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Tune protection parameters and review lock behavior
Assess whether cooldown/stoploss protection improves risk metrics rather than just reducing trades.
Goal
Goal: Assess whether cooldown/stoploss protection improves risk metrics rather than just reducing trades.
Steps
- Confirm
space="protection"parameters and select the protection. [hyperopt] - Run
freqtrade hyperopt --spaces protection ...on the same data. [hyperopt] - Backtest held-out data with
--enable-protections; report locks, drawdown, and trades. [hyperopt]
How to verify
Protection is explicitly enabled, tuned on development data, and reviewed out-of-sample.
Troubleshooting
If nothing changes, verify the enable flag, parameter space, and strategy compatibility.
Permissions
Prerequisites
- Python 3.11+, Freqtrade installed, a pinned strategy, and a local user-data directory.
Permissions
- Use public market data and local history; treat every trading decision as research and never connect a live account.
Limitations
Compare risk and return metrics with protections enabled and disabled, and validate tuned values on a separate time range.
Pinned upstream source
- Repository
- freqtrade/freqtrade
- File path
- docs/hyperopt.md
- Pinned commit
82e4c9604c51523f7e05c5a297167cf2b13a2129- Source checked
- 2026-10-14 · Reviewed against the pinned upstream source
Repository metrics
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License: GPLv3
Main topic
Build a reproducible crypto research workflow