I build systematic trading technology from first principles.
My work is about engineering precision systems where finance, code, and probability converge.
I treat markets as complex adaptive systems. The challenge — and obsession — is to distill that complexity into structure: signals, models, and execution engines that can run at scale without relying on guesswork or gut feel.
- Strategy Engineering: Translating ideas into executable code, from hypothesis → backtest → live system.
- Infrastructure: Building robust pipelines for data ingestion, signal generation, execution, and risk management.
- Research: Studying market microstructure, statistical edges, and alternative data sources.
- Automation: Eliminating latency, human error, and inefficiency with systems that operate reliably under pressure.
- Languages: Python for research, C++/Rust for speed, Go for infrastructure.
- Data: Time-series modeling, stochastic processes, high-frequency tick data, event-driven streams.
- Systems: Broker/FIX APIs, cloud-based backtesting, execution frameworks, risk overlays.
- Approach: Scientific rigor (hypothesis → experiment → falsify → refine), no shortcuts, no black boxes.
Markets punish certainty. The only edge is adaptability, discipline, and the ability to keep questioning your own models.
I don’t believe in “set and forget.” Every system is a living thing — it must evolve as markets evolve. The job isn’t to predict the future but to build tools that can survive it.
- Twitter/X: @rootquant
- Open to collaboration on ambitious trading tech — not toys, but serious systems.
- Outside markets: I study philosophy, systems theory, and technology — anything that sharpens the lens through which I build.
