Algorithmic trading · AI systems
I build the AI that builds trading strategies.
Nearly two decades designing systematic strategies — and the last few months building a framework of AI agents that build them for me. You describe a strategy in one sentence; a purpose-built agent writes it, then proves it by loading it into a live StrategyQuant.
Try it as a sentence · "long when EMA(20) crosses above EMA(50), 30-pip stop"
The frontier of my work
A framework for agentic strategy development
Most of algorithmic trading is still done by hand: wire an indicator, drag a block, run a search, finish the scaffold yourself. Over the past few months I've been building the layer above that — a suite of Claude Code agents and skills that turn plain English into real StrategyQuant artifacts, and a live oracle that verifies every one of them against a running platform before it counts.
The principle is simple: an AI can propose, but nothing is trusted until StrategyQuant itself accepts it. Generation is cheap; verification is everything.
One sentence
A plain-English trading idea — the entry, the exit, the intent.
sqx-builder
A Sonnet agent resolves every atom against your install and writes a finished strategy.
Live SQX load
The .sqx is loaded into a running StrategyQuant over REST. LOAD PASS = accepted.
Graded & graduated
A whole population is grid-tested and judged on DSR + PBO — graduate, revise, or kill.
The skill suite — natural language in, import-ready artifact out
Strategy Builder
"make me a strategy that trades a session breakout with an ATR trail"
A finished, ready-to-backtest .sqx — every rule and parameter concrete. A finished strategy, not a template with holes. Driven by the sqx-builder agent.
Custom Block Builder
"a trailing stop two ATRs under the Hull moving average"
A validated, import-ready AlgoWizard custom block, built from the indicators your own StrategyQuant install actually has.
Strategy Template Builder
"breakouts only in the trend direction, session-gated"
A ready-to-import builder template — the scaffold the SQX builder fills as it searches — with a real, falsifiable entry thesis.
Random Group Builder
"a Value group of EMA, KAMA and ATR periods"
A ready-to-import random group — the curated menu the builder draws one item from per strategy to fill a slot.
The strategy oracle
The piece I'm proudest of. Every strategy the agent builds is loaded into a running StrategyQuant X over its REST API — the platform parses the strategy and either accepts or rejects it. A LOAD PASS is proof, not a promise: bad atoms and unproven shapes get caught here, before you ever waste a backtest on them.
It's now growing from a load oracle into a trade oracle — driving StrategyQuant's retester headlessly to read back real trades and statistics, no clicking required.
The Template Factory
The next layer ties it all together: take a trading hypothesis, have the skills author the template and its groups, oracle-check that it loads, run a grid of ~10,000 strategies across instruments, and judge the whole population on out-of-sample statistics — Deflated Sharpe and the Probability of Backtest Overfitting. A template earns a verdict: graduate, revise, or kill. Judged as a population, never by its best offspring.
hypothesis → author → oracle → 10k-strategy grid → DSR + PBO gate → graduate / revise / kill
The rest of the toolkit
Everything else I do
The agentic work sits on nearly two decades of hands-on systematic trading. The fundamentals are still the service.
Custom Indicators & Blocks
Bespoke indicators, signals and building blocks for StrategyQuant. 135 already published →
Strategy Development
Idea to live system — generation, robustness testing, walk-forward and deployment, with anti-overfitting rigor throughout.
Robustness Audits
An independent second opinion on a strategy before you risk capital — Monte Carlo, edge-ratio, walk-forward, PBO/DSR.
Machine Learning for Trading
Predictive models, feature engineering and regime classification — with the discipline to know when ML actually helps.
Automation & Tooling
Custom databank columns, Monte Carlo methods, and Python automation around StrategyQuant — sqcli pipelines and batch research.
Consulting & Mentoring
Hands-on guidance for traders, quants and teams — strategy design, system architecture, and research process.
Let's build something that holds up.
Whether it's a custom block, a full strategy, an AI workflow around StrategyQuant, or an honest second opinion — tell me what you're working on.
Get in touch