AMF-BlackSwan Crypto
AMF-BLACKSWAN-CRYPTO Crypto AI adaptation short book — Swan Composite v1.1.0: the 10 lowest composite scores (67% AI Adaptation Score + 33% market verdict versus BTC, conviction-weighted 5–20%) among cryptocurrencies whose public materials claim AI — AI in name only and bolt-on AI, no listing younger than 90 days or crowded short (scoring run 2026-11-05), refreshed with each run HITL-dynamicAI-managed Index Basket · Theme: Black Swan Events: Crypto AI-washing Short Book · 10 components selected by fine-tuned AI models from a network of hundreds and dynamically swapped based on proprietary algorithms.
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Performance
Profile
Score-driven crypto portfolio: the AI
system reads every scored project’s public record — its CoinGecko
profile, homepage, agent cards and llms.txt, whitepaper, docs and
public repositories — and places it on one scale: no mention of AI,
AI in name only, bolt-on AI, AI-native, or greenfield
(built with AI from the ground up, the highest reward). The Crypto AI Adaptation
Score combines that level with how much of the claim is verifiable in code and
shipped product, the credibility of the claims and recent developer activity.
This book shorts the lowest-scoring coins
that claim AI — AI in name only or bolt-on claims the public record does
not back — that pass the liquidity screen (price, market-cap and traded-dollar
floors, acquirable on a supported venue), equal-weighted, and is recomposed with each
scoring run. Every rebalance keeps the index level continuous; live trading stays
behind Human-In-The-Loop approval.
Constituent research
One sourced Crypto AI Adaptation Research Report per constituent: why the project’s own public record places it in the CBlackSwan short book (claims AI the record does not back) — the sources quoted verbatim, the adoption level (no mention, name only, bolt-on, native, greenfield), what is verifiable in code and product, developer activity and what would change the verdict. Every factual sentence names its source. Scoring run 2026-11-05.
| Rank | Project | Level | AAS | Market | Composite | Weight | Report |
|---|---|---|---|---|---|---|---|
| 1 | ALGO Algorand | 1 | 23.4 | 36.5 | 27.7 | 14.5% | Read the report |
| 2 | ADA Cardano | 1 | 24.7 | 37.1 | 28.8 | 13.6% | Read the report |
| 3 | APT Aptos | 1 | 21.1 | 45.7 | 29.3 | 11.8% | Read the report |
| 4 | XRP XRP | 1 | 21.9 | 48.1 | 30.6 | 10.8% | Read the report |
| 5 | DOT Polkadot | 1 | 21.1 | 51.5 | 31.2 | 9.9% | Read the report |
| 6 | ENS Ethereum Name Service | 1 | 23.1 | 48.3 | 31.5 | 9.4% | Read the report |
| 7 | ZK ZKsync | 1 | 21.9 | 52.5 | 32.1 | 8.5% | Read the report |
| 8 | SUI Sui | 1 | 21.5 | 53.9 | 32.3 | 7.8% | Read the report |
| 9 | RSR Reserve Rights | 1 | 23.0 | 52.9 | 33.0 | 7.1% | Read the report |
| 10 | OP Optimism | 1 | 21.5 | 56.8 | 33.3 | 6.4% | Read the report |
How to read the columns: AAS is the AI Adaptation Score (0–100) from the project's own public materials; Market is the market verdict — the Failure-To-Adapt capture signal: how the asset moved on days BTC fell versus days it rose over 90 days (50 = moves with it, below = falls more and rises less); Composite blends them (67% AI Adaptation Score + 33% market verdict) and sets the Rank — the lowest composites make the book; Weight is the conviction weight (rank tilt × agreement of the inputs with the book's direction, clamped 5–20%). A mandate leg is held by operator instruction outside the ranking and is not scored. Each report explains the constituent's own evidence.
Holdings
| Component | Connection | Weight | Relevance | |
|---|---|---|---|---|
| CS-01 ▸ | direct | 14.51% | 0.000 | |
|
CS-01 Direct holding — its core business is the fund’s theme · weight 14.51% · AI model relevance 0.000. |
||||
| CS-02 ▸ | direct | 13.63% | 0.000 | |
|
CS-02 Direct holding — its core business is the fund’s theme · weight 13.63% · AI model relevance 0.000. |
||||
| CS-03 ▸ | direct | 11.85% | 0.000 | |
|
CS-03 Direct holding — its core business is the fund’s theme · weight 11.85% · AI model relevance 0.000. |
||||
| CS-04 ▸ | direct | 10.85% | 0.000 | |
|
CS-04 Direct holding — its core business is the fund’s theme · weight 10.85% · AI model relevance 0.000. |
||||
| CS-05 ▸ | direct | 9.94% | 0.000 | |
|
CS-05 Direct holding — its core business is the fund’s theme · weight 9.94% · AI model relevance 0.000. |
||||
| CS-06 ▸ | direct | 9.39% | 0.000 | |
|
CS-06 Direct holding — its core business is the fund’s theme · weight 9.39% · AI model relevance 0.000. |
||||
| CS-07 ▸ | direct | 8.52% | 0.000 | |
|
CS-07 Direct holding — its core business is the fund’s theme · weight 8.52% · AI model relevance 0.000. |
||||
| CS-08 ▸ | direct | 7.81% | 0.000 | |
|
CS-08 Direct holding — its core business is the fund’s theme · weight 7.81% · AI model relevance 0.000. |
||||
| CS-09 ▸ | direct | 7.10% | 0.000 | |
|
CS-09 Direct holding — its core business is the fund’s theme · weight 7.10% · AI model relevance 0.000. |
||||
| CS-10 ▸ | direct | 6.39% | 0.000 | |
|
CS-10 Direct holding — its core business is the fund’s theme · weight 6.39% · AI model relevance 0.000. |
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Headlines
Signaling Network
How all crypto assets in this universe connect — each dot is a crypto asset, links are association strength (co-appearance on ontology concepts, decaying with ontology distance). This fund’s components sit inside this network. Click a dot to inspect it.
Derived, relative association measure (ontology distance × AI model scores). Not correlations, not price relationships, not trading signals.
Supply-Chain Return Map
The Signaling Network’s concept nodes, ranked by momentum. Each tile is an ontology category — sized by breadth of exposure (its direct constituents) and colored by their median trailing‑30‑day return. Hover a tile for its movers.
Median is outlier-robust: a single split-glitch cannot color a tile green. Illustrative of ontology-cluster momentum, not investment advice.