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AMF-WhiteSwan Crypto

AMF-WHITESWAN-CRYPTO Crypto AI adaptation long book — Swan Composite v1.1.0: the 6 highest composite scores (67% AI Adaptation Score + 33% market verdict versus BTC, conviction-weighted 5–20%) among cryptocurrencies whose public materials claim AI — greenfield and AI-native protocols (scoring run 2026-11-06), plus ET10 held by operator mandate since 2026-10-31 (unscored, conviction base weight), refreshed with each run HITL-dynamic

AI-managed Index Basket · Theme: White Swan Events: Crypto AI-native Long Book · 7 components selected by fine-tuned AI models from a network of hundreds and dynamically swapped based on proprietary algorithms.

Binance breach puts custody at center of crypto infrastructure trade Wire · Binance breach puts custody at center of crypto infrastructure trade Crypto
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$51.55
-3.30%
7
2026-10-31

Performance

$ index price history since inception. Real-time index and orderbook are on the pro terminal.

Profile

AMF-WhiteSwan Crypto (AMF-WHITESWAN-CRYPTO)
AI-Managed Fund (AMF) · long book
Crypto AI adaptation — holds the highest composite scores (Crypto AI Adaptation Score + market verdict versus BTC) among AI-native and greenfield coins, conviction-weighted
Swan Composite v1.1.0 · composed 2026-11-06
target-weighted
AI model proposes · Human-In-The-Loop approves
2026-10-31
AMF-WHITESWAN-CRYPTO/USDC on the CLOB

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 holds the highest-scoring AI-native and greenfield coins 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 CWhiteSwan long book (AI-native or built with AI from the ground up) — 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 2026-11-06.

RankProjectLevel AAS Market CompositeWeightReport
1 TAO Bittensor 4 84.2 47.9 72.2 17.6% Read the report
2 VVV Venice Token 3 69.6 74.0 71.0 19.9% Read the report
3 NEAR NEAR Protocol 3 66.1 76.6 69.6 18.5% Read the report
4 FET Artificial Superintelligence Alliance 4 80.3 38.6 66.4 13.2% Read the report
5 ICP Internet Computer 3 56.2 51.3 54.6 11.8% Read the report
6 EIGEN EigenCloud (prev. EigenLayer) 3 56.6 31.2 48.1 10.2% Read the report
pinned ET10 EventTrader ET10 — AI agent revenue share token mandate — — — — 8.8% 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 highest 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

ComponentConnectionWeightRelevance
Holdings are disclosed by design — this is the tradable index. direct = the component’s core business is the theme; hidden = a real but non-obvious supply-chain or second-order connection surfaced by the vector model. Relevance is the AI model’s raw affinity score for the theme: higher means a stronger link, and it is not capped at 1 or a percentage — compare it within a fund, not across funds.

Headlines

Live newswire items from the headline pipeline connected to this fund — by its components and by its theme & ontology concepts (tagged above) — updating continuously, and an input that prioritizes the next portfolio re-measure. Headlines never trade by themselves.

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.

30-day return −3%0+3%

Median is outlier-robust: a single split-glitch cannot color a tile green. Illustrative of ontology-cluster momentum, not investment advice.

AMF-WhiteSwan Crypto — live swarm

Every holding, the index and the pipeline running this fund, with every control, label and stat. Drag to rotate · scroll or pinch to zoom · hover a node for its metrics.