MeridianAlgo.js

MeridianAlgo is a professional-grade, high-performance quantitative finance framework for JavaScript and TypeScript. It provides institutional-quality tools for algorithmic trading, backtesting, risk management, and portfolio optimization in a single, unified package.

Key Features

• High Performance: Native TypeScript implementation optimized for large datasets.
• Technical Indicators (100+): Classic (SMA, RSI, MACD) to advanced (GARCH, Hurst Exponent, VPIN, Kalman Filter).
• Backtesting Engine: Realistic time-based simulation with custom commission and slippage models.
• Risk Management: VaR, CVaR, Stress Testing, and Performance Attribution.
• Portfolio Optimization: Mean-Variance (Markowitz), Black-Litterman, and Risk Parity.
• Plugin Architecture: Easily extend the framework with custom data adapters, strategies, and models.
• Machine Learning: Built-in utilities for feature engineering, regime detection, and state-space models.

Installation

# Using npm
npm install meridianalgo

# Using pnpm
pnpm add meridianalgo

# Using yarn
yarn add meridianalgo

Quick Start

Basic Backtest

import { TimeBasedEngine, Indicators, YahooAdapter } from 'meridianalgo';

async function run() {
  const data = await new YahooAdapter().ohlcv('AAPL', {
    start: '2023-01-01',
    end: '2024-01-01',
    interval: '1d'
  });

  const engine = new TimeBasedEngine({
    initialCash: 100000,
    data,
    strategy: {
      id: 'simple-ema',
      next: (bar) => {
        // Your logic here
        return { t: bar.t, value: 1 };
      }
    }
  });

  const result = await engine.run();
  console.log(`Total Return: ${result.metrics.totalReturn * 100}%`);
}

Advanced Quantitative Tools

MeridianAlgo v4.0.0+ includes cutting-edge tools for modern quants:

• Hurst Exponent: Measure time-series persistence and mean reversion.
• Fractional Differencing: Achieve stationarity while preserving long-term memory.
• Ornstein-Uhlenbeck Process: Estimate mean reversion speed and long-term equilibrium.
• Kalman Filter: Dynamic state estimation and noise reduction for signals.
• Black-Litterman: Blend market equilibrium with subjective investor views.

Project Structure

The project has been consolidated into a streamlined single-package structure for better performance and easier dependency management:

src/
├── core/         # Core types & Plugin system
├── indicators/   # Classic & Advanced TA Indicators
├── data/         # Adapters (Yahoo, Binance, Alpaca, Polygon)
├── backtest/     # Simulation Engines
├── strategies/   # Templates & Logical Composers
├── risk/         # Metrics (VaR, Sharpe) & Stress Testing
├── portfolio/    # Optimization & Allocation Models
├── execution/    # Order Management & Broker Adapters
└── utils/        # Math, Stats, & Time Utilities

Documentation

• Quick Start Guide
• API Reference
• Developer Guide
• Mathematical Foundations

Contributing

We welcome contributions! See CONTRIBUTING.md for details on how to get involved.

License & Disclaimer

Copyright (c) 2026 Meridian Algorithmic Research Team. Licensed under the MIT License.

DISCLAIMER: This software is for educational and research purposes only. Trading financial markets involves significant risk of loss. Read the full DISCLAIMER before use.