Analysis for Artificial Superintelligence Alliance
Description & usage
Artificial Superintelligence Alliance (FET) is an AI-oriented crypto asset focused on agent-based automation, data markets, and interoperable AI services. Within its ecosystem, the token acts as the economic layer for service consumption, incentives, and participant coordination. Key fundamentals are real integrations, network usage, and technical quality of the AI infrastructure.
FET is mainly used to pay for network services, coordinate incentives, and support governance in AI-agent infrastructure markets.
Basic info
- Symbol
- FET
- Category
- AI
- Available history
- 7.3 years
- Last trading day
- 06/04/2026
Market context
- DXY
- 120.89last available value
- US 10Y Real
- 1.99%
- Fed Balance
- $6.68T
- CPI YoY
- 2.4%
- Fed Rate
- 3.75%
- US 10Y
- 4.35%
- VIX
- 24.54
- HY OAS
- 3.17%
- Brent
- $121.88
- Core CPI
- 2.5%
- US 2Y
- 3.84%
- ISM PMI
- –
Score overview
Analysis summary
Overall, the chart is trying to recover, but the rebound is not fully confirmed yet. Performance is currently doing more of the work than stability, with sub-scores of 73 for performance, 51 for stability and 67 for trend.
The main support is that selling pressure looks less one-sided than before. Price is 15.0 % versus SMA50 and twelve-month momentum is -73.7 %, which fits an early repair phase more than a fully rebuilt uptrend.
The main drag is missing confirmation. The bounce is visible, but trend strength is still modest and the longer moving-average reference is still at 15.0 %, so the rebound is still short of a cleaner uptrend.
The next key change would be confirmation that the rebound is broadening. More strength versus the longer averages would upgrade this from a bounce to a firmer trend.
Historical evaluation and qualitative market context only, not investment advice.
Price chart
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Scores and metrics
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Scores
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Metrics
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Data snapshot
- Snapshot as of
- Jun 04, 2026
- Last trading day
- Jun 04, 2026
- Snapshot status
- Validated
- Data quality
- Passed
Freshness, data quality, and exclusions stay visible. Unavailable values and insufficient history are never treated as valid data.
