Upgrade existing indicator

I am looking for an experienced MQL4/MQL5 HFT developer to build or optimize a High-Frequency Trading (HFT) Expert Advisor that can successfully pass proprietary trading firm challenges and perform consistently under live trading conditions with brokers such as 8cap or BlackBull Markets . The developer should have proven experience with HFT execution, ultra-low-latency trading, broker execution, slippage, spreads

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

Version document : 1.0 Plateforme : TradingView Langage : Pine Script v6 Type : Indicateur d'analyse et d'aide à la décision (non-exécutant) 1. Présentation du projet Nom du produit ONYX SR V2 — Intelligent Support & Resistance Scalping System Objectif Créer un indicateur TradingView capable d'identifier automatiquement des opportunités de scalping basées sur : supports et résistances dynamiques ; action du prix ;

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