Start with a defined rule
Algorithmic trading uses software to evaluate instructions and manage parts of a trading workflow. Those instructions can describe entry conditions, exit conditions, sizing and operational limits. A clear rule is a starting point, not evidence that a strategy will work.
Separate research from execution
Historical testing can help examine an idea, but results depend on data quality, assumptions, transaction costs and modelling choices. A strategy can behave differently in changing markets. Simulation and supervised evaluation help identify limitations before any live use.
Plan for operational risk
Connectivity loss, rejected orders, delayed data and software errors can interrupt a workflow. Monitoring, reconciliation, defined limits and a documented stop procedure are essential considerations. Automation does not remove market risk.
Markets involve risk. Education and automation do not guarantee returns. Services and availability are subject to applicable law and provider terms. Read our risk disclosure