What is aster-bot?

Aster Bot is an automated trading system for AsterDEX, a decentralized exchange for cryptocurrency perpetual futures contracts. Perpetual futures are a type of trading instrument that lets you bet on whether a cryptocurrency price will go up or down, with leverage, without an expiry date. This bot connects to AsterDEX's public API and places buy and sell orders automatically based on pre-programmed strategies, running around the clock without manual intervention. The README opens with a prominent disclaimer: trading digital assets involves substantial risk, the example screenshots in the docs are illustrative rather than guarantees, and users should read the risk warnings before running anything with real money. The project is aimed at technically comfortable operators who already understand what they are doing, not beginners. The bot supports two built-in trading strategies. One is called Watermellon and uses moving averages combined with a momentum indicator to identify trends. The other is called Peach Hybrid and has two modes: one that tracks market bias and direction, and another that looks for momentum surges. Which strategy you use and how it behaves is controlled entirely through environment variables and configuration, with no code changes required. Risk management features include configurable position size limits, leverage caps, stop-loss and take-profit levels, a trailing stop that adjusts as prices move in your favor, and a limit on how often the bot can flip between long and short positions per hour. All trades are logged to CSV and JSON files organized by date, and the bot maintains state across restarts so it can reconcile with actual open positions on the exchange. The system runs as a Node.js application and is designed to be deployed on a VPS or personal machine. It supports a dry-run mode for testing strategy behavior with no real orders placed, which the README recommends using before switching to live trading. The project is built in TypeScript and intended for developers comfortable reading logs and adjusting configuration before scaling up position sizes.