Multi-Symbol Parameter Optimization - Test Your Strategy Across All Markets at Once
Your strategy's stop loss works great on Gold — but how does it hold up on Bitcoin? Will the same take-profit target that nails EURUSD also work for GBPJPY? Until now, you had to guess, or run separate workflows for every symbol and stitch the results together manually.
One Sweep, Multiple Symbols
The Parameter Loop worker doesn't care what symbols your strategy trades. Connect a multi-symbol data fetcher and your strategy runs exactly the same way for every asset — but the Parameter Loop adds a second dimension: it also sweeps the parameters.
The result is a 3D optimization grid:
Symbol × Stop Loss × Take Profit = Total Iterations
3 × 5 × 5 = 75
Every combination runs automatically. The best parameter set for XAUUSD might be different from the best set for BTCUSD — and the results table shows you both.
Workflow: Multi-Symbol Risk Optimization
[Trigger] → [Fetch Prices (XAUUSD, BTCUSD, EURUSD)] → [Swing Finder] → [Backtest] → [Parameter Loop]
Step 1: Fetch Multi-Symbol Data
Your Fetch Prices worker pulls OHLC data for all three symbols:
{
"symbols": ["XAUUSD", "BTCUSD", "EURUSD"],
"timeframe": "1h",
"limit": 2000
}
The Swing Finder detects swing points across all three independently. The Backtest evaluates each symbol's signals separately and returns combined statistics.
Step 2: Configure the Sweep
In the Parameter Loop's two-column dialog, set up the grid:
Sweep parameters:
[
{"name": "stop_loss", "values": [1.0, 2.0, 3.0, 4.0, 5.0]},
{"name": "take_profit", "values": [2.0, 3.0, 4.0, 5.0, 6.0]}
]
Ranking: Collect result.sharpe_ratio, rank by max.
Step 3: Read the Results
The results table shows every combination for every symbol. You can instantly see:
| Iteration | p.stop_loss | p.take_profit | r.sharpe_ratio | r.total_return | r.max_drawdown |
|---|---|---|---|---|---|
| 12 | 3.0 | 4.0 | 1.92 | +28.4% | -5.8% |
| 37 | 2.0 | 3.0 | 1.45 | +18.2% | -8.3% |
| 55 | 4.0 | 5.0 | 1.21 | +15.1% | -11.2% |
The best combination works across all three symbols — not just one. This is portfolio-level optimization in a single click.
When to Use Multi-Symbol Sweeps
| Scenario | Why It Works |
|---|---|
| Portfolio strategy | Find parameters that balance risk across all assets |
| Cross-market validation | If parameters only work on one symbol, they're overfitted |
| Volatility regime testing | See which symbol needs tighter SL vs wider TP |
| Strategy generalization | Build strategies that adapt to any market, not just one |
Live Production: Auto-Deploy Per-Symbol Parameters
Save the sweep results as a session, then set the Backtest's Production Mode to use_best. On every scheduled run, the optimized parameters load automatically — no re-sweep needed.
The takeaway: One workflow, one sweep, unlimited symbols. Stop guessing which parameters work where — let the Parameter Loop find out.