Syntalium Wiki
Risk Management in Crypto: Institutional Controls
TL;DR
Durable performance starts with controlled downside. Define hard limits before execution and enforce them consistently.
Clear explanation
Crypto moves faster than discretionary reaction speed, so risk rules must be explicit and pre-committed.
Core controls include per-trade risk caps, daily stop limits, portfolio heat limits, and correlation checks.
Institutional practice separates signal quality from risk permissions, especially in high-entropy regimes.
Technical example: portfolio heat control
A portfolio limits total open risk to 2.5% of NAV; one proposed correlated position is rejected.
- Compute trade risk from entry, stop, and size.
- Aggregate risk across correlated positions.
- Reject or resize positions above heat cap.
- Log decision with score and SNAP context.
ASCII model
Signal quality -> Risk gate -> Position sizing -> Heat check -> ExecutionRisk controls by layer
| Layer | Control | Failure prevented |
|---|---|---|
| Trade | Fixed risk per position | Single-trade outsized loss |
| Book | Heat + correlation limits | Clustered drawdown |
| Process | Daily stop + review | Policy drift |
Internal links
- Market Status framework
Align exposure with CLEAR/TENSE/NO-TRADE states.
- Verify historical context
Audit whether losses were variance or process violation.
- What is Market Score
Use score bands to adjust portfolio risk budgets.
- How to interpret scores
Turn score movements into formal control actions.
FAQ
Most common crypto risk mistake?
Oversizing during unstable regimes and ignoring correlation concentration.
Should stops always be static?
Not usually. Volatility-aware stops are generally more robust in crypto.
How should policy be documented?
Use a written rulebook with limits, escalation triggers, and review cadence.