Ewa: Automated MT5 Trading with Verified Performance and Risk Controls

This Ewa review presents a systematic 2026 performance analysis using both live MT5 records and out-of-sample backtests. In this review we compare key metrics such as monthly return, maximum drawdown, and win rate to industry baselines, and the performance analysis highlights periods of stress where the model adapts entry thresholds. Ewa is engineered to combine recurrent neural networks, long short-term memory models, and supervised learning with a secondary visual intelligence layer to interpret chart patterns and contextual events. The result is an advisor that can adjust to changing regimes more quickly than static-rule systems. What makes Ewa unique is its two-mode architecture that separates signal discovery from execution logic. One mode focuses on statistical arbitrage-style mean reversion while the other follows momentum and trend continuation, allowing the system to reduce single-strategy failure risk. The algorithm continuously retrains using recent market data and applies confidence weighting before opening positions, and the visual intelligence component flags low-confidence setups for reduced sizing. The developer, Abdurahim Aras, designed Ewa specifically for MT5 and emphasizes transparent parameters and logging. Typical market conditions where Ewa performs best include trending forex and liquid commodity micro-trends, while highly erratic, low-liquidity sessions reduce effectiveness. Risk management is implemented with per-trade stop loss, equity-based maximum exposure, and time-based trade termination. Expected performance characteristics are steady but not exponential growth: realistic monthly returns target mid-single digits with drawdowns contained through adaptive sizing and dual-strategy diversification.