XRP taker buy-sell ratio flexes a 2026 high while $1 holds the line — the chart says one thing, the on-chain whispers another 🪙

XRP's derivatives market just printed its most aggressive taker buy-sell ratio of 2026, according to CryptoQuant, as buyers piled into perpetual swaps and helped lift the token 5.35% in the past 24 hours. The 7-day moving average of the ratio pushed back above 1, a level traders watch as a signal that taker demand is dominating aggressive selling.

That bullish derivatives print, however, is being met with a more cautious on-chain backdrop. Coin Days Destroyed spiked to its largest reading since April, indicating that previously dormant XRP coins were moved in volume — a pattern often associated with profit-taking or capitulation. The move coincided with XRP trading above $1.10, suggesting long-dormant holders used the bounce to unload tokens. The $1 psychological support level has held through the selling so far.

Wallet-flow data flagged by analyst Amr Taha shows a separate signal worth watching: the 7-day net depositing/withdrawing wallet count slid to -6,210 on June 30, a flip from net deposits to net withdrawals. Wallet withdrawal trends are sometimes read as accumulation behavior, though they do not on their own confirm smart-money buying.

The top of the holder pyramid tells a more conflicted story. The percentage of $XRP supply held by the top 1% of addresses slipped from 87.98% to 87.87% through June, indicating distribution rather than accumulation. For context, that concentration metric had climbed from 87.57% in January to nearly 88% at its 2026 peak before the recent decline. A 1 billion XRP unlock reported earlier has amplified questions about how much supply the market can absorb without breaking the $1 floor.

With XRP holding above $1 even as short-term traders chase the move higher and long-dormant coins change hands, the tape is sending mixed signals. Broader market-wide sentiment and Bitcoin price action will continue to shape XRP's near-term direction alongside these derivatives and on-chain metrics.