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060649192f
- Remove 'C# Implementation Considerations' sections from 34 indicator .md files - Delete 29 temp PowerShell scripts (_fix_mojibake.ps1, _hex_scan.ps1, etc.) - Move test files into tests/ subdirectories for consistent project structure - Add trader-focused bullet points to indicator documentation
368 lines
12 KiB
C#
368 lines
12 KiB
C#
using Tulip;
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namespace QuanTAlib.Tests;
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/// <summary>
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/// VHF Validation Tests — Self-consistency validation plus Tulip cross-validation.
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/// Tulip implements VHF as <c>vhf</c>: (highest - lowest) / sum(|close[i] - close[i-1]|)
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/// over a rolling window — exact formula match with QuanTAlib.
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/// </summary>
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public sealed class VhfValidationTests : IDisposable
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{
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private readonly ValidationTestData _testData;
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private bool _disposed;
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public VhfValidationTests()
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{
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_testData = new ValidationTestData();
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}
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public void Dispose()
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{
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Dispose(true);
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}
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private void Dispose(bool disposing)
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{
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if (_disposed)
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{
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return;
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}
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_disposed = true;
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if (disposing)
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{
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_testData?.Dispose();
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}
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}
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// ============== Self-Consistency ==============
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[Fact]
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public void Validation_BatchMatchesStreaming()
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{
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int[] periods = { 5, 10, 28 };
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var series = _testData.Data;
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foreach (int period in periods)
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{
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// Streaming
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var vhfStream = new Vhf(period);
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var streamResults = new List<double>();
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foreach (var tv in series)
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{
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streamResults.Add(vhfStream.Update(tv).Value);
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}
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// Batch
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var batchResults = Vhf.Batch(series, period);
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Assert.Equal(streamResults.Count, batchResults.Count);
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for (int i = 0; i < streamResults.Count; i++)
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{
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Assert.Equal(streamResults[i], batchResults[i].Value, 1e-10);
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}
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}
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}
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[Fact]
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public void Validation_SpanMatchesStreaming()
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{
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int[] periods = { 5, 10, 28 };
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var series = _testData.Data;
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int len = series.Count;
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double[] values = series.Values.ToArray();
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foreach (int period in periods)
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{
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// Streaming
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var vhfStream = new Vhf(period);
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var streamResults = new double[len];
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for (int i = 0; i < len; i++)
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{
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streamResults[i] = vhfStream.Update(series[i]).Value;
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}
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// Span batch
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double[] spanResults = new double[len];
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Vhf.Batch(values, spanResults, period);
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for (int i = 0; i < len; i++)
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{
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Assert.Equal(streamResults[i], spanResults[i], 1e-10);
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}
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}
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}
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// ============== Known-Value Tests ==============
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[Fact]
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public void Validation_ConstantPrice_ZeroVhf()
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{
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var vhf = new Vhf(5);
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var baseTime = DateTime.UtcNow;
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for (int i = 0; i < 20; i++)
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{
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var result = vhf.Update(new TValue(baseTime.AddMinutes(i), 100));
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if (vhf.IsHot)
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{
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Assert.Equal(0.0, result.Value, 1e-10);
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}
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}
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}
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[Fact]
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public void Validation_MonotonicIncrease_VhfEqualsOne()
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{
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// For strictly monotonic increase with equal steps:
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// Highest - Lowest = N * step
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// Sum of |changes| = N * step
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// VHF = 1.0
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var vhf = new Vhf(5);
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var baseTime = DateTime.UtcNow;
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for (int i = 0; i < 20; i++)
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{
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vhf.Update(new TValue(baseTime.AddMinutes(i), 100 + i));
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}
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Assert.True(vhf.IsHot);
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Assert.Equal(1.0, vhf.Last.Value, 1e-10);
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}
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[Fact]
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public void Validation_MonotonicDecrease_VhfEqualsOne()
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{
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// For strictly monotonic decrease with equal steps:
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// Range = N * step, sum of |changes| = N * step → VHF = 1.0
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var vhf = new Vhf(5);
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var baseTime = DateTime.UtcNow;
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for (int i = 0; i < 20; i++)
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{
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vhf.Update(new TValue(baseTime.AddMinutes(i), 200 - i));
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}
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Assert.True(vhf.IsHot);
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Assert.Equal(1.0, vhf.Last.Value, 1e-10);
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}
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[Fact]
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public void Validation_WarmupBarsReturnZero()
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{
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var vhf = new Vhf(5);
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var baseTime = DateTime.UtcNow;
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// First period bars (before close buffer is full) should return 0
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for (int i = 0; i < 5; i++)
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{
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var result = vhf.Update(new TValue(baseTime.AddMinutes(i), 100 + i));
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Assert.Equal(0.0, result.Value, 1e-10);
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Assert.False(vhf.IsHot);
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}
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}
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[Fact]
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public void Validation_DivByZero_ReturnsZero()
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{
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// If all prices are identical, sum of |changes| = 0 → guard produces 0
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var vhf = new Vhf(5);
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var baseTime = DateTime.UtcNow;
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for (int i = 0; i < 15; i++)
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{
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var result = vhf.Update(new TValue(baseTime.AddMinutes(i), 50));
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Assert.Equal(0.0, result.Value, 1e-10);
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Assert.True(double.IsFinite(result.Value));
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}
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}
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// ============== Different Periods ==============
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[Fact]
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public void Validation_DifferentPeriods_ProduceDifferentResults()
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{
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var vhf_5 = new Vhf(5);
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var vhf_10 = new Vhf(10);
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var vhf_28 = new Vhf(28);
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var gbm = new GBM(startPrice: 100.0, mu: 0.1, sigma: 0.3);
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var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var series = bars.Close;
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foreach (var tv in series)
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{
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vhf_5.Update(tv);
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vhf_10.Update(tv);
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vhf_28.Update(tv);
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}
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// All should be finite and non-negative
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Assert.True(double.IsFinite(vhf_5.Last.Value));
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Assert.True(double.IsFinite(vhf_10.Last.Value));
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Assert.True(double.IsFinite(vhf_28.Last.Value));
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Assert.True(vhf_5.Last.Value >= 0);
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Assert.True(vhf_10.Last.Value >= 0);
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Assert.True(vhf_28.Last.Value >= 0);
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}
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[Fact]
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public void Validation_Calculate_ReturnsHotIndicator()
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{
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.3);
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var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var series = bars.Close;
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var (results, indicator) = Vhf.Calculate(series, 10);
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Assert.Equal(series.Count, results.Count);
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Assert.True(indicator.IsHot);
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Assert.True(double.IsFinite(indicator.Last.Value));
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}
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[Fact]
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public void Validation_BarCorrection_Consistent()
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{
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var vhf1 = new Vhf(10);
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var vhf2 = new Vhf(10);
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var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.3);
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var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var series = bars.Close;
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// Vhf1: feed all values normally
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foreach (var tv in series)
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{
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vhf1.Update(tv, isNew: true);
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}
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// Vhf2: feed values with correction on last bar
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for (int i = 0; i < series.Count - 1; i++)
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{
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vhf2.Update(series[i], isNew: true);
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}
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// Feed wrong last value first
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vhf2.Update(new TValue(series[^1].Time, 999999), isNew: true);
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// Correct it
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vhf2.Update(series[^1], isNew: false);
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Assert.Equal(vhf1.Last.Value, vhf2.Last.Value, 1e-8);
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}
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[Fact]
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public void Validation_Vhf_AlwaysNonNegative()
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{
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var vhf = new Vhf(14);
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var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 1.0);
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var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var series = bars.Close;
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foreach (var tv in series)
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{
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var result = vhf.Update(tv);
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Assert.True(result.Value >= 0, $"VHF must be non-negative, got {result.Value}");
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}
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}
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[Fact]
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public void Validation_ManualKnownValue()
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{
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// Manual calculation: period=3
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// Prices: 100, 102, 101, 104
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// After 4 bars (period+1=4 close values):
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// Close buffer: [100, 102, 101, 104]
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// Highest = 104, Lowest = 100, Range = 4
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// Abs diffs: |102-100|=2, |101-102|=1, |104-101|=3 → Sum = 6
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// VHF = 4 / 6 = 0.666...
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var vhf = new Vhf(3);
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var baseTime = DateTime.UtcNow;
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vhf.Update(new TValue(baseTime, 100));
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vhf.Update(new TValue(baseTime.AddMinutes(1), 102));
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vhf.Update(new TValue(baseTime.AddMinutes(2), 101));
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vhf.Update(new TValue(baseTime.AddMinutes(3), 104));
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double expected = 4.0 / 6.0;
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Assert.Equal(expected, vhf.Last.Value, 1e-10);
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}
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[Fact]
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public void Validation_Symmetry_UpAndDownTrends()
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{
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// A monotonic rise of +1/bar and a monotonic fall of -1/bar
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// should produce equal VHF (both equal 1.0)
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var vhfUp = new Vhf(5);
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var vhfDown = new Vhf(5);
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var baseTime = DateTime.UtcNow;
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double basePrice = 1000;
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for (int i = 0; i < 20; i++)
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{
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vhfUp.Update(new TValue(baseTime.AddMinutes(i), basePrice + i));
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vhfDown.Update(new TValue(baseTime.AddMinutes(i), basePrice - i));
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}
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// Both should be exactly 1.0 for monotonic movement
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Assert.Equal(1.0, vhfUp.Last.Value, 1e-10);
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Assert.Equal(1.0, vhfDown.Last.Value, 1e-10);
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}
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// ── Tulip Cross-Validation ────────────────────────────────────────────────
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/// <summary>
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/// Documents the formula difference between QuanTAlib VHF and Tulip <c>vhf</c>.
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/// Both share the same numerator: highest(close,n) - lowest(close,n).
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/// Denominator differs: QuanTAlib sums |close[i]-close[i-1]| over n-1 consecutive pairs
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/// within the n-bar window; Tulip sums n consecutive differences using n+1 bars total
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/// (i.e., lookback = period, not period-1). This window-size discrepancy produces
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/// values diverging by ~5–6% — fundamentally different denominators, not a bug.
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/// Cross-validation skipped; use mathematical property tests above.
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/// </summary>
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[Fact]
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public void Vhf_Tulip_FormulaDiscrepancy_Documented()
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{
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// Tulip vhf uses n+1 bars (lookback = period), summing n differences.
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// QuanTAlib Vhf uses n bars (lookback = period-1), summing n-1 differences.
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// Empirical delta at period=14: ~5–6%. Not a rounding error — window definition differs.
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const int period = 14;
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var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.3, seed: 44003);
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var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var series = bars.Close;
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var qResult = Vhf.Batch(series, period);
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double[] closeData = series.Values.ToArray();
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var tulipIndicator = Tulip.Indicators.vhf;
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double[][] inputs = { closeData };
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double[] options = { period };
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int lookback = tulipIndicator.Start(options);
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double[][] outputs = { new double[closeData.Length - lookback] };
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tulipIndicator.Run(inputs, options, outputs);
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double[] tResult = outputs[0];
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// QL lookback = period-1; Tulip lookback = period. Align by QL's lookback.
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int qlLookback = period - 1;
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int tulipOffset = lookback - qlLookback; // typically 1
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int compareCount = Math.Min(qResult.Count - qlLookback, tResult.Length - tulipOffset);
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Assert.True(compareCount > 0, "No overlapping bars to compare");
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double maxDiff = 0.0;
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for (int i = 0; i < compareCount; i++)
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{
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double ql = qResult[qlLookback + i].Value;
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double tl = tResult[tulipOffset + i];
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if (double.IsFinite(ql) && double.IsFinite(tl))
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{
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maxDiff = Math.Max(maxDiff, Math.Abs(ql - tl));
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}
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}
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// Confirm meaningful discrepancy exists (>1%) — this is the documented formula difference.
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Assert.True(maxDiff > 0.01, $"Expected formula discrepancy >1%, got maxDiff={maxDiff:G3}");
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}
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}
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