trade-data-generator

Market Depth Generator is a lightweight library for simulating market depth, trade data, and OHLC candlesticks. Designed for trading platforms and financial applications, it generates realistic trading data with customizable configurations.

🌟 Features

Simulate Market Depth with dynamic buy and sell orders.
Generate OHLC Candlesticks (Open, High, Low, Close) with customizable intervals.
Track Executed Trades in real-time with configurable precision and step sizes.
Precision handling for prices and trade volumes per symbol.
Timezone-specific Market Hours for Forex and Equity.
Multi-symbol support for crypto.
WebSocket integration for real-time updates.
Fully customizable and developer-friendly.

🚀 Installation

Install via npm:

npm install market-depth-generator

🛠️ Usage

1. Basic Example

Create a simple WebSocket server that generates and serves market depth and trade data:

const MarketDepthGenerator = require("trade-data-generator");
const express = require("express");
const WebSocket = require("ws");

const PORT = 8080;
const app = express();

// Initialize the MarketDepthGenerator
const generator = new MarketDepthGenerator({
  symbols: ["BTCUSD", "ETHUSD"], // Add multiple symbols
  middlePrice: 305.12, // Base price for simulation
  precision: { BTCUSD: 2, ETHUSD: 4 }, // Set precision per symbol
  stepSize: { BTCUSD: 0.01, ETHUSD: 0.0001 }, // Set step size per symbol
  marketType: "forex", // Set market type (crypto, forex, equity)
  marketRegion: "NYSE", // Region-specific market hours (e.g., NYSE, LSE)
  timezoneOffset: 330, // Timezone offset (e.g., IST = 330 minutes)
});

(async () => {
  setInterval(() => {
    try {
      generator.simulateTrade("BTCUSD");
    } catch (err) {
      console.error("Error simulating trade:", err.message);
    }
  }, 1000);
})();

// HTTP API for fetching market depth for a specific symbol
app.get("/api/market-depth/:symbol", (req, res) => {
  const symbol = req.params.symbol;
  try {
    const depth = generator.getMarketDepth(symbol);
    res.json(depth);
  } catch (err) {
    res.status(400).json({ error: err.message });
  }
});

// HTTP API for fetching market stats for a specific symbol
app.get("/api/market-stats/:symbol", (req, res) => {
  const symbol = req.params.symbol;
  try {
    const stats = generator.getMarketStats(symbol);
    res.json(stats);
  } catch (err) {
    res.status(400).json({ error: err.message });
  }
});

const server = app.listen(PORT, () => {
  console.log(`Server running on http://localhost:${PORT}`);
});

// WebSocket server for real-time updates
const wss = new WebSocket.Server({ server });

wss.on("connection", (ws) => {
  console.log("Client connected");

  const sendMarketUpdates = setInterval(() => {
    const updates = {};

    Object.keys(generator.symbols).forEach((symbol) => {
      updates[symbol] = {
        depth: generator.getMarketDepth(symbol),
        stats: generator.getMarketStats(symbol),
      };
    });

    ws.send(JSON.stringify(updates));
  }, 2500);

  ws.on("close", () => {
    clearInterval(sendMarketUpdates);
    console.log("Client disconnected");
  });
});

Run the script and connect a WebSocket client to view the live simulation data.

📡 Output

The WebSocket server broadcasts the following JSON structure:

{
  "BTCUSD": {
    "marketDepth": {
      "buyOrders": [
        { "price": "1.23456", "quantity": "10.1234" },
        { "price": "1.23450", "quantity": "5.4321" }
      ],
      "sellOrders": [
        { "price": "1.23470", "quantity": "8.5678" },
        { "price": "1.23480", "quantity": "3.2100" }
      ]
    },
    "lastPrice": "1.23456",
    "priceChange": "0.00010",
    "percentageChange": "0.81",
    "highPrice": "1.23480",
    "lowPrice": "1.23450",
    "volume": "123.45",
    "candlestickData": [
      {
        "open": "1.23000",
        "high": "1.24000",
        "low": "1.23000",
        "close": "1.23456",
        "volume": "100.50",
        "timestamp": "2025-01-10T12:00:00Z"
      }
    ]
  }
}

📖 Documentation

Configuration Options

Option	Type	Default	Description
`symbols`	Array	`['BTCUSDT']`	List of symbols for simulation.
`middlePrice`	Number	`305.12`	Base price for market simulation.
`precision`	Object	`{}`	Set precision per symbol (e.g., `{ BTCUSD: 2 }`).
`stepSize`	Object	`{}`	Set price step size per symbol.
`marketType`	String	`crypto`	Type of market (`crypto`, `forex`, or `equity`).
`marketRegion`	String	`null`	Region for equity market hours (e.g., `NYSE`).
`timezoneOffset`	Number	`0`	Timezone offset in minutes (e.g., IST = 330).
`simulationInterval`	Number	`1000`	Interval (ms) for simulating trades.
`updateInterval`	Number	`2500`	Interval (ms) for broadcasting updates.

🧪 Testing

Run tests using Jest:

npm test

📌 Important Notes

Precision Handling:
Customize precision for prices and volumes using the precision configuration per symbol. This ensures prices and volumes match realistic exchange behavior.
Step Size:
Define stepSize per symbol to simulate realistic price jumps for each trade.
Redis Connectivity:
The library no longer handles Redis connectivity internally. Users are responsible for initializing and managing their own Redis connections.
Candlestick Data:
Candlestick (OHLC) data is now directly accessible via getCandlestickData(symbol). You can save this data to Redis or any other database based on your preferences.

📌 TODOs

[x] Add support for multiple symbols.
[x] Add precision and step size configurations.
[ ] Extend candlestick intervals beyond 1 minute.
[ ] Add more realistic trade simulations.
[ ] Implement better test coverage for edge cases.
[ ] Add support for WebSocket authentication.

🌟 What's New in Version 1.4.1

Market Hours Support:
- Integrated time-zone-specific market hours for Forex and Equity markets.
- Automatic market status checks based on region and timezone.
Precision and Step Sizes:
- Added per-symbol precision and step size configurations.
Real-time WebSocket Updates:
- Improved candlestick data and market stats streaming.

👤 Author

Love Pareek
GitHub: monupareeklg

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🛠️ Contributing

Contributions are welcome! Please follow these steps:

Fork the repository.
Create a new branch for your feature or bug fix: git checkout -b feature-name.
Commit your changes: git commit -m 'Add a new feature'.
Push to the branch: git push origin feature-name.
Submit a pull request.

Make sure your code is clean and well-documented before submitting. We appreciate your contributions!

🌟 Support

If you like this project, please give it a ⭐️ on GitHub!

For issues, feel free to open a ticket on the GitHub issues page.

Need help or have questions? Contact me at monupareeklg@gmail.com.