Files
QuanTAlib/lib/statistics/bias/Bias.Quantower.Tests.cs
T
Miha Kralj c034cbd5e5 Add Yang-Zhang Volatility (YZV) Indicator Implementation
- Introduced YZV class for calculating Yang-Zhang Volatility, a comprehensive volatility measure that incorporates overnight, open-to-close, and high-low components.
- Implemented calculation methods, including batch processing for TBarSeries and spans.
- Added documentation for YZV, detailing its mathematical foundation, performance profile, and trading applications.
- Updated volume index documentation to reflect changes in file paths.
- Refactored VWMA calculation method to use a more generic source parameter instead of price.
2026-02-02 19:47:21 -08:00

244 lines
8.4 KiB
C#

using TradingPlatform.BusinessLayer;
namespace QuanTAlib.Tests;
public class BiasIndicatorTests
{
[Fact]
public void BiasIndicator_Constructor_SetsDefaults()
{
var indicator = new BiasIndicator();
Assert.Equal(20, indicator.Period);
Assert.Equal(SourceType.Close, indicator.Source);
Assert.True(indicator.ShowColdValues);
Assert.Equal("BIAS - Price Deviation from SMA", indicator.Name);
Assert.True(indicator.SeparateWindow);
Assert.True(indicator.OnBackGround);
}
[Fact]
public void BiasIndicator_MinHistoryDepths_EqualsZero()
{
var indicator = new BiasIndicator();
Assert.Equal(0, BiasIndicator.MinHistoryDepths);
Assert.Equal(0, ((IWatchlistIndicator)indicator).MinHistoryDepths);
}
[Fact]
public void BiasIndicator_ShortName_IncludesPeriodAndSource()
{
var indicator = new BiasIndicator { Period = 20 };
Assert.Contains("BIAS", indicator.ShortName, StringComparison.Ordinal);
Assert.Contains("20", indicator.ShortName, StringComparison.Ordinal);
}
[Fact]
public void BiasIndicator_Initialize_CreatesInternalBias()
{
var indicator = new BiasIndicator { Period = 10 };
// Initialize should not throw
indicator.Initialize();
// After init, line series should exist
Assert.Single(indicator.LinesSeries);
}
[Fact]
public void BiasIndicator_ProcessUpdate_HistoricalBar_ComputesValue()
{
var indicator = new BiasIndicator { Period = 5 };
indicator.Initialize();
// Add historical data
var now = DateTime.UtcNow;
indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
// Process update
var args = new UpdateArgs(UpdateReason.HistoricalBar);
indicator.ProcessUpdate(args);
// Line series should have a value
Assert.Equal(1, indicator.LinesSeries[0].Count);
Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(0)));
}
[Fact]
public void BiasIndicator_ProcessUpdate_NewBar_ComputesValue()
{
var indicator = new BiasIndicator { Period = 5 };
indicator.Initialize();
var now = DateTime.UtcNow;
indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
indicator.HistoricalData.AddBar(now.AddMinutes(1), 102, 108, 100, 106);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
Assert.Equal(2, indicator.LinesSeries[0].Count);
}
[Fact]
public void BiasIndicator_ProcessUpdate_NewTick_ProcessesWithoutError()
{
var indicator = new BiasIndicator { Period = 5 };
indicator.Initialize();
var now = DateTime.UtcNow;
indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
double firstValue = indicator.LinesSeries[0].GetValue(0);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewTick));
double secondValue = indicator.LinesSeries[0].GetValue(0);
Assert.True(double.IsFinite(firstValue));
Assert.True(double.IsFinite(secondValue));
}
[Fact]
public void BiasIndicator_MultipleUpdates_ProducesCorrectBiasSequence()
{
var indicator = new BiasIndicator { Period = 3 };
indicator.Initialize();
var now = DateTime.UtcNow;
double[] closes = { 100, 100, 100, 110, 100 };
foreach (var close in closes)
{
indicator.HistoricalData.AddBar(now, close, close + 2, close - 2, close);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
now = now.AddMinutes(1);
}
// All values should be finite
for (int i = 0; i < closes.Length; i++)
{
Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(closes.Length - 1 - i)));
}
}
[Fact]
public void BiasIndicator_DifferentSourceTypes_Work()
{
var sources = new[] { SourceType.Open, SourceType.High, SourceType.Low, SourceType.Close, SourceType.HL2, SourceType.HLC3 };
foreach (var source in sources)
{
var indicator = new BiasIndicator { Period = 5, Source = source };
indicator.Initialize();
var now = DateTime.UtcNow;
indicator.HistoricalData.AddBar(now, 100, 110, 90, 105);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(0)),
$"Source {source} should produce finite value");
}
}
[Fact]
public void BiasIndicator_CalculatesBiasCorrectly()
{
var indicator = new BiasIndicator { Period = 3 };
indicator.Initialize();
var now = DateTime.UtcNow;
// Add 3 bars with close = 100, then one with close = 110
// SMA(3) of [100, 100, 100] = 100
// BIAS when price = 100, SMA = 100 → 0%
indicator.HistoricalData.AddBar(now, 100, 100, 100, 100);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
Assert.Equal(0.0, indicator.LinesSeries[0].GetValue(0), 1e-10);
indicator.HistoricalData.AddBar(now.AddMinutes(1), 100, 100, 100, 100);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
Assert.Equal(0.0, indicator.LinesSeries[0].GetValue(0), 1e-10);
indicator.HistoricalData.AddBar(now.AddMinutes(2), 100, 100, 100, 100);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
Assert.Equal(0.0, indicator.LinesSeries[0].GetValue(0), 1e-10);
// Now add a bar with close = 110
// SMA(3) of [100, 100, 110] = 310/3 ≈ 103.333
// BIAS = (110 / 103.333) - 1 ≈ 0.0645 (6.45%)
indicator.HistoricalData.AddBar(now.AddMinutes(3), 110, 110, 110, 110);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
double expectedSma = (100.0 + 100.0 + 110.0) / 3.0;
double expectedBias = (110.0 / expectedSma) - 1.0;
Assert.Equal(expectedBias, indicator.LinesSeries[0].GetValue(0), 1e-10);
}
[Fact]
public void BiasIndicator_ConstantPrice_ZeroBias()
{
var indicator = new BiasIndicator { Period = 5 };
indicator.Initialize();
var now = DateTime.UtcNow;
// All bars at same price should produce zero bias
for (int i = 0; i < 10; i++)
{
indicator.HistoricalData.AddBar(now.AddMinutes(i), 100, 100, 100, 100);
indicator.ProcessUpdate(i == 0 ? new UpdateArgs(UpdateReason.HistoricalBar) : new UpdateArgs(UpdateReason.NewBar));
Assert.Equal(0.0, indicator.LinesSeries[0].GetValue(0), 1e-10);
}
}
[Fact]
public void BiasIndicator_UpTrend_PositiveBias()
{
var indicator = new BiasIndicator { Period = 3 };
indicator.Initialize();
var now = DateTime.UtcNow;
double[] closes = { 100, 101, 102, 103, 104, 105 };
for (int i = 0; i < closes.Length; i++)
{
indicator.HistoricalData.AddBar(now.AddMinutes(i), closes[i], closes[i], closes[i], closes[i]);
indicator.ProcessUpdate(i == 0 ? new UpdateArgs(UpdateReason.HistoricalBar) : new UpdateArgs(UpdateReason.NewBar));
}
// In uptrend, price should be above SMA, so bias > 0
Assert.True(indicator.LinesSeries[0].GetValue(0) > 0, "Bias should be positive in uptrend");
}
[Fact]
public void BiasIndicator_DownTrend_NegativeBias()
{
var indicator = new BiasIndicator { Period = 3 };
indicator.Initialize();
var now = DateTime.UtcNow;
double[] closes = { 105, 104, 103, 102, 101, 100 };
for (int i = 0; i < closes.Length; i++)
{
indicator.HistoricalData.AddBar(now.AddMinutes(i), closes[i], closes[i], closes[i], closes[i]);
indicator.ProcessUpdate(i == 0 ? new UpdateArgs(UpdateReason.HistoricalBar) : new UpdateArgs(UpdateReason.NewBar));
}
// In downtrend, price should be below SMA, so bias < 0
Assert.True(indicator.LinesSeries[0].GetValue(0) < 0, "Bias should be negative in downtrend");
}
[Fact]
public void BiasIndicator_Period_CanBeChanged()
{
var indicator = new BiasIndicator { Period = 50 };
Assert.Equal(50, indicator.Period);
indicator.Period = 100;
Assert.Equal(100, indicator.Period);
}
}