DrTrAdE™ Quant Lab
Research · Optimisation & Validation Platform
DEEPER INSIGHTS
HIGHER CONVICTION
01Backtest Configuration Configure your SweepFlow™ research run.
Initial planned 1R risk: $1,000
02Strategy Settings Choose settings in plain English. All 40 SweepFlow inputs are still available.
Set your entry, stops, trading sessions and targets below. Your backtest uses these precise settings. No optimisation boxes to worry about.
⚙ Inputs40 SweepFlow settings · tap to expand
Edit all SweepFlow settings here. In AUTO, tick any input to compare different values. Unticked inputs remain fixed.
FIXED runs use precisely the entered inputs.
10,000 combinations maximum per job. Large grids may be slow even below the safety limit.
👁 Review exactly what this backtest will use — see all settings on this page
Open to review every SweepFlow input and AUTO comparison choice, no file download needed.
03Backtest Results Run a backtest or open a saved result
Top-ranked settings from the Python optimisation
Winning AUTO settings — optimised inputs only
Ranked by Python: net R after costs, then lower drawdown, then trade count. Loading the best settings does not launch a job.
Performance Summary
Real curves require trade-by-trade results from the Python server.
Monthly P&L Calendar
Awaiting trade history
Saved Results
Equity Curve · Cumulative R
Built only from actual sequential R outcomes. No fabricated performance data.
Account Balance · Percentage Risk Model
Modelled on the chosen starting balance and fixed or compounded percentage risk. Risk % controls the monetary reporting model, not the Python engine's trade size.
Monthly Performance
| Month (New York) | Closed Trades | Modelled P&L |
|---|
Monthly P&L Heatmap
Daily P&L in New York time. Select a closed trading day to inspect its total.
Trade-by-Trade Execution Ledger
Entry and exit times are New York local time (EST/EDT automatically). Exit time is the candle timestamp recorded by Python, not a tick-by-tick broker execution time. An exit marked “(level)” is the calculated SL/TP target, not a confirmed fill.
| # | Entry (NY) | Side | Entry Price | SL | TP1 | TP2 | TP1 Hit | Exit (NY) | Exit Type | Exit Price / Level | Realised R | Modelled P&L |
|---|
All Inputs Used in This Run
Snapshot taken at submission time; includes all 40 SweepFlow parameters, date range, execution mode, optimisation axes and balance/risk model.
Saved Backtest Results
Saved snapshots currently remain in this browser (up to 24). Permanent server-side saved history is pending its Python endpoint. Original completed server job files remain untouched.
Compare Saved Backtests
Select two to four browser-saved runs. Compare real performance metrics and every SweepFlow input directly, without downloading JSON.