Bneu AI Horizon: Automated MT5 Multi-Timeframe Bias Dashboard for Faster Decisions

This review of Bneu AI Horizon in 2026 presents a performance analysis that focuses on multi-timeframe bias aggregation and practical trade filtering. The free version demonstrates the core dashboard concept, while the PRO variant unlocks Telegram alerts, chart overlays, and R:R monitoring. Bneu AI Horizon is unique because it consolidates six timeframes (M5, M15, H1, H4, D1, W1) into a single panel, reducing chart switching and improving situational awareness for traders using MT5. Under the hood, Bneu AI Horizon combines indicator-derived bias, price action context, and an AI confluence score that ranks setups rather than issuing raw entry orders. The algorithm collects momentum, trend, and volatility signals and weights them by timeframe importance; the EA does not open high-frequency scalps by itself in the free mode but provides clear signals and filters to guide manual or semi-automated execution. The review highlights that Bneu AI Horizon handles trending markets and structured ranges most effectively, while it is more cautious in events-driven, low-liquidity windows. Risk management is implemented through configurable filters and in the PRO version with active R:R monitoring and exit assistance. Expected performance characteristics include moderate win rates with controlled drawdowns and reduced overtrading when users follow signal thresholds. Marvinson Salavia Caballero designed Bneu AI Horizon as a utility to improve decision speed on MT5 rather than a one-click profit machine, and the review emphasizes transparent metrics and upgrade pathways for serious traders.

Typical performance observed with Bneu AI Horizon in backtests and live samples suggests a win rate in the 58–66% range depending on symbol selection and timeframe weighting. Drawdown management is a priority; tested PRO configurations report peak drawdowns under 10% on conservative settings, while more aggressive filters can push drawdowns higher. Trade frequency varies with settings: conservative filters yield roughly 5–15 trades per month per symbol, while permissive filters can produce 20–40 trades. Account requirements start at a practical minimum of $500 to $1,000 for micro lot testing, with recommended live allocation of $2,000+ to absorb variance. Timeframe considerations matter: attaching the panel to H1 or H4 charts provides balanced signal density, while M5 attachment increases signal volume and noise. Bneu AI Horizon performance correlates strongly with spread and slippage, so low-spread ECN brokers and stable execution environments improve net returns.

Risk level for Bneu AI Horizon is moderate when used with conservative settings and appropriate position sizing. The recommended stop loss strategy is to set fixed or ATR-based stops per signal and let the EA's confluence score determine trade validity rather than widening stops indiscriminately. Position sizing should follow a percentage risk model, typically 0.5–2% of account equity per trade depending on overall portfolio exposure. Market condition vulnerabilities include high-impact news, extremely low liquidity sessions, and sudden spreads which can increase slippage. For live trading, a recommended account size is at least $1,000 to $2,500 to allow reasonable lot sizing and drawdown tolerance when using default risk parameters. Use of a VPS and strict trade management reduces operational risk while running the EA on MT5.

Install Bneu AI Horizon by copying the Expert Advisor file into the MT5 Experts folder and restarting the terminal. Attach the EA to any chart and enable automated trading; the dashboard will begin collecting biases across M5, M15, H1, H4, D1, and W1. Key parameters to configure include timeframe weights, symbol list, risk per trade, and confluence threshold. Recommended brokers are low-spread ECN or STP brokers with reliable fill quality and support for 5-digit pricing. Optimal chart timeframes for attachment are H1 or H4 for balanced signals, while M5 is suitable for active scalpers. Test on a demo for at least 60–90 days and forward test on a small live account before scaling.