Designing Modular Trading Infrastructure with Risk and Reliability Layers
Summary
The article outlines a proposed end-to-end system for researching, backtesting, and operating automated trades, initially focused on US equities and ETFs through a brokerage interface. Its architecture separates data ingestion and validation, price and trading records, signal generation, portfolio and order management, risk controls, brokerage connectivity, execution, and accounting. Signals serve as recommendations; an order-management system consults a risk layer that can modify or reject orders based on constraints such as leverage, sector exposure, margin, and trading volume.
The design also treats operational reliability as part of trading infrastructure. It calls for scheduling, monitoring, logging, backups, version control, automated tests, deployment practices, and remote hosting. These are design goals for a future article series, rather than demonstrated system results. The author emphasizes that automation cannot remove all human oversight, particularly around data quality, and that reproducible results depend on consistent processed data and random seeds. The proposed system begins with one asset class to limit complexity, with cross-asset support as a later aim.
Key ideas
- Separate data services, signal generation, order management, risk controls, brokerage connectivity, execution, and accounting into modular components.
- Treat trading signals as recommendations that pass through portfolio and risk checks before orders are constructed.
- Validate incoming data and retain historical trading and configuration records for research and operations.
- Build reliability practices such as monitoring, logging, backups, testing, and deployment into the system design.
- Automation still requires human attention to issues such as questionable input data.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.