourceData: TSeries<Double>;
    Result :=
        function(const Value: Double): Double
        begin
            sourceData.Add(Value, Period);
            if (sourceData.Count >= Period) then
                Result := CalculateSMA(sourceData, Period)
            else
                Result := Double.NaN;
        end;
end;

// Standard Stochastic Oscillator using an SMA for the %D line.
class function TIndicators.CreateStochastic(KPeriod, DPeriod: Integer): TConvertFunc<TOhlcItem, TStochasticResult>;
begin
    Result := CreateStochastic(KPeriod, CreateSMA(DPeriod));
end;

// Creates a Stochastic Oscillator using an injectable moving average for the %D line.
class function TIndicators.CreateStochastic(
    KPeriod: Integer;
    const SmaD: TConvertFunc<Double, Double>
): TConvertFunc<TOhlcItem, TStochasticResult>;
begin
    var sourceData: TSeries<TOhlcItem>;

    Result :=
        function(const Value: TOhlcItem): TStochasticResult
        var
            i: Integer;
            highestHigh, lowestLow: Double;
        begin
            sourceData.Add(Value, KPeriod);
            Result.K := Double.NaN;
            Result.D := Double.NaN;

            if (sourceData.Count >= KPeriod) then
            begin
                highestHigh := -MaxDouble;
                lowestLow := MaxDouble;
                for i := 0 to KPeriod - 1 do
                begin
                    // Correctly use High and Low fields
                    if (sourceData[i].High > highestHigh) then
                        highestHigh := sourceData[i].High;
                    if (sourceData[i].Low < lowestLow) then
                        lowestLow := sourceData[i].Low;
                end;

                if (highestHigh > lowestLow) then
                    // Correctly use the current Close
                    Result.K := 100 * (sourceData[0].Close - lowestLow) / (highestHigh - lowestLow)
                else
                    Result.K := 100; // Or 50, depends on convention

                Result.D := SmaD(Result.K);
            end;
        end;
end;

// Standard ATR using an EMA for smoothing.
class function TIndicators.CreateATR(Period: Integer): TConvertFunc<TOhlcItem, Double>;
begin
    Result := CreateATR(CreateEMA(Period));
end;

// Calculates the Average True Range (ATR) using an injectable moving average.
class function TIndicators.CreateATR(const MovAvgTR: TConvertFunc<Double, Double>): TConvertFunc<TOhlcItem, Double>;
begin
    var sourceData: TSeries<TOhlcItem>;

    Result :=
        function(const Value: TOhlcItem): Double
        var
            tr: Double;
        begin
            // We only need the previous bar to calculate true range.
            sourceData.Add(Value, 2);

            if (sourceData.Count < 2) then
            begin
                // Feed a dummy value to keep the moving average count in sync. It will correctly return NaN.
                Result := MovAvgTR(0);
                Exit;
            end;

            // Calculate current True Range.
            tr := Max(Value.High - Value.Low, Max(Abs(Value.High - sourceData[1].Close), Abs(Value.Low - sourceData[1].Close)));

            // Feed the calculated TR into the provided moving average function.
            Result := MovAvgTR(tr);
        end;
end;

// Standard Keltner Channels using an EMA for the middle line and an EMA-based ATR.
class function TIndicators.CreateKeltnerChannels(Period: Integer; Multiplier: Double): TConvertFunc<TOhlcItem, TKeltnerChannelsResult>;
begin
    Result := CreateKeltnerChannels(CreateEMA(Period), CreateATR(Period), Multiplier);
end;

// Calculates Keltner Channels using an injectable ATR and middle band moving average.
class function TIndicators.CreateKeltnerChannels(
    const MovAvgMiddle: TConvertFunc<Double, Double>;
    const AtrFunc: TConvertFunc<TOhlcItem, Double>;
    Multiplier: Double
): TConvertFunc<TOhlcItem, TKeltnerChannelsResult>;
begin
    Result :=
        function(const Value: TOhlcItem): TKeltnerChannelsResult
        var
            atrValue, middleValue, typicalPrice: Double;
        begin
            // Calculate Typical Price for the middle band.
            typicalPrice := (Value.High + Value.Low + Value.Close) / 3.0;

            // Get values from the provided indicator functions.
            middleValue := MovAvgMiddle(typicalPrice);
            atrValue := AtrFunc(Value);

            // Set default NaN values for the warm-up period.
            Result.MiddleBand := middleValue;
            Result.UpperBand := Double.NaN;
            Result.LowerBand := Double.NaN;

            // Once both middle band and ATR have valid (non-NaN) values, calculate the channels.
            if not IsNan(middleValue) and not IsNan(atrValue) then
            begin
                Result.UpperBand := middleValue + (atrValue * Multiplier);
                Result.LowerBand := middleValue - (atrValue * Multiplier);
            end;
        end;
end;

class function TIndicators.CreateMean: TConvertFunc<TArray<Double>, Double>;
begin
    Result :=
        function(const Value: TArray<Double>): Double
        begin
            if Length(Value) = 0 then
                exit(NaN);
            Result := Value[0];
            for var i := 1 to High(Value) do
                Result := Result + Value[i];
            Result := Result / Length(Value);
        end;
end;

end.