Historical analogs
Similar setups to $OPTIMUS
Past moments, on any token in this dataset, whose scores and market context looked most like this token's latest snapshot — and what happened in the 24 hours after. Statistical context, not a promise.
Live
Similar setups
0
of 675 eligible snapshots
Median 24h
—
follow-through after the setup
Worst 24h drawdown
—
deepest intraday fall
Positive after 24h
—
N = 0
ConfidenceConfidence: Insufficient dataOnly 2 comparable features (need ≥ 3)
No outcome distribution
Only 2 comparable features (need ≥ 3)
This setup now
Snapshot 2026-10-11 18:02 UTC — the vector being matched
- Momentum
- —
- Crowding
- —
- Early Quality
- —
- Narrative Velocity
- 17
- Price change 1h
- —
- Volume acceleration
- —
- Liquidity
- $147.8K
Features that are missing right now (for example no market data) are left out of the distance rather than guessed; 2 of 7 features were comparable.
Matched historical setups
No historical setup was close enough
Only 2 comparable features (need ≥ 3)
Method & point-in-time rules
analog-v1.0
- Distance: Euclidean over z-scored features (Momentum, Crowding, Early Quality, Narrative Velocity, Price change 1h, Volume acceleration, Liquidity), z-scored across the eligible candidate set; nearest 40 within a distance of 2.5. Similarity = 1 − distance / 2.5.
- Candidates are hourly score snapshots whose 24h outcome had resolved strictly before this snapshot (2026-10-11 18:02 UTC): nothing that happened afterwards is used. Snapshots of $OPTIMUS within ±24h are excluded.
- Considered 7,048 resolved snapshots · 675 had every comparable feature · 0 excluded as the same token nearby · 0 rejected as not yet resolved.
- Dead tokens stay in the candidate set, so outcomes include collapses (survivorship-safe). Returns are measured from the first price at or after each snapshot.
FomoQuant provides analytics and historical/statistical context, not financial advice or guaranteed predictions.