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Skip the grind and grab 9 custom-built USDJPY trading projects for StrategyQuant — 3 each for H1, H4, and D1 timeframes. I personally built and tested these to save you time and help you get real results faster. Whether you’re running prop firm challenges or just refining your algo game, these are solid, proven blueprints…
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I’m giving away 9 custom-built GBPUSD algo trading projects for StrategyQuant — 3 each for H1, H4, and D1 timeframes. These are not random builds — I’ve tested, filtered, and battle-hardened each one myself. Whether you’re just getting started or want to level up your portfolio, these projects are your launchpad. Download them, plug them…
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This custom EURUSD StrategyQuant X project is built for the Daily (D1) chart and uses Volatility-based building blocks to target high-probability counter-trend setups. With trade durations designed to ride out market swings, this strategy allows positions to remain open over weekends and adapts Stop Loss and Take Profit levels from 100 to 800 pips. Lower…
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Discover a high-performance EURUSD H4 custom project built in StrategyQuant X using counter-trend logic. This strategy is designed to catch profitable pullbacks on the H4 chart while allowing trades to stay open over weekends for bigger swings. Built on IC Markets data (2009–2015), it includes thorough robustness testing on multiple timeframes and markets, including USDJPY…
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In this blog, I’ll walk you through a custom StrategyQuant X project built specifically for EURUSD on the H1 timeframe. This system uses a mean reversion logic in the Builder phase, tested on IC Markets data from 2009–2015 with solid In Sample and Out of Sample periods. It’s structured for adaptability, and you can easily…
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In StrategyQuant X, three key building blocks—Bar & Time, Price, and Operators—form the foundation of any automated trading strategy. Time settings like “Bar Hour” and “Current Day” help align trades with market behavior. Price data like “Close,” “Daily High,” or “Heiken Ashi Open” provide the essential data points. Operators like “Crosses Above,” “Is Rising,” and…
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Retesting your strategy on other markets, timeframes, and slippage levels is essential for building robust trading systems in StrategyQuant. This guide covers how to expand testing across correlated instruments like NAS100 and S&P500, how to shift between timeframes like M30, H1, and H4, and how to simulate realistic and high-slippage conditions for Forex, CFDs, and…
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If you’re running trading algorithms or automated strategies, using a VPS (Virtual Private Server) is a game changer. It keeps your system running 24/7 without interruptions, even when your home internet or power goes down. With ultra-fast execution speeds, reliable uptime, and enhanced security, a VPS gives traders the edge they need in today’s markets.…
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Training algorithmic strategies on CFDs like oil, gold, and indices can give traders a real edge in prop firm challenges. In this guide, we break down how to structure your training and validation periods for CFD products such as USOIL.cash, XAUUSD, and US100.cash. Learn how to apply robust filters like Profit Factor, Return-to-Drawdown, and trade…
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When developing Forex strategies for prop firm challenges, backtesting with both In-Sample and Out-of-Sample (OOS) data is essential to avoid overfitting. Using tools like StrategyQuant, ensure your strategy trains on data from multiple periods, such as 2009–2022, and validates on OOS data like 2018–2022. Test your strategy on recent market conditions as well as older…
