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77 lines
2.5 KiB
C#
77 lines
2.5 KiB
C#
using System.Runtime.CompilerServices;
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namespace QuanTAlib;
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/// <summary>
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/// CTI: Ehler's Correlation Trend Indicator
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/// A momentum oscillator that measures the correlation between the price and a lagged version of the price.
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/// </summary>
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/// <remarks>
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/// The CTI calculation process:
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/// 1. Calculate the correlation between the price and a lagged version of the price over a specified period.
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/// 2. Normalize the correlation values to oscillate between -1 and 1.
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/// 3. Use the normalized correlation values to calculate the CTI.
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///
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/// Key characteristics:
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/// - Oscillates between -1 and 1
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/// - Positive values indicate bullish momentum
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/// - Negative values indicate bearish momentum
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///
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/// Formula:
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/// CTI = 2 * (Correlation - 0.5)
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///
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/// Sources:
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/// John Ehlers - "Cybernetic Analysis for Stocks and Futures" (2004)
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/// https://www.investopedia.com/terms/c/correlation-trend-indicator.asp
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/// </remarks>
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[SkipLocalsInit]
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public sealed class Cti : AbstractBase
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{
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private readonly int _period;
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private readonly CircularBuffer _priceBuffer;
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private readonly Corr _correlation;
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/// <param name="source">The data source object that publishes updates.</param>
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/// <param name="period">The calculation period (default: 20)</param>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public Cti(object source, int period = 20) : this(period)
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{
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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public Cti(int period = 20)
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{
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_period = period;
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_priceBuffer = new CircularBuffer(period);
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_correlation = new Corr(period);
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WarmupPeriod = period;
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Name = "CTI";
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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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_index++;
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}
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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protected override double Calculation()
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{
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ManageState(Input.IsNew);
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_priceBuffer.Add(Input.Value, Input.IsNew);
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var laggedPrice = _index >= _period ? _priceBuffer[_index - _period] : double.NaN;
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_correlation.Calc(new TValue(Input.Time, Input.Value, Input.IsNew), new TValue(Input.Time, laggedPrice, Input.IsNew));
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if (_index < _period - 1) return double.NaN;
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var correlation = _correlation.Value;
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return 2 * (correlation - 0.5);
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}
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}
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