Algorithmic and automated systems

Algorithmic trading turns a set of rules into software. It can make execution more consistent, but it can also repeat a flawed rule faster than a person. Automation is a tool, not a source of guaranteed returns.

Define the rules first

Specify the market, data, timeframe, entry condition, exit condition and risk limit. “Buy when the market looks strong” is not a complete rule. A system also needs instructions for missing data, duplicate orders, rejected orders and a lost connection.

Know the platform distinction

MetaTrader Expert Advisors and no-code bot platforms are different systems. Do not assume a bot built for one product can run on another platform or trade the same contracts. Check the supported products, execution model and current documentation before selecting a tool.

Backtest without fooling yourself

Include spreads, commissions, financing and plausible slippage. Avoid using information that would not have been available at the decision time. Keep some data separate from development, and test across different conditions. A profitable historical test does not prove that a system will work in future.

Overfitting and operational risk

Adding more settings can make past results look impressive while making future results fragile. Software bugs, data errors and outages can also cause unintended orders. Use position limits, duplicate-order protection, monitoring and a way to stop the system.

Human oversight still matters

A bot has no fear, but its developer can still overreact to a losing streak or overtrust a winning one. Measure actual execution against the test and investigate changes. Faster execution is not necessarily better execution.

Your next steps

Write a simple strategy in plain language before writing code. Test it on historical data, then in a demo environment. Document the conditions that would make you stop the test, including unexpected orders or a breach of the chosen risk limit.