Risk Management in Algorithmic Trading: A Guide

Why risk management comes before strategy

Even the best strategy goes through a bad stretch. Risk management is the set of rules that keeps the account alive through it. Judge results not only by "how much did it make" but by "how much could it have lost in the worst case".

Four core principles

1. Position sizing: size each trade so only a small part of the account is at risk. Derive size from a formula, not emotion: amount to risk ÷ distance between entry and stop.
2. Loss limits: set limits in advance for the day and for total drawdown. When a limit is hit the system should stop automatically, and restarting should be a conscious human decision.
3. Leverage: leverage magnifies gains and losses. Start small, especially with futures, and set a ceiling.
4. Operational risk: lost connections, bad data, duplicate orders, server outages. Keep logs, set up alerts, and regularly reconcile positions with the real state at the exchange.

Apply it in testing too

Run the same risk rules in backtests and paper trading; otherwise results are unrealistic. See the Backtesting and Paper Trading Guide.

Extra care in 24/7 markets

In continuous markets such as crypto the system must run safely overnight too: a guide to running crypto bots 24/7.

Remember

Never trade with more than you can afford to lose.

This article is for education only and is not investment advice. Past results do not guarantee future results; trading carries a risk of loss.