📊 TA-Lib

A powerful TypeScript library designed specifically for Technical Analysis in trading and financial markets.

🌟 Overview

TA-Lib provides a comprehensive collection of technical indicators and functions for analyzing financial market data. Built with TypeScript, it offers type safety and modern programming patterns for reliable technical analysis.

✨ Features

• 📈 Multiple Technical Indicators - MACD, RSI, Bollinger Bands, ADX, OBV, Alligator, VWAP, ATR, and more
• 🧮 Domain-Specific Language (DSL) - Create and evaluate trading strategies using a simple expression language
• 🔄 Strategy Backtesting - Test your trading strategies against historical data
• 🛠️ Extensible Architecture - Easily add new indicators and functions
• 📊 Type-Safe API - Fully typed interfaces for reliable development

🚀 Getting Started

Installation

npm install ta-lib-ts

Basic Usage

import { compute_rsi, compute_macd, compute_bollinger_bands } from 'ta-lib-ts';

// Calculate RSI
const rsi = compute_rsi(closePrices, 14);

// Calculate MACD
const macd = compute_macd(closePrices, 12, 26, 9);

// Calculate Bollinger Bands
const bb = compute_bollinger_bands(candleData, 20, 2);

Using the DSL Parser

import { DSLParser } from 'ta-lib-ts';
import { DEFAULT_FUNCTION_REGISTRY } from 'ta-lib-ts';

// Create a parser with candle data and the default function registry
const parser = new DSLParser(candleData, DEFAULT_FUNCTION_REGISTRY);

// Evaluate expressions
const result = parser.evaluate("ema(9, 0) > ema(21, 0)");

Backtesting Strategies

import { StrategyRunner, StrategySchema } from 'ta-lib-ts';
import { DEFAULT_FUNCTION_REGISTRY } from 'ta-lib-ts';

// Define a strategy
const strategy: StrategySchema = {
    name: "Golden Cross",
    entry_long: "ema(9, 0) > ema(21, 0)",
    exit_long: "ema(9, 0) < ema(21, 0)",
    capital: 1000,
    stop_loss_expr: "entry_price() * 0.95",
};

// Run the strategy
const runner = new StrategyRunner(candleData, strategy, DEFAULT_FUNCTION_REGISTRY);
const results = runner.run();
const report = runner.get_report();

📋 Available Indicators

| Indicator | Function | Description | |-----------|----------|-------------| | EMA | compute_ema(data, period) | Exponential Moving Average | | MACD | compute_macd(data, short_period, long_period, signal_period) | Moving Average Convergence Divergence | | RSI | compute_rsi(data, period) | Relative Strength Index | | Bollinger Bands | compute_bollinger_bands(data, period, multiplier) | Bollinger Bands | | ADX | compute_adx(data, period) | Average Directional Index | | OBV | compute_obv(data) | On-Balance Volume | | Alligator | compute_alligator(data, jaw_period, teeth_period, lips_period) | Williams Alligator Indicator | | VWAP | compute_vwap(data) | Volume Weighted Average Price | | ATR | compute_atr(data, period) | Average True Range |

🧩 DSL Functions

The library includes a powerful Domain-Specific Language for creating trading strategies. Available functions include:

• Basic price data: open(), high(), low(), close()
• Technical indicators: ema(), macd_macd_line(), macd_signal_line(), rsi(), obv(), vwap(), atr()
• Strategy context: entry_price(), exit_price()
• Utility functions: avg()

🛠️ Development

Building the Project

npm install
npm run build

Running Tests

npm test

📄 License

MIT

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

This README provides a comprehensive overview of your TA-Lib project, including features, usage examples, available indicators, and development instructions. The emojis add visual appeal and help organize the different sections.