Turn ideas into testable strategies.

Draft the logic in natural language, attach markets and regimes, and let Quantora generate something you can simulate and refine.

1. Describe the idea

Write this like you would explain it to another trader. The AI will propose structure, filters, and risk from here.

2. Risk guardrails

These are the constraints Quantora should never violate once this runs in automation.

Draft logic (AI, beta)

In the live product, this panel will show the strategy logic that Quantora infers from your description.

IF session == "London"
  AND regime in ["Range", "Chop"]
  AND distance_from_VWAP > threshold
THEN
  fade_move(direction = mean_revert)
  size = f(volatility, win_rate, max_risk_per_trade)

Backtest shell (simulated)

This section will eventually show key stats from walk-forward tests.

Win rate 58%
Max drawdown -9.3%
Sharpe (sim) 1.4
Trades (sample) 432

All numbers here are simulated for demonstration. They do not represent live trading or actual performance.

Simulation result (simulated)

Quick summary for the last simulated run from this idea.

Net PnL +0.0%
Win rate 0%
Trades 0
Max DD 0%

Promotion

In production, you'd promote from idea → backtest → paper → live with explicit approvals.

Current: idea only Open Backtesting Lab