From Investor
to System Builder

My relationship with markets started the way it does for most — manually. I spent years studying price action, developing intuition for how different instruments behave, and building a disciplined approach to position sizing and risk. I was a long-term investor first, someone who understood that patience and consistency matter far more than trying to time every move.

Over time I became fascinated by the systematic side of trading — the idea that a well-constructed, rules-based strategy could remove the emotional variability that makes discretionary trading so difficult to sustain at scale. I started reading everything I could find on algorithmic system development, studying the work of developers I respected and learning how the best systematic traders approached the craft.

I invested significant time studying under some of the most rigorous systematic trading developers I could find. Not just the mechanics of coding EAs, but the principles behind building strategies that are genuinely robust — approaches that hold up in live markets and not just in backtests. This is where most aspiring algo traders go wrong: they optimise for the past instead of building for the future.

What became clear to me through this process was that the difference between a strategy that works and one that fails in live conditions almost always comes down to how it was developed — specifically, whether it was built to be robust or built to look good on paper. That insight shaped everything I went on to build.

I made a deliberate choice early on to build exclusively on pure price action — no indicators, no lagging signals, no complexity for its own sake. Indicators are derived from price; they don't contain information that isn't already in the raw chart. They also introduce additional parameters, and every additional parameter is an additional opportunity to overfit a strategy to historical noise rather than genuine market structure.

My systems are built on what price actually does: support and resistance, breakout behaviour, momentum structure, and the behavioural patterns that recur across markets and timeframes because they are driven by human psychology and institutional activity rather than market-specific anomalies that disappear as soon as they are exploited.

Every strategy I develop goes through rigorous in-sample and out-of-sample validation. The in-sample data is used exclusively for strategy development — the out-of-sample data is kept completely untouched until the strategy is fully defined and ready to be tested blind. If a strategy degrades significantly on out-of-sample data, it is discarded. No exceptions.

I use Monte Carlo simulations to stress-test each strategy across thousands of randomised variations of trade order, slight parameter perturbations, and synthetic market conditions. A strategy that only works in a very specific historical sequence of trades is not a strategy — it is a coincidence. Monte Carlo stress testing separates the two.

Finally, I run correlation analysis across all systems before combining them into a portfolio. The goal is to ensure that individual strategy drawdown periods do not coincide — that when one system is experiencing a difficult period, the others are providing a counterbalance. This is what genuine portfolio diversification looks like at the strategy level.

What started as a hobby — building systems for my own portfolio in the evenings — gradually produced results that genuinely surprised me. Not in a single backtest, but in live performance. Systems running on my own accounts, trading my own capital, consistently outperforming the manual approach I had spent years refining.

That performance, combined with requests from traders in my network who had seen the results, led me to a decision: if these systems are strong enough for my own capital, they are strong enough to share. XYZ Capital is the result of that decision — an honest effort to make genuinely robust, long-term focused automated trading systems available to serious traders, while continuing to run them within my own portfolio alongside every client who uses them.

I have no interest in selling systems I don't run myself. Every EA available through XYZ Capital is active on my own live accounts. That alignment matters to me, and I think it should matter to you too.