Token Research

apyUSD

APYUSDRank #182

$1.37USD

+0.20% 24h+0.32% 7d+3.09% 30d
Stale· data 4d 22h oldOfficial site

The information on this page is market data and educational analysis, not financial advice. Past on-chain activity does not guarantee future results. Always do your own research.

Live chart

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Source: Binance USDT market (≈USD) · 15m candles · UTC · awaiting first tick. Market prices from one venue — not a consolidated tape. Educational information only, not financial advice.

Price history

$1.36$1.36$1.37$1.37$1.37$1.37$1.372026-09-032026-09-062026-09-082026-09-10$1.37
2026-09-032026-09-10 UTC · $1.37$1.37 (+0.26%)Source: CoinGecko · cached up to 60 min

Structural risk profile

Observed characteristics of APYUSD market data — volatility, liquidity depth, drawdowns, size and supply.

51/100

Moderate observed risk

High confidence· 100%
  • Price volatility · weight 25%34/100

    Annualized volatility of 54% over the observed window.

  • Liquidity depth · weight 25%79/100

    24h traded volume of $667,928 (0.36% of market cap).

  • Market size · weight 15%58/100

    Market capitalization of $185,338,634.

  • Observed drawdown · weight 15%30/100

    Worst peak-to-trough decline of 26.6% in the observed window.

  • Distance from all-time high · weight 10%100/100

    Trading 100.0% below its all-time high.

  • Supply not yet circulating · weight 10%0/100

    0.0% of total supply is not yet circulating.

24h traded volume of $667,928 (0.36% of market cap).

Trading 100.0% below its all-time high.

Market capitalization of $185,338,634.

Annualized volatility of 54% over the observed window.

These are observed structural characteristics of past and current market data — not a prediction, not a recommendation.

Higher score = more observed structural risk. Computed from CoinGecko market data; the number is calculated, never generated by AI. A low score does not mean an asset is safe.

Smart Money Intelligence

Observed positioning of scored wallets over 30 days — computed from real whale events, rule-based, never a prediction.

10/100

distribution

50 baseline − 40 flow imbalance (net distribution 100% of $3.7M) − 0 breadth (0 scored wallets). Measures observed positioning, not investment quality.

Accumulation side · $0K

  • smart-money accumulation $0K
  • whale accumulation $0K
  • exchange outflows $0K
  • buy swaps $0K

Distribution side · $3.7M

  • whale distribution $3.7M
  • exchange inflows $0K
  • sell swaps $0K

Smart money consensus (7d · 0 scored wallets)

Insufficient scored-wallet data — no scored wallet was active on this asset in the last 7 days, so no consensus can be claimed.

Scenario weights — derived from current observed signals, not forecasts

Accumulation continues · 10%

  • market regime currently risk-on

Consolidation · 45%

  • balanced observed flows
  • no dominant pressure side

Distribution pressure · 45%

  • whale distribution observed ($3.7M/30d)
Professional lenses (5) — rule-based analysis from the data above
  • Institutional Fund confidence low

    What would a hedge fund analyst likely examine here?

    A fund analyst would typically flag the net distribution and examine venue inflows as potential supply overhang.

    Data: observed 30d flows: $0K accumulation-side vs $3.7M distribution-side · 0 scored wallets active in 7d

    On-chain flows describe PAST positioning of a small observed universe; they do not determine prices. Data can be incomplete or delayed.

  • Whale Investor confidence low

    What would a large holder likely watch?

    A large holder would typically watch the exchange inflows as a sign that peers are staging liquidity venue-side.

    Data: exchange outflows $0K vs inflows $0K (30d)

    On-chain flows describe PAST positioning of a small observed universe; they do not determine prices. Data can be incomplete or delayed.

  • Swing Trader confidence low

    What would a technical trader likely track?

    A swing trader would typically track whether the current distribution side persists across sessions, using the flow imbalance as context rather than a signal by itself.

    Data: observed 30d flows: $0K accumulation-side vs $3.7M distribution-side

    On-chain flows describe PAST positioning of a small observed universe; they do not determine prices. Data can be incomplete or delayed.

  • Risk Manager confidence low

    How would a professional frame the risk?

    A risk manager would typically size any exposure against the observed concentration: flows driven by few wallets reverse faster than broad-based moves, and venue-side supply adds liquidity risk.

    Data: 0 scored wallets in the 7d sample · venue-side supply $0K (30d inflows)

    On-chain flows describe PAST positioning of a small observed universe; they do not determine prices. Data can be incomplete or delayed.

  • Long-Term Investor confidence low

    What would a long-horizon allocator likely note?

    A long-horizon allocator would typically treat current flows as noise at their horizon and focus on fundamentals this dashboard does not measure.

    Data: Insufficient scored-wallet data — no scored wallet was active on this asset in the last 7 days, so no consensus can be claimed.

    On-chain flows describe PAST positioning of a small observed universe; they do not determine prices. Data can be incomplete or delayed.

Educational description of observed on-chain positioning (2 events · 1 wallets). Not financial advice, not a prediction, and never a buy or sell recommendation.

Price (USD)

$1.37

Market cap

$185.3M

24h volume

$667,928

Circulating supply

135,083,781

All-time high

$4,799.87

From ATH

-99.97%

On-chain intelligence

Contract addresses

  • ethereum0x38eeb52f0771140d10c4e9a9a72349a329fe8a6a
  • base0x2c271ddf484ac0386d216eb7eb9ff02d4dc0f6aa
  • binance smart chain0xa14556f13516c53ff035858ffd21e1625e7eadfd
  • solanaEx8hKasfFCfj3yGuN5TyYRUjHePgVs3uYUJRT8geT7rv

Market data by CoinGecko, refreshed every 5 minutes. Educational information only — not financial advice.