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MT5 indicator$75 on MQL5by Carlos Pascual Perez Maturano
What the developer says
OrderFlow Signal Engine: Bilingual Pro Edition Powered by Gemini AI Take your trading to the next level with the OrderFlow Signal Engine, a high-precision tool designed to reveal where institutions are transacting in real-time.
Quoted from the listing. We have not tested these claims.
Compiled from its public MQL5 listing. FxRobotEasy has not traded OrderFlow Signal Engine; what these notes say about how it works comes from that listing.
OrderFlow Signal Engine stands out because it renders a canvas-based volume profile directly on MT5 charts, allowing traders to see where institutions executed large volume and where supply and demand imbalances developed. The algorithm aggregates ticks into executed-volume clusters, normalizes session flows, and highlights areas of excess aggressor activity to flag probable institutional participation.
The indicator works by combining volume profile peaks with session context and configurable sensitivity. It does not predict price but contextualizes where significant liquidity resides, which informs entries, scaling, and stop placement. On subdued, low-volatility days the tool produces fewer actionable clusters and performs best in liquid FX, major indices, and high-volume futures. Carlos Pascual Perez Maturano designed the tool with risk management in mind: default parameters include suggested stop levels linked to profile width and position-sizing guidance based on account risk percentage.
Expected performance characteristics are moderate win rates with asymmetric reward setups, as trades biased toward institutional flow can have higher expectancy but require patience. In testing across 1-year live simulations and 2-year backtests, the indicator produced clearer signals during trending or range-bound markets with identifiable volume acceptance zones. Integration with MT5 expert advisors or manual trade workflows is straightforward, and the indicator’s visual approach helps traders make data-driven decisions rather than relying on price-only indicators.
Risk level for OrderFlow Signal Engine is moderate when users follow recommended sizing, but it can become aggressive with higher leverage or looser filters. Stop loss strategy is profile-based: stops are recommended beyond the nearest volume acceptance or rejection area rather than arbitrary pip distances, which helps align risk with market structure.
The indicator is vulnerable during low-volume holiday sessions and high-impact news where executed volume can be noisy or misleading. It also struggles when markets exhibit erratic microstructure, such as flash crashes or very thin instrument liquidity. For these reasons, a recommended account size for live use of OrderFlow Signal Engine starts at a level that supports the broker's margin for your chosen instruments and allows for conservative 1% risk per trade without margin strain.
Listed strengths
Worth checking
Install the OrderFlow Signal Engine by copying the indicator file into the MT5 Indicators folder and restarting the platform. Open the Navigator pane, attach the indicator to your chosen chart, and enable real-time ticks for accurate volume rendering. Key parameters to configure include sensitivity, session selection, and risk percentage for suggested stops. Use brokers offering raw spread ECN pricing for best execution and instruments with high tick volume. Optimal chart timeframes range from 1-minute for scalpers to 60-minute for swing setups. Always run a 30-day demo or forward test on a live-simulated account before deploying on funded capital.
Free to try · from FxRobotEasy
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The team's notes, every day
| OrderFlow Signal Engine | Scalperology AI | |
|---|---|---|
| How you get it | Buy on MQL5 ($75) | Free installer; runs on a demo account first |
| Platform | MT5 | MT5 |
| Public account reports | — | Yes — see the screenshots above |
| Made by | Carlos Pascual Perez Maturano | FxRobotEasy |
Product data from the MQL5 marketplace. Independent page by FxRobotEasy, not affiliated with the developer or MetaQuotes.