Set up the desktop, sign in, connect a supported account, and open your first workspace.
8 min readClarity before complexity.
Learn the workflows, architecture, and research model behind QuantStation—without trading mythology or hidden assumptions.
Start with the workflow.
Create a strategy project, validate typed properties, and queue a first regular backtest.
12 min readImport compatible reports, compare runs, and interpret drawdown and concentration.
10 min readUnderstand local storage, isolated workers, trusted services, and live execution intent.
7 min readUse SDK references, scaffolding, and platform-porting guidance from an AI coding client.
9 min readSeparate exploration, out-of-sample evidence, stress testing, and the final trading decision.
11 min readBuilt on serious tools.
QuantStation connects a React workspace to a trusted Rust host, isolated Python research workers, and the NautilusTrader runtime.
Direct answers.
What is QuantStation?+
A native desktop workstation for systematic trading research, execution context, performance analysis, and deliberate review.
Can I build in Python and Rust?+
Yes. Research projects can contain Python and native Rust implementations. Persistent paper and broker-live strategy sessions are currently Python-only.
Where does my private work live?+
Journals, notes, playbooks, attachments, and AI history begin in a private local store. Eligible plans can add owner-scoped remote sync.
Does a backtest predict future returns?+
No. Backtests, optimization, Monte Carlo, and simulations are research evidence—not guarantees of future performance.
Which plan do I need for live trading?+
The current product gate opens the Trading workspace at Pro and above. Contact us before launch for final plan and purchase details.
Does QuantStation hold broker credentials?+
The React interface does not. Credential handling, authenticated I/O, and broker actions are owned by trusted Rust and server-side layers.