Crypto Trading Bots: Market-Making, Arbitrage, Trend Following, and Alerts
Summary
This introductory article explains how trading bots apply user-defined rules to monitor markets and place trades. It outlines why the author considers crypto suitable for algorithmic trading, citing volatility, continuous market access, and the market’s relative youth, while also warning that volatile conditions can enable speculative pump-and-dump activity. Bots can use indicators or momentum signals, automate order handling, and route orders across venues.
The article describes three common approaches: market making through limit orders on both sides of the book, arbitrage across exchanges, and trend following that enters in rising markets and exits as trends fall. It then sketches a TradingView workflow: create and backtest an EMA crossover strategy, add inputs or risk controls, set alerts, and connect alerts to an execution service for automation. The discussion is introductory and gives no performance evidence or detailed implementation code. Market-making is noted to be limited by low liquidity and intense competition; the article does not discuss fees, slippage, or the operational risks of automated execution in depth.
Key ideas
- A trading bot executes orders when user-defined algorithmic conditions are met.
- Market making seeks to earn the spread with limit orders on both sides of an order book, but depends on liquidity and competition.
- Cross-exchange arbitrage seeks to capture price differences between markets.
- Trend-following systems use market direction to guide entries and exits.
- A TradingView strategy can be backtested, configured to send alerts, and linked to an external execution service.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.