TrendSniiper: Automated MT5 Trading with Verified Live Performance and AI Precision

This TrendSniiper review examines live trading logs, backtests and user reports to assess 2026 performance and provide an evidence-based analysis of behavior under different market regimes. The first pass shows TrendSniiper identifying multi-bar trend continuations and avoiding low-probability countertrend moves, which is reflected in its trade selection and timing. The codebase relies on ONNX-exported AI components alongside classical MA and volatility filters to produce entry signals and dynamic exits. Fernando Borges Rocha designed TrendSniiper with a modular structure so traders can load provided set files and tune risk parameters on MT5. The algorithm differentiates itself through hybrid decision making: machine learning for pattern recognition plus deterministic risk rules for position sizing and stop placement. TrendSniiper tends to perform best in directional markets with persistent momentum and can scale down exposure in range-bound conditions. Backtests and verified live samples indicate consistent trend capture and shorter average trade durations compared with pure breakout systems. In practical terms, TrendSniiper’s strengths are systematic risk controls, transparent parameter sets, and developer support for setup. Limitations include occasional sensitivity to sudden news-driven volatility and the need for appropriate broker conditions like low slippage and steady execution. Overall, TrendSniiper demonstrates repeatable behavior, and traders should validate set files on a demo account before live deployment to confirm compatibility with their MT5 broker and risk tolerance.