Zama

ZAMARank #202

$0.064347USD

+1.89% 24h+63.32% 7d+109.94% 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

Loading live market…

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

2026-07-22 → 2026-07-29 UTC · $0.040274 → $0.064083 (+59.12%)Source: CoinGecko · cached up to 60 min

Structural risk profile

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

55/100

Elevated observed risk

High confidence· 100%

Price volatility · weight 25%88/100
Annualized volatility of 108% over the observed window.
Liquidity depth · weight 25%35/100
24h traded volume of $38,857,712 (27.44% of market cap).
Market size · weight 15%62/100
Market capitalization of $141,616,553.
Observed drawdown

Smart Money Intelligence

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

28/100

distribution

50 baseline − 22 flow imbalance (net distribution 54% of $11.9M) − 0 breadth (0 scored wallets). Measures observed positioning, not investment quality.

Accumulation side · $2.7M

smart-money accumulation $0K
whale accumulation $0K
exchange outflows $2.7M
buy swaps $0K

Distribution side · $9.2M

whale distribution $9.2M
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 · 21%

net exchange outflows (supply leaving venues)
market regime currently risk-on

Consolidation · 45%

balanced observed flows
no dominant pressure side

Distribution pressure ·

Price (USD)

$0.064347

Market cap

$141.6M

24h volume

$38.9M

Circulating supply

2,200,000,000

All-time high

$0.066136

From ATH

-2.85%

On-chain intelligence

ZAMA on ETHEREUM496 observed transfers · 6 whale events · holder analytics & structure scores

Contract addresses

ethereum0xa12cc123ba206d4031d1c7f6223d1c2ec249f4f3
binance smart chain0x6907a5986c4950bdaf2f81828ec0737ce787519f
zama gateway mainnet0xce762c7fdaac795d31a266b9247f8958c159c6d4
solana4Zp52aF4hZi9fzH19xpbWKYKQvgLyCN67KFbrQDqeTKh

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 flag the net distribution and examine venue inflows as potential supply overhang.
Data: observed 30d flows: $2.7M accumulation-side vs $9.2M 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 net exchange outflows — supply moving to self-custody historically accompanies holding behavior.
Data: exchange outflows $2.7M 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: $2.7M accumulation-side vs $9.2M 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.