Built for researchers who ship
Manifold-BT started from a simple frustration: existing backtesting tools force you to choose between speed and correctness. That's a false trade-off, so we wrote the engine in Rust and wrapped it in Python.
Why this exists
Most backtesting frameworks were designed when a year of daily bars was a "large" dataset. They work fine for prototyping, until you need realistic execution modeling, sub-minute resolution, or parameter sweeps across thousands of combinations.
At that point, Python-native frameworks hit a wall. You start cutting corners: skip the walk-forward, assume zero slippage, test fewer parameters. Research quality suffers.
Manifold-BT takes a different approach. The core engine is Rust, operating on Apache Arrow columnar arrays with zero-copy semantics. Indicators, simulation, and metrics run with sub-second single-shot backtests and 552K-combo sweeps in seconds.
But speed alone isn't the point. The real value is what speed enables: running a full walk-forward on every idea, testing execution assumptions properly, and never skipping the robustness checks because they "take too long."
Design principles
Correctness first
execution realismEvery fill, every fee, every funding payment is modeled explicitly. We'd rather surface an uncomfortable result than hide it behind optimistic assumptions.
Speed enables rigor
552K combos in secondsWhen a full walk-forward takes seconds instead of hours, you actually run it. Performance isn't a feature, it's what makes good research habits practical.
Reproducibility by default
deterministic replayManifests pin data versions, parameters, and engine builds. Every result can be replayed exactly, months or years later.
Python where it matters
zero frictionSignal logic, analysis, and visualization stay in Python. The heavy lifting happens in Rust, invisible to the researcher. No context-switching required.
Stack
The engine is structured as a Rust workspace exposed to Python via PyO3. Key dependencies are chosen for correctness and performance, not novelty.
Open source at the core
The engine, indicators, and simulation logic are open source. Pro features add convenience, the core research capability is free.