mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-22 04:28:04 +00:00
Add Stochastic Oscillator implementation and validation tests
- Implemented Stochastic Oscillator (%K and %D) in Stoch.cs with streaming and batch processing capabilities. - Added validation tests for the Stochastic Oscillator in Stoch.Validation.Tests.cs, ensuring consistency with Skender.Stock.Indicators. - Created documentation for the Stochastic Oscillator in Stoch.md, detailing its mathematical formula, architecture, parameters, and common pitfalls. - Updated project file to include necessary numeric libraries for highest and lowest calculations.
This commit is contained in:
Miha Kralj
@@ -0,0 +1,317 @@
|
||||
using System.Runtime.CompilerServices;
|
||||
using System.Runtime.InteropServices;
|
||||
|
||||
namespace QuanTAlib;
|
||||
|
||||
/// <summary>
|
||||
/// CFO: Chande Forecast Oscillator
|
||||
/// </summary>
|
||||
/// <remarks>
|
||||
/// Measures the percentage difference between the current price and the
|
||||
/// Time Series Forecast (linear regression endpoint):
|
||||
/// <c>CFO = 100 × (source − TSF) / source</c>
|
||||
///
|
||||
/// Uses O(1) incremental sumY / sumXY maintenance from the PineScript reference.
|
||||
/// When source equals zero, returns NaN to avoid division by zero.
|
||||
///
|
||||
/// References:
|
||||
/// Tushar Chande, "The New Technical Trader", 1994
|
||||
/// PineScript reference: cfo.pine
|
||||
/// </remarks>
|
||||
[SkipLocalsInit]
|
||||
public sealed class Cfo : AbstractBase
|
||||
{
|
||||
private readonly int _period;
|
||||
private readonly RingBuffer _buffer;
|
||||
|
||||
// Precomputed linear regression constants (full window)
|
||||
private readonly double _sumX; // 0 + 1 + ... + (period-1)
|
||||
private readonly double _denomX; // period * sumX2 - sumX²
|
||||
|
||||
[StructLayout(LayoutKind.Auto)]
|
||||
private record struct State(
|
||||
double SumY,
|
||||
double SumXY,
|
||||
int Count,
|
||||
double LastValid);
|
||||
private State _state;
|
||||
private State _p_state;
|
||||
|
||||
private const int ResyncInterval = 1000;
|
||||
private int _tickCount;
|
||||
|
||||
/// <summary>
|
||||
/// Creates CFO with specified period.
|
||||
/// </summary>
|
||||
/// <param name="period">Lookback period for linear regression (must be > 0)</param>
|
||||
public Cfo(int period = 14)
|
||||
{
|
||||
if (period <= 0)
|
||||
{
|
||||
throw new ArgumentException("Period must be greater than 0", nameof(period));
|
||||
}
|
||||
|
||||
_period = period;
|
||||
_buffer = new RingBuffer(period);
|
||||
Name = $"Cfo({period})";
|
||||
WarmupPeriod = period;
|
||||
|
||||
_sumX = period * (period - 1) / 2.0;
|
||||
double sumX2 = period * (period - 1.0) * (2.0 * period - 1.0) / 6.0;
|
||||
_denomX = period * sumX2 - _sumX * _sumX;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Creates CFO with specified source and period.
|
||||
/// </summary>
|
||||
public Cfo(ITValuePublisher source, int period = 14) : this(period)
|
||||
{
|
||||
source.Pub += Handle;
|
||||
}
|
||||
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
|
||||
|
||||
/// <summary>
|
||||
/// True if the indicator has enough data for valid results.
|
||||
/// </summary>
|
||||
public override bool IsHot => _buffer.IsFull;
|
||||
|
||||
/// <summary>
|
||||
/// Period of the indicator.
|
||||
/// </summary>
|
||||
public int Period => _period;
|
||||
|
||||
/// <inheritdoc/>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public override TValue Update(TValue input, bool isNew = true)
|
||||
{
|
||||
double value = input.Value;
|
||||
|
||||
// Sanitize input
|
||||
if (!double.IsFinite(value))
|
||||
{
|
||||
value = double.IsFinite(_state.LastValid) ? _state.LastValid : 0.0;
|
||||
}
|
||||
else
|
||||
{
|
||||
_state.LastValid = value;
|
||||
}
|
||||
|
||||
if (isNew)
|
||||
{
|
||||
_p_state = _state;
|
||||
|
||||
// O(1) incremental sumXY maintenance (PineScript algorithm)
|
||||
if (_buffer.Count == _buffer.Capacity)
|
||||
{
|
||||
double oldest = _buffer.Oldest;
|
||||
_state.SumY -= oldest;
|
||||
_state.SumXY -= _state.SumY;
|
||||
_state.SumXY += (_period - 1) * value;
|
||||
}
|
||||
else
|
||||
{
|
||||
_state.SumXY += _state.Count * value;
|
||||
_state.Count++;
|
||||
}
|
||||
|
||||
_state.SumY += value;
|
||||
_buffer.Add(value);
|
||||
|
||||
_tickCount++;
|
||||
if (_buffer.IsFull && _tickCount >= ResyncInterval)
|
||||
{
|
||||
_tickCount = 0;
|
||||
RecalculateSums();
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
_state = _p_state;
|
||||
|
||||
_buffer.UpdateNewest(value);
|
||||
RecalculateSums();
|
||||
}
|
||||
|
||||
if (!_buffer.IsFull)
|
||||
{
|
||||
Last = new TValue(input.Time, 0.0);
|
||||
PubEvent(Last, isNew);
|
||||
return Last;
|
||||
}
|
||||
|
||||
// Linear regression: slope, intercept, TSF
|
||||
double slope = (_period * _state.SumXY - _sumX * _state.SumY) / _denomX;
|
||||
double intercept = (_state.SumY - slope * _sumX) / _period;
|
||||
double tsf = Math.FusedMultiplyAdd(slope, _period - 1, intercept);
|
||||
|
||||
// CFO = 100 * (source - tsf) / source
|
||||
double cfo = value == 0.0 ? double.NaN : 100.0 * (value - tsf) / value;
|
||||
|
||||
Last = new TValue(input.Time, cfo);
|
||||
PubEvent(Last, isNew);
|
||||
return Last;
|
||||
}
|
||||
|
||||
/// <inheritdoc/>
|
||||
public override TSeries Update(TSeries source)
|
||||
{
|
||||
int len = source.Count;
|
||||
var t = new List<long>(len);
|
||||
var v = new List<double>(len);
|
||||
CollectionsMarshal.SetCount(t, len);
|
||||
CollectionsMarshal.SetCount(v, len);
|
||||
|
||||
var tSpan = CollectionsMarshal.AsSpan(t);
|
||||
var vSpan = CollectionsMarshal.AsSpan(v);
|
||||
|
||||
Batch(source.Values, vSpan, _period);
|
||||
source.Times.CopyTo(tSpan);
|
||||
|
||||
// Update internal state to match final position
|
||||
for (int i = 0; i < len; i++)
|
||||
{
|
||||
Update(new TValue(source.Times[i], source.Values[i]), isNew: true);
|
||||
}
|
||||
|
||||
return new TSeries(t, v);
|
||||
}
|
||||
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
private void RecalculateSums()
|
||||
{
|
||||
_state.SumY = 0.0;
|
||||
_state.SumXY = 0.0;
|
||||
_state.Count = _buffer.Count;
|
||||
for (int i = 0; i < _buffer.Count; i++)
|
||||
{
|
||||
double v = _buffer[i];
|
||||
_state.SumY += v;
|
||||
_state.SumXY += i * v;
|
||||
}
|
||||
}
|
||||
|
||||
/// <inheritdoc/>
|
||||
public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
|
||||
{
|
||||
for (int i = 0; i < source.Length; i++)
|
||||
{
|
||||
Update(new TValue(DateTime.UtcNow, source[i]), isNew: true);
|
||||
}
|
||||
}
|
||||
|
||||
/// <inheritdoc/>
|
||||
public override void Reset()
|
||||
{
|
||||
_buffer.Clear();
|
||||
_state = default;
|
||||
_p_state = default;
|
||||
_tickCount = 0;
|
||||
Last = default;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Calculates CFO for entire series.
|
||||
/// </summary>
|
||||
public static TSeries Batch(TSeries source, int period = 14)
|
||||
{
|
||||
int len = source.Count;
|
||||
var t = new List<long>(len);
|
||||
var v = new List<double>(len);
|
||||
CollectionsMarshal.SetCount(t, len);
|
||||
CollectionsMarshal.SetCount(v, len);
|
||||
|
||||
var tSpan = CollectionsMarshal.AsSpan(t);
|
||||
var vSpan = CollectionsMarshal.AsSpan(v);
|
||||
|
||||
Batch(source.Values, vSpan, period);
|
||||
source.Times.CopyTo(tSpan);
|
||||
|
||||
return new TSeries(t, v);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Batch CFO calculation with O(1) incremental linear regression.
|
||||
/// </summary>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period = 14)
|
||||
{
|
||||
if (source.Length != output.Length)
|
||||
{
|
||||
throw new ArgumentException("Source and output must have the same length", nameof(output));
|
||||
}
|
||||
|
||||
if (period <= 0)
|
||||
{
|
||||
throw new ArgumentException("Period must be greater than 0", nameof(period));
|
||||
}
|
||||
|
||||
int len = source.Length;
|
||||
if (len == 0)
|
||||
{
|
||||
return;
|
||||
}
|
||||
|
||||
double sumX = period * (period - 1) / 2.0;
|
||||
double sumX2 = period * (period - 1.0) * (2.0 * period - 1.0) / 6.0;
|
||||
double denomX = period * sumX2 - sumX * sumX;
|
||||
|
||||
double sumY = 0.0;
|
||||
double sumXY = 0.0;
|
||||
int count = 0;
|
||||
double lastValid = 0.0;
|
||||
|
||||
var valueBuffer = new RingBuffer(period);
|
||||
|
||||
for (int i = 0; i < len; i++)
|
||||
{
|
||||
double val = source[i];
|
||||
|
||||
if (!double.IsFinite(val))
|
||||
{
|
||||
val = lastValid;
|
||||
}
|
||||
else
|
||||
{
|
||||
lastValid = val;
|
||||
}
|
||||
|
||||
// O(1) incremental sumXY maintenance
|
||||
if (valueBuffer.Count == valueBuffer.Capacity)
|
||||
{
|
||||
double oldest = valueBuffer.Oldest;
|
||||
sumY -= oldest;
|
||||
sumXY -= sumY;
|
||||
sumXY += (period - 1) * val;
|
||||
}
|
||||
else
|
||||
{
|
||||
sumXY += count * val;
|
||||
count++;
|
||||
}
|
||||
|
||||
sumY += val;
|
||||
valueBuffer.Add(val);
|
||||
|
||||
if (count < period)
|
||||
{
|
||||
output[i] = 0.0;
|
||||
continue;
|
||||
}
|
||||
|
||||
double slope = (period * sumXY - sumX * sumY) / denomX;
|
||||
double intercept = (sumY - slope * sumX) / period;
|
||||
double tsf = Math.FusedMultiplyAdd(slope, period - 1, intercept);
|
||||
|
||||
output[i] = val == 0.0 ? double.NaN : 100.0 * (val - tsf) / val;
|
||||
}
|
||||
}
|
||||
|
||||
public static (TSeries Results, Cfo Indicator) Calculate(TSeries source, int period = 14)
|
||||
{
|
||||
var indicator = new Cfo(period);
|
||||
TSeries results = indicator.Update(source);
|
||||
return (results, indicator);
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user