The time between seeing a signal and the order reaching the broker includes several steps. Each one can be optimised.
Steps:
1. Recognising the signal (human reaction time).
2. Deciding to act.
3. Clicking or pressing a hotkey.
4. Platform processing the order.
5. Network transmission to the broker.
6. Broker processing and fill.
Optimisations:
- Pre-plan: know entry, stop and size before the signal appears.
- One-click trading enabled, with default lot size set.
- Hotkeys for buy/sell/close.
- VPS near the broker to reduce network time.
- Fewer indicators and charts to keep the platform responsive.
Measuring: MT5's Journal shows order send and fill times. Compare across different setups.
The biggest gains are usually in steps 1–3: preparation and decisiveness. Network optimisation matters less for discretionary trading.
How long does it take you from signal to fill?
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From MT5 chart to broker execution without delay
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FXS London Scalper
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- Joined: Sun Oct 18, 2026 12:25 pm
From MT5 chart to broker execution without delay
FXS Official Team | London Session Desk
Recommended broker for automated trading & scalping
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Shadow Trader
- Posts: 5438
- Joined: Wed Sep 09, 2026 5:19 pm
Re: From MT5 chart to broker execution without delay
Most backtests fill orders at the signal price instantly. Real orders take time: platform processing, network transit, broker handling, liquidity provider response. The total might be 20 ms or 500 ms.
During that delay, price moves. In a quiet market, it moves a fraction of a pip. In a fast market, several.
Adding a delay to a backtest is straightforward with tick data. When a signal fires at tick N, the order fills at the price of the first tick that arrives after the delay has passed. The delay can be fixed, like 150 ms, or drawn from a distribution measured in live trading.
The results are sobering. Strategies that rely on catching the start of a move lose most of their profit with 200 ms added. Strategies that enter on pullbacks or wait for confirmations barely notice.
That difference reveals which type of edge is real. An edge that disappears with a tiny delay was probably an artifact of unrealistically fast fills.
A rough test is to run the backtest at delays of 0, 100, 300, and 1000 ms and plot the profit. The shape of the curve says how fragile the strategy is.
There's a subtler variation worth testing too: the delay may not be constant. Execution times during a news burst can triple compared to a calm minute. A backtest that models delay as proportional to recent tick rate, with the busiest moments getting the longest delays, matches live behavior more closely than a fixed number.
The result is a more honest picture of the worst trades, which tend to occur exactly when delay and volatility rise together. A strategy that remains positive under that harsher model has earned some trust, while one that only works under the generous assumption probably relies on a speed advantage that the retail path cannot supply.
How sensitive is the profit to execution delay in the strategy tested here?
During that delay, price moves. In a quiet market, it moves a fraction of a pip. In a fast market, several.
Adding a delay to a backtest is straightforward with tick data. When a signal fires at tick N, the order fills at the price of the first tick that arrives after the delay has passed. The delay can be fixed, like 150 ms, or drawn from a distribution measured in live trading.
The results are sobering. Strategies that rely on catching the start of a move lose most of their profit with 200 ms added. Strategies that enter on pullbacks or wait for confirmations barely notice.
That difference reveals which type of edge is real. An edge that disappears with a tiny delay was probably an artifact of unrealistically fast fills.
A rough test is to run the backtest at delays of 0, 100, 300, and 1000 ms and plot the profit. The shape of the curve says how fragile the strategy is.
There's a subtler variation worth testing too: the delay may not be constant. Execution times during a news burst can triple compared to a calm minute. A backtest that models delay as proportional to recent tick rate, with the busiest moments getting the longest delays, matches live behavior more closely than a fixed number.
The result is a more honest picture of the worst trades, which tend to occur exactly when delay and volatility rise together. A strategy that remains positive under that harsher model has earned some trust, while one that only works under the generous assumption probably relies on a speed advantage that the retail path cannot supply.
How sensitive is the profit to execution delay in the strategy tested here?