【反常】SUI 交易量碾压 AVAX、NEAR、HYPE,交易员却集体撤离?

ambcryptoPublicado em 2025-07-31Última atualização em 2025-07-31

Resumo

SUI 在可扩展性方面的成功推动了其销量,但其价格仍然疲软。

关键要点

SUI 的月交易量超过了 AVAX、HYPE 和 NEAR 的总和,达到 445.9 亿美元。交易量的激增与 BTCfi 在 DeepBook 上的上线以及 TVL 创纪录的增长同步。

截至发稿时,根据 CoinMarketCap 的数据, Sui [SUI]在过去 24 小时内下跌了 4% 。继本周早些时候短暂上涨之后,此次下跌反映了加密货币市场的整体情绪。

SUI 一度飙升至 4.40 美元的局部高点,尽管有所回调,但链上交易量依然强劲。CoinGecko 的数据显示,SUI 的交易量持续上升。

SUI 赢得比赛

从分析来看,SUI 代币的交易量超过了Avalanche [AVAX]、Hyperliquid [HYPE]和Near Protocol [NEAR]的总和。

SUI 7 月份的交易量为 445.9 亿美元,比其竞争对手高出 80 亿美元。该交易量涵盖了中心化交易所 (CEX) 和去中心化交易所 (DEX) 的所有掉期交易,这证明了该山寨币的广泛接受度。

交易量的增长是由 Cetus 等不断发展的协议和新推出的 BTCfi 共同推动的,这些协议为网络开辟了新的流动性途径。

是什么推动了这一激增?

SUI 交易量的主要驱动因素之一是其 DeFi 协议,该协议现已支持比特币 [BTC]。考虑到 BTC 代币的扩容难度,这是一个新的里程碑。

BTCfi 将允许在 SUI 的 DeepBook 上使用比特币来为资金池、交易永续合约和期权、杠杆、借贷提供流动性。

正如 X (前身为 Twitter)所述,这将在 L1 区块链上引入全新的流动性。

自 1 月份以来,SUI 的总锁定价值增长了 480% 以上,到 7 月底达到 22.95 亿美元。

当考虑流动性质押、借款和重复计算的资金时,TVL 总额达到了 34.8 亿美元,创历史新高。

稳定币活动也保持强劲,市值为 10.36 亿美元,每日流入量为 236 万美元,表明跨协议的资本部署稳定。

SUI 翻转 Ichimoku Cloud 阻力

尽管山寨币在交易量方面领先,但价格却试图维持在一目均衡表上方。价格走势已经突破了该水平,这与下降趋势线相吻合。

SUI 的交易价格为 3.82 美元,价格似乎已重新测试 3.61 美元区域。

动量震荡指标显示出温和的看涨势头,但卖方占据了成交量主导地位。

资金流量指数 (MFI) 降至 36.47,表明尽管结构性增长呈正增长,但资金仍在流出该资产。

尽管价格疲软,但衍生品数据显示前景谨慎乐观。持仓量加权融资利率仍为正值,表明多头交易者仍在为空头支付。

与此同时,未平仓合约从 26.6 亿美元下降至 24.1 亿美元,但关键的是仍保持在 20 亿美元的门槛之上。

这种韧性暗示,即使在更广泛的市场调整中,机构或鲸鱼的兴趣也没有完全枯竭。

Leituras Relacionadas

Probability in the Price: How World Cup Odds Are Calculated

**The Probability in the Price: How World Cup Odds Are Calculated** Two major systems released their "championship probabilities" before the 2026 World Cup, and they disagreed on the favorite. Prediction market aggregators listed France at around **17%**, while the Opta supercomputer gave European champion Spain **16.1%**. These numbers look similar, but their production methods are fundamentally different. The market's **17%** is the **price** that clears after hundreds of millions of dollars in trading across platforms like Polymarket and Kalshi, where contracts trade between 0 and 100 cents, directly representing implied probability. This liquidity is provided by crypto-native market makers like Wintermute, though the market still has "the liquidity profile of an early-stage" asset class. In contrast, Opta's **16.1%** is a **simulated frequency**. Its model uses team data (including betting market odds as an input) to estimate match probabilities, then runs **10,000 full tournament simulations**, counting how often each team wins. Which is more accurate? There is **no rigorous, cross-tournament academic study** directly comparing their track records. However, a persistent **longshot bias**—where low-probability outcomes are systematically overvalued—observed in traditional betting for nearly a century, has also been found in modern crypto prediction markets. Research shows low-price contracts on Kalshi/Polymer less likely to pay out than their implied odds suggest. Unlike traditional bookmakers, prediction markets operate on **public blockchain ledgers**, making every transaction auditable and enabling such research. However, price formation is also influenced by **regulatory uncertainty**, as seen in recent US state-level bans and legal battles over jurisdiction. In summary, the "probability" you see is either a **market-clearing price** subject to behavioral biases and liquidity constraints, or a **model-simulated frequency** that partially incorporates market data. The question of which method is more reliable remains open, highlighting the importance of asking: **How was this number produced?**

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