Sweep Hunter by EV: Automated MT5 Trading with Verified Results

Sweep Hunter by EV review for 2026 provides an in-depth look at how this MT5 Expert Advisor approaches session reversal opportunities and liquidity sweeps. The performance analysis in this review highlights verified live-account samples and backtest snapshots that demonstrate the EA's focus on short-duration, higher-probability trades executed around major session transitions. Enrique Valeros Muriana designed the EA to automatically identify the Asian session boundaries, validate the internal price structure, and execute when the London open creates a sweep through liquidity, which the algorithm interprets as a high-probability reversal setup. What makes Sweep Hunter by EV unique is its specific focus on the Asian-to-London volatility transition combined with automated validation checks that reduce noise entries. The algorithm evaluates multi-candle patterns and volume or spread filters (when available) to confirm the sweep, then applies adaptive stop loss and profit targets based on recent range size. Market conditions it handles best include well-defined overnight ranges followed by a clearly timed London session opening move. The EA uses position sizing tied to account risk percentage and includes configurable max concurrent trades and time window restrictions to manage exposure. Expected performance characteristics include moderate trade frequency, higher win rate on validated sweeps, and a propensity for short-duration positions that close within a few hours. Sweep Hunter by EV is priced at $39 and carries a 4.5/5 rating from 100 reviews on the marketplace, reflecting consistent user feedback about ease of use and steady performance when optimized for the broker environment. Results will vary by account size, broker execution, and parameter tuning.

Performance review of Sweep Hunter by EV shows typical win rate expectations in the 65-78% range on validated live samples, depending on parameter settings and the currency pairs used. Historical and live account samples included in marketplace listings indicate maximum drawdowns around 8-15% on balanced allocation tests when standard risk settings are used, with improved drawdown control if conservative risk per trade is selected. Trade frequency is moderate, averaging 4-20 trades per week depending on market conditions and the number of pairs enabled. Account requirements generally start at $500 for micro-lot testing, but practical live use benefits from $1,000 to $2,000 minimum to allow reasonable lot sizing and risk diversification. Timeframe considerations favor lower intraday charts for execution with H1 or M5 for range detection and entry confirmation, and results are sensitive to broker spreads and slippage.

Sweep Hunter by EV carries a moderate risk profile as it targets volatile session transitions and uses leverage-sensitive position sizing. The stop loss strategy is dynamic and based on recent Asian range size, allowing the EA to adapt to varying volatility, while take profit targets aim for asymmetrical reward relative to risk on confirmed sweeps. Position sizing is percentage-based per trade, so recommended settings should align with account equity and risk tolerance; many users limit risk to 0.5-1.5% per trade. Vulnerabilities include prolonged low-volatility periods, expensive spreads during news events, and sudden liquidity gaps at session overlaps. Recommended account size for conservative live deployment is at least $1,000 with a tested broker that offers tight spreads and reliable execution.

To install Sweep Hunter by EV on MT5, download the EA file and place it in the Experts folder of your MT5 data directory, then restart the platform so the EA appears in the Navigator panel. Attach the EA to a chart and enable automated trading; configure key parameters such as risk percent per trade, maximum concurrent trades, allowed trade hours, and the list of currency pairs to trade. Recommended brokers are ECN or STP accounts with low spreads and fast execution. Use H1 or M5 charts for range detection and entry confirmation and run forward tests on a demo account for at least three months before live deployment to fine-tune settings.