Documentation Index
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Shadow mode runs your strategy live against real market data — but without placing real orders. It’s the bridge between historical backtesting and live trading. You see exactly what trades the strategy would have executed in real time, with real exchange data, but no capital at risk.
What shadow mode is
Live evaluation, no orders
The strategy receives the same real-time market data your live bot would. It evaluates conditions and decides “this is when I’d buy.” But it does not actually place orders.
Records what would have happened
Every “would-have-bought” and “would-have-sold” event is recorded. After running for some time, you have a record of the strategy’s “shadow trades” — what it would have done if active.
Compares against backtest expectations
Compare shadow-mode behavior to backtest expectations. Does the shadow mirror what backtest predicted? Match = confidence; mismatch = investigation needed.
Free of slippage and fee uncertainty
Pure strategy-logic test. No real fills, no real slippage. Doesn’t capture all real-world frictions but isolates the strategy decision logic.
When to use shadow mode
✅ After backtest, before live deployment
✅ After backtest, before live deployment
Backtest validates on history. Shadow mode validates on the present. Together they’re stronger than either alone.Run shadow mode for 2-4 weeks. If shadow behavior matches backtest predictions, deploy live with small capital.
✅ When backtest isn't trustable for real-time conditions
✅ When backtest isn't trustable for real-time conditions
Some real-world conditions aren’t fully captured in backtests:
- Latency to the exchange in your specific VPS location.
- Fast-moving market behavior that historical candles don’t fully represent.
- Recent regime characteristics that backtest’s window may not cover.
✅ When you're testing a new strategy you want to validate before risking capital
✅ When you're testing a new strategy you want to validate before risking capital
A custom SignalEditor recipe with several tuning parameters. Even after walk-forward backtest validation, shadow mode in real time gives you another layer of confidence.
✅ When operator is risk-averse
✅ When operator is risk-averse
For operators who value low-risk approaches, shadow mode lets you verify a strategy’s real-time behavior over an extended period (4+ weeks) before committing any real capital.Slow but cautious. Many operators benefit from this discipline.
How to set up shadow mode
Author the strategy you want to shadow-test
Pre-built mode or SignalEditor recipe. Same as live operation.
Configure for shadow mode in the SignalEditor
For SignalEditor recipes: start the strategy with
dry_run flag enabled (or whatever shadow-mode flag the SignalEditor exposes). The strategy evaluates and logs intended actions but does not POST to webhooks.For pre-built modes: set canBuy: false on the mode. The mode will evaluate buy conditions and log “would have bought” events but won’t actually place orders.Note: canBuy: false doesn’t fully shadow — it skips the order, but tracks of what would have happened are limited. For richer shadow tracking, the SignalEditor’s dry_run is more capable.Watch the Dashboard's logs and analytics
The Dashboard surfaces “would have triggered” events. Track these against the backtest’s expectations.
Run for at least 2 weeks
Shadow mode shorter than 2 weeks may not include enough variability to be informative. 4 weeks is better.
Compare shadow behavior to backtest predictions
Does shadow mode produce trades at the same frequency backtest predicted? At similar prices? At similar conditions?If yes: the strategy’s logic transfers to live conditions. Deploy with small capital.If no: investigate the divergence before deploying any capital.
Limitations of shadow mode
Shadow vs forward-test on small capital
These are different tools for different purposes:| Shadow mode | Forward-test (small live) | |
|---|---|---|
| Capital risk | Zero | Small ($1,500–$3,000) |
| Real fills | No | Yes |
| Slippage modeling | No | Yes (real) |
| Operator emotional involvement | Low | Higher |
| Validation depth | Strategy logic | Strategy + frictions + emotions |
| Time investment | 2-4 weeks | 2-4 weeks |
| Use when | Logic uncertainty | Logic confident, want full validation |
Common mistakes with shadow mode
❌ Running too short
❌ Running too short
Shadow for 3 days, see good results, deploy live. The 3 days happen to be in a regime that’s particularly suited to your strategy. Live deployment runs into a different regime and underperforms.Fix: minimum 2 weeks of shadow; ideally 4 weeks. Multiple regime characters need to be experienced.
❌ Confusing shadow mode with live
❌ Confusing shadow mode with live
Operators sometimes forget shadow mode is shadow — they look at “would have bought” P&L and treat it as if it were realized.Fix: clearly label shadow vs live in your operator records. Shadow P&L is hypothetical; live P&L is real.
❌ Not comparing shadow to backtest
❌ Not comparing shadow to backtest
Running shadow mode but never explicitly comparing to backtest expectations. Missing the diagnostic value.Fix: explicitly: “Backtest predicted 8 trades/week, shadow showed 6. That’s roughly aligned. Backtest predicted 12 trades/week, shadow showed 2. That’s a substantial divergence — investigate before live.”
❌ Shadowing for 4 weeks then skipping forward-test
❌ Shadowing for 4 weeks then skipping forward-test
Shadow validates strategy logic. It doesn’t validate strategy + frictions + operator emotion. The forward-test step is still needed.Fix: shadow → small-capital forward-test → full deployment. Don’t skip forward-test even after extensive shadow.
Best practices
What’s next
Why backtest
The fundamentals.
Reading results
Interpreting backtest output.
Walk-forward
Catching curve-fitting before deployment.
Common mistakes
Pitfalls to avoid in your validation pipeline.