Everything you need to trade systematic ideas with context.
Charting, strategy research, execution, performance analysis, and deliberate review—connected inside one native workstation.
Turn strategy logic into repeatable research.
Create versioned Python and native Rust projects with typed properties, local datasets, and isolated validation. The Quant MCP authoring companion helps with SDK reference, scaffolding, and platform-porting guidance.
- Python and native Rust
- Typed property schemas
- Local Bars, L1, L2, and L3 datasets
- Isolated validation
Find evidence that survives the next question.
Run regular backtests, out-of-sample walk-forward optimization, and multi-objective optimization with bounded parallel workers. Compare every result through the same reporting model.
- Regular backtests
- Walk-forward optimization
- Multi-objective Pareto research
- CPU and supported GPU acceleration
Read the market. Control the action.
Connect supported accounts, stream market context, and work across single, split, or four-chart layouts. Inspect orders, fills, positions, and effective risk rules without leaving the workstation.
- Historical and live charts
- Persistent studies and drawings
- Smart orders, alerts, and hotkeys
- Confirmed flatten and cancel controls
Find the runs worth trusting.
Load reports recursively, compare statistics, settings, trades, and equity curves, and inspect quality, drawdown, recovery, and concentration before the next decision.
- Portfolio and concentration analysis
- Trade and period inspection
- Monte Carlo stress testing
- Journal, notebook, and playbooks