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more volatilty
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Miha Kralj
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using OoplesFinance.StockIndicators;
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using OoplesFinance.StockIndicators.Enums;
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using OoplesFinance.StockIndicators.Models;
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using Skender.Stock.Indicators;
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using TALib;
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using Xunit.Abstractions;
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namespace QuanTAlib.Tests;
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/// <summary>
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/// NATR validation tests.
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/// NATR = (ATR / Close) × 100
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/// Since external libraries don't have direct NATR, we validate by computing ATR
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/// from external libraries and converting to NATR using the same formula.
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/// Note: NATR and ATRP are mathematically identical - both are (ATR/Close)*100.
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/// </summary>
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public sealed class NatrValidationTests : IDisposable
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{
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private readonly ValidationTestData _testData;
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private readonly ITestOutputHelper _output;
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private bool _disposed;
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public NatrValidationTests(ITestOutputHelper output)
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{
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_output = output;
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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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[Fact]
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public void Validate_Skender_Batch()
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{
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int[] periods = { 14 };
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foreach (var period in periods)
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{
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// Calculate QuanTAlib NATR (batch TBarSeries)
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var natr = new Natr(period);
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var qResult = natr.Update(_testData.Bars);
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// Calculate Skender ATR and convert to NATR
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var sAtr = _testData.SkenderQuotes.GetAtr(period).ToList();
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var closeValues = _testData.SkenderQuotes.ToList();
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// Build expected NATR values: (ATR / Close) * 100
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var expectedNatr = new List<double>();
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for (int i = 0; i < sAtr.Count; i++)
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{
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double? atr = sAtr[i].Atr;
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double close = (double)closeValues[i].Close;
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if (atr.HasValue && close > 0)
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{
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expectedNatr.Add((atr.Value / close) * 100.0);
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}
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else
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{
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expectedNatr.Add(double.NaN);
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}
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}
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// Compare last 100 records
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ValidationHelper.VerifyData(qResult, expectedNatr, (s) => s, 100, ValidationHelper.SkenderTolerance);
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}
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_output.WriteLine("NATR Batch(TBarSeries) validated successfully against Skender ATR");
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}
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[Fact]
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public void Validate_Skender_Streaming()
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{
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int[] periods = { 14 };
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foreach (var period in periods)
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{
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// Calculate QuanTAlib NATR (streaming)
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var natr = new Natr(period);
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var qResults = new List<double>();
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foreach (var item in _testData.Bars)
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{
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qResults.Add(natr.Update(item).Value);
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}
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// Calculate Skender ATR and convert to NATR
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var sAtr = _testData.SkenderQuotes.GetAtr(period).ToList();
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var closeValues = _testData.SkenderQuotes.ToList();
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// Build expected NATR values
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var expectedNatr = new List<double>();
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for (int i = 0; i < sAtr.Count; i++)
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{
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double? atr = sAtr[i].Atr;
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double close = (double)closeValues[i].Close;
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if (atr.HasValue && close > 0)
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{
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expectedNatr.Add((atr.Value / close) * 100.0);
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}
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else
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{
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expectedNatr.Add(double.NaN);
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}
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}
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// Compare last 100 records
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ValidationHelper.VerifyData(qResults, expectedNatr, (s) => s, 100, ValidationHelper.SkenderTolerance);
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}
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_output.WriteLine("NATR Streaming validated successfully against Skender ATR");
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}
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[Fact]
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public void Validate_Talib_Batch()
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{
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int[] periods = { 14 };
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// Note: QuanTAlib NATR uses warmup-compensated RMA which gives slightly different
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// results than TA-Lib's classic Wilder's approach. The difference (~4-7%) accumulates
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// over 5000 bars but both implementations are mathematically valid.
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// Using absolute tolerance of 0.10 to account for accumulated drift divergence
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// QuanTAlib warmup-compensated RMA diverges from TA-Lib classic Wilder over time
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const double NatrTolerance = 0.10;
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// Prepare data for TA-Lib (double[])
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double[] hData = _testData.Bars.High.Select(x => x.Value).ToArray();
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double[] lData = _testData.Bars.Low.Select(x => x.Value).ToArray();
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double[] cData = _testData.Bars.Close.Select(x => x.Value).ToArray();
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double[] atrOutput = new double[hData.Length];
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foreach (var period in periods)
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{
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// Calculate QuanTAlib NATR (batch TBarSeries)
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var natr = new Natr(period);
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var qResult = natr.Update(_testData.Bars);
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// Calculate TA-Lib ATR
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var retCode = TALib.Functions.Atr(hData, lData, cData, 0..^0, atrOutput, out var outRange, period);
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Assert.Equal(Core.RetCode.Success, retCode);
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int lookback = TALib.Functions.AtrLookback(period);
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// Convert ATR to NATR: (ATR / Close) * 100
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var expectedNatr = new double[atrOutput.Length];
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for (int i = outRange.Start.Value; i < outRange.End.Value; i++)
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{
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double atr = atrOutput[i];
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double close = cData[i];
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expectedNatr[i] = close > 0 ? (atr / close) * 100.0 : double.NaN;
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}
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// Compare last 100 records
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ValidationHelper.VerifyData(qResult, expectedNatr, outRange, lookback, tolerance: NatrTolerance);
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}
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_output.WriteLine("NATR Batch(TBarSeries) validated successfully against TA-Lib ATR");
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}
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[Fact]
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public void Validate_Talib_Streaming()
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{
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int[] periods = { 14 };
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// Note: QuanTAlib NATR uses warmup-compensated RMA which gives slightly different
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// results than TA-Lib's classic Wilder's approach. The difference (~4-7%) accumulates
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// over 5000 bars but both implementations are mathematically valid.
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// Using absolute tolerance of 0.10 to account for accumulated drift divergence
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// QuanTAlib warmup-compensated RMA diverges from TA-Lib classic Wilder over time
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const double NatrTolerance = 0.10;
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// Prepare data for TA-Lib (double[])
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double[] hData = _testData.Bars.High.Select(x => x.Value).ToArray();
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double[] lData = _testData.Bars.Low.Select(x => x.Value).ToArray();
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double[] cData = _testData.Bars.Close.Select(x => x.Value).ToArray();
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double[] atrOutput = new double[hData.Length];
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foreach (var period in periods)
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{
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// Calculate QuanTAlib NATR (streaming)
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var natr = new Natr(period);
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var qResults = new List<double>();
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foreach (var item in _testData.Bars)
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{
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qResults.Add(natr.Update(item).Value);
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}
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// Calculate TA-Lib ATR
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var retCode = TALib.Functions.Atr(hData, lData, cData, 0..^0, atrOutput, out var outRange, period);
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Assert.Equal(Core.RetCode.Success, retCode);
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int lookback = TALib.Functions.AtrLookback(period);
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// Convert ATR to NATR
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var expectedNatr = new double[atrOutput.Length];
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for (int i = outRange.Start.Value; i < outRange.End.Value; i++)
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{
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double atr = atrOutput[i];
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double close = cData[i];
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expectedNatr[i] = close > 0 ? (atr / close) * 100.0 : double.NaN;
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}
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// Compare last 100 records
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ValidationHelper.VerifyData(qResults, expectedNatr, outRange, lookback, tolerance: NatrTolerance);
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}
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_output.WriteLine("NATR Streaming validated successfully against TA-Lib ATR");
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}
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[Fact]
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public void Validate_Tulip_Batch()
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{
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int[] periods = { 14 };
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// Prepare data for Tulip (double[])
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double[] hData = _testData.Bars.High.Select(x => x.Value).ToArray();
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double[] lData = _testData.Bars.Low.Select(x => x.Value).ToArray();
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double[] cData = _testData.Bars.Close.Select(x => x.Value).ToArray();
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foreach (var period in periods)
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{
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// Calculate QuanTAlib NATR (batch TBarSeries)
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var natr = new Natr(period);
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var qResult = natr.Update(_testData.Bars);
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// Calculate Tulip ATR
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var atrIndicator = Tulip.Indicators.atr;
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double[][] inputs = { hData, lData, cData };
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double[] options = { period };
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// Tulip ATR lookback
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int lookback = atrIndicator.Start(options);
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double[][] outputs = { new double[hData.Length - lookback] };
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atrIndicator.Run(inputs, options, outputs);
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var tAtr = outputs[0];
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// Convert ATR to NATR: (ATR / Close) * 100
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var expectedNatr = new double[tAtr.Length];
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for (int i = 0; i < tAtr.Length; i++)
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{
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int dataIndex = lookback + i;
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double close = cData[dataIndex];
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expectedNatr[i] = close > 0 ? (tAtr[i] / close) * 100.0 : double.NaN;
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}
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// Compare last 100 records
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ValidationHelper.VerifyData(qResult, expectedNatr, lookback, tolerance: ValidationHelper.TulipTolerance);
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}
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_output.WriteLine("NATR Batch(TBarSeries) validated successfully against Tulip ATR");
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}
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[Fact]
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public void Validate_Tulip_Streaming()
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{
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int[] periods = { 14 };
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// Prepare data for Tulip (double[])
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double[] hData = _testData.Bars.High.Select(x => x.Value).ToArray();
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double[] lData = _testData.Bars.Low.Select(x => x.Value).ToArray();
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double[] cData = _testData.Bars.Close.Select(x => x.Value).ToArray();
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foreach (var period in periods)
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{
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// Calculate QuanTAlib NATR (streaming)
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var natr = new Natr(period);
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var qResults = new List<double>();
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foreach (var item in _testData.Bars)
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{
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qResults.Add(natr.Update(item).Value);
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}
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// Calculate Tulip ATR
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var atrIndicator = Tulip.Indicators.atr;
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double[][] inputs = { hData, lData, cData };
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double[] options = { period };
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// Tulip ATR lookback
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int lookback = atrIndicator.Start(options);
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double[][] outputs = { new double[hData.Length - lookback] };
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atrIndicator.Run(inputs, options, outputs);
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var tAtr = outputs[0];
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// Convert ATR to NATR
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var expectedNatr = new double[tAtr.Length];
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for (int i = 0; i < tAtr.Length; i++)
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{
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int dataIndex = lookback + i;
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double close = cData[dataIndex];
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expectedNatr[i] = close > 0 ? (tAtr[i] / close) * 100.0 : double.NaN;
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}
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// Compare last 100 records
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ValidationHelper.VerifyData(qResults, expectedNatr, lookback, tolerance: ValidationHelper.TulipTolerance);
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}
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_output.WriteLine("NATR Streaming validated successfully against Tulip ATR");
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}
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[Fact]
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public void Validate_Ooples_Batch()
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{
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int[] periods = { 14 };
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// Prepare data for Ooples (List<TickerData>)
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var ooplesData = _testData.SkenderQuotes.Select(q => new TickerData
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{
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Date = q.Date,
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Close = (double)q.Close,
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High = (double)q.High,
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Low = (double)q.Low,
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Open = (double)q.Open,
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Volume = (double)q.Volume
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}).ToList();
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foreach (var period in periods)
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{
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// Calculate QuanTAlib NATR (batch TBarSeries)
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var natr = new Natr(period);
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var qResult = natr.Update(_testData.Bars);
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// Calculate Ooples ATR
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var stockData = new StockData(ooplesData);
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var oAtr = stockData.CalculateAverageTrueRange(MovingAvgType.WildersSmoothingMethod, period).OutputValues.Values.First();
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// Convert ATR to NATR
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var expectedNatr = new List<double>();
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for (int i = 0; i < oAtr.Count; i++)
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{
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double atr = oAtr[i];
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double close = ooplesData[i].Close;
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expectedNatr.Add(close > 0 ? (atr / close) * 100.0 : double.NaN);
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}
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// Compare last 100 records
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ValidationHelper.VerifyData(qResult, expectedNatr, (s) => s, 100, ValidationHelper.OoplesTolerance);
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}
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_output.WriteLine("NATR Batch(TBarSeries) validated successfully against Ooples ATR");
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}
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}
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