adding missing validations

lib/numerics/expdist/Expdist.Quantower.Tests.cs

@@ -0,0 +1,195 @@
+using Xunit;
+using TradingPlatform.BusinessLayer;
+
+namespace QuanTAlib.Tests;
+
+public class ExpdistIndicatorTests
+{
+    [Fact]
+    public void ExpdistIndicator_Constructor_SetsDefaults()
+    {
+        var indicator = new ExpdistIndicator();
+
+        Assert.Equal(SourceType.Close, indicator.Source);
+        Assert.Equal(50, indicator.Period);
+        Assert.Equal(3.0, indicator.Lambda);
+        Assert.True(indicator.ShowColdValues);
+        Assert.Equal("EXPDIST - Exponential Distribution CDF", indicator.Name);
+        Assert.True(indicator.SeparateWindow);
+        Assert.True(indicator.OnBackGround);
+    }
+
+    [Fact]
+    public void ExpdistIndicator_MinHistoryDepths_EqualsPeriod()
+    {
+        var indicator = new ExpdistIndicator { Period = 30 };
+        Assert.Equal(30, indicator.MinHistoryDepths);
+    }
+
+    [Fact]
+    public void ExpdistIndicator_ShortName_IsCorrect()
+    {
+        var indicator = new ExpdistIndicator { Period = 20, Lambda = 1.5 };
+        Assert.Equal("EXPDIST(20,1.50)", indicator.ShortName);
+    }
+
+    [Fact]
+    public void ExpdistIndicator_Initialize_CreatesTwoLineSeries()
+    {
+        var indicator = new ExpdistIndicator();
+        indicator.Initialize();
+
+        Assert.Equal(2, indicator.LinesSeries.Count);
+        Assert.Equal("ExpDist", indicator.LinesSeries[0].Name);
+        Assert.Equal("Mid", indicator.LinesSeries[1].Name);
+    }
+
+    [Fact]
+    public void ExpdistIndicator_ProcessUpdate_HistoricalBar_ComputesValue()
+    {
+        var indicator = new ExpdistIndicator { Period = 5 };
+        indicator.Initialize();
+
+        var now = DateTime.UtcNow;
+        for (int i = 0; i < 5; i++)
+        {
+            indicator.HistoricalData.AddBar(now.AddMinutes(i), 0, 105 + i, 95 - i, 100 + i);
+            var args = new UpdateArgs(UpdateReason.HistoricalBar);
+            indicator.ProcessUpdate(args);
+        }
+
+        // After 5 bars (= period), should have valid output
+        double val = indicator.LinesSeries[0].GetValue(0);
+        Assert.True(double.IsFinite(val), "Output must be finite after warmup");
+        Assert.True(val >= 0.0 && val <= 1.0, $"Output {val} must be in [0,1]");
+    }
+
+    [Fact]
+    public void ExpdistIndicator_ProcessUpdate_NewBar_AddsNewValue()
+    {
+        var indicator = new ExpdistIndicator { Period = 3 };
+        indicator.Initialize();
+
+        var now = DateTime.UtcNow;
+        // Feed 3 historical bars
+        for (int i = 0; i < 3; i++)
+        {
+            indicator.HistoricalData.AddBar(now.AddMinutes(i), 0, 105, 95, 100 + i);
+            indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
+        }
+
+        // Feed a new bar
+        indicator.HistoricalData.AddBar(now.AddMinutes(3), 0, 106, 96, 103);
+        indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
+
+        Assert.Equal(4, indicator.LinesSeries[0].Count);
+    }
+
+    [Fact]
+    public void ExpdistIndicator_ProcessUpdate_NewTick_ProcessesWithoutError()
+    {
+        var indicator = new ExpdistIndicator { Period = 3 };
+        indicator.Initialize();
+
+        var now = DateTime.UtcNow;
+        indicator.HistoricalData.AddBar(now, 0, 105, 95, 100);
+        indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
+        indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewTick));
+
+        // 2 values: one historical, one intra-bar update
+        Assert.Equal(2, indicator.LinesSeries[0].Count);
+    }
+
+    [Fact]
+    public void ExpdistIndicator_MidLine_IsAlwaysHalf()
+    {
+        var indicator = new ExpdistIndicator { Period = 3 };
+        indicator.Initialize();
+
+        var now = DateTime.UtcNow;
+        for (int i = 0; i < 5; i++)
+        {
+            indicator.HistoricalData.AddBar(now.AddMinutes(i), 0, 105, 95, 100 + i);
+            indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
+        }
+
+        // Mid line should always be 0.5
+        for (int i = 0; i < indicator.LinesSeries[1].Count; i++)
+        {
+            double mid = indicator.LinesSeries[1].GetValue(i);
+            Assert.Equal(0.5, mid, 1e-10);
+        }
+    }
+
+    [Fact]
+    public void ExpdistIndicator_DifferentSourceType_Works()
+    {
+        var indicator = new ExpdistIndicator { Period = 3, Source = SourceType.High };
+        indicator.Initialize();
+
+        var now = DateTime.UtcNow;
+        for (int i = 0; i < 3; i++)
+        {
+            // High = 110+i, Low = 90, Close = 100
+            indicator.HistoricalData.AddBar(now.AddMinutes(i), 0, 110 + i, 90, 100);
+            indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
+        }
+
+        double val = indicator.LinesSeries[0].GetValue(0);
+        Assert.True(double.IsFinite(val));
+    }
+
+    [Fact]
+    public void ExpdistIndicator_OutputInRange_AfterManyBars()
+    {
+        var indicator = new ExpdistIndicator { Period = 20 };
+        indicator.Initialize();
+
+        var now = DateTime.UtcNow;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 64001);
+        var bars = gbm.Fetch(50, now.Ticks, TimeSpan.FromMinutes(1));
+
+        for (int i = 0; i < bars.Close.Count; i++)
+        {
+            double price = bars.Close[i].Value;
+            indicator.HistoricalData.AddBar(
+                new DateTime(bars.Close[i].Time, DateTimeKind.Utc),
+                0, price * 1.01, price * 0.99, price);
+            indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
+        }
+
+        // Check all computed values are in [0, 1]
+        for (int i = 0; i < indicator.LinesSeries[0].Count; i++)
+        {
+            double val = indicator.LinesSeries[0].GetValue(i);
+            Assert.True(val >= 0.0 && val <= 1.0, $"Value {val} at index {i} out of range");
+        }
+    }
+
+    [Fact]
+    public void ExpdistIndicator_HighLambda_OutputNearOne()
+    {
+        // With lambda=10, CDF saturates toward 1 very quickly for x > 0
+        var indicator = new ExpdistIndicator { Period = 5, Lambda = 10.0 };
+        indicator.Initialize();
+
+        var now = DateTime.UtcNow;
+        // Provide strictly increasing prices so the current bar is always above minimum
+        for (int i = 0; i < 5; i++)
+        {
+            indicator.HistoricalData.AddBar(now.AddMinutes(i), 0, 101 + i, 99 + i, 100 + i);
+            indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
+        }
+
+        double val = indicator.LinesSeries[0].GetValue(0);
+        Assert.True(double.IsFinite(val));
+        Assert.True(val >= 0.0 && val <= 1.0);
+    }
+
+    [Fact]
+    public void ExpdistIndicator_CustomLambda_ShortNameReflects()
+    {
+        var indicator = new ExpdistIndicator { Period = 14, Lambda = 2.5 };
+        Assert.Equal("EXPDIST(14,2.50)", indicator.ShortName);
+    }
+}

lib/numerics/expdist/Expdist.Quantower.cs

@@ -0,0 +1,69 @@
+using System.Drawing;
+using TradingPlatform.BusinessLayer;
+using static QuanTAlib.IndicatorExtensions;
+
+namespace QuanTAlib;
+
+/// <summary>
+/// EXPDIST (Exponential Distribution CDF) Quantower indicator.
+/// Computes F(x; λ) = 1 - exp(-λx) applied to a min-max normalized price series
+/// over a rolling lookback window.
+/// </summary>
+public class ExpdistIndicator : Indicator, IWatchlistIndicator
+{
+    [DataSourceInput]
+    public SourceType Source { get; set; } = SourceType.Close;
+
+    [InputParameter("Period", sortIndex: 0, minimum: 1, maximum: 2000, increment: 1)]
+    public int Period { get; set; } = 50;
+
+    [InputParameter("Lambda", sortIndex: 1, minimum: 0.01, maximum: 100.0, increment: 0.1, decimalPlaces: 2)]
+    public double Lambda { get; set; } = 3.0;
+
+    [InputParameter("Show Cold Values", sortIndex: 100)]
+    public bool ShowColdValues { get; set; } = true;
+
+    private Expdist? _expdist;
+    private Func<IHistoryItem, double>? _selector;
+
+    public int MinHistoryDepths => Period;
+    public override string ShortName => $"EXPDIST({Period},{Lambda:F2})";
+
+    public ExpdistIndicator()
+    {
+        Name = "EXPDIST - Exponential Distribution CDF";
+        Description = "Applies the exponential CDF to a min-max normalized price series";
+        SeparateWindow = true;
+        OnBackGround = true;
+    }
+
+    protected override void OnInit()
+    {
+        _expdist = new Expdist(Period, Lambda);
+        _selector = Source.GetPriceSelector();
+
+        AddLineSeries(new LineSeries("ExpDist", Color.Cyan, 2, LineStyle.Solid));
+        // Reference level at 0.5 (midpoint)
+        AddLineSeries(new LineSeries("Mid", Color.Gray, 1, LineStyle.Dash));
+    }
+
+    protected override void OnUpdate(UpdateArgs args)
+    {
+        if (_expdist == null || _selector == null)
+        {
+            return;
+        }
+
+        var item = HistoricalData[0, SeekOriginHistory.End];
+        double value = _selector(item);
+        bool isNew = args.IsNewBar();
+
+        TValue input = new(item.TimeLeft, value);
+        _expdist.Update(input, isNew);
+
+        bool isHot = _expdist.IsHot;
+
+        LinesSeries[0].SetValue(_expdist.Last.Value, isHot, ShowColdValues);
+        LinesSeries[1].SetValue(0.5, isHot, ShowColdValues);
+    }
+}

lib/numerics/expdist/Expdist.Tests.cs

@@ -0,0 +1,651 @@
+using Xunit;
+
+namespace QuanTAlib.Tests;
+
+public class ExpdistTests
+{
+    private const double Tolerance = 1e-10;
+
+    // ─── A) Constructor validation ────────────────────────────────────────────
+
+    [Fact]
+    public void Constructor_DefaultParameters_SetsProperties()
+    {
+        var indicator = new Expdist();
+        Assert.Equal("Expdist(50,3.00)", indicator.Name);
+        Assert.Equal(50, indicator.WarmupPeriod);
+        Assert.False(indicator.IsHot);
+    }
+
+    [Fact]
+    public void Constructor_CustomParameters_SetsName()
+    {
+        var indicator = new Expdist(20, 1.5);
+        Assert.Equal("Expdist(20,1.50)", indicator.Name);
+        Assert.Equal(20, indicator.WarmupPeriod);
+    }
+
+    [Fact]
+    public void Constructor_InvalidPeriod_ThrowsArgumentException()
+    {
+        var ex = Assert.Throws<ArgumentException>(() => new Expdist(period: 0));
+        Assert.Equal("period", ex.ParamName);
+    }
+
+    [Fact]
+    public void Constructor_NegativePeriod_ThrowsArgumentException()
+    {
+        var ex = Assert.Throws<ArgumentException>(() => new Expdist(period: -1));
+        Assert.Equal("period", ex.ParamName);
+    }
+
+    [Fact]
+    public void Constructor_ZeroLambda_ThrowsArgumentException()
+    {
+        var ex = Assert.Throws<ArgumentException>(() => new Expdist(lambda: 0.0));
+        Assert.Equal("lambda", ex.ParamName);
+    }
+
+    [Fact]
+    public void Constructor_NegativeLambda_ThrowsArgumentException()
+    {
+        var ex = Assert.Throws<ArgumentException>(() => new Expdist(lambda: -1.0));
+        Assert.Equal("lambda", ex.ParamName);
+    }
+
+    // ─── B) Basic calculation ─────────────────────────────────────────────────
+
+    [Fact]
+    public void Update_ReturnsValidTValue()
+    {
+        var indicator = new Expdist(period: 5);
+        var time = DateTime.UtcNow;
+        var input = new TValue(time, 100.0);
+        var result = indicator.Update(input);
+        Assert.Equal(input.Time, result.Time);
+        Assert.True(double.IsFinite(result.Value));
+    }
+
+    [Fact]
+    public void Update_OutputInRange()
+    {
+        var indicator = new Expdist(period: 5, lambda: 2.0);
+        var time = DateTime.UtcNow;
+        double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
+
+        foreach (var p in prices)
+        {
+            indicator.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+        }
+
+        Assert.True(indicator.Last.Value >= 0.0, "Output must be >= 0");
+        Assert.True(indicator.Last.Value <= 1.0, "Output must be <= 1");
+    }
+
+    [Fact]
+    public void Last_IsAccessible_AfterUpdate()
+    {
+        var indicator = new Expdist(period: 3);
+        var time = DateTime.UtcNow;
+        indicator.Update(new TValue(time, 50.0));
+        Assert.NotEqual(default, indicator.Last);
+    }
+
+    [Fact]
+    public void IsHot_Property_ReflectsWarmup()
+    {
+        var indicator = new Expdist(period: 5);
+        var time = DateTime.UtcNow;
+
+        for (int i = 0; i < 4; i++)
+        {
+            indicator.Update(new TValue(time.AddMinutes(i), 100.0 + i));
+            Assert.False(indicator.IsHot);
+        }
+
+        indicator.Update(new TValue(time.AddMinutes(4), 104.0));
+        Assert.True(indicator.IsHot);
+    }
+
+    [Fact]
+    public void Update_AtMaxOfWindow_ReturnsNearOne()
+    {
+        // When current value equals window max, x=1.0 → CDF(1, λ) → close to 1
+        var indicator = new Expdist(period: 5, lambda: 3.0);
+        var time = DateTime.UtcNow;
+        double[] prices = { 100.0, 102.0, 98.0, 101.0, 110.0 }; // 110 is max
+
+        foreach (var p in prices)
+        {
+            indicator.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+        }
+
+        // CDF(1.0, 3.0) = 1 - exp(-3) ≈ 0.9502
+        Assert.True(indicator.Last.Value > 0.9, $"Expected near 1 but got {indicator.Last.Value}");
+    }
+
+    [Fact]
+    public void Update_AtMinOfWindow_ReturnsZero()
+    {
+        // When current value equals window min, x=0.0 → CDF(0, λ) = 0
+        var indicator = new Expdist(period: 5, lambda: 3.0);
+        var time = DateTime.UtcNow;
+        double[] prices = { 110.0, 102.0, 98.0, 101.0, 90.0 }; // 90 is min
+
+        foreach (var p in prices)
+        {
+            indicator.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+        }
+
+        Assert.Equal(0.0, indicator.Last.Value, Tolerance);
+    }
+
+    // ─── C) State + bar correction ────────────────────────────────────────────
+
+    [Fact]
+    public void Update_IsNewTrue_AdvancesState()
+    {
+        var indicator = new Expdist(period: 5);
+        var time = DateTime.UtcNow;
+        double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
+
+        foreach (var p in prices)
+        {
+            indicator.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+        }
+
+        double first = indicator.Last.Value;
+
+        indicator.Update(new TValue(time, 110.0));
+        double second = indicator.Last.Value;
+
+        Assert.NotEqual(first, second, Tolerance);
+    }
+
+    [Fact]
+    public void Update_IsNewFalse_RewritesLastBar()
+    {
+        var indicator = new Expdist(period: 5);
+        var time = DateTime.UtcNow;
+
+        double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
+        foreach (var p in prices)
+        {
+            indicator.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+        }
+
+        // New bar with value A
+        indicator.Update(new TValue(time, 110.0), true);
+        double valueA = indicator.Last.Value;
+
+        // Correct same bar with value B
+        indicator.Update(new TValue(time, 90.0), false);
+        double valueB = indicator.Last.Value;
+
+        Assert.NotEqual(valueA, valueB, Tolerance);
+    }
+
+    [Fact]
+    public void Update_IterativeCorrection_RestoresState()
+    {
+        var time = DateTime.UtcNow;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 62001);
+        var bars = gbm.Fetch(20, time.Ticks, TimeSpan.FromMinutes(1));
+
+        // Streaming without corrections
+        var straight = new Expdist(period: 5);
+        for (int i = 0; i < bars.Close.Count; i++)
+        {
+            straight.Update(bars.Close[i]);
+        }
+
+        double finalStraight = straight.Last.Value;
+
+        // With corrections (wrong → corrected)
+        var corrected = new Expdist(period: 5);
+        for (int i = 0; i < bars.Close.Count; i++)
+        {
+            corrected.Update(new TValue(bars.Close[i].Time, 999.0), true);
+            corrected.Update(bars.Close[i], false);
+        }
+
+        Assert.Equal(finalStraight, corrected.Last.Value, Tolerance);
+    }
+
+    [Fact]
+    public void Reset_ClearsState()
+    {
+        var indicator = new Expdist(period: 5);
+        var time = DateTime.UtcNow;
+        double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
+
+        foreach (var p in prices)
+        {
+            indicator.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+        }
+
+        Assert.True(indicator.IsHot);
+
+        indicator.Reset();
+
+        Assert.False(indicator.IsHot);
+        Assert.Equal(default, indicator.Last);
+    }
+
+    // ─── D) Warmup / convergence ──────────────────────────────────────────────
+
+    [Fact]
+    public void IsHot_FlipsAtPeriod()
+    {
+        int period = 10;
+        var indicator = new Expdist(period);
+        var time = DateTime.UtcNow;
+
+        for (int i = 0; i < period - 1; i++)
+        {
+            indicator.Update(new TValue(time.AddMinutes(i), 100.0 + i));
+            Assert.False(indicator.IsHot, $"Should not be hot at bar {i + 1}");
+        }
+
+        indicator.Update(new TValue(time.AddMinutes(period - 1), 100.0 + period));
+        Assert.True(indicator.IsHot, "Should be hot after period bars");
+    }
+
+    // ─── E) Robustness ────────────────────────────────────────────────────────
+
+    [Fact]
+    public void Update_NaN_UsesLastValidValue()
+    {
+        var indicator = new Expdist(period: 5);
+        var time = DateTime.UtcNow;
+        double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
+
+        foreach (var p in prices)
+        {
+            indicator.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+        }
+
+        double before = indicator.Last.Value;
+
+        indicator.Update(new TValue(time, double.NaN));
+        Assert.Equal(before, indicator.Last.Value, Tolerance);
+    }
+
+    [Fact]
+    public void Update_PositiveInfinity_UsesLastValidValue()
+    {
+        var indicator = new Expdist(period: 5);
+        var time = DateTime.UtcNow;
+        double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
+
+        foreach (var p in prices)
+        {
+            indicator.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+        }
+
+        double before = indicator.Last.Value;
+        indicator.Update(new TValue(time, double.PositiveInfinity));
+        Assert.Equal(before, indicator.Last.Value, Tolerance);
+    }
+
+    [Fact]
+    public void Update_NegativeInfinity_UsesLastValidValue()
+    {
+        var indicator = new Expdist(period: 5);
+        var time = DateTime.UtcNow;
+        double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
+
+        foreach (var p in prices)
+        {
+            indicator.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+        }
+
+        double before = indicator.Last.Value;
+        indicator.Update(new TValue(time, double.NegativeInfinity));
+        Assert.Equal(before, indicator.Last.Value, Tolerance);
+    }
+
+    [Fact]
+    public void Update_BatchNaN_Stable()
+    {
+        var indicator = new Expdist(period: 5);
+        var time = DateTime.UtcNow;
+
+        double[] prices = { 100.0, double.NaN, 102.0, double.NaN, 98.0, 105.0, 103.0 };
+        foreach (var p in prices)
+        {
+            var result = indicator.Update(new TValue(time, p));
+            Assert.True(double.IsFinite(result.Value), "Output must always be finite");
+            time = time.AddMinutes(1);
+        }
+    }
+
+    [Fact]
+    public void Update_FlatRange_ReturnsExpCdfAtHalf()
+    {
+        // When all values in window are identical, range=0 → x=0.5
+        // CDF(0.5, λ) = 1 - exp(-λ * 0.5)
+        var indicator = new Expdist(period: 5, lambda: 2.0);
+        var time = DateTime.UtcNow;
+
+        for (int i = 0; i < 10; i++)
+        {
+            indicator.Update(new TValue(time.AddMinutes(i), 100.0));
+        }
+
+        double expected = 1.0 - Math.Exp(-2.0 * 0.5); // 1 - exp(-1) ≈ 0.6321
+        Assert.Equal(expected, indicator.Last.Value, 1e-6);
+    }
+
+    // ─── F) Consistency: batch == streaming == span == eventing ──────────────
+
+    [Fact]
+    public void AllModes_ConsistencyCheck()
+    {
+        int count = 100;
+        int period = 20;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 62002);
+        var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+        var source = bars.Close;
+
+        // Streaming
+        var streaming = new Expdist(period);
+        for (int i = 0; i < source.Count; i++)
+        {
+            streaming.Update(source[i]);
+        }
+
+        // Batch (TSeries)
+        var batch = Expdist.Batch(source, period);
+
+        // Span
+        var rawValues = new double[source.Count];
+        for (int i = 0; i < source.Count; i++)
+        {
+            rawValues[i] = source[i].Value;
+        }
+
+        var spanOutput = new double[source.Count];
+        Expdist.Batch(rawValues, spanOutput, period);
+
+        // Eventing
+        var eventResults = new List<double>();
+        var eventSource = new TSeries();
+        var eventIndicator = new Expdist(eventSource, period);
+        eventIndicator.Pub += (object? s, in TValueEventArgs e) => eventResults.Add(e.Value.Value);
+
+        for (int i = 0; i < source.Count; i++)
+        {
+            eventSource.Add(source[i], true);
+        }
+
+        // Verify last value matches across all modes
+        double streamingLast = streaming.Last.Value;
+        double batchLast = batch[source.Count - 1].Value;
+        double spanLast = spanOutput[source.Count - 1];
+        double eventLast = eventResults[^1];
+
+        Assert.Equal(streamingLast, batchLast, Tolerance);
+        Assert.Equal(streamingLast, spanLast, Tolerance);
+        Assert.Equal(streamingLast, eventLast, Tolerance);
+    }
+
+    [Fact]
+    public void Streaming_VsBatch_AllValues_Match()
+    {
+        int count = 80;
+        int period = 15;
+        var gbm = new GBM(startPrice: 50, mu: 0.0, sigma: 0.3, seed: 62003);
+        var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+        var source = bars.Close;
+
+        var streaming = new Expdist(period);
+        var streamingVals = new double[count];
+        for (int i = 0; i < count; i++)
+        {
+            streaming.Update(source[i]);
+            streamingVals[i] = streaming.Last.Value;
+        }
+
+        var batch = Expdist.Batch(source, period);
+
+        for (int i = 0; i < count; i++)
+        {
+            Assert.Equal(streamingVals[i], batch[i].Value, Tolerance);
+        }
+    }
+
+    // ─── G) Span API tests ────────────────────────────────────────────────────
+
+    [Fact]
+    public void Batch_Span_EmptySource_ThrowsArgumentException()
+    {
+        var ex = Assert.Throws<ArgumentException>(() =>
+            Expdist.Batch([], Array.Empty<double>()));
+        Assert.Equal("source", ex.ParamName);
+    }
+
+    [Fact]
+    public void Batch_Span_OutputTooShort_ThrowsArgumentException()
+    {
+        double[] src = { 1.0, 2.0, 3.0 };
+        double[] dst = new double[2];
+        var ex = Assert.Throws<ArgumentException>(() =>
+            Expdist.Batch(src, dst));
+        Assert.Equal("output", ex.ParamName);
+    }
+
+    [Fact]
+    public void Batch_Span_InvalidPeriod_ThrowsArgumentException()
+    {
+        double[] src = { 1.0, 2.0, 3.0 };
+        double[] dst = new double[3];
+        var ex = Assert.Throws<ArgumentException>(() =>
+            Expdist.Batch(src, dst, period: 0));
+        Assert.Equal("period", ex.ParamName);
+    }
+
+    [Fact]
+    public void Batch_Span_InvalidLambda_ThrowsArgumentException()
+    {
+        double[] src = { 1.0, 2.0, 3.0 };
+        double[] dst = new double[3];
+        var ex = Assert.Throws<ArgumentException>(() =>
+            Expdist.Batch(src, dst, lambda: 0.0));
+        Assert.Equal("lambda", ex.ParamName);
+    }
+
+    [Fact]
+    public void Batch_Span_NegativeLambda_ThrowsArgumentException()
+    {
+        double[] src = { 1.0, 2.0, 3.0 };
+        double[] dst = new double[3];
+        var ex = Assert.Throws<ArgumentException>(() =>
+            Expdist.Batch(src, dst, lambda: -1.0));
+        Assert.Equal("lambda", ex.ParamName);
+    }
+
+    [Fact]
+    public void Batch_Span_OutputInRange()
+    {
+        int count = 100;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 62004);
+        var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+
+        double[] src = new double[count];
+        for (int i = 0; i < count; i++)
+        {
+            src[i] = bars.Close[i].Value;
+        }
+
+        double[] dst = new double[count];
+        Expdist.Batch(src, dst, period: 20);
+
+        foreach (double v in dst)
+        {
+            Assert.True(v >= 0.0 && v <= 1.0, $"Output {v} out of [0,1] range");
+        }
+    }
+
+    [Fact]
+    public void Batch_Span_HandlesNaN()
+    {
+        double[] src = { 100.0, double.NaN, 102.0, 98.0, 105.0, 103.0 };
+        double[] dst = new double[src.Length];
+        Expdist.Batch(src, dst, period: 5);
+
+        foreach (double v in dst)
+        {
+            Assert.True(double.IsFinite(v), "Span output should always be finite");
+        }
+    }
+
+    [Fact]
+    public void Batch_Span_NoStackOverflow_LargeData()
+    {
+        int count = 5000;
+        double[] src = new double[count];
+        for (int i = 0; i < count; i++)
+        {
+            src[i] = 100.0 + Math.Sin(i * 0.1) * 10.0;
+        }
+
+        double[] dst = new double[count];
+        Expdist.Batch(src, dst, period: 300);
+
+        foreach (double v in dst)
+        {
+            Assert.True(double.IsFinite(v));
+        }
+    }
+
+    [Fact]
+    public void Batch_Span_MatchesStreaming()
+    {
+        int count = 60;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.25, seed: 62005);
+        var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+
+        double[] src = new double[count];
+        for (int i = 0; i < count; i++)
+        {
+            src[i] = bars.Close[i].Value;
+        }
+
+        double[] spanOut = new double[count];
+        Expdist.Batch(src, spanOut, period: 14);
+
+        var streaming = new Expdist(period: 14);
+        for (int i = 0; i < count; i++)
+        {
+            streaming.Update(bars.Close[i]);
+            Assert.Equal(streaming.Last.Value, spanOut[i], Tolerance);
+        }
+    }
+
+    // ─── H) Chainability ──────────────────────────────────────────────────────
+
+    [Fact]
+    public void Pub_EventFires()
+    {
+        var indicator = new Expdist(period: 3);
+        int count = 0;
+        indicator.Pub += (object? sender, in TValueEventArgs args) => count++;
+
+        var time = DateTime.UtcNow;
+        indicator.Update(new TValue(time, 100.0));
+        indicator.Update(new TValue(time.AddMinutes(1), 102.0));
+        indicator.Update(new TValue(time.AddMinutes(2), 98.0));
+
+        Assert.Equal(3, count);
+    }
+
+    [Fact]
+    public void Chaining_Constructor_Works()
+    {
+        int period = 5;
+        var source = new TSeries();
+        var indicator = new Expdist(source, period);
+
+        var time = DateTime.UtcNow;
+        double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
+
+        foreach (var p in prices)
+        {
+            source.Add(new TValue(time, p), true);
+            time = time.AddMinutes(1);
+        }
+
+        Assert.True(indicator.IsHot);
+        Assert.True(indicator.Last.Value >= 0.0 && indicator.Last.Value <= 1.0);
+    }
+
+    [Fact]
+    public void Pub_EventValue_MatchesLast()
+    {
+        var indicator = new Expdist(period: 5);
+        TValue? lastEvent = null;
+        indicator.Pub += (object? s, in TValueEventArgs e) => lastEvent = e.Value;
+
+        var time = DateTime.UtcNow;
+        double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
+
+        foreach (var p in prices)
+        {
+            indicator.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+        }
+
+        Assert.NotNull(lastEvent);
+        Assert.Equal(indicator.Last.Value, lastEvent.Value.Value, Tolerance);
+    }
+
+    // ─── Additional: Lambda parameter effects ───────────────────────────────
+
+    [Fact]
+    public void DifferentLambda_ProduceDifferentResults()
+    {
+        int count = 60;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 62006);
+        var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+
+        var ind1 = new Expdist(period: 20, lambda: 1.0);
+        var ind2 = new Expdist(period: 20, lambda: 3.0);
+        var ind3 = new Expdist(period: 20, lambda: 10.0);
+
+        for (int i = 0; i < count; i++)
+        {
+            ind1.Update(bars.Close[i]);
+            ind2.Update(bars.Close[i]);
+            ind3.Update(bars.Close[i]);
+        }
+
+        // Higher lambda should compress more toward 1.0 for same x
+        Assert.True(ind3.Last.Value >= ind1.Last.Value - 1e-4,
+            "Higher lambda should produce >= CDF value for same x > 0");
+        Assert.NotEqual(ind1.Last.Value, ind2.Last.Value, 1e-4);
+    }
+
+    [Fact]
+    public void Calculate_StaticMethod_ReturnsTuple()
+    {
+        int count = 50;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 62007);
+        var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+
+        var (results, instance) = Expdist.Calculate(bars.Close, period: 20);
+
+        Assert.Equal(count, results.Count);
+        Assert.True(instance.IsHot);
+        Assert.Equal(results[^1].Value, instance.Last.Value, Tolerance);
+    }
+}

lib/numerics/expdist/Expdist.Validation.Tests.cs

@@ -0,0 +1,334 @@
+using Xunit;
+
+namespace QuanTAlib.Tests;
+
+/// <summary>
+/// ExpdistValidationTests — validates against known mathematical properties
+/// of the exponential CDF. Known-value tests call Expdist.ExpCdf directly
+/// (bypassing windowing) so results are exact closed-form comparisons.
+/// Streaming/batch tests check invariants (bounds, monotonicity, finiteness)
+/// that hold regardless of window state.
+/// </summary>
+public class ExpdistValidationTests
+{
+    private const double Tolerance = 1e-9;
+    private const double LooseTolerance = 1e-6;
+
+    // ─── Known-value tests via ExpCdf static method ──────────────────────────
+    // F(x; λ) = 1 - exp(-λx), closed-form, no special functions.
+
+    [Theory]
+    [InlineData(0.0, 1.0, 0.0)]                          // F(0; 1) = 0
+    [InlineData(1.0, 1.0, 0.6321205588285578)]           // F(1; 1) = 1 - 1/e
+    [InlineData(2.0, 1.0, 0.8646647167633873)]           // F(2; 1) = 1 - exp(-2)
+    [InlineData(0.5, 1.0, 0.3934693402873666)]           // F(0.5; 1) = 1 - exp(-0.5)
+    [InlineData(1.0, 2.0, 0.8646647167633873)]           // F(1; 2) = 1 - exp(-2)
+    [InlineData(0.5, 2.0, 0.6321205588285578)]           // F(0.5; 2) = 1 - 1/e
+    [InlineData(1.0, 3.0, 0.9502129316321360)]           // F(1; 3) = 1 - exp(-3)
+    [InlineData(0.5, 3.0, 0.7768698398515702)]           // F(0.5; 3) = 1 - exp(-1.5)
+    [InlineData(0.0, 5.0, 0.0)]                          // F(0; 5) = 0 always
+    public void ExpCdf_KnownValues(double x, double lambda, double expected)
+    {
+        double actual = Expdist.ExpCdf(x, lambda);
+        Assert.Equal(expected, actual, LooseTolerance);
+    }
+
+    // ─── PDF known values ────────────────────────────────────────────────────
+
+    [Theory]
+    [InlineData(0.0, 2.0, 2.0)]      // f(0; 2) = 2
+    [InlineData(0.0, 1.0, 1.0)]      // f(0; 1) = 1
+    [InlineData(1.0, 1.0, 0.36787944117144233)]  // f(1; 1) = exp(-1)
+    [InlineData(0.0, 0.5, 0.5)]      // f(0; 0.5) = 0.5
+    public void ExpPdf_KnownValues(double x, double lambda, double expected)
+    {
+        double actual = Expdist.ExpPdf(x, lambda);
+        Assert.Equal(expected, actual, LooseTolerance);
+    }
+
+    // ─── Boundary conditions ─────────────────────────────────────────────────
+
+    [Theory]
+    [InlineData(1.0)]
+    [InlineData(2.0)]
+    [InlineData(5.0)]
+    [InlineData(10.0)]
+    public void ExpCdf_AtZero_IsAlwaysZero(double lambda)
+    {
+        Assert.Equal(0.0, Expdist.ExpCdf(0.0, lambda), Tolerance);
+    }
+
+    [Theory]
+    [InlineData(1.0)]
+    [InlineData(3.0)]
+    [InlineData(10.0)]
+    public void ExpCdf_AtNegative_IsAlwaysZero(double lambda)
+    {
+        Assert.Equal(0.0, Expdist.ExpCdf(-1.0, lambda), Tolerance);
+        Assert.Equal(0.0, Expdist.ExpCdf(-100.0, lambda), Tolerance);
+    }
+
+    [Theory]
+    [InlineData(1.0)]
+    [InlineData(3.0)]
+    [InlineData(10.0)]
+    public void ExpCdf_AtLargeX_ApproachesOne(double lambda)
+    {
+        double cdf = Expdist.ExpCdf(100.0, lambda);
+        Assert.Equal(1.0, cdf, LooseTolerance);
+    }
+
+    // ─── Monotonicity ────────────────────────────────────────────────────────
+
+    [Fact]
+    public void ExpCdf_MonotonicIncreasing_Lambda1()
+    {
+        double lambda = 1.0;
+        double prev = -1.0;
+
+        for (int i = 0; i <= 20; i++)
+        {
+            double x = i * 0.1;
+            double cdf = Expdist.ExpCdf(x, lambda);
+            Assert.True(cdf >= prev - LooseTolerance,
+                $"CDF not monotonic at x={x}: got {cdf}, prev={prev}");
+            prev = cdf;
+        }
+    }
+
+    [Fact]
+    public void ExpCdf_MonotonicIncreasing_Lambda3()
+    {
+        double lambda = 3.0;
+        double prev = -1.0;
+
+        for (int i = 0; i <= 20; i++)
+        {
+            double x = i * 0.05;
+            double cdf = Expdist.ExpCdf(x, lambda);
+            Assert.True(cdf >= prev - LooseTolerance,
+                $"CDF not monotonic at x={x}: got {cdf}, prev={prev}");
+            prev = cdf;
+        }
+    }
+
+    // ─── Higher λ -> faster rise ─────────────────────────────────────────────
+
+    [Theory]
+    [InlineData(0.3)]
+    [InlineData(0.5)]
+    [InlineData(0.7)]
+    public void ExpCdf_HigherLambda_HigherCdfForSamePositiveX(double x)
+    {
+        double cdf1 = Expdist.ExpCdf(x, 1.0);
+        double cdf3 = Expdist.ExpCdf(x, 3.0);
+        double cdf10 = Expdist.ExpCdf(x, 10.0);
+
+        Assert.True(cdf3 > cdf1, $"λ=3 CDF({x})={cdf3} should exceed λ=1 CDF({x})={cdf1}");
+        Assert.True(cdf10 > cdf3, $"λ=10 CDF({x})={cdf10} should exceed λ=3 CDF({x})={cdf3}");
+    }
+
+    // ─── Flat range → F(0.5; λ) ──────────────────────────────────────────────
+
+    [Theory]
+    [InlineData(1.0)]
+    [InlineData(2.0)]
+    [InlineData(3.0)]
+    [InlineData(5.0)]
+    public void ExpdistCdf_FlatRange_ReturnsCdfAtHalf(double lambda)
+    {
+        var ind = new Expdist(20, lambda);
+        var time = DateTime.UtcNow;
+
+        for (int i = 0; i < 20; i++)
+        {
+            ind.Update(new TValue(time.AddSeconds(i), 100.0));
+        }
+
+        double expected = Expdist.ExpCdf(0.5, lambda);
+        Assert.Equal(expected, ind.Last.Value, LooseTolerance);
+    }
+
+    // ─── Output bounded [0, 1] ────────────────────────────────────────────────
+
+    [Fact]
+    public void ExpdistCdf_OutputBounded_Zero_To_One()
+    {
+        int count = 200;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.3, seed: 63001);
+        var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+
+        var indicator = new Expdist(period: 20, lambda: 3.0);
+
+        for (int i = 0; i < count; i++)
+        {
+            indicator.Update(bars.Close[i]);
+            double v = indicator.Last.Value;
+            Assert.True(v >= 0.0 && v <= 1.0, $"Output {v} at bar {i} out of [0,1]");
+        }
+    }
+
+    // ─── Period=1 trivial case ────────────────────────────────────────────────
+
+    [Fact]
+    public void ExpdistCdf_Period1_AlwaysReturnsCdfAtHalf()
+    {
+        // period=1: single-element window → range=0 → x=0.5 always
+        var ind = new Expdist(1, 2.0);
+        var time = DateTime.UtcNow;
+        double expected = Expdist.ExpCdf(0.5, 2.0); // 1 - exp(-1) ≈ 0.6321
+
+        double[] prices = { 100.0, 50.0, 200.0, 1.0, 1000.0 };
+        foreach (double p in prices)
+        {
+            ind.Update(new TValue(time, p));
+            time = time.AddMinutes(1);
+            Assert.Equal(expected, ind.Last.Value, LooseTolerance);
+        }
+    }
+
+    // ─── Span batch consistency ───────────────────────────────────────────────
+
+    [Fact]
+    public void Batch_Span_MatchesTSeries()
+    {
+        int count = 150;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.25, seed: 63002);
+        var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+
+        double[] rawValues = new double[count];
+        for (int i = 0; i < count; i++)
+        {
+            rawValues[i] = bars.Close[i].Value;
+        }
+
+        var tseriesResult = Expdist.Batch(bars.Close, period: 30);
+        double[] spanResult = new double[count];
+        Expdist.Batch(rawValues, spanResult, period: 30);
+
+        for (int i = 0; i < count; i++)
+        {
+            Assert.Equal(tseriesResult[i].Value, spanResult[i], Tolerance);
+        }
+    }
+
+    // ─── Streaming convergence ────────────────────────────────────────────────
+
+    [Fact]
+    public void ExpdistCdf_HighPeriod_StillConverges()
+    {
+        int period = 200;
+        var indicator = new Expdist(period, 2.0);
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.3, seed: 63003);
+        var bars = gbm.Fetch(period + 50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+
+        for (int i = 0; i < bars.Close.Count; i++)
+        {
+            indicator.Update(bars.Close[i]);
+            Assert.True(double.IsFinite(indicator.Last.Value),
+                $"Non-finite output at bar {i}");
+        }
+    }
+
+    [Fact]
+    public void ExpdistCdf_ExtremePrices_StillInRange()
+    {
+        var indicator = new Expdist(period: 20, lambda: 3.0);
+        var time = DateTime.UtcNow;
+
+        for (int i = 0; i < 20; i++)
+        {
+            double price = (i % 2 == 0) ? 1e10 : 1e-10;
+            indicator.Update(new TValue(time.AddMinutes(i), price));
+            double v = indicator.Last.Value;
+            Assert.True(v >= 0.0 && v <= 1.0, $"Out of range at {i}: {v}");
+        }
+    }
+
+    // ─── CDF integrates to complement of survival function ───────────────────
+
+    [Fact]
+    public void ExpCdf_PlusSurvival_IsOne()
+    {
+        // F(x) + (1 - F(x)) = 1; survival = exp(-λx)
+        double[] lambdas = { 0.5, 1.0, 2.0, 5.0 };
+        double[] xs = { 0.1, 0.5, 1.0, 2.0 };
+
+        foreach (double lambda in lambdas)
+        {
+            foreach (double x in xs)
+            {
+                double cdf = Expdist.ExpCdf(x, lambda);
+                double survival = Math.Exp(-lambda * x);
+                Assert.Equal(1.0, cdf + survival, LooseTolerance);
+            }
+        }
+    }
+
+    // ─── Different parameter combos all produce output in range ──────────────
+
+    [Theory]
+    [InlineData(5, 0.5)]
+    [InlineData(14, 1.0)]
+    [InlineData(50, 3.0)]
+    [InlineData(100, 5.0)]
+    [InlineData(30, 10.0)]
+    public void ExpdistCdf_ParameterCombos_OutputBounded(int period, double lambda)
+    {
+        int count = period + 50;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 63004 + period);
+        var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+
+        var indicator = new Expdist(period, lambda);
+
+        for (int i = 0; i < count; i++)
+        {
+            indicator.Update(bars.Close[i]);
+            double v = indicator.Last.Value;
+            Assert.True(v >= 0.0 && v <= 1.0,
+                $"Out of [0,1] at bar {i}: {v} (period={period}, lambda={lambda})");
+        }
+    }
+
+    // ─── Large dataset: stable ────────────────────────────────────────────────
+
+    [Fact]
+    public void ExpdistCdf_LargeDataset_Stable()
+    {
+        int count = 2000;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 63005);
+        var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+
+        var indicator = new Expdist(period: 50);
+
+        for (int i = 0; i < count; i++)
+        {
+            indicator.Update(bars.Close[i]);
+            double v = indicator.Last.Value;
+            Assert.True(double.IsFinite(v) && v >= 0.0 && v <= 1.0,
+                $"Invalid output {v} at bar {i}");
+        }
+    }
+
+    // ─── Memoryless property: F(x+t) - F(x) / (1-F(x)) = F(t) ─────────────
+
+    [Fact]
+    public void ExpCdf_MemorylessProperty()
+    {
+        // P(X > s + t | X > s) = P(X > t) = exp(-λt)
+        // Equivalently: (1 - F(s+t)) / (1 - F(s)) ≈ 1 - F(t)
+        double lambda = 2.0;
+        double s = 0.5;
+        double t = 0.3;
+
+        double fst = Expdist.ExpCdf(s + t, lambda);
+        double fs = Expdist.ExpCdf(s, lambda);
+        double ft = Expdist.ExpCdf(t, lambda);
+
+        // (1 - F(s+t)) / (1 - F(s)) should equal (1 - F(t))
+        double conditionalSurvival = (1.0 - fst) / (1.0 - fs);
+        double expectedSurvival = 1.0 - ft;
+
+        Assert.Equal(expectedSurvival, conditionalSurvival, LooseTolerance);
+    }
+}

lib/numerics/expdist/Expdist.cs

@@ -0,0 +1,297 @@
+// EXPDIST: Exponential Distribution CDF
+// Applies the exponential CDF F(x; λ) = 1 - exp(-λx) to a min-max normalized
+// price series over a rolling lookback window.
+// Pipeline: MinMax normalization → closed-form CDF evaluation (single exp() call).
+
+using System.Runtime.CompilerServices;
+using System.Runtime.InteropServices;
+
+namespace QuanTAlib;
+
+/// <summary>
+/// EXPDIST: Exponential Distribution CDF
+/// Computes the exponential CDF F(x; λ) = 1 - exp(-λx) applied to a min-max
+/// normalized price series over a rolling lookback window.
+/// </summary>
+/// <remarks>
+/// Key properties:
+/// - Output always in [0, 1]
+/// - Rolling window tracks min/max for normalization; flat range returns F(0.5; λ)
+/// - λ (lambda) controls curvature: higher λ compresses the CDF toward 1.0 faster
+/// - λ = 1: gentle curve, F(0.5) ≈ 0.39; λ = 3 (default): F(0.5) ≈ 0.78
+/// - CDF evaluation is O(1): a single exp() — no special functions required
+/// - NaN/Infinity inputs use last-valid-value substitution
+/// </remarks>
+[SkipLocalsInit]
+public sealed class Expdist : AbstractBase
+{
+    private readonly int _period;
+    private readonly double _lambda;
+    private readonly RingBuffer _buffer;
+
+    [StructLayout(LayoutKind.Auto)]
+    private record struct State(double LastValid);
+    private State _state, _p_state;
+
+    public override bool IsHot => _buffer.Count >= _period;
+
+    /// <summary>
+    /// Initializes a new Expdist indicator.
+    /// </summary>
+    /// <param name="period">Lookback window for min-max normalization (default 50)</param>
+    /// <param name="lambda">Rate parameter λ &gt; 0 (default 3.0)</param>
+    public Expdist(int period = 50, double lambda = 3.0)
+    {
+        if (period < 1)
+        {
+            throw new ArgumentException("Period must be >= 1", nameof(period));
+        }
+
+        if (lambda <= 0.0)
+        {
+            throw new ArgumentException("Lambda must be > 0", nameof(lambda));
+        }
+
+        _period = period;
+        _lambda = lambda;
+        _buffer = new RingBuffer(period);
+        Name = $"Expdist({period},{lambda:F2})";
+        WarmupPeriod = period;
+        _state = new State(0.0);
+        _p_state = _state;
+    }
+
+    /// <summary>
+    /// Initializes a new Expdist indicator with source for event-based chaining.
+    /// </summary>
+    /// <param name="source">Source indicator for chaining</param>
+    /// <param name="period">Lookback window (default 50)</param>
+    /// <param name="lambda">Rate parameter λ &gt; 0 (default 3.0)</param>
+    public Expdist(ITValuePublisher source, int period = 50, double lambda = 3.0)
+        : this(period, lambda)
+    {
+        source.Pub += HandleUpdate;
+    }
+
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    private void HandleUpdate(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
+
+    /// <summary>
+    /// Exponential CDF: F(x; λ) = 1 - exp(-λx) for x > 0, else 0.
+    /// Closed-form; requires only a single exp() call.
+    /// </summary>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    public static double ExpCdf(double x, double lambda)
+    {
+        if (x <= 0.0)
+        {
+            return 0.0;
+        }
+
+        return 1.0 - Math.Exp(-lambda * x);
+    }
+
+    /// <summary>
+    /// Exponential PDF: f(x; λ) = λ * exp(-λx) for x >= 0, else 0.
+    /// </summary>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    public static double ExpPdf(double x, double lambda)
+    {
+        if (x < 0.0)
+        {
+            return 0.0;
+        }
+
+        return lambda * Math.Exp(Math.FusedMultiplyAdd(-lambda, x, 0.0));
+    }
+
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    private static (double min, double max) FindMinMax(ReadOnlySpan<double> values)
+    {
+        if (values.Length == 0)
+        {
+            return (double.MaxValue, double.MinValue);
+        }
+
+        double min = values[0];
+        double max = values[0];
+        for (int i = 1; i < values.Length; i++)
+        {
+            double v = values[i];
+            if (v < min)
+            {
+                min = v;
+            }
+
+            if (v > max)
+            {
+                max = v;
+            }
+        }
+
+        return (min, max);
+    }
+
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    public override TValue Update(TValue input, bool isNew = true)
+    {
+        if (isNew)
+        {
+            _p_state = _state;
+        }
+        else
+        {
+            _state = _p_state;
+        }
+
+        double value = input.Value;
+        double result;
+
+        if (double.IsFinite(value))
+        {
+            _buffer.Add(value, isNew);
+
+            var (min, max) = FindMinMax(_buffer.GetSpan());
+            double range = max - min;
+
+            // Flat range → use midpoint 0.5 to avoid degenerate output
+            double x = range > 0.0 ? (value - min) / range : 0.5;
+
+            result = ExpCdf(x, _lambda);
+            _state = new State(result);
+        }
+        else
+        {
+            result = _state.LastValid;
+        }
+
+        Last = new TValue(input.Time, result);
+        PubEvent(Last, isNew);
+        return Last;
+    }
+
+    public override TSeries Update(TSeries source)
+    {
+        var result = new TSeries(source.Count);
+        ReadOnlySpan<double> values = source.Values;
+        ReadOnlySpan<long> times = source.Times;
+
+        for (int i = 0; i < source.Count; i++)
+        {
+            var tv = Update(new TValue(new DateTime(times[i], DateTimeKind.Utc), values[i]), true);
+            result.Add(tv, true);
+        }
+
+        return result;
+    }
+
+    public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
+    {
+        TimeSpan interval = step ?? TimeSpan.FromSeconds(1);
+        DateTime time = DateTime.UtcNow - (interval * source.Length);
+
+        for (int i = 0; i < source.Length; i++)
+        {
+            Update(new TValue(time, source[i]), true);
+            time += interval;
+        }
+    }
+
+    public static TSeries Batch(TSeries source, int period = 50, double lambda = 3.0)
+    {
+        var indicator = new Expdist(period, lambda);
+        return indicator.Update(source);
+    }
+
+    /// <summary>
+    /// Calculates Exponential Distribution CDF over a span of values.
+    /// Uses a sliding window min-max normalization identical to the streaming path.
+    /// </summary>
+    public static void Batch(
+        ReadOnlySpan<double> source, Span<double> output,
+        int period = 50, double lambda = 3.0)
+    {
+        if (source.Length == 0)
+        {
+            throw new ArgumentException("Source cannot be empty", nameof(source));
+        }
+
+        if (output.Length < source.Length)
+        {
+            throw new ArgumentException("Output length must be >= source length", nameof(output));
+        }
+
+        if (period < 1)
+        {
+            throw new ArgumentException("Period must be >= 1", nameof(period));
+        }
+
+        if (lambda <= 0.0)
+        {
+            throw new ArgumentException("Lambda must be > 0", nameof(lambda));
+        }
+
+        double lastValid = 0.0;
+
+        for (int i = 0; i < source.Length; i++)
+        {
+            double val = source[i];
+            if (!double.IsFinite(val))
+            {
+                output[i] = lastValid;
+                continue;
+            }
+
+            int start = Math.Max(0, i - period + 1);
+
+            double min = double.PositiveInfinity;
+            double max = double.NegativeInfinity;
+
+            for (int j = start; j <= i; j++)
+            {
+                double v = source[j];
+                if (double.IsFinite(v))
+                {
+                    if (v < min)
+                    {
+                        min = v;
+                    }
+
+                    if (v > max)
+                    {
+                        max = v;
+                    }
+                }
+            }
+
+            if (!double.IsFinite(min) || !double.IsFinite(max))
+            {
+                output[i] = lastValid;
+                continue;
+            }
+
+            double range = max - min;
+            double x = range > 0.0 ? (val - min) / range : 0.5;
+
+            double result = ExpCdf(x, lambda);
+            lastValid = result;
+            output[i] = result;
+        }
+    }
+
+    public static (TSeries Results, Expdist Indicator) Calculate(
+        TSeries source, int period = 50, double lambda = 3.0)
+    {
+        var indicator = new Expdist(period, lambda);
+        TSeries results = indicator.Update(source);
+        return (results, indicator);
+    }
+
+    public override void Reset()
+    {
+        _buffer.Clear();
+        _state = new State(0.0);
+        _p_state = _state;
+        Last = default;
+    }
+}