Telegram to MT4: source code (.mq4) to be converted to MT5 (.mq5)

I need an Expert Advisor for MT5 on XAUUSD 1min timeframe using SMC concepts. STRATEGY RULES: SELL: 1. Identify previous day High/Low as liquidity 2. Entry only during London-NY session: 15:00-19:00 GMT+3 3. If price sweeps previous day High and closes back below it 4. Check for bearish 1min FVG below sweep candle 5. Wait for BOS - lower low 6. Entry: Sell at 50% of the FVG 7. SL: 10 pips above sweep wick 8. TP: 2R

Hello looking for someone to convert an indicator from tradingview to Thinkorswim I have attached the codes from trading view Also, I like make it trigger (alert) a one-time alert when the trend changes, and can also create a custom watchlist column that flags symbols currently in a new trend so you can scan multiple stocks easily. And like the watchlist to show only fresh trend changes or the current trend direction

I want to build a fundamental news trading bot that trade off economic news data, as we know every economic news data released always have effect on the asset associated with it, so this bot will take a trade instantly based on the news data released either to buy or sell, it will come with good money management and also SL and TP target based on price and pips value

I have a EA/indicator that I want built. I should say 1st off dont know how to code myself so I will be using AI to verify that the source code is complete and matches the documents spec or if better so if you can not truly do the job do not waste either of out time. This is a idea I came.up wit and used AI to produce a framework for it.... and of course AI isn't 100% accurate so I need a knowledgeable quantitative

Specification : 1. Goal I am commissioning a mean-reversion grid Expert Advisor for XAUUSD on MT5. The deliverable is the complete, commented .mq5 source (strictly personal usel). Offers limited to compiled .ex5 will not be considered. 2. Required framework (non-negotiable) 2.1. Works natively on M5; signals evaluated on closed bars; symmetric long/short. 2.2. Entry logic built on Bollinger Bands + Moving Average

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

I am looking for an experienced MQL5 developer to create a fully automated Expert Advisor (EA) for MetaTrader 5 based on a Price Action strategy. The bot needs to automatically identify specific candlestick formations and market structure levels, execute trades, and manage risk using a dynamic trailing stop.The EA should monitor the chart for the following price action setup:Market Structure / Trend Filter:The bot

I am looking for an experienced MQL5 developer to build a high-frequency (HFT) latency arbitrage Expert Advisor for Pepperstone MT5 , using LMAX as the leading price feed. The initial focus will be on US30 (Dow Jones) , and if the strategy proves successful, I want the EA to be easily expandable to additional symbols such as NAS100, GER40, XAUUSD, major forex pairs, and other supported instruments. The EA should

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