The moment a strategy leaves the backtester and connects to a broker, it stops being a maths exercise and becomes a software system running in the real world. Plenty of strategies that look great in simulation stumble here — not because the idea was wrong, but because live execution is a different discipline. Here is what to expect.
The gaps a backtest hides
Live trading exposes things a naive backtest glosses over: real spread and slippage, orders that get partially filled or rejected, data feeds that hiccup, and latency between decision and execution. The first job of going live is to make your assumptions about these explicit and conservative.
Demo first, always
Never let a strategy touch real money before it has run on a demo or paper account that mirrors live conditions. This is where you catch the boring, fatal bugs — an order sent twice, a position never closed, a timezone off by an hour. In MQL5 the Strategy Tester and a demo account make this straightforward; in Python you paper-trade against the broker’s sandbox API.
Build the unglamorous infrastructure
A live system needs logging (so you can see what it did), monitoring and alerts (so you know when it breaks), and a kill switch (so you can stop it fast). None of this shows up in a backtest, but all of it is what lets you sleep while code trades. Treat it as part of the strategy, not an afterthought.
Start small and stay humble
When you do go live, start with the smallest size that is meaningful and scale slowly as the system proves itself. AlgoPro University’s advanced tier walks through this whole transition. As always, this is educational material and not financial advice — live trading carries real risk of loss.