JavaScript Crypto Bot

🚀 Overview

This is an automated JavaScript Crypto Trading Bot designed to analyze market trends, execute trades, and optimize profit strategies. The bot integrates various indicators such as MACD, EMA, Bollinger Bands, VWAP, ATR, and ADX to enhance decision-making.

✨ Features

• 📈 Real-time market analysis using ccxt
• 🔄 Supports multiple timeframes with custom strategies
• 📊 Technical indicators: MACD, EMA, Bollinger Bands, VWAP, ATR, ADX
• 🔍 Trend analysis using best-fit lines and support/resistance levels
• 📂 Saves historical OHLCV data for analysis

📦 Installation

Prerequisites

Make sure you have Node.js installed on your system.

1. Clone the repository:

   git clone https://github.com/ocirede/JavaScript_Crypto_Bot.git
   cd JavaScript_Crypto_Bot

2. Install dependencies:

   npm install

3. Set up environment variables (create a .env file):

   BINGX_API_KEY=your_api_key
   BINGX_SECRET_KEY=your_secret_key

   ⚠️ Do NOT share your API keys!

🚀 Usage

Start the bot with:

node bot.js

Available Scripts

• npm start - Starts the bot
• npm run backtest - Runs backtesting on historical data
• npm run analyze - Generates trading analysis

⚙️ Configuration

Modify config.json to customize trading strategies, indicators, and risk management settings.

{
  "timeframe": "1h",
  "strategy": "macd_vwap",
  "indicators": {
    "ema_period": 55,
    "bollinger_bands": 14
  },
  "risk_management": {
    "max_drawdown": 5,
    "stop_loss": 2
  }
}

📊 Supported Indicators

• MACD (Moving Average Convergence Divergence)
• EMA (Exponential Moving Average)
• VWAP (Volume-Weighted Average Price)
• Bollinger Bands
• ATR (Average True Range)
• ADX (Average Directional Index)

🔥 Upcoming Features

• 📡 Integration with TradingView for alerts
• 🤖 Machine learning-based pattern recognition
• 📉 Multiple exchange support (Coinbase, Kraken, etc.)
• 🐍 Planned Python translation for improved performance and flexibility

📜 License

This project is private. If you'd like to contribute or use the bot, please contact me.

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👨‍💻 Developed by Federico Diaferia