Add TRAMA implementation and comprehensive tests

- Implemented the TRAMA (Trend Regularity Adaptive Moving Average) class with adaptive EMA logic.
- Added unit tests for TRAMA functionality, including constructor validation, basic calculations, state management, and robustness checks.
- Created validation tests to ensure consistency across different modes of operation (streaming, batch, and static calculations).
- Enhanced documentation for TRAMA, including performance profiles and quality metrics.
- Updated workspace configuration by removing unnecessary folder references.

lib/trends_FIR/kaiser/Kaiser.Quantower.Tests.cs

@@ -0,0 +1,171 @@
+using TradingPlatform.BusinessLayer;
+
+namespace QuanTAlib.Tests;
+
+public class KaiserIndicatorTests
+{
+    [Fact]
+    public void KaiserIndicator_Constructor_SetsDefaults()
+    {
+        var indicator = new KaiserIndicator();
+
+        Assert.Equal(14, indicator.Period);
+        Assert.Equal(3.0, indicator.Beta);
+        Assert.Equal(SourceType.Close, indicator.Source);
+        Assert.True(indicator.ShowColdValues);
+        Assert.Equal("KAISER - Kaiser Window Moving Average", indicator.Name);
+        Assert.False(indicator.SeparateWindow);
+        Assert.True(indicator.OnBackGround);
+    }
+
+    [Fact]
+    public void KaiserIndicator_MinHistoryDepths_IsZero()
+    {
+        var indicator = new KaiserIndicator { Period = 14 };
+
+        Assert.Equal(0, KaiserIndicator.MinHistoryDepths);
+        Assert.Equal(0, ((IWatchlistIndicator)indicator).MinHistoryDepths);
+    }
+
+    [Fact]
+    public void KaiserIndicator_ShortName_IncludesPeriodAndSource()
+    {
+        var indicator = new KaiserIndicator { Period = 10, Beta = 5.0 };
+
+        Assert.Contains("KAISER", indicator.ShortName, StringComparison.Ordinal);
+        Assert.Contains("10", indicator.ShortName, StringComparison.Ordinal);
+        Assert.Contains("5.0", indicator.ShortName, StringComparison.Ordinal);
+    }
+
+    [Fact]
+    public void KaiserIndicator_SourceCodeLink_IsValid()
+    {
+        var indicator = new KaiserIndicator();
+
+        Assert.Contains("github.com", indicator.SourceCodeLink, StringComparison.Ordinal);
+        Assert.Contains("Kaiser.Quantower.cs", indicator.SourceCodeLink, StringComparison.Ordinal);
+    }
+
+    [Fact]
+    public void KaiserIndicator_Initialize_CreatesInternalKaiser()
+    {
+        var indicator = new KaiserIndicator { Period = 14 };
+
+        indicator.Initialize();
+
+        Assert.Single(indicator.LinesSeries);
+    }
+
+    [Fact]
+    public void KaiserIndicator_ProcessUpdate_HistoricalBar_ComputesValue()
+    {
+        var indicator = new KaiserIndicator { Period = 5 };
+        indicator.Initialize();
+
+        var now = DateTime.UtcNow;
+        indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
+
+        var args = new UpdateArgs(UpdateReason.HistoricalBar);
+        indicator.ProcessUpdate(args);
+
+        Assert.Equal(1, indicator.LinesSeries[0].Count);
+        Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(0)));
+    }
+
+    [Fact]
+    public void KaiserIndicator_ProcessUpdate_NewBar_ComputesValue()
+    {
+        var indicator = new KaiserIndicator { 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 KaiserIndicator_ProcessUpdate_NewTick_ProcessesWithoutError()
+    {
+        var indicator = new KaiserIndicator { 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 KaiserIndicator_MultipleUpdates_ProducesCorrectSequence()
+    {
+        var indicator = new KaiserIndicator { Period = 5 };
+        indicator.Initialize();
+
+        var now = DateTime.UtcNow;
+        double[] closes = { 100, 102, 104, 103, 105, 107, 106 };
+
+        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);
+        }
+
+        for (int i = 0; i < closes.Length; i++)
+        {
+            Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(closes.Length - 1 - i)));
+        }
+    }
+
+    [Fact]
+    public void KaiserIndicator_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 KaiserIndicator { 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 KaiserIndicator_Period_CanBeChanged()
+    {
+        var indicator = new KaiserIndicator { Period = 14 };
+        Assert.Equal(14, indicator.Period);
+
+        indicator.Period = 20;
+        Assert.Equal(20, indicator.Period);
+        Assert.Equal(0, KaiserIndicator.MinHistoryDepths);
+    }
+
+    [Fact]
+    public void KaiserIndicator_Beta_CanBeChanged()
+    {
+        var indicator = new KaiserIndicator { Beta = 3.0 };
+        Assert.Equal(3.0, indicator.Beta);
+
+        indicator.Beta = 8.6;
+        Assert.Equal(8.6, indicator.Beta);
+    }
+}

lib/trends_FIR/kaiser/Kaiser.Quantower.cs

@@ -0,0 +1,59 @@
+using System.Drawing;
+using System.Runtime.CompilerServices;
+using TradingPlatform.BusinessLayer;
+
+namespace QuanTAlib;
+
+[SkipLocalsInit]
+public sealed class KaiserIndicator : Indicator, IWatchlistIndicator
+{
+    [InputParameter("Period", sortIndex: 1, 2, 2000, 1, 0)]
+    public int Period { get; set; } = 14;
+
+    [InputParameter("Beta", sortIndex: 2, minimum: 0.0, maximum: 20.0, increment: 0.1, decimalPlaces: 1)]
+    public double Beta { get; set; } = 3.0;
+
+    [IndicatorExtensions.DataSourceInput]
+    public SourceType Source { get; set; } = SourceType.Close;
+
+    [InputParameter("Show cold values", sortIndex: 21)]
+    public bool ShowColdValues { get; set; } = true;
+
+    private Kaiser _kaiser = null!;
+    private readonly LineSeries _series;
+    private string _sourceName = null!;
+    private Func<IHistoryItem, double> _priceSelector = null!;
+
+    public static int MinHistoryDepths => 0;
+    int IWatchlistIndicator.MinHistoryDepths => MinHistoryDepths;
+
+    public override string ShortName => $"KAISER {Period},{Beta:F1}:{_sourceName}";
+    public override string SourceCodeLink => "https://github.com/mihakralj/QuanTAlib/blob/main/lib/trends_FIR/kaiser/Kaiser.Quantower.cs";
+
+    public KaiserIndicator()
+    {
+        OnBackGround = true;
+        SeparateWindow = false;
+        Name = "KAISER - Kaiser Window Moving Average";
+        Description = "Kaiser Window Moving Average";
+        _series = new LineSeries(name: $"KAISER {Period}", color: IndicatorExtensions.Averages, width: 2, style: LineStyle.Solid);
+        AddLineSeries(_series);
+    }
+
+    protected override void OnInit()
+    {
+        _priceSelector = Source.GetPriceSelector();
+        _sourceName = Source.ToString();
+        _kaiser = new Kaiser(Period, Beta);
+        base.OnInit();
+    }
+
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    protected override void OnUpdate(UpdateArgs args)
+    {
+        bool isNew = args.IsNewBar();
+        var item = HistoricalData[Count - 1, SeekOriginHistory.Begin];
+        double value = _kaiser.Update(new TValue(item.TimeLeft.Ticks, _priceSelector(item)), isNew).Value;
+        _series.SetValue(value, _kaiser.IsHot, ShowColdValues);
+    }
+}

lib/trends_FIR/kaiser/Kaiser.Tests.cs

@@ -0,0 +1,410 @@
+namespace QuanTAlib.Tests;
+
+public class KaiserTests
+{
+    private const int DefaultPeriod = 14;
+    private const double DefaultBeta = 3.0;
+    private const double Epsilon = 1e-10;
+
+    private static TSeries MakeSeries(int count = 500)
+    {
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 42);
+        return gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1)).Close;
+    }
+
+    private readonly TSeries _data = MakeSeries();
+
+    // ── A) Constructor validation ──────────────────────────────────────
+
+    [Theory]
+    [InlineData(0)]
+    [InlineData(1)]
+    [InlineData(-5)]
+    public void Constructor_InvalidPeriod_Throws(int period)
+    {
+        var ex = Assert.Throws<ArgumentException>(() => new Kaiser(period));
+        Assert.Equal("period", ex.ParamName);
+    }
+
+    [Fact]
+    public void Constructor_NegativeBeta_Throws()
+    {
+        var ex = Assert.Throws<ArgumentException>(() => new Kaiser(14, beta: -1.0));
+        Assert.Equal("beta", ex.ParamName);
+    }
+
+    [Theory]
+    [InlineData(2)]
+    [InlineData(14)]
+    [InlineData(100)]
+    public void Constructor_ValidPeriod_Succeeds(int period)
+    {
+        var kaiser = new Kaiser(period);
+        Assert.Contains(period.ToString(System.Globalization.CultureInfo.InvariantCulture), kaiser.Name, StringComparison.Ordinal);
+    }
+
+    [Fact]
+    public void Constructor_DefaultBeta_InName()
+    {
+        var kaiser = new Kaiser(14, 3.0);
+        Assert.Equal("Kaiser(14,3.0)", kaiser.Name);
+    }
+
+    [Fact]
+    public void Constructor_NullSource_Throws()
+    {
+        Assert.Throws<NullReferenceException>(() => new Kaiser(null!, DefaultPeriod));
+    }
+
+    // ── B) Basic calculation ───────────────────────────────────────────
+
+    [Fact]
+    public void Update_ReturnsTValue()
+    {
+        var kaiser = new Kaiser(DefaultPeriod);
+        var result = kaiser.Update(new TValue(DateTime.UtcNow, 100.0));
+        Assert.IsType<TValue>(result);
+    }
+
+    [Fact]
+    public void Last_IsAccessible()
+    {
+        var kaiser = new Kaiser(DefaultPeriod);
+        kaiser.Update(new TValue(DateTime.UtcNow, 100.0));
+        Assert.True(double.IsFinite(kaiser.Last.Value));
+    }
+
+    [Fact]
+    public void Name_IsCorrect()
+    {
+        var kaiser = new Kaiser(14, 5.0);
+        Assert.Equal("Kaiser(14,5.0)", kaiser.Name);
+    }
+
+    [Fact]
+    public void Update_ReturnsFiniteValue()
+    {
+        var kaiser = new Kaiser(DefaultPeriod);
+        foreach (var tv in _data)
+        {
+            var result = kaiser.Update(tv);
+            Assert.True(double.IsFinite(result.Value));
+        }
+    }
+
+    // ── C) State + bar correction ──────────────────────────────────────
+
+    [Fact]
+    public void IsNew_True_AdvancesState()
+    {
+        var kaiser = new Kaiser(5);
+        var now = DateTime.UtcNow;
+        kaiser.Update(new TValue(now, 10.0), isNew: true);
+        kaiser.Update(new TValue(now.AddMinutes(1), 20.0), isNew: true);
+        Assert.True(double.IsFinite(kaiser.Last.Value));
+    }
+
+    [Fact]
+    public void IsNew_False_RewritesCurrentBar()
+    {
+        var kaiser = new Kaiser(5, 3.0);
+        var now = DateTime.UtcNow;
+
+        for (int i = 0; i < 10; i++)
+        {
+            kaiser.Update(new TValue(now.AddMinutes(i), 100.0 + i), isNew: true);
+        }
+
+        double beforeCorrection = kaiser.Last.Value;
+        kaiser.Update(new TValue(now.AddMinutes(9), 999.0), isNew: false);
+        double afterCorrection = kaiser.Last.Value;
+
+        Assert.NotEqual(beforeCorrection, afterCorrection, Epsilon);
+    }
+
+    [Fact]
+    public void IterativeCorrections_Restore()
+    {
+        var kaiser = new Kaiser(5, 3.0);
+        var now = DateTime.UtcNow;
+
+        for (int i = 0; i < 10; i++)
+        {
+            kaiser.Update(new TValue(now.AddMinutes(i), 100.0 + i), isNew: true);
+        }
+
+        double original = kaiser.Last.Value;
+
+        for (int c = 0; c < 5; c++)
+        {
+            kaiser.Update(new TValue(now.AddMinutes(9), 200.0 + c), isNew: false);
+        }
+
+        kaiser.Update(new TValue(now.AddMinutes(9), 109.0), isNew: false);
+        Assert.Equal(original, kaiser.Last.Value, Epsilon);
+    }
+
+    [Fact]
+    public void Reset_ClearsState()
+    {
+        var kaiser = new Kaiser(DefaultPeriod);
+        foreach (var tv in _data)
+        {
+            kaiser.Update(tv);
+        }
+
+        kaiser.Reset();
+        Assert.False(kaiser.IsHot);
+    }
+
+    // ── D) Warmup/convergence ──────────────────────────────────────────
+
+    [Fact]
+    public void IsHot_FlipsAtPeriod()
+    {
+        var kaiser = new Kaiser(5);
+        for (int i = 0; i < 4; i++)
+        {
+            kaiser.Update(new TValue(DateTime.UtcNow, 100.0 + i));
+            Assert.False(kaiser.IsHot);
+        }
+        kaiser.Update(new TValue(DateTime.UtcNow, 105.0));
+        Assert.True(kaiser.IsHot);
+    }
+
+    [Fact]
+    public void WarmupPeriod_MatchesPeriod()
+    {
+        var kaiser = new Kaiser(10);
+        Assert.Equal(10, kaiser.WarmupPeriod);
+    }
+
+    // ── E) Robustness ──────────────────────────────────────────────────
+
+    [Fact]
+    public void NaN_UsesLastValidValue()
+    {
+        var kaiser = new Kaiser(5);
+        for (int i = 0; i < 5; i++)
+        {
+            kaiser.Update(new TValue(DateTime.UtcNow, 100.0));
+        }
+
+        kaiser.Update(new TValue(DateTime.UtcNow, double.NaN));
+        Assert.True(double.IsFinite(kaiser.Last.Value));
+    }
+
+    [Fact]
+    public void Infinity_UsesLastValidValue()
+    {
+        var kaiser = new Kaiser(5);
+        for (int i = 0; i < 5; i++)
+        {
+            kaiser.Update(new TValue(DateTime.UtcNow, 100.0));
+        }
+
+        kaiser.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
+        Assert.True(double.IsFinite(kaiser.Last.Value));
+    }
+
+    [Fact]
+    public void BatchNaN_Safe()
+    {
+        var kaiser = new Kaiser(5);
+        var src = MakeSeries(50);
+        var result = kaiser.Update(src);
+        Assert.Equal(src.Count, result.Count);
+        for (int i = 0; i < result.Count; i++)
+        {
+            Assert.True(double.IsFinite(result[i].Value));
+        }
+    }
+
+    // ── F) Consistency (4-API match) ───────────────────────────────────
+
+    [Fact]
+    public void AllModes_ProduceSameResults()
+    {
+        int period = 10;
+        double beta = 3.0;
+        var src = MakeSeries(100);
+
+        // Streaming
+        var streaming = new Kaiser(period, beta);
+        var streamResults = new double[src.Count];
+        for (int i = 0; i < src.Count; i++)
+        {
+            streamResults[i] = streaming.Update(src[i]).Value;
+        }
+
+        // Batch (TSeries)
+        var batchResults = Kaiser.Batch(src, period, beta);
+
+        // Span
+        var spanOutput = new double[src.Count];
+        Kaiser.Batch(src.Values, spanOutput, period, beta);
+
+        // Event-based
+        var publisher = new TSeries();
+        var eventKaiser = new Kaiser(publisher, period, beta);
+        var eventResults = new double[src.Count];
+        for (int i = 0; i < src.Count; i++)
+        {
+            publisher.Add(src[i], isNew: true);
+            eventResults[i] = eventKaiser.Last.Value;
+        }
+
+        for (int i = 0; i < src.Count; i++)
+        {
+            Assert.Equal(streamResults[i], batchResults[i].Value, 1e-6);
+            Assert.Equal(streamResults[i], spanOutput[i], 1e-6);
+            Assert.Equal(streamResults[i], eventResults[i], 1e-6);
+        }
+    }
+
+    // ── G) Span API tests ──────────────────────────────────────────────
+
+    [Fact]
+    public void Batch_Span_MismatchedLengths_Throws()
+    {
+        var src = new double[10];
+        var output = new double[5];
+        var ex = Assert.Throws<ArgumentException>(() => Kaiser.Batch(src, output, 5));
+        Assert.Equal("output", ex.ParamName);
+    }
+
+    [Fact]
+    public void Batch_Span_PeriodTooSmall_Throws()
+    {
+        var src = new double[10];
+        var output = new double[10];
+        var ex = Assert.Throws<ArgumentException>(() => Kaiser.Batch(src, output, 1));
+        Assert.Equal("period", ex.ParamName);
+    }
+
+    [Fact]
+    public void Batch_Span_EmptyInput_NoOp()
+    {
+        var src = ReadOnlySpan<double>.Empty;
+        var output = Span<double>.Empty;
+        Kaiser.Batch(src, output, 5);
+        Assert.True(true);
+    }
+
+    // ── H) Chainability ────────────────────────────────────────────────
+
+    [Fact]
+    public void Pub_Fires()
+    {
+        var kaiser = new Kaiser(5);
+        int count = 0;
+        kaiser.Pub += (object? _, in TValueEventArgs _) => count++;
+        kaiser.Update(new TValue(DateTime.UtcNow, 100.0));
+        Assert.Equal(1, count);
+    }
+
+    [Fact]
+    public void EventBased_Chaining()
+    {
+        var source = new TSeries();
+        using var kaiser = new Kaiser(source, 5);
+
+        source.Add(new TValue(DateTime.UtcNow, 100.0), isNew: true);
+        Assert.True(double.IsFinite(kaiser.Last.Value));
+    }
+
+    [Fact]
+    public void Dispose_UnsubscribesFromSource()
+    {
+        var source = new TSeries();
+        var kaiser = new Kaiser(source, 5);
+        kaiser.Dispose();
+
+        source.Add(new TValue(DateTime.UtcNow, 100.0), isNew: true);
+        Assert.Equal(default, kaiser.Last);
+    }
+
+    [Fact]
+    public void Dispose_Idempotent()
+    {
+        var kaiser = new Kaiser(5);
+        kaiser.Dispose();
+        kaiser.Dispose();
+        Assert.True(true);
+    }
+
+    // ── I) Kaiser-specific: beta behavior ──────────────────────────────
+
+    [Fact]
+    public void BetaZero_ReducesToSma()
+    {
+        int period = 5;
+        var kaiser = new Kaiser(period, beta: 0.0);
+        var sma = new Sma(period);
+
+        var src = MakeSeries(50);
+        for (int i = 0; i < src.Count; i++)
+        {
+            kaiser.Update(src[i]);
+            sma.Update(src[i]);
+        }
+
+        Assert.Equal(sma.Last.Value, kaiser.Last.Value, 1e-8);
+    }
+
+    [Fact]
+    public void HigherBeta_SmoothsMore()
+    {
+        var src = MakeSeries(100);
+        int period = 14;
+
+        var kaiserLow = new Kaiser(period, beta: 1.0);
+        var kaiserHigh = new Kaiser(period, beta: 8.0);
+
+        double sumDiffLow = 0;
+        double sumDiffHigh = 0;
+
+        for (int i = 0; i < src.Count; i++)
+        {
+            double raw = src[i].Value;
+            kaiserLow.Update(src[i]);
+            kaiserHigh.Update(src[i]);
+
+            if (kaiserLow.IsHot && kaiserHigh.IsHot)
+            {
+                sumDiffLow += Math.Abs(raw - kaiserLow.Last.Value);
+                sumDiffHigh += Math.Abs(raw - kaiserHigh.Last.Value);
+            }
+        }
+
+        Assert.True(sumDiffHigh >= sumDiffLow * 0.8);
+    }
+
+    [Fact]
+    public void ConstantInput_ReturnsConstant()
+    {
+        var kaiser = new Kaiser(7, 3.0);
+        for (int i = 0; i < 20; i++)
+        {
+            kaiser.Update(new TValue(DateTime.UtcNow, 42.0));
+        }
+        Assert.Equal(42.0, kaiser.Last.Value, 1e-10);
+    }
+
+    [Fact]
+    public void Calculate_ReturnsResultsAndIndicator()
+    {
+        var (results, indicator) = Kaiser.Calculate(_data, 14, 3.0);
+        Assert.Equal(_data.Count, results.Count);
+        Assert.True(indicator.IsHot);
+    }
+
+    [Fact]
+    public void Prime_SetsState()
+    {
+        var kaiser = new Kaiser(5, 3.0);
+        var src = MakeSeries(20);
+        kaiser.Prime(src.Values);
+        Assert.True(kaiser.IsHot);
+    }
+}

lib/trends_FIR/kaiser/Kaiser.Validation.Tests.cs

@@ -0,0 +1,149 @@
+namespace QuanTAlib.Tests;
+
+using Xunit;
+
+public class KaiserValidationTests
+{
+    private static TSeries MakeSeries(int count = 500)
+    {
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 42);
+        return gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1)).Close;
+    }
+
+    private readonly TSeries _data = MakeSeries();
+
+    [Fact]
+    public void Batch_Matches_Streaming()
+    {
+        int period = 14;
+        double beta = 3.0;
+
+        var streaming = new Kaiser(period, beta);
+        var streamResults = new double[_data.Count];
+        for (int i = 0; i < _data.Count; i++)
+        {
+            streamResults[i] = streaming.Update(_data[i]).Value;
+        }
+
+        var batchResults = Kaiser.Batch(_data, period, beta);
+
+        for (int i = 0; i < _data.Count; i++)
+        {
+            Assert.Equal(streamResults[i], batchResults[i].Value, 1e-9);
+        }
+    }
+
+    [Fact]
+    public void Span_Matches_Streaming()
+    {
+        int period = 14;
+        double beta = 3.0;
+
+        var streaming = new Kaiser(period, beta);
+        var streamResults = new double[_data.Count];
+        for (int i = 0; i < _data.Count; i++)
+        {
+            streamResults[i] = streaming.Update(_data[i]).Value;
+        }
+
+        var spanOutput = new double[_data.Count];
+        Kaiser.Batch(_data.Values, spanOutput, period, beta);
+
+        for (int i = 0; i < _data.Count; i++)
+        {
+            Assert.Equal(streamResults[i], spanOutput[i], 1e-9);
+        }
+    }
+
+    [Theory]
+    [InlineData(2)]
+    [InlineData(7)]
+    [InlineData(14)]
+    [InlineData(50)]
+    public void DifferentPeriods_ProduceValidResults(int period)
+    {
+        var kaiser = new Kaiser(period, 3.0);
+        foreach (var tv in _data)
+        {
+            var result = kaiser.Update(tv);
+            Assert.True(double.IsFinite(result.Value));
+        }
+        Assert.True(kaiser.IsHot);
+    }
+
+    [Fact]
+    public void ConstantInput_ConvergesToConstant()
+    {
+        var kaiser = new Kaiser(10, 3.0);
+        for (int i = 0; i < 50; i++)
+        {
+            kaiser.Update(new TValue(DateTime.UtcNow, 42.0));
+        }
+        Assert.Equal(42.0, kaiser.Last.Value, 1e-10);
+    }
+
+    [Fact]
+    public void Calculate_ReturnsHotIndicator()
+    {
+        var (results, indicator) = Kaiser.Calculate(_data, 14, 3.0);
+        Assert.True(indicator.IsHot);
+        Assert.Equal(_data.Count, results.Count);
+    }
+
+    [Fact]
+    public void BarCorrection_Consistency()
+    {
+        int period = 7;
+        var kaiser = new Kaiser(period, 3.0);
+
+        for (int i = 0; i < 20; i++)
+        {
+            kaiser.Update(new TValue(DateTime.UtcNow, 100.0 + i), isNew: true);
+        }
+
+        double original = kaiser.Last.Value;
+
+        kaiser.Update(new TValue(DateTime.UtcNow, 999.0), isNew: false);
+        kaiser.Update(new TValue(DateTime.UtcNow, 119.0), isNew: false);
+
+        Assert.Equal(original, kaiser.Last.Value, 1e-10);
+    }
+
+    [Fact]
+    public void SubsetStability()
+    {
+        int period = 10;
+        double beta = 3.0;
+        var src = MakeSeries(200);
+
+        var full = new Kaiser(period, beta);
+        for (int i = 0; i < src.Count; i++)
+        {
+            full.Update(src[i]);
+        }
+
+        var subset = new Kaiser(period, beta);
+        for (int i = 0; i < src.Count; i++)
+        {
+            subset.Update(src[i]);
+        }
+
+        Assert.Equal(full.Last.Value, subset.Last.Value, 1e-10);
+    }
+
+    [Theory]
+    [InlineData(0.0)]
+    [InlineData(3.0)]
+    [InlineData(5.65)]
+    [InlineData(8.6)]
+    public void DifferentBetas_ProduceValidResults(double beta)
+    {
+        var kaiser = new Kaiser(14, beta);
+        foreach (var tv in _data)
+        {
+            var result = kaiser.Update(tv);
+            Assert.True(double.IsFinite(result.Value));
+        }
+        Assert.True(kaiser.IsHot);
+    }
+}

lib/trends_FIR/kaiser/Kaiser.cs

@@ -0,0 +1,418 @@
+using System.Buffers;
+using System.Runtime.CompilerServices;
+using System.Runtime.InteropServices;
+
+namespace QuanTAlib;
+
+/// <summary>
+/// KAISER: Kaiser Window Moving Average
+/// </summary>
+/// <remarks>
+/// Symmetric FIR filter using the Kaiser-Bessel window function for optimal
+/// sidelobe attenuation. The beta parameter continuously controls the trade-off
+/// between main lobe width (transition band sharpness) and sidelobe attenuation.
+///
+/// Calculation: Precomputed weights via modified Bessel function I0, applied as
+/// FIR convolution over sliding window. Beta=0 gives SMA, beta≈5.65 Blackman,
+/// beta≈8.6 Hamming.
+/// </remarks>
+/// <seealso href="Kaiser.md">Detailed documentation</seealso>
+[SkipLocalsInit]
+public sealed class Kaiser : AbstractBase
+{
+    private readonly int _period;
+    private readonly double _beta;
+    private readonly double[] _weights;
+    private readonly RingBuffer _buffer;
+    private readonly ITValuePublisher? _source;
+    private readonly TValuePublishedHandler? _pubHandler;
+    private bool _isNew = true;
+    private bool _disposed;
+    private double _lastValidValue = double.NaN;
+    private double _p_lastValidValue = double.NaN;
+
+    public bool IsNew => _isNew;
+    public override bool IsHot => _buffer.IsFull;
+
+    /// <summary>
+    /// Creates KAISER with specified period and beta.
+    /// </summary>
+    /// <param name="period">Lookback period (>= 2)</param>
+    /// <param name="beta">Shape parameter controlling sidelobe attenuation (0..20, default 3.0)</param>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    public Kaiser(int period = 14, double beta = 3.0)
+    {
+        if (period < 2)
+        {
+            throw new ArgumentException("Period must be at least 2", nameof(period));
+        }
+        if (beta < 0)
+        {
+            throw new ArgumentException("Beta must be non-negative", nameof(beta));
+        }
+
+        _period = period;
+        _beta = beta;
+        Name = $"Kaiser({_period},{_beta:F1})";
+        WarmupPeriod = _period;
+
+        _buffer = new RingBuffer(_period);
+        _weights = new double[_period];
+
+        ComputeKaiserWeights(_weights, _period, _beta);
+    }
+
+    /// <summary>
+    /// Creates KAISER connected to a data source for event-based updates.
+    /// </summary>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    public Kaiser(ITValuePublisher source, int period = 14, double beta = 3.0) : this(period, beta)
+    {
+        _source = source;
+        _pubHandler = Handle;
+        _source.Pub += _pubHandler;
+    }
+
+    /// <summary>
+    /// Modified Bessel function of the first kind, order 0.
+    /// 25-term power series: I0(x) = sum_{m=0}^{25} [(x/2)^m / m!]^2
+    /// </summary>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    private static double BesselI0(double x)
+    {
+        double sum = 1.0;
+        double term = 1.0;
+        double halfX = x * 0.5;
+        for (int m = 1; m <= 25; m++)
+        {
+            term *= halfX / m;
+            sum += term * term;
+        }
+        return sum;
+    }
+
+    /// <summary>
+    /// Computes Kaiser window weights and normalizes to sum=1.
+    /// w(k) = I0(beta * sqrt(1 - t^2)) / I0(beta), where t = 2k/(N-1) - 1.
+    /// </summary>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    private static void ComputeKaiserWeights(Span<double> weights, int period, double beta)
+    {
+        double i0Beta = BesselI0(beta);
+        double nm1 = period - 1;
+
+        double wsum = 0.0;
+        for (int k = 0; k < period; k++)
+        {
+            double t = nm1 > 0 ? (2.0 * k / nm1) - 1.0 : 0.0;
+            double argSq = 1.0 - t * t;
+            double arg = argSq > 0 ? Math.Sqrt(argSq) : 0.0;
+            double w = i0Beta > 0 ? BesselI0(beta * arg) / i0Beta : 1.0;
+            weights[k] = w;
+            wsum += w;
+        }
+
+        if (Math.Abs(wsum) > double.Epsilon)
+        {
+            double inv = 1.0 / wsum;
+            for (int k = 0; k < period; k++)
+            {
+                weights[k] *= inv;
+            }
+        }
+    }
+
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    public override TValue Update(TValue input, bool isNew = true)
+    {
+        _isNew = isNew;
+        return Update(input, isNew, publish: true);
+    }
+
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    private TValue Update(TValue input, bool isNew, bool publish)
+    {
+        if (isNew)
+        {
+            _p_lastValidValue = _lastValidValue;
+        }
+        else
+        {
+            _lastValidValue = _p_lastValidValue;
+        }
+
+        double val = GetValidValue(input.Value);
+
+        if (!double.IsFinite(val))
+        {
+            Last = new TValue(input.Time, double.NaN);
+            if (publish) { PubEvent(Last, isNew); }
+            return Last;
+        }
+
+        if (isNew)
+        {
+            _lastValidValue = val;
+            _buffer.Add(val);
+
+            int count = _buffer.Count;
+            double result;
+
+            if (count < _period)
+            {
+                result = val;
+            }
+            else
+            {
+                result = ConvolveFull(_buffer, _weights);
+            }
+
+            Last = new TValue(input.Time, result);
+            if (publish) { PubEvent(Last, isNew); }
+            return Last;
+        }
+        else
+        {
+            _buffer.Snapshot();
+            double prevLast = _lastValidValue;
+            double prevPLast = _p_lastValidValue;
+
+            _lastValidValue = val;
+            _buffer.UpdateNewest(val);
+
+            int count = _buffer.Count;
+            double result;
+
+            if (count < _period)
+            {
+                result = val;
+            }
+            else
+            {
+                result = ConvolveFull(_buffer, _weights);
+            }
+
+            Last = new TValue(input.Time, result);
+
+            _buffer.Restore();
+            _lastValidValue = prevLast;
+            _p_lastValidValue = prevPLast;
+
+            if (publish) { PubEvent(Last, isNew); }
+            return Last;
+        }
+    }
+
+    public override TSeries Update(TSeries source)
+    {
+        if (source.Count == 0)
+        {
+            return new TSeries([], []);
+        }
+
+        int len = source.Count;
+        var t = new List<long>(len);
+        var v = new List<double>(len);
+        CollectionsMarshal.SetCount(t, len);
+        CollectionsMarshal.SetCount(v, len);
+
+        var tSpan = CollectionsMarshal.AsSpan(t);
+        var vSpan = CollectionsMarshal.AsSpan(v);
+
+        Batch(source.Values, vSpan, _period, _beta);
+        source.Times.CopyTo(tSpan);
+
+        Reset();
+        int startIndex = Math.Max(0, len - _period);
+        for (int i = startIndex; i < len; i++)
+        {
+            Update(source[i], isNew: true, publish: false);
+        }
+
+        return new TSeries(t, v);
+    }
+
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
+
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    private double GetValidValue(double input)
+    {
+        if (double.IsFinite(input))
+        {
+            return input;
+        }
+        return double.IsFinite(_lastValidValue) ? _lastValidValue : double.NaN;
+    }
+
+    /// <summary>
+    /// FIR convolution using SIMD DotProduct over circular buffer.
+    /// Weight[0] corresponds to oldest bar, Weight[period-1] to newest.
+    /// </summary>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    private static double ConvolveFull(RingBuffer buffer, double[] weights)
+    {
+        ReadOnlySpan<double> internalBuf = buffer.InternalBuffer;
+        int head = buffer.StartIndex;
+        int period = buffer.Capacity;
+
+        int part1Len = period - head;
+        double sum1 = internalBuf.Slice(head, part1Len).DotProduct(weights.AsSpan(0, part1Len));
+        double sum2 = internalBuf[..head].DotProduct(weights.AsSpan(part1Len));
+
+        return sum1 + sum2;
+    }
+
+    public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
+    {
+        foreach (var value in source)
+        {
+            Update(new TValue(DateTime.MinValue, value));
+        }
+    }
+
+    public static TSeries Batch(TSeries source, int period = 14, double beta = 3.0)
+    {
+        var kaiser = new Kaiser(period, beta);
+        return kaiser.Update(source);
+    }
+
+    /// <summary>
+    /// Calculates Kaiser Window MA over a span of values.
+    /// </summary>
+    [MethodImpl(MethodImplOptions.AggressiveInlining)]
+    public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period = 14, double beta = 3.0, double nanValue = double.NaN)
+    {
+        if (period < 2)
+        {
+            throw new ArgumentException("Period must be at least 2", nameof(period));
+        }
+        if (source.Length != output.Length)
+        {
+            throw new ArgumentException("Source and output must have the same length", nameof(output));
+        }
+        if (source.Length == 0)
+        {
+            return;
+        }
+
+        int len = source.Length;
+        const int StackallocThreshold = 256;
+
+        double[]? weightsRented = period > StackallocThreshold ? ArrayPool<double>.Shared.Rent(period) : null;
+        Span<double> weights = period <= StackallocThreshold
+            ? stackalloc double[period]
+            : weightsRented!.AsSpan(0, period);
+
+        double[]? ringRented = period > StackallocThreshold ? ArrayPool<double>.Shared.Rent(period) : null;
+        Span<double> ring = period <= StackallocThreshold
+            ? stackalloc double[period]
+            : ringRented!.AsSpan(0, period);
+
+        double[]? cleanRented = len > StackallocThreshold ? ArrayPool<double>.Shared.Rent(len) : null;
+        Span<double> clean = len <= StackallocThreshold
+            ? stackalloc double[len]
+            : cleanRented!.AsSpan(0, len);
+
+        ComputeKaiserWeights(weights, period, beta);
+
+        try
+        {
+            double lastValid = nanValue;
+            for (int i = 0; i < len; i++)
+            {
+                double val = source[i];
+                if (double.IsFinite(val))
+                {
+                    lastValid = val;
+                    clean[i] = val;
+                }
+                else if (double.IsFinite(lastValid))
+                {
+                    clean[i] = lastValid;
+                }
+                else
+                {
+                    clean[i] = double.NaN;
+                }
+            }
+
+            int ringIdx = 0;
+            int count = 0;
+
+            for (int i = 0; i < len; i++)
+            {
+                double val = clean[i];
+
+                ring[ringIdx] = val;
+                ringIdx++;
+                if (ringIdx >= period)
+                {
+                    ringIdx = 0;
+                }
+
+                if (count < period)
+                {
+                    count++;
+                }
+
+                if (count < period)
+                {
+                    output[i] = val;
+                    continue;
+                }
+
+                int part1Len = period - ringIdx;
+
+                ReadOnlySpan<double> ringRo = ring;
+                double sum = ringRo.Slice(ringIdx, part1Len).DotProduct(weights.Slice(0, part1Len))
+                           + ringRo[..ringIdx].DotProduct(weights.Slice(part1Len));
+
+                output[i] = sum;
+            }
+        }
+        finally
+        {
+            if (weightsRented != null)
+            {
+                ArrayPool<double>.Shared.Return(weightsRented);
+            }
+            if (ringRented != null)
+            {
+                ArrayPool<double>.Shared.Return(ringRented);
+            }
+            if (cleanRented != null)
+            {
+                ArrayPool<double>.Shared.Return(cleanRented);
+            }
+        }
+    }
+
+    public static (TSeries Results, Kaiser Indicator) Calculate(TSeries source, int period = 14, double beta = 3.0)
+    {
+        var indicator = new Kaiser(period, beta);
+        TSeries results = indicator.Update(source);
+        return (results, indicator);
+    }
+
+    public override void Reset()
+    {
+        _buffer.Clear();
+        _lastValidValue = double.NaN;
+        _p_lastValidValue = double.NaN;
+        Last = default;
+    }
+
+    protected override void Dispose(bool disposing)
+    {
+        if (!_disposed)
+        {
+            if (disposing && _source != null && _pubHandler != null)
+            {
+                _source.Pub -= _pubHandler;
+            }
+            _disposed = true;
+        }
+        base.Dispose(disposing);
+    }
+}