MycLib/Src/Myc.Trade.Indicators.pas

unit Myc.Trade.Indicators;

interface

uses
    System.SysUtils,
    System.Math,
    Myc.Trade.Types,
    Myc.Trade.DataArray;

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;

    TIndicators = record
    private
        class function CalculateSMA(const Series: TMycDataArray<Double>; const Period: Integer): Double; static;
        class function CalculateStdDev(const Series: TMycDataArray<Double>; const Period: Integer): Double; static;
        class function CalculateWMA(const Series: TMycDataArray<Double>; const Period: Integer): Double; static;
    public
        // Simple Moving Average
        class function CreateSMA(Period: Integer): TFunc<Double, Double>; static;
        // Exponential Moving Average
        class function CreateEMA(Period: Integer): TFunc<Double, Double>; static;
        // Hull Moving Average
        class function CreateHMA(Period: Integer): TFunc<Double, Double>; static;
        // Relative Strength Index
        class function CreateRSI(Period: Integer): TFunc<Double, Double>; static;
        // Moving Average Convergence Divergence
        class function CreateMACD(FastPeriod, SlowPeriod, SignalPeriod: Integer): TFunc<Double, TMacdResult>; static;
        // Stochastic Oscillator
        class function CreateStochastic(KPeriod, DPeriod: Integer): TFunc<TOhlcItem, TStochasticResult>; static;
        // Bollinger Bands
        class function CreateBollingerBands(Period: Integer; Multiplier: Double): TFunc<Double, TBollingerBandsResult>; static;
    end;

implementation

{ TIndicators }

class function TIndicators.CalculateSMA(const Series: TMycDataArray<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: TMycDataArray<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: TMycDataArray<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): TFunc<Double, TBollingerBandsResult>;
begin
    var sourceData := TMycDataArray<Double>.CreateEmpty;
    Result :=
        function(Value: Double): TBollingerBandsResult
        var
            stdDev: Double;
        begin
            sourceData := 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): TFunc<Double, Double>;
begin
    var lastEma: Double := Double.NaN;
    var sourceData := TMycDataArray<Double>.CreateEmpty;
    var multiplier := 2 / (Period + 1);

    Result :=
        function(Value: Double): Double
        begin
            sourceData := 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): TFunc<Double, Double>;
begin
    var periodHalf := Period div 2;
    var periodSqrt := Round(Sqrt(Period));
    var sourceData := TMycDataArray<Double>.CreateEmpty;
    var diffSeries := TMycDataArray<Double>.CreateEmpty;

    Result :=
        function(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 := 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 := 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;

class function TIndicators.CreateMACD(FastPeriod, SlowPeriod, SignalPeriod: Integer): TFunc<Double, TMacdResult>;
begin
    var emaFast := CreateEMA(FastPeriod);
    var emaSlow := CreateEMA(SlowPeriod);
    var emaSignal := CreateEMA(SignalPeriod);

    Result :=
        function(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): TFunc<Double, Double>;
begin
    var avgGain: Double := Double.NaN;
    var avgLoss: Double := Double.NaN;
    var sourceData := TMycDataArray<Double>.CreateEmpty;

    Result :=
        function(Value: Double): Double
        var
            change, gain, loss, rs: Double;
            gainSum, lossSum: Double;
            i: Integer;
        begin
            sourceData := 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): TFunc<Double, Double>;
begin
    var sourceData := TMycDataArray<Double>.CreateEmpty;
    Result :=
        function(Value: Double): Double
        begin
            sourceData := sourceData.Add(Value, Period);
            if (sourceData.Count >= Period) then
                Result := CalculateSMA(sourceData, Period)
            else
                Result := Double.NaN;
        end;
end;

class function TIndicators.CreateStochastic(KPeriod, DPeriod: Integer): TFunc<TOhlcItem, TStochasticResult>;
begin
    var sourceData := TMycDataArray<TOhlcItem>.CreateEmpty;
    var smaD := CreateSMA(DPeriod);

    Result :=
        function(Value: TOhlcItem): TStochasticResult
        var
            i: Integer;
            highestHigh, lowestLow: Double;
        begin
            sourceData := 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;

end.