Trading infrastructure
Quant
A trading system, from the tick up.
An async feed handler with auto-reconnect, an in-memory order book reconstructor, a lakehouse that rolls ticks into OHLCV candles in Parquet and DuckDB, NumPy-vectorized indicators written without a TA library, and a pluggable strategy engine that emits strict entry and exit signals.
Signals are replayed second by second in an event-driven backtester, with latency and slippage injected by a market simulator, checked by a risk gate (position sizing, stop-loss, max drawdown), routed to a live exchange or paper trading, measured (Sharpe, Sortino, profit factor) and logged to a millisecond audit trail — all monitored from a real-time web terminal.
- Repositories
- 12
- Lines
- 15,497
- Commits
- 216
- Test files
- 58
- Built
- Jun 2026 – Jul 2026
- Mostly
- Python
L1 Market data
L2 Analytics
L3 Backtest & execution
L4 Risk & audit
↳ Flagship
↳ Flagship
Where it all comes together
L1
Market data
L2
Analytics
L3
Backtest & execution
L4