QuanTAlib/.github/copilot-instructions.md

QuanTAlib AI Coding Agent Instructions

Project Overview

QuanTAlib is a high-performance C# library for quantitative technical analysis targeting .NET 8.0. Provides 50+ technical indicators optimized for sub-millisecond real-time streaming calculations using circular buffers, SIMD operations, and event-driven architecture. Used in production live trading environments.

Critical Architecture Patterns

Core Data Flow

All indicators inherit from AbstractBase (lib/core/abstractBase.cs) implementing ITValue:

// Standard indicator lifecycle:
TValue/TBar Input → Calc() → ManageState(isNew) → Calculation() → Process() → Pub event

Critical concept: The isNew parameter differentiates:

• isNew=true: New bar/candle arrives → increment _index, backup all state variables
• isNew=false: Update to current bar → restore backed-up state, recalculate with new value

This dual-mode processing is essential for real-time trading where the current bar updates continuously before the next bar starts. Every indicator must handle both modes correctly - validated extensively in Tests/test_updates_*.cs.

Circular Buffer Pattern

CircularBuffer (lib/core/circularbuffer.cs) provides memory-efficient fixed-capacity storage:

• Never grows beyond initial capacity (fixed memory footprint regardless of data volume)
• O(1) add/access operations with wraparound
• SIMD-optimized aggregations (Sum, Min, Max, Average) using System.Numerics.Vector
• Critical: Always use Add(item, isNew) - the isNew flag controls append vs update behavior

State Management in Indicators

Every indicator must implement this pattern to support bar updates:

protected override void ManageState(bool isNew)
{
    if (isNew) {
        _index++;
        _p_prevValue = _prevValue;      // Backup state
        _p_lastEma = _lastEma;           // Backup all stateful variables
    } else {
        _prevValue = _p_prevValue;       // Restore state
        _lastEma = _p_lastEma;           // Restore all stateful variables
    }
}

Pattern: Use _p_ prefix for backup variables (e.g., _p_lastEma, _p_isInit, _p_e). When isNew=false, restore ALL stateful variables before recalculating. See lib/trends/Ema.cs for reference implementation.

Development Workflow

MCP-Orchestrated Process

Research Gate: Before implementing non-trivial indicators, use Context7 MCP to retrieve authoritative formulas/references. Embed citation tags in PR descriptions.

Decomposition: Use Sequential-Thinking MCP for complex multi-stage work (SIMD refactors, multi-timeframe logic, performance optimization epics).

Task Tracking: Taskmaster MCP holds the canonical task graph. Feature branches follow pattern: feature/{taskId}-{slug}. Tasks include: feature, performance, documentation with status transitions (not-started → in-progress → done).

Quality Gates:

1. Formula citation required for non-trivial indicators (Context7 tag in PR description)
2. Benchmark data required for performance-related changes
3. Taskmaster task IDs must be referenced in PR body with closing keywords
4. Update memory-bank/progress.md after merge when threshold met (≥5 feature tasks or perf epic completes)

Build & Test Commands

# Build solution (or use VS Code Task: "build")
dotnet build QuanTAlib.sln

# Run all tests (or use VS Code Task: "test")
dotnet test --no-build --verbosity:normal

# Run with coverage
dotnet test /p:CollectCoverage=true /p:CoverletOutputFormat=lcov /p:CoverletOutput=./lcov.info --no-build

# Clean build artifacts
dotnet clean QuanTAlib.sln

VS Code Tasks: Use Run Task menu for build, test, test with coverage, clean - configured in .vscode/tasks.json.

Adding a New Indicator

1. Research: Get formula/specification. For non-trivial indicators, use Context7 to retrieve authoritative references.

2. Location: Place in appropriate lib/ subdirectory:

   • trends/ - Trend indicators (SMA, EMA, JMA, etc.)
   • oscillators/ - RSI, Stochastic, CCI, etc.
   • momentum/ - MACD, ADX, ROC, etc.
   • volatility/ - ATR, Bollinger Bands, volatility measures
   • volume/ - Volume-based indicators
   • statistics/ - Statistical measures, correlations

3. Template structure:

using System.Runtime.CompilerServices;
namespace QuanTAlib;

[SkipLocalsInit]
public sealed class MyIndicator : AbstractBase
{
    private readonly int _period;
    private CircularBuffer _buffer;
    private double _prevValue, _p_prevValue;  // State + backup with _p_ prefix
    
    [MethodImpl(MethodImplOptions.AggressiveInlining)]
    public MyIndicator(int period)
    {
        ArgumentOutOfRangeException.ThrowIfLessThan(period, 1);
        _period = period;
        _buffer = new(period);
        WarmupPeriod = period;  // Set when indicator stabilizes (95% accuracy)
        Name = $"MyIndicator({period})";
        Init();
    }
    
    [MethodImpl(MethodImplOptions.AggressiveInlining)]
    public override void Init()
    {
        base.Init();
        _prevValue = 0;
        _buffer = new(_period);
    }
    
    [MethodImpl(MethodImplOptions.AggressiveInlining)]
    protected override void ManageState(bool isNew)
    {
        if (isNew) {
            _index++;
            _p_prevValue = _prevValue;
        } else {
            _prevValue = _p_prevValue;
        }
    }
    
    [MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
    protected override double Calculation()
    {
        ManageState(Input.IsNew);
        _buffer.Add(Input.Value, Input.IsNew);
        
        // Implement calculation logic
        double result = _buffer.Average();  // Example using SIMD-optimized operation
        _prevValue = result;
        
        IsHot = _index >= WarmupPeriod;  // Mark when indicator reaches accuracy threshold
        return result;
    }
}

4. Testing: Create update test in appropriate Tests/test_updates_*.cs file:

[Fact]
public void MyIndicator_Update()
{
    var indicator = new MyIndicator(period: 14);
    double initialValue = indicator.Calc(new TValue(DateTime.Now, 100.0, IsNew: true));
    
    // Apply 100 random updates with isNew=false
    for (int i = 0; i < 100; i++)
    {
        indicator.Calc(new TValue(DateTime.Now, GetRandomDouble(), IsNew: false));
    }
    
    // Final value with same input should equal initial value
    double finalValue = indicator.Calc(new TValue(DateTime.Now, 100.0, IsNew: false));
    Assert.Equal(initialValue, finalValue, precision: 8);
}

5. Validation: Compare against reference implementations (TALib, Trady, Skender) in appropriate test file.

Quantower Integration

For platform indicators in quantower/, create wrapper classes inheriting from Quantower's Indicator:

public class MyIndicator : Indicator, IWatchlistIndicator
{
    [InputParameter("Period", sortIndex: 1, 1, 2000, 1, 0)]
    public int Period { get; set; } = 14;
    
    private QuanTAlib.MyIndicator? ma;
    protected LineSeries? Series;
    
    protected override void OnInit()
    {
        ma = new QuanTAlib.MyIndicator(period: Period);
        base.OnInit();
    }
    
    protected override void OnUpdate(UpdateArgs args)
    {
        TValue input = this.GetInputValue(args, Source);
        TValue result = ma!.Calc(input);
        Series!.SetValue(result.Value);
    }
}

• Use private lib/ indicator instances
• Map OnUpdate() to indicator's Calc() method
• Extract output from indicator state/properties
• Apply IndicatorExtensions for styling and painting

Code Style Requirements

Performance First

• Use [MethodImpl(MethodImplOptions.AggressiveInlining)] for all public methods and hot paths
• Use [MethodImpl(MethodImplOptions.AggressiveOptimization)] for Calculation() methods
• Apply [SkipLocalsInit] to indicator classes to skip zero-initialization
• Prefer SIMD operations in CircularBuffer for aggregations (Sum, Min, Max, Average)
• Minimize allocations in Calculation() methods - reuse buffers and avoid LINQ
• Use sealed classes when possible for devirtualization

C# Conventions

• No inline comments within methods - code should be self-documenting through clear naming
• Use XML doc comments for public classes/methods only - include purpose, formula description, and source citations
• PascalCase for public members, _camelCase for private fields
• _p_ prefix for backup state variables used in ManageState()
• Compact code - minimal whitespace between logical blocks
• Latest C# features: ArgumentOutOfRangeException.ThrowIfLessThan, pattern matching, collection expressions, etc.
• No namespace imports in individual files - Directory.Build.props enables implicit usings

Project Settings (Directory.Build.props)

• LangVersion: preview - use cutting-edge C# features
• AllowUnsafeBlocks: true - SIMD and unsafe operations permitted
• Nullable: enable - strict nullability checking enforced
• Target: net8.0
• DisableImplicitNamespaceImports: true - explicit namespace control
• Release optimizations: AOT, ReadyToRun, TieredCompilation, trimming enabled

Key Files & Directories

Core Library Structure

lib/
├── core/              # AbstractBase, CircularBuffer, TSeries, TBar, TValue, ITValue
├── trends/            # Trend indicators: SMA, EMA, DEMA, TEMA, JMA, KAMA, etc. (25+ indicators)
├── oscillators/       # RSI, Stochastic, Williams %R, CCI, Fisher, CTI, etc.
├── momentum/          # MACD, ADX, DMI, ROC, TRIX, Vortex, PMO, etc.
├── volatility/        # ATR, Bollinger Bands, Keltner Channels, volatility measures
├── volume/            # Volume-based indicators (OBV, MFI, etc.)
├── statistics/        # Statistical measures, correlations
└── errors/            # Error metrics: MAE, MSE, RMSE, MAPE, R-squared, etc.

Critical Reference Files

• lib/core/abstractBase.cs - Base class for all indicators with lifecycle management
• lib/core/circularbuffer.cs - Memory-efficient storage with SIMD operations
• lib/core/TValue.cs - Immutable record struct for time-value pairs with IsNew/IsHot flags
• lib/core/TBar.cs - OHLCV bar data structure
• Directory.Build.props - Solution-wide MSBuild properties and optimizations
• memory-bank/systemPatterns.md - Architecture patterns and design decisions
• memory-bank/activeContext.md - Current work focus, MCP policies, and operational rules
• memory-bank/progress.md - Completed features, roadmap, and version history

Testing Reference

• Tests/test_updates_*.cs - Update behavior validation (IsNew handling) - CRITICAL TESTS
• Tests/test_quantower.cs - Quantower integration validation
• Tests/test_talib.cs - Cross-validation against TA-Lib reference library
• Tests/test_Trady.cs - Cross-validation against Trady reference library
• Tests/test_skender.stock.cs - Cross-validation against Skender.Stock.Indicators

Common Patterns

Multi-Stage Smoothing

Many indicators (DEMA, TEMA, MACD) use cascaded smoothing with child indicator instances:

private readonly Ema _ema1;
private readonly Ema _ema2;

public MyIndicator(int period)
{
    _ema1 = new Ema(period);
    _ema2 = new Ema(period);
}

protected override double Calculation()
{
    _ema1.Calc(Input.Value, Input.IsNew);
    _ema2.Calc(_ema1.Value, Input.IsNew);  // Feed output of first into second
    return _ema2.Value;
}

Bar-Based vs Value-Based Indicators

• Value-based: Accept TValue, process single values (most indicators like SMA, EMA, RSI)
• Bar-based: Accept TBar (OHLCV), process bar data (ATR, Stochastic, volume indicators)

Override appropriate Calc() method:

// For bar-based indicators
public override TValue Calc(TBar barInput)
{
    BarInput = barInput;
    return Process(barInput.Close, barInput.Time, barInput.IsNew);
}

WarmupPeriod Calculation

Set WarmupPeriod to indicate when the indicator reaches 95% accuracy (used for IsHot flag):

// For exponential smoothing with constant alpha/k
WarmupPeriod = (int)Math.Ceiling(Math.Log(0.05) / Math.Log(1 - k));

// For simple period-based indicators
WarmupPeriod = period;

// For multi-stage indicators
WarmupPeriod = stage1.WarmupPeriod + stage2.WarmupPeriod;

Event-Driven Updates

Indicators support pub-sub pattern through Pub event:

// Publishing side (automatic in AbstractBase.Process())
Pub?.Invoke(this, new ValueEventArgs(value));

// Subscribing side
var ema = new Ema(20);
ema.Pub += (sender, args) => Console.WriteLine($"New EMA value: {args.Tick.Value}");

// Or subscribe one indicator to another
var sma = new Sma(10);
var ema = new Ema(sma, period: 20);  // EMA automatically subscribes to SMA's Pub event

Validation Strategy

1. Update tests (CRITICAL): Verify isNew=false behavior converges to isNew=true with same final value after 100 random updates. This validates state management correctness. See Tests/test_updates_*.cs.

2. Reference comparison: Validate against TALib, Trady, or Skender implementations. Expect high precision match (typically 8+ decimal places).

3. Edge cases: Test with:

   • Insufficient data (count < period)
   • NaN and Infinity inputs (should propagate last valid value)
   • Extreme values (very large/small numbers)
   • Zero and negative values where applicable

4. Performance: Benchmark calculation time - target < 0.5ms per update. Use BenchmarkDotNet for precise measurements.

Documentation Requirements

• XML doc comments on public classes/methods describing:
  • Purpose and use case
  • Formula/algorithm description
  • Source citations (URLs to papers, documentation, books)
  • Parameter constraints and validation
• Mathematical formulas in doc comments with proper notation
• No internal code comments - let code structure communicate intent through clear naming
• Update memory-bank/progress.md after significant feature completion (threshold: ≥5 feature tasks merged)

GitVersion & Releases

• Semantic versioning via GitVersion.yml
• Version properties auto-injected: $(GitVersion_MajorMinorPatch), $(GitVersion_AssemblySemVer)
• Commit messages influence version bumps using conventional commits:
  • +semver: major or +semver: breaking → major bump
  • +semver: minor or +semver: feature → minor bump
  • +semver: patch or +semver: fix → patch bump
  • +semver: none or +semver: skip → no bump
• main branch: ContinuousDeployment mode, patch increment
• dev branch: ContinuousDelivery mode, pre-release weight 30000
• Build creates NuGet package with embedded version metadata and source link