Files
QuanTAlib/lib/oscillators/Cti.cs
T

77 lines
2.5 KiB
C#

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