Risk-Tier Performance · Review Cadence
How tier reads enter the loop.
Read this first
Further illustration
The Dynamic 7-Tier Benchmark converts the drawdown distribution into modeled tier-usage expectations: given the gate transitions the evidence implies, T1-T3 should host most deployment while T5-T7 stay exceptional. Live tier dwell is audited against this profile every cycle.
The seven-tier ladder with modeled dwell: how often each tier should be in use given the gate history. High tiers exist to be rare.
Review cadence
01How tier reads enter the loop.
Tier usage is reviewed monthly alongside gate dwell and throttle behavior. The comparison is conditional: usage is judged against what the model expects given the gates actually visited — heavy T5 usage during a Growth-dominant quarter is normal; the same usage during Buffer dwell is a governance breach in progress.
- Tier-conditional R: each tier must show outcomes proportional to its extra risk, or the ladder is being climbed for nothing.
- Override log cross-check: elevated tier usage plus frequent Full Tier overrides is the classic aggression-drift signature.
- Under-usage gets equal scrutiny — authorized tiers left idle is modeled expectancy left unmonetized.
Where it lives
02Inside Risk-Tier Performance.
Within Risk-Tier Performance, this is one load-bearing idea — worth its own page. The parent module frames it this way: The benchmark models expected usage and performance across T1–T7. Comparing live tier behavior against those bands reveals aggression drift, under-deployment, and whether higher tiers are actually converting their extra risk into extra return.
The conditional read
03Usage is judged against the gates that actually happened.
A month spent mostly in low tiers is not automatically timidity — under a compressed gate history it is exactly correct. The review therefore conditions expected dwell on realized gate states before scoring the gap, so operators are graded on their behavior inside the month they actually had, not an average month that never occurred.
How MARS uses this
Monthly review places live tier usage against the model conditionally — usage is judged given the gates that actually occurred, not against an unconditional average. This chart is the review's exhibit: the gap between modeled and lived deployment, tier by tier, read alongside gate dwell before any conclusion.
How it benefits you
Aggression creep gets caught while it is still a pattern on a chart rather than an oversized loss. Equally, unnecessary timidity shows up as a measurable gap, so you deploy the edge you have actually earned instead of leaving modeled expectancy on the table.
The monthly exhibit: live tier deployment against conditional expectation, the gaps being the agenda.
Connected inside MARS
This module doesn't work alone.
Go deeper
Operator briefs on this territory.
Deep dive — 01
How often tier performance gets re-examined — and why not more.
Slice a small sample seven ways and something always looks broken. Cadence is the cure.
Read the full brief →
Deep dive — 02
Tier usage is graded against the gates that actually occurred.
Heavy T5 in a Growth quarter is normal. The same usage under Buffer dwell is a breach in progress.
Read the full brief →
Deep dive — 03
The governance layer is required to justify itself, on the same evidence as everything else.
With-throttle against no-throttle, on the same paths. The governance layer does not get a pass.
Read the full brief →
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