Simple opposite trade copy EA

I need a fully automated trading robot designed to generate consistent profits while strictly controlling risk and minimizing losses. The robot should use a combination of strategies, including trend-following, scalping, and price action, and must be able to adapt to different market conditions such as trending and ranging markets. It should analyze the market using indicators like Moving Averages, RSI, MACD, and

1. IF price forms: - Higher highs + higher lows → TREND = BUY - Lower highs + lower lows → TREND = SELL ELSE → NO TRADE 2. IF: - Trend = BUY - Price retraces to support zone - Bullish engulfing candle forms - TDI green crosses above red (optional) THEN: - Execute BUY 3. IF: - Trend = SELL - Price retraces to resistance - Bearish engulfing forms - TDI confirms THEN: - Execute SELL 4. Risk per trade = 1% of account Lot

Project Overview ​I am looking for a high-level Algorithmic Trader / Developer to build a sophisticated, fully automated scalping system for the Nasdaq-100 Future (NQ) . The system must integrate institutional order flow logic with market structure analysis. ​The core logic must be written in Python , acting as a central hub that bridges ATAS (as the primary data source for Order Flow) and MetaTrader 5 (as the

I am looking for an experienced quantitative developer to analyze and optimize an MT5 Expert Advisor that I have already developed. The EA is relatively complex and includes: Multiple strategies (Trend Pullback, Breakout, Mean Reversion, EMA Reclaim) Scoring system combining technical score and probabilistic filter Regime detection (ADX based) Volatility filters (ATR regime) Correlation and cluster exposure control

Title: Design and Development of an Automated Forex Trading Robot Using MQL5 and Machine Learning Techniques Abstract: This project focuses on the design and development of an automated Forex trading robot that integrates MQL5 programming and machine learning techniques. The system aims to predict market movements and execute trades automatically, minimizing human error and emotional trading. By leveraging historical