ApeCoin

APERank #198

$0.145818USD

-4.48% 24h-2.14% 7d+7.44% 30d

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

24h 7d 30d 90d 1y

line candles

07:30 → 07:00 UTC · $0.152657 → $0.145819 (-4.48%)Source: CoinGecko · cached up to 5 min

Structural risk profile

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

56/100

Elevated observed risk

High confidence· 100%

Price volatility · weight 25%77/100
Annualized volatility of 97% over the observed window.
Liquidity depth · weight 25%43/100
24h traded volume of $19,025,779 (13.05% of market cap).
Market size · weight 15%61/100
Market capitalization of $145,833,791.
Observed drawdown

Smart Money Intelligence

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

63/100

accumulation

50 baseline + 13 flow imbalance (net accumulation 33% of $4.3M) + 0 breadth (0 scored wallets). Measures observed positioning, not investment quality.

Accumulation side · $2.9M

smart-money accumulation $0K
whale accumulation $2.9M
exchange outflows $0K
buy swaps $0K

Distribution side · $1.4M

whale distribution $0K
exchange inflows $1.4M
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 · 43%

market regime currently risk-on

Consolidation · 45%

balanced observed flows
no dominant pressure side

Distribution pressure · 12%

Price (USD)

$0.145818

Market cap

$145.8M

24h volume

$19.0M

Circulating supply

1,000,000,000

All-time high

$26.7

From ATH

-99.45%

On-chain intelligence

APE on ETHEREUM43 observed transfers · 4 whale events · holder analytics & structure scores

Contract addresses

ethereum0x4d224452801aced8b2f0aebe155379bb5d594381
hyperevm0xab11329560fa9c9c860bb21a9342215a1265bbb0
binance smart chain0x8f86a15ec17cb3369d8b3e666dadbc11daa82b79
monad0x6a7e3f839382fbb6a6131d4aae864aaeb362292d
solanaC1MHyoTJpRTeS9AQCyspNVu2EWAYCZwmJ1jNkEArFP1f
polygon pos0xb7b31a6bc18e48888545ce79e83e06003be70930
robinhood0x8f86a15ec17cb3369d8b3e666dadbc11daa82b79
arbitrum one0x7f9fbf9bdd3f4105c478b996b648fe6e828a1e98

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

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 note the net accumulation and examine whether the flow is broad (many wallets) or concentrated (one actor), before treating it as a positioning signal.
Data: observed 30d flows: $2.9M accumulation-side vs $1.4M 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 $1.4M (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 accumulation side persists across sessions, using the flow imbalance as context rather than a signal by itself.
Data: observed 30d flows: $2.9M accumulation-side vs $1.4M 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 $1.4M (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 note that observed professional positioning leans toward accumulation, while weighing it against 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.