Services Quantitative Research & Trading Systems

Quantitative Research & Trading Systems

Systematic strategies that survive out-of-sample - and live capital.

I research, build, and deploy systematic trading strategies end to end - signal research through execution and live monitoring - for options and crypto markets.

Who this is for

  • Prop trading desks and hedge funds that need a researcher who owns the full stack - signal, backtest, execution, deployment
  • Family offices wanting a systematic overlay run with discipline
  • Crypto trading firms building HFT / MFT execution and microstructure infrastructure

Problems this solves

  • Strategies look great in-sample and fall apart the moment real capital is at risk
  • Backtests that ignore slippage, latency, and regime change - so live never matches paper
  • Research notebooks that never become a monitored, deployable live system
  • No honest way to tell whether an edge has quietly stopped working

What I do

Signal Research

Factor identification, statistical-significance and multiple-comparison testing, information-coefficient analysis

Execution-Aware Backtesting

Walk-forward analysis with regime splits, slippage and latency modeling, position sizing, and documented failure modes

Volatility & Microstructure

IV surfaces, skew, regime classification; order-flow and liquidity analysis for high-frequency markets

Live Deployment & Monitoring

Paper → small size → full allocation, with drift and regime monitoring so you know when an edge decays

Deliverables

  • An execution-aware backtesting framework you own, with walk-forward and regime testing built in
  • A documented strategy with its assumptions, edge, and failure modes written down
  • A monitored live-deployment path from paper trading to full allocation
  • Risk and execution logic your team can run without me

How we'd work together

Diagnostic review (1–2 weeks)

Strategy and methodology audit - overfitting review, validation design, and an honest read on whether the edge is real.

Research sprint (4–8 weeks)

Focused signal research or an execution-aware backtesting framework built to your markets.

Full build (2–6 months)

Research through live deployment, with monitoring and a clean handoff to your team.

Example outcomes

Built and ran live systematic index-options strategies on real capital at Mastertrust

Now researching crypto HFT market-making and index-options MFT execution at NK Securities

Backtesting frameworks with walk-forward validation, regime splits, and slippage modeling that hold up live

Tools & methods

Python NumPy Pandas PyTorch XGBoost C++ / Rust (latency) PostgreSQL Redis

Related case studies

Have a problem worth solving?

Whether you need a quantitative researcher, a Machine Learning systems builder, or a technical advisor, I take a small number of consulting engagements at a time.

Book a call →