Files
MycLib/Src/Myc.Trade.Indicators.pas
T
2025-07-13 21:49:42 +02:00

356 lines
12 KiB
ObjectPascal

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): TIndicatorFunc<Double, Double>; static;
// Exponential Moving Average
class function CreateEMA(Period: Integer): TIndicatorFunc<Double, Double>; static;
// Hull Moving Average
class function CreateHMA(Period: Integer): TIndicatorFunc<Double, Double>; static;
// Relative Strength Index
class function CreateRSI(Period: Integer): TIndicatorFunc<Double, Double>; static;
// Moving Average Convergence Divergence
class function CreateMACD(FastPeriod, SlowPeriod, SignalPeriod: Integer): TIndicatorFunc<Double, TMacdResult>; static;
// Stochastic Oscillator
class function CreateStochastic(KPeriod, DPeriod: Integer): TIndicatorFunc<TOhlcItem, TStochasticResult>; static;
// Bollinger Bands
class function CreateBollingerBands(Period: Integer; Multiplier: Double): TIndicatorFunc<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): TIndicatorFunc<Double, TBollingerBandsResult>;
begin
var sourceData := TMycDataArray<Double>.CreateEmpty;
Result :=
function(const 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): TIndicatorFunc<Double, Double>;
begin
var lastEma: Double := Double.NaN;
var sourceData := TMycDataArray<Double>.CreateEmpty;
var multiplier := 2 / (Period + 1);
Result :=
function(const 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): TIndicatorFunc<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(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 := 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): TIndicatorFunc<Double, TMacdResult>;
begin
var emaFast := CreateEMA(FastPeriod);
var emaSlow := CreateEMA(SlowPeriod);
var emaSignal := CreateEMA(SignalPeriod);
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): TIndicatorFunc<Double, Double>;
begin
var avgGain: Double := Double.NaN;
var avgLoss: Double := Double.NaN;
var sourceData := TMycDataArray<Double>.CreateEmpty;
Result :=
function(const 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): TIndicatorFunc<Double, Double>;
begin
var sourceData := TMycDataArray<Double>.CreateEmpty;
Result :=
function(const 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): TIndicatorFunc<TOhlcItem, TStochasticResult>;
begin
var sourceData := TMycDataArray<TOhlcItem>.CreateEmpty;
var smaD := CreateSMA(DPeriod);
Result :=
function(const 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.