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Roadmap for a Low-Latency Trading Backtester and Live Trading System

Article Stratmill research code

Summary

This roadmap outlines development work for a quantitative trading toolkit spanning Python reporting, Rust backtesting, live trading, exchange connectors, orchestration, and examples. Its backtesting topics include Level 3 order-book simulation, combining data feeds with different update rates and depth, adjusting latency for collection location, queue-position modeling, market-depth processing, fee models, and order modification. It also identifies planned data formats and latency controls.

The live system section covers bot connectivity, exchange support, and separating market data from order management. Example strategies include market making with time-series models, statistical arbitrage, optimal execution, and queue-position methods. Completed and planned items are marked, giving readers a snapshot of project scope rather than validated performance evidence. The roadmap does not report benchmark results or explain implementation details, and its status may change over time.

Key ideas

  • The project roadmap describes order-book-aware backtesting with Level 3 data and queue-position considerations.
  • It highlights feed fusion and latency adjustment as ways to model market data and execution conditions.
  • The planned system includes fee models, order modification, and additional exchange connectors.
  • Listed market-making examples draw on statistical models, arbitrage, execution, and queue position.
  • The roadmap records development status but provides no performance evaluation.

Tags

BacktestingHigh-frequency tradingMarket microstructureExecutionMarket making

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.