Static code analysis provided by ndepend

QuanTAlib - Quantitative Technical Indicators Without Compromises

TA libraries face a fundamental choice: accept approximations for simplicity OR enforce math rigor. QuanTAlib chooses rigor.

Quantitative TA library (QuanTAlib) is a C# library built on the premise that you shouldn't have to choose. Modern CPUs process 4-8 FLOPS per cycle via SIMD. Modern .NET exposes memory layouts making hardware acceleration trivial. QuanTAlib exploits both. Result: mathematically rigorous indicators at speeds making real-time multi-symbol analysis practical on ordinary hardware.

Key Features

• Zero Allocation: Hot paths are allocation-free. No GC pauses during trading.
• SIMD Accelerated: Uses AVX2/AVX-512 for 8x throughput on modern CPUs.
• O(1) Streaming: Constant time updates regardless of lookback period.
• Platform Agnostic: Runs on .NET 8/9/10, compatible with Quantower, NinjaTrader, QuantConnect.
• Mathematically Rigorous: Validated against original research papers and established libraries.

Indicators

Category	Count	What It Measures	Representative Indicators
Trends (FIR)	17	Finite Impulse Response moving averages	SMA, WMA, HMA, ALMA, TRIMA, LSMA, EPMA
Trends (IIR)	23	Infinite Impulse Response moving averages	EMA, DEMA, TEMA, T3, JMA, KAMA, VIDYA
Filters	18	Signal processing and noise reduction filters	Bessel, Butterworth, Gaussian, Savitzky-Golay, Ehlers Super Smoother
Oscillators	19	Indicators that fluctuate around a center line	RSI, MACD, Stochastic, AO, APO, CCI, Ultimate Oscillator
Dynamics	18	Trend strength and direction indicators	ADX, Aroon, SuperTrend, Vortex, Chop, Ichimoku
Momentum	16	Speed and magnitude of price changes	Momentum, ROC, Velocity, RSX, Qstick, KDJ
Volatility	26	Size and variability of price movements	ATR, Bollinger Band Width, Historical Volatility, True Range
Volume	26	Trading activity and price-volume relationships	OBV, VWAP, MFI, ADL, CMF, TVI, Force Index
Statistics	30	Statistical measures and tests	Correlation, Variance, StdDev, Skewness, Kurtosis, Z-Score
Channels	23	Price boundaries and range definitions	Bollinger Bands, Keltner Channels, Donchian Channels
Cycles	14	Cycle analysis and signal processing	Hilbert Transform, Homodyne, Phasor, Ehlers Sine Wave
Reversals	12	Pattern recognition and reversal detection	Pivot Points, Fractals, Swings, Pivot Components
Forecasts	1	Predictive indicators and projections	Time Series Forecast, AFIRMA, Chande Forecast Oscillator
Errors	26	Error metrics and loss functions	RMSE, MAE, MAPE, SMAPE, MASE, R-Squared
Numerics	15	Mathematical transformations	Log, Exp, Sqrt, Tanh, ReLU, Sigmoid

Browse all 284 indicators →

Quick Start

Install from NuGet:

dotnet add package QuanTAlib

Calculate an SMA in real-time:

using QuanTAlib;

var sma = new Sma(period: 14);
double price = 100.0;

// Update with new price
var result = sma.Update(new TValue(DateTime.UtcNow, price));

if (result.IsHot)
{
    Console.WriteLine($"SMA: {result.Value}");
}

Performance Snapshot

QuanTAlib is designed for speed. Here is how it compares calculating a 500,000 bar SMA against other libraries:

Library	Mean Time	Allocations	Relative Speed
QuanTAlib (Span)	318.3 μs	0 B	1.00x (baseline)
TA-Lib	356.4 μs	34 B	1.12x slower
Tulip Indicators	359.3 μs	0 B	1.13x slower
Skender Indicators	71,277 μs	50.8 MB	224x slower

See Benchmarks for full details and methodology.

Documentation

Core Concepts

• Architecture: Learn about SoA layout, SIMD, and design philosophy.
• API Reference: Deep dive into the Tri-Modal Architecture (Batch, Streaming, Priming).
• Indicators: Full catalog of available indicators and their mathematical families.
• Usage Guides: Detailed patterns for Span, Streaming, Batch, and Eventing modes.
• Integration: Setup guides for Quantower, NinjaTrader, and QuantConnect.

Analysis & Validation

• Benchmarks: Detailed performance evidence and test methodology.
• Error Metrics: Implementation details for 20+ error metrics and loss functions.
• Trend Comparison: Comparative analysis of lag, smoothness, and accuracy.
• MA Qualities: Theoretical framework for evaluating moving averages.
• Validation: Verification matrices against TA-Lib, Skender, and other libraries.
• Glossary: Definitions of core QuanTAlib concepts, types, and terminology.