Token Research

Ripple USD

RLUSDRank #40

$0.999952USD

-0.00% 24h-0.01% 7d-0.02% 30d
Stale· data 1d 12h 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

$0.99985$0.9999$0.99995$1$106:1014:0922:0806:08$0.999943
06:1006:08 UTC · $0.999971$0.999943 (-0.00%)Source: CoinGecko · cached up to 5 mindata may be stale

Structural risk profile

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

11/100

Low observed risk

High confidence· 100%
  • Price volatility · weight 28%0/100

    Annualized volatility of 1% over the observed window.

  • Liquidity depth · weight 28%25/100

    24h traded volume of $101,555,911 (4.19% of market cap).

  • Market size · weight 17%21/100

    Market capitalization of $2,422,732,313.

  • Observed drawdown · weight 17%0/100

    Worst peak-to-trough decline of 0.1% in the observed window.

  • Distance from all-time high · weight 11%8/100

    Trading 6.8% below its all-time high.

24h traded volume of $101,555,911 (4.19% of market cap).

Market capitalization of $2,422,732,313.

Trading 6.8% below its all-time high.

Worst peak-to-trough decline of 0.1% in 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.

42/100

distribution

50 baseline − 8 flow imbalance (net distribution 19% of $1165.5M) − 0 breadth (0 scored wallets). Measures observed positioning, not investment quality.

Accumulation side · $472.6M

  • smart-money accumulation $0K
  • whale accumulation $187.8M
  • exchange outflows $284.8M
  • buy swaps $0K

Distribution side · $692.8M

  • whale distribution $404.6M
  • exchange inflows $288.2M
  • 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 · 30%

  • market regime currently risk-on

Consolidation · 45%

  • balanced observed flows
  • no dominant pressure side

Distribution pressure · 25%

  • whale distribution observed ($404.6M/30d)
  • net exchange inflows (supply moving to venues)
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: $472.6M accumulation-side vs $692.8M 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 $284.8M vs inflows $288.2M (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: $472.6M accumulation-side vs $692.8M 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 $288.2M (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 (79 events · 6 wallets). Not financial advice, not a prediction, and never a buy or sell recommendation.

Price (USD)

$0.999952

Market cap

$2.42B

24h volume

$101.6M

Circulating supply

2,422,848,190

All-time high

$1.07

From ATH

-6.79%

On-chain intelligence

Contract addresses

  • xrp524C555344000000000000000000000000000000.rMxCKbEDwqr76QuheSUMdEGf4B9xJ8m5De
  • ethereum0x8292bb45bf1ee4d140127049757c2e0ff06317ed

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