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https://github.com/mihakralj/QuanTAlib.git
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122 lines
4.7 KiB
C#
122 lines
4.7 KiB
C#
using System.Runtime.CompilerServices;
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namespace QuanTAlib;
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/// <summary>
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/// SMI: Stochastic Momentum Index
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/// A double-smoothed momentum indicator that shows where the close is relative
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/// to the midpoint of the recent high/low range. It helps identify overbought
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/// and oversold conditions with higher accuracy than traditional stochastics.
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/// </summary>
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/// <remarks>
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/// The SMI calculation process:
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/// 1. Calculate median price distance (Close - (High + Low)/2)
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/// 2. Calculate highest high and lowest low over period
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/// 3. First smoothing of median distance and range
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/// 4. Second smoothing of first smoothed values
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/// 5. Scale to percentage (-100 to +100)
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///
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/// Key characteristics:
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/// - Oscillates between -100 and +100
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/// - Double smoothing reduces noise
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/// - Traditional overbought level at +40
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/// - Traditional oversold level at -40
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/// - Centerline crossovers signal trend changes
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///
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/// Formula:
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/// D = Close - (High + Low)/2
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/// HL = Highest High - Lowest Low
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/// First smoothing:
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/// SD = EMA(EMA(D, period1), period2)
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/// SHL = EMA(EMA(HL, period1), period2)
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/// SMI = 100 * (SD / (SHL/2))
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///
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/// Sources:
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/// William Blau - "Momentum, Direction, and Divergence" (1995)
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/// https://www.tradingview.com/scripts/stochasticmomentumindex/
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///
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/// Note: Default periods (10,3,3) are commonly used values
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/// </remarks>
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[SkipLocalsInit]
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public sealed class Smi : AbstractBase
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{
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private readonly CircularBuffer _highs;
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private readonly CircularBuffer _lows;
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private readonly Ema _dEma1;
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private readonly Ema _dEma2;
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private readonly Ema _hlEma1;
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private readonly Ema _hlEma2;
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private const int DefaultPeriod = 10;
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private const int DefaultSmooth1 = 3;
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private const int DefaultSmooth2 = 3;
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private const double ScalingFactor = 100.0;
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/// <param name="period">The lookback period (default 10).</param>
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/// <param name="smooth1">First smoothing period (default 3).</param>
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/// <param name="smooth2">Second smoothing period (default 3).</param>
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/// <exception cref="ArgumentOutOfRangeException">Thrown when any period is less than 1.</exception>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public Smi(int period = DefaultPeriod, int smooth1 = DefaultSmooth1, int smooth2 = DefaultSmooth2)
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{
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if (period < 1)
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throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than 0");
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if (smooth1 < 1)
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throw new ArgumentOutOfRangeException(nameof(smooth1), "Smooth1 must be greater than 0");
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if (smooth2 < 1)
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throw new ArgumentOutOfRangeException(nameof(smooth2), "Smooth2 must be greater than 0");
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_highs = new(period);
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_lows = new(period);
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_dEma1 = new(smooth1);
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_dEma2 = new(smooth2);
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_hlEma1 = new(smooth1);
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_hlEma2 = new(smooth2);
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WarmupPeriod = period + smooth1 + smooth2;
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Name = $"SMI({period},{smooth1},{smooth2})";
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}
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/// <param name="source">The data source object that publishes updates.</param>
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/// <param name="period">The lookback period.</param>
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/// <param name="smooth1">First smoothing period.</param>
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/// <param name="smooth2">Second smoothing period.</param>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public Smi(object source, int period = DefaultPeriod, int smooth1 = DefaultSmooth1, int smooth2 = DefaultSmooth2)
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: this(period, smooth1, smooth2)
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{
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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new BarSignal(Sub));
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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protected override void ManageState(bool isNew)
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{
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if (isNew)
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{
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_highs.Add(BarInput.High);
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_lows.Add(BarInput.Low);
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_index++;
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}
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
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protected override double Calculation()
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{
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ManageState(BarInput.IsNew);
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// Calculate median price distance and range
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double midpoint = (BarInput.High + BarInput.Low) / 2.0;
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double distance = BarInput.Close - midpoint;
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double range = _highs.Max() - _lows.Min();
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// First smoothing
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double smoothD1 = _dEma1.Calc(new TValue(BarInput.Time, distance, BarInput.IsNew));
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double smoothHL1 = _hlEma1.Calc(new TValue(BarInput.Time, range, BarInput.IsNew));
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// Second smoothing
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double smoothD2 = _dEma2.Calc(new TValue(BarInput.Time, smoothD1, BarInput.IsNew));
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double smoothHL2 = _hlEma2.Calc(new TValue(BarInput.Time, smoothHL1, BarInput.IsNew));
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// Calculate SMI
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return smoothHL2 >= double.Epsilon ? ScalingFactor * (smoothD2 / (smoothHL2 / 2.0)) : 0;
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}
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}
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