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Add validation tests for various volume and momentum indicators
- Introduced Massi validation tests to ensure mathematical properties hold for the Mass Index indicator. - Added Va validation tests for Volume Accumulation, checking for finite outputs and correct accumulation behavior. - Implemented Vf validation tests for Volume Force, verifying outputs for rising and falling prices, and ensuring batch and streaming results match. - Created Vo validation tests for Volume Oscillator, confirming behavior with constant, increasing, and decreasing volumes. - Developed Vroc validation tests for Volume Rate of Change, validating outputs for constant volume and changes in volume. - Updated project file to include new momentum indicators (MACD and RSI) in the compilation.
This commit is contained in:
Miha Kralj
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// Vf: Mathematical property validation tests
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// Volume Force is a QuanTAlib-specific indicator combining price change with volume
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// and EMA smoothing. No standard external library equivalents. Validation uses
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// mathematical property testing.
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namespace QuanTAlib.Tests;
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using Xunit;
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public class VfValidationTests
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{
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private const int DefaultPeriod = 14;
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private const int TestDataLength = 500;
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[Fact]
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public void Vf_Output_IsFiniteForGbmData()
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{
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var bars = new GBM(sigma: 0.5, seed: 123).Fetch(TestDataLength, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var vf = new Vf(DefaultPeriod);
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for (int i = 0; i < bars.Count; i++)
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{
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var result = vf.Update(bars[i], isNew: true);
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Assert.True(double.IsFinite(result.Value),
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$"Vf output must be finite at bar {i}, got {result.Value}");
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}
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}
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[Fact]
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public void Vf_FirstBar_ReturnsZero()
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{
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var vf = new Vf(DefaultPeriod);
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var bar = new TBar(DateTime.UtcNow, 100, 101, 99, 100, 1000);
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var result = vf.Update(bar, isNew: true);
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// First bar has no previous close, so raw VF = 0
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Assert.Equal(0.0, result.Value, precision: 10);
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}
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[Fact]
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public void Vf_RisingPrice_PositiveForce()
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{
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var vf = new Vf(DefaultPeriod);
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// First bar
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var bar1 = new TBar(DateTime.UtcNow, 100, 100, 100, 100, 1000);
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vf.Update(bar1, isNew: true);
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// Rising price: positive raw VF
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var bar2 = new TBar(DateTime.UtcNow.AddMinutes(1), 105, 105, 100, 105, 1000);
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var result = vf.Update(bar2, isNew: true);
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// rawVF = (105 - 100) * 1000 = 5000, EMA of that should be positive
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Assert.True(result.Value > 0,
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$"Vf should be positive for rising price, got {result.Value}");
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}
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[Fact]
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public void Vf_FallingPrice_NegativeForce()
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{
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var vf = new Vf(DefaultPeriod);
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// First bar
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var bar1 = new TBar(DateTime.UtcNow, 100, 100, 100, 100, 1000);
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vf.Update(bar1, isNew: true);
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// Falling price: negative raw VF
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var bar2 = new TBar(DateTime.UtcNow.AddMinutes(1), 95, 100, 95, 95, 1000);
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var result = vf.Update(bar2, isNew: true);
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// rawVF = (95 - 100) * 1000 = -5000, EMA of that should be negative
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Assert.True(result.Value < 0,
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$"Vf should be negative for falling price, got {result.Value}");
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}
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[Fact]
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public void Vf_ConstantPrice_ZeroForce()
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{
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var vf = new Vf(DefaultPeriod);
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// Feed constant-price bars
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for (int i = 0; i < 50; i++)
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{
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var bar = new TBar(
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DateTime.UtcNow.AddMinutes(i),
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100, 100, 100, 100, 1000);
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vf.Update(bar, isNew: true);
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}
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// No price change → raw VF = 0 each bar → EMA converges to 0
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Assert.Equal(0.0, vf.Last.Value, precision: 8);
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}
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[Fact]
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public void Vf_HighVolume_AmplifiesForce()
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{
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// Low volume
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var vfLow = new Vf(DefaultPeriod);
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var bar1Low = new TBar(DateTime.UtcNow, 100, 100, 100, 100, 100);
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vfLow.Update(bar1Low, isNew: true);
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var bar2Low = new TBar(DateTime.UtcNow.AddMinutes(1), 105, 105, 100, 105, 100);
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vfLow.Update(bar2Low, isNew: true);
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// High volume
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var vfHigh = new Vf(DefaultPeriod);
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var bar1High = new TBar(DateTime.UtcNow, 100, 100, 100, 100, 10000);
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vfHigh.Update(bar1High, isNew: true);
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var bar2High = new TBar(DateTime.UtcNow.AddMinutes(1), 105, 105, 100, 105, 10000);
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vfHigh.Update(bar2High, isNew: true);
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// Higher volume should produce larger absolute VF
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Assert.True(System.Math.Abs(vfHigh.Last.Value) > System.Math.Abs(vfLow.Last.Value),
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$"High volume VF ({vfHigh.Last.Value}) should exceed low volume VF ({vfLow.Last.Value})");
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}
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[Fact]
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public void Vf_BatchAndStreaming_ProduceSameResults()
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{
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var bars = new GBM(sigma: 0.5, seed: 123).Fetch(TestDataLength, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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// Batch
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var batchResults = Vf.Batch(bars, DefaultPeriod);
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// Streaming
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var streamVf = new Vf(DefaultPeriod);
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var streamResults = new double[bars.Count];
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for (int i = 0; i < bars.Count; i++)
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{
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var result = streamVf.Update(bars[i], isNew: true);
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streamResults[i] = result.Value;
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}
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Assert.Equal(batchResults.Count, bars.Count);
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for (int i = 0; i < bars.Count; i++)
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{
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Assert.Equal(batchResults.Values[i], streamResults[i], precision: 8);
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}
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}
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[Fact]
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public void Vf_SpanAndStreaming_ProduceSameResults()
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{
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var bars = new GBM(sigma: 0.5, seed: 123).Fetch(TestDataLength, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var spanOutput = new double[bars.Count];
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Vf.Batch(bars.Close.Values, bars.Volume.Values, spanOutput, DefaultPeriod);
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// Streaming
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var streamVf = new Vf(DefaultPeriod);
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for (int i = 0; i < bars.Count; i++)
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{
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var result = streamVf.Update(bars[i], isNew: true);
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Assert.Equal(spanOutput[i], result.Value, precision: 8);
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}
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}
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[Fact]
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public void Vf_DifferentPeriods_ProduceDifferentSmoothing()
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{
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var bars = new GBM(sigma: 0.5, seed: 123).Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var vf3 = new Vf(period: 3);
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var vf50 = new Vf(period: 50);
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for (int i = 0; i < bars.Count; i++)
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{
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vf3.Update(bars[i], isNew: true);
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vf50.Update(bars[i], isNew: true);
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}
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Assert.NotEqual(vf3.Last.Value, vf50.Last.Value);
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}
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[Fact]
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public void Vf_BarCorrection_IsNewFalse_RestoresState()
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{
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var bars = new GBM(sigma: 0.5, seed: 123).Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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var vf = new Vf(DefaultPeriod);
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for (int i = 0; i < 30; i++)
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{
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vf.Update(bars[i], isNew: true);
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}
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vf.Update(bars[30], isNew: true);
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double afterNew = vf.Last.Value;
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vf.Update(bars[30], isNew: false);
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double afterCorrection = vf.Last.Value;
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Assert.Equal(afterNew, afterCorrection, precision: 10);
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}
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}
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