Historical analogs
Similar setups to $MALFOID
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
2
of 1,086 eligible snapshots
Median 24h
-2.5%
follow-through after the setup
Worst 24h drawdown
-15.6%
deepest intraday fall
Positive after 24h
50%
N = 2
ConfidenceConfidence: LOW2 similar setups · 24h outcomes resolved before 2026-10-11 21:12 UTC · 2026-10-10 → 2026-10-10
24h return after similar setups
N = 2 · Positive after 24h 50% (95% CI 9–91%)
- Median
- -2.5%
- CI -15.6% … +10.5%
- Trimmed mean
- -2.5%
- 10% each side
- Mean
- -2.5%
- σ 18.4%
- Range
- -15.6% … +10.5%
- p5
- -14.3%
- p10
- -13.0%
- p25
- -9.0%
- p50
- -2.5%
- p75
- +4.0%
- p90
- +7.9%
- p95
- +9.2%
This setup now
Snapshot 2026-10-11 21:12 UTC — the vector being matched
- Momentum
- —
- Crowding
- —
- Early Quality
- —
- Narrative Velocity
- 53
- Price change 1h
- +18.8%
- Volume acceleration
- +484%
- Liquidity
- $75.1K
Features that are missing right now (for example no market data) are left out of the distance rather than guessed; 4 of 7 features were comparable.
Matched historical setups
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 21:12 UTC): nothing that happened afterwards is used. Snapshots of $MALFOID within ±24h are excluded.
- Considered 7,656 resolved snapshots · 1,086 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.