Systematic GBPUSD Research
Research trading ideas with data, Python and a repeatable process, not signals or predictions.
GBPUSD Research helps experienced traders define, backtest, validate and stress-test GBPUSD trading ideas using a practical, evidence-based methodology. Built on a background in Computer Science, financial markets, high-frequency trading software engineering and a PhD in Computer Science, the approach applies research and systems-engineering principles to trading.
Free Guide
The GU Systematic Research Framework
Learn the practical process for turning a GBPUSD trading idea into testable research.Learn how to develop a hypothesis, define objective rules, avoid look-ahead bias and overfitting, and evaluate results using expectancy, profit factor, Sharpe, Sortino and drawdown. A practical starting point for replacing assumptions with a structured GBPUSD research process.
Masterclass
Practical GBPUSD Systematic Research
Turn trading ideas into structured experiments using Python, backtesting and statistical analysis.Learn how to specify, test, evaluate and stress-test GBPUSD trading ideas using practical Python research notebooks. Work through historical testing, performance analysis, out-of-sample testing, robustness checks and research documentation—so you understand not just what your backtest shows, but whether the evidence deserves to be trusted.
1-to-1 Private
GBPUSD Research Intensive
Private research support for traders who want to rigorously test their own ideas.Bring your trading hypothesis, strategy, backtest, Python notebook or research problem. We examine your methodology, data and results, then investigate performance, drawdown, parameter sensitivity and robustness using appropriate research techniques. Leave with a clearer research specification, stronger evidence and a practical roadmap for further testing and validation.