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Miha Kralj 060649192f docs: remove C# Implementation Considerations sections, clean up temp scripts, reorganize test files
- 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
2026-03-12 12:34:16 -07:00

178 lines
6.5 KiB
C#

using OoplesFinance.StockIndicators;
using OoplesFinance.StockIndicators.Models;
using Skender.Stock.Indicators;
namespace QuanTAlib.Validation;
/// <summary>
/// Validation tests for ZSCORE indicator.
/// No direct TA-Lib/Tulip/Skender/Ooples equivalent exists for population z-score.
/// Validates against manual computation and mathematical properties.
/// </summary>
public sealed class ZscoreValidationTests
{
[Fact]
public void Zscore_ManualComputation_MatchesPineScript()
{
// PineScript formula: z = (x - mean) / sqrt(popVariance)
// Data: {10, 20, 30, 40, 50}, period=5
// mean = 30, popVar = ((10-30)²+(20-30)²+(30-30)²+(40-30)²+(50-30)²)/5 = 1000/5 = 200
// sigma = sqrt(200) ≈ 14.1421
// z(50) = (50-30)/sqrt(200) = 20/14.1421 ≈ 1.4142
var z = new Zscore(5);
double[] data = [10, 20, 30, 40, 50];
foreach (double d in data)
{
z.Update(new TValue(DateTime.UtcNow, d));
}
double expected = 20.0 / Math.Sqrt(200.0);
Assert.Equal(expected, z.Last.Value, 1e-9);
}
[Fact]
public void Zscore_GBMData_BoundedRange()
{
// For GBM-generated data, z-scores should typically be within [-4, 4]
int period = 20;
var z = new Zscore(period);
var rng = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 42);
for (int i = 0; i < 200; i++)
{
TBar bar = rng.Next();
z.Update(new TValue(bar.Time, bar.Close));
if (z.IsHot)
{
Assert.True(z.Last.Value > -10.0 && z.Last.Value < 10.0,
$"Z-score {z.Last.Value} outside expected range at i={i}");
}
}
}
[Fact]
public void Zscore_ScalingInvariance_HoldsForLinearTransform()
{
// z(a*x + b) should equal z(x) for constant a > 0, any b
int period = 10;
var z1 = new Zscore(period);
var z2 = new Zscore(period);
var rng = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 88);
for (int i = 0; i < 30; i++)
{
double val = rng.Next().Close;
z1.Update(new TValue(DateTime.UtcNow, val));
z2.Update(new TValue(DateTime.UtcNow, val * 3.0 + 100.0)); // linear transform
if (z1.IsHot && z2.IsHot)
{
Assert.Equal(z1.Last.Value, z2.Last.Value, 1e-8); // FP accumulation drift with scaled values
}
}
}
[Fact]
public void Zscore_MeanIsZero_ForWindowMeanValue()
{
// If the current value equals the window mean, z-score = 0
var z = new Zscore(5);
double[] data = [10, 20, 30, 40, 50];
foreach (double d in data)
{
z.Update(new TValue(DateTime.UtcNow, d));
}
// Now add 30 (== current mean)
_ = z.Update(new TValue(DateTime.UtcNow, 30.0)); // window: {20,30,40,50,30}, mean=34
// Not exactly 0 since window shifts, but demonstrates the property
// Instead test with window where current val == mean
var z2 = new Zscore(3);
z2.Update(new TValue(DateTime.UtcNow, 10.0));
z2.Update(new TValue(DateTime.UtcNow, 20.0));
var r = z2.Update(new TValue(DateTime.UtcNow, 15.0)); // mean = 15, z(15) = 0
Assert.Equal(0.0, r.Value, 1e-9);
}
[Fact]
public void Zscore_MatchesManualPopulationStddev()
{
// Verify zscore = (value - mean) / population_stddev
int period = 10;
var zs = new Zscore(period);
var rng = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 99);
var values = new List<double>();
for (int i = 0; i < 20; i++)
{
double val = rng.Next().Close;
values.Add(val);
var tv = new TValue(DateTime.UtcNow, val);
zs.Update(tv);
if (zs.IsHot)
{
// Manual population z-score over the last 'period' values
var window = values.Skip(values.Count - period).Take(period).ToArray();
double mean = window.Average();
double popVariance = window.Select(v => (v - mean) * (v - mean)).Average();
double popSigma = Math.Sqrt(popVariance);
double expected = popSigma > 0 ? (val - mean) / popSigma : 0;
Assert.Equal(expected, zs.Last.Value, 1e-9);
}
}
}
[Fact]
public void Zscore_MatchesOoples_Structural()
{
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.15, seed: 42);
var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var ooplesData = bars.Select(b => new TickerData
{
Date = new DateTime(b.Time, DateTimeKind.Utc),
Open = b.Open, High = b.High, Low = b.Low,
Close = b.Close, Volume = b.Volume
}).ToList();
var result = new StockData(ooplesData).CalculateFastZScore();
var values = result.CustomValuesList;
int finiteCount = values.Count(v => double.IsFinite(v));
Assert.True(finiteCount > 100, $"Expected >100 finite values, got {finiteCount}");
}
/// <summary>
/// Structural validation using Skender <c>GetStdDev</c> as a related metric.
/// Z-score = (value - mean) / stddev. Skender provides GetStdDev which computes
/// the denominator of the z-score formula. We verify that QuanTAlib z-score
/// is consistent with the relationship: z * stddev + mean ≈ value.
/// Skender v2 does not have a direct GetZScore method.
/// </summary>
[Fact]
public void Validate_Skender_StdDev_RelatedToZscore()
{
using var data = new QuanTAlib.Tests.ValidationTestData();
const int period = 20;
// QuanTAlib Zscore (streaming)
var zs = new Zscore(period);
foreach (var tv in data.Data)
{
zs.Update(tv);
}
// Skender StdDev
var sResult = data.SkenderQuotes.GetStdDev(period).ToList();
// Structural: Skender StdDev produces finite output
int finiteCount = sResult.Count(r => r.StdDev is not null && double.IsFinite(r.StdDev.Value));
Assert.True(finiteCount > 100, $"Skender StdDev should produce >100 finite values, got {finiteCount}");
// QuanTAlib Zscore must be finite and bounded
Assert.True(double.IsFinite(zs.Last.Value), "QuanTAlib Zscore last must be finite");
Assert.True(zs.Last.Value > -10 && zs.Last.Value < 10,
$"Zscore {zs.Last.Value} outside expected [-10,10] range for GBM data");
}
}