Crypto Turmoil: How The US Banking Collapse Dented Institutional Trading

Bitcoinist发布于2023-10-23更新于2023-10-24

文章摘要

March witnessed a series of bank failures that have had ramifications for institutional crypto trading, putting a damper on what...

March witnessed a series of bank failures that have had ramifications for institutional crypto trading, putting a damper on what was once considered a bustling market space.
According to the latest insights from the blockchain intelligence platform Chainalysis, concerning North America, the fallout from these bank closures has been far-reaching, impacting the pace and volume of large-scale crypto transactions. 
A Dip In Institutional Crypto Activity
Chainalysis’s recent report highlights the drop in “institutional” cryptocurrency transaction volume – transactions valued at more than $10 million. Starting in April 2023, the volume of these transactions plunged sharply, particularly in the North American region.
Interestingly, this downturn was specific to institutional transactions, as professional and retail trading volumes reportedly “remained constant.”

Crypto transaction volume transfer wise from July 2022 to June 2023.

Transaction volume transfer-wise from July 2022 to June 2023. | Source: Chainalysis The report points directly to the banking crisis in March, which led to several major US bank shutdowns, including the “Silicon Valley Bank and the crypto-friendly banks Signature and Silvergate” as factors that resulted in this drop.
In addition, the failure of troubled digital currency exchanges and lending desks, such as FTX and Alameda Research, in the preceding November further exacerbated the decline, according to the Chainalysis report.
The Exodus Of Stablecoins From North America
Furthermore, in the Chainlalysis report, one of the notable aftermaths of the banking crisis has been the dwindling dominance of stablecoins in North America. Stablecoins, primarily USD-pegged tokens, accounting for roughly 90% of global activity, began to lose ground in North America from February 2023 onwards.
Within a short span from February to June, the percentage of digital currency volume in the region attributable to stablecoins declined from 70.3% to 48.8%.

North America crypto transaction volume by asset type from June 2022 to July 2023.

North America crypto transaction volume by asset type from June 2022 to July 2023. | Source: Chainalysis Chainalysis’s research further underscores that since the spring of 2023, there has been a noticeable shift of stablecoin inflows from US -US-licensed crypto services to their non-U.S. counterparts.
Related Reading: Nigeria’s Crypto Adoption Continues To Surge Amid Economic Challenges: Report
This shift denotes a broader migration pattern, with businesses and traders seeking financial shores beyond US jurisdictions. The report noted:
Since [the] spring of 2023, the majority of stablecoin inflows to the 50 biggest crypto services have shifted from US licensed-services to non-U.S. licensed services, undoing a shift in the opposite direction that occurred over the course of late 2022 and early 2023.

Stablecoin inflows in U.S. licensed-services compared to in non-U.S. licensed services.

Stablecoin inflows in US-licensed services compared to non-US-licensed services. | Source: Chainalysis Chainalysis further disclosed that non-U.S. licensed platforms received 54.6% of stablecoin inflows among the top 50 services as of June.

The global crypto market cap value on TradingView

The global crypto market cap value on the 1-day chart. Source: Crypto TOTAL Market Cap on TradingView.com Featured image from iStock, Chart from TradingView

热门币种推荐

你可能也喜欢

加州理工用AI攻克量子化学60年难题,1块显卡做完7800块的活

加州理工学院Anima Anandkumar团队利用人工智能攻克了量子化学领域存在60年的计算瓶颈。他们开发的AI模型“Kohn-Sham FNO”将密度泛函理论(DFT)的计算复杂度从传统的立方级降低至近线性级,实现了革命性突破。 传统DFT计算随体系增大,计算量呈立方增长,难以模拟大分子体系。该团队创新性地采用傅里叶神经算子,在DFT的迭代求解流程中替代了最耗时的核心计算步骤,而非直接预测最终结果。这种“思维链”式的分步迭代方法保证了计算的稳定性和外推能力,即使模型输出有误,后续迭代也能纠正,并能在超出能力范围时通过发散发出警报。 该模型仅用8504个结构进行训练,便能同时处理分子和固体材料,覆盖元素周期表前五行元素,展现出优异的泛化能力。在外推至训练集未见的大型药物分子时,其误差远低于直接预测模型。 实际验证中,该模型在单块NVIDIA B300 GPU上成功完成了包含8250个原子(82500个价电子)的金属缺陷模拟,计算完美收敛。相比之下,2019年一项对类似规模体系的全量DFT计算动用了约7800块GPU。实测计算缩放指数为1.03(近线性),而传统方法为3.37(立方级),意味着体系越大,效率优势越显著。 这项研究标志着AI开始替代物理计算中最耗时的重复运算部分。团队已基于此创立公司,并计划进一步完善模型以覆盖完整能量计算流程,未来在药物研发、电池材料设计等领域具有巨大应用潜力。

marsbit28分钟前

加州理工用AI攻克量子化学60年难题,1块显卡做完7800块的活

marsbit28分钟前

交易

现货

热门文章

加密市场宏观研报:美国“加密货币周”来袭,ETH开启机构军备赛高潮

本周,加密市场迎来两股重磅催化——华盛顿“加密货币周”的立法攻势与以太坊机构布局的密集爆发,共同构成加密行业2025年下半年的“政策拐点”与“资金拐点”。这一轮加密周期的深层逻辑,正从比特币转向以太坊、稳定币及链上金融基础设施。我们认为:美国的政策明朗化+以太坊的机构化扩展,标志着加密行业正进入结构性转正阶段,市场配置的重心亦应逐步从“价格博弈”过渡至“规则+基础设施的制度红利捕捉”。

2.3k人学过发布于 2025.07.17更新于 2025.07.17

加密市场宏观研报:美国“加密货币周”来袭,ETH开启机构军备赛高潮

相关讨论

欢迎来到HTX社区。在这里,您可以了解最新的平台发展动态并获得专业的市场意见。以下是用户对ETH(ETH)币价的意见。

活动图片