Convert Pine Script Strategy to MetaTrader Expert Advisor

I have a High-Frequency Trading (HFT) Expert Advisor for both MT4 and MT5 designed primarily for US30 (Dow Jones Index) . The EA performs consistently and profitably on demo accounts, but when I run it on an IC Markets Raw or Standard live account, it starts generating losses under what appear to be the same trading conditions. At this time, I cannot provide the source code (.mq4/.mq5). I can only provide the

1. Use two EMAs: 20 and 50. If EMA 20 is above EMA 50 → uptrend (look for buys) If EMA 20 is below EMA 50 → downtrend (look for sells) 2. Wait for a pullback into the area between the two EMAs. - For buys: price must touch or move between EMA 20 and EMA 50 during the last few candles. - For stils: same idea, but in a downtrend. 3. Entry signal: Buy: a bullish engulfing candle in an uptrend after the pullback

Ниже представлено готовое, технически выверенное Техническое задание (ТЗ) . Вы можете полностью скопировать этот текст и разместить его на бирже фриланса (например, MQL5.com в разделе «Фриланс» или на Smart-Lab). Данное ТЗ написано на профессиональном языке, понятном разработчикам торговых систем для терминала QUIK (на языке Lua) . ТЕХНИЧЕСКОЕ ЗАДАНИЕ (ТЗ) Разработка мультивалютного торгового робота для терминала

Start ↓ Detect Trend (H4) ↓ Confirm Structure (H1) ↓ Wait for Pullback ↓ Check Indicators ↓ Calculate Confidence Score ↓ Score ≥ 80? ├── No → Wait └── Yes ↓ Calculate Lot Size ↓ Place Order ↓ Set Stop Loss ↓ Set Take Profit ↓ Manage Trade ↓ Move to Break-even ↓ Trail Stop ↓ Close Trade. IF Price > EMA200 (H4) AND EMA50 > EMA200 (H4) AND ADX > 25 AND RSI between 55 and 70 AND MACD Main > Signal AND Bullish engulfing

HIGH-FREQUENCY M5/M15 CONCURRENT ENTRY SNIPER import time class HighFrequencySniper: def __init__(self): self.target_profit = 25.00 # Targeted Delta Move self.max_execution_time = 3600 # 1 Hour Sandbox (Seconds) self.lot_allocation = "CALIBRATED_TO_RISK" def execute_hft_scan(self, current_price, m5_rsi, m15_order_block): print(f"[SCANNING] Current Kernel Metric: ${current_price:.2f

Act as a professional Quantitative Developer and Risk Manager. I want to build a systematic trading strategy rulebook that prioritizes capital preservation and statistical edge over raw performance. Please generate a structured trading strategy using the following framework: 1. ASSET CLASS & TIMEFRAME: - Asset: [e.g., Apple (AAPL), Bitcoin (BTC), or EUR/USD] - Timeframe: [e.g., 5-minute, 1-hour, Daily] 2. CORE

Part 1: Project setup Input settings (risk, stop loss, take profit, EMA periods) Indicator initialization Trade management framework Part 2: Trading logic EMA crossover detection Buy/Sell entry rules One-trade-per-symbol check Part 3: Risk management Automatic lot size calculation Stop-loss and take-profit placement Trade execution and error handling Part 4: Final touches On-screen information Optimization

Hello, I am reopening this project with a fully updated and clarified specification. I am looking for a high‑level MQL5 developer who can deliver a clean, stable, and professional Phase 1 version of my: Institutional‑Grade Multi‑Currency MT5 EA (A2SR + SMC + Smart Recovery + Smart Grid + Liquidity + Volatility + Safety Filters) This EA is not a simple indicator conversion or a basic strategy. It is a structured