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Automated Trading-System Engineering

Independent work on market-data and broker integrations, and the reliability questions that arise when software interacts with external systems.

Independent researchEngineering experiments and research
  • Python
  • Data workflows
  • Broker APIs
  • Research orchestration
SYSTEM OVERVIEW CONCEPTUAL
  1. 01Market data
  2. 02Data validation
  3. 03Research
  4. 04Backtesting
  5. 05Risk evaluation
  6. 06Decision / audit
A generalized engineering model; not an exact production deployment.

Why I started it

This is my independent automated trading-system engineering project. I use it to work on software that receives changing external data and interacts with broker APIs. That gives me a different setting for questions I know from production engineering: how current is the input, which state can I trust, and what should happen when a dependency stops responding?

The work and the decisions

My work spans market-data ingestion, broker API integration, and comparing WebSocket delivery with REST. I have also worked on questions around stale data, system state and recovery, operational monitoring, deployment reliability, controlled execution, safeguards, and testing.

The project remains experimental. My focus is on the integration work and the failure questions around it.

Freshness is one of the decisions I want to make explicit. Receiving a response and having current information are different things. Streaming and request-based delivery also create different failure questions: a quiet connection, a delayed response, or an interrupted request each needs interpretation. I do not treat the choice of transport as a complete reliability solution.

State, recovery, and external actions

The difficult boundary is between what my software believes and what an external service has done. An interrupted request can leave an uncertain outcome. That makes state handling, recovery, and execution controls subjects for deliberate validation, rather than features I can infer from a diagram.

The diagram above is a conceptual model of the responsibilities, rather than a deployment diagram.

Current work

I am working through data freshness, state, recovery, and controlled execution as separate engineering questions. The next step is to make the behavior under failure easier to test and explain.

I keep strategy discovery and evaluation in a separate research track. Generating a candidate or completing a backtest does not establish operational readiness. The distinction matters to me: external data, research output, and permission to act have different responsibilities.