Building a Production Quant Trading System

Most writing about quant trading is about finding edges. This book is about the unglamorous 90% that decides whether a trading idea survives contact with a live market: proving the edge is real, wiring it to a broker without lying to yourself, sizing it so a bad month does not end you, and running it as a process that survives restarts, data outages and your own future mistakes.

It is built around a single real, sanitised system, a multi-strategy, broker-connected book called Titan, used as the running case study. Titan is opinionated and battle-scarred: it has shipped look-ahead bugs, mis-sized a position by a third on a currency assumption, crash-looped on its own data-quality gate, and had an entire quarter of "validated" results thrown out because the methodology underneath them could not be trusted. Those scars are the point. You will learn more from why each guardrail exists than from any clean architecture diagram.

What the book works through:

• Foundations - the architecture, stack choices and project layout that survive live markets
• Research and validation - deflated Sharpe ratios, walk-forward that is genuinely out-of-sample, a catalogue of the ways a backtest lies, and a decision matrix for when a strategy is ready
• Data - sourcing, storage, and the quality gate that keeps bad ticks out of research
• Research to production - broker realities and a typed contract that keeps live behaviour identical to the backtest
• Portfolio and risk - position sizing via a modified Kelly criterion, a correlation-aware allocator, and a layered safety system with a real kill switch
• Deploy and operations - containerisation, the paper-to-live transition, and a runbook for incidents at 3am

This is a guide to the engineering and methodology of a production systematic-trading stack. It is not a source of alpha: specific parameters, instrument lists and live performance are deliberately omitted or clearly labelled as illustrative. The value is the process, which is exactly what is safe to share. It is educational material, not investment advice.

Written by Dr. Rayan Azhari, who has followed the markets for fifteen years and built the system he wanted to read about. A sanitised, runnable companion framework on GitHub holds the validation, risk and metrics modules the chapters describe.