Aave 整合 Chainlink SVR 以夺回与预言机相关的 MEV

大规模清算、加密货币崩盘、到处都是恐慌 —— 但一位顶级分析师表示，这可能是加密货币迄今为止最大的机会。美国总统唐纳德·特朗普的关税是否真的会推动比特币的下一个大动作？ 编者注：本文撰写于美国政府与墨西哥政府达成临时协议之前，该协议至少暂停执行关税为期一个月。您可以在此处阅读有关此进展的信息。 美国新一轮关税引发的最新一波经济不确定性导致加密货币市场急剧下滑。 比特币在货币调整时代的作用专家观点：关税将如何重塑加密货币市场接下来会发生什么？ 关税作为战略杠杆 美国经济战略的持续转变，特别是关税方面的转变，超出了贸易政策的范畴，是更广泛的货币政策的一部分。 由于全球贸易依赖美元，外国政府和央行必须持有大量美元储备。这种动态导致美元结构性高估，削弱美国出口竞争力，同时允许政府以优惠条件借款。 为了维持这一体系，美国历史上一直存在持续的贸易逆差，实际上是以牺牲自己的工业基础为代价来向世界提供美元。 然而，帕克指出，现在美国正在寻找方法来抵消美元高估的负面影响，同时又不放弃其借贷优势。关税就是在这种背景下使用的——不是作为一种传统的保护主义措施，而是一种影响外国政府的美元储备和美国国债持有量的工具。 帕克表示：“如果成功，关税将为 1985 年广场协议的现代版本奠定基础。但美国没有进行直接谈判，而是施加不对称的经济压力。” 其目标是鼓励贸易伙伴从短期美国国债持有转向长期债务，这可能有助于稳定美国债务市场，同时促进美元可控贬值。 “人们以为关税只是与贸易有关，”帕克补充道。“但如果你退一步来看，它们是一个更广泛的货币战略的一部分——如果执行得当，可能会重塑整个全球金融平衡。” 比特币在货币调整时代的作用 如果美国在维持低借贷成本的同时削弱美元，那么金融环境可能会对比特币等风险资产变得更加有利。Park 解释道： “特朗普的主要目标是降低 10 年期美国国债收益率，原因很简单——他的经济利益依赖于此，尤其是在房地产领域。他敦促鲍威尔降低短期利率，但后来意识到这没有奏效，这是催化剂。永远不要低估那些明显受利润驱动的人的直接动机——与他们保持一致可能是战略性的。” 最初，政府向美联储施压，要求其降息。当这一方法没有产生预期效果时，关税就成了下一个工具。 随着关税增加成本，并拖累主要贸易依赖型经济体的经济增长，外国政府可能会采取货币宽松和财政刺激措施，这可能会导致其货币兑美元贬值。这反过来会将通胀输出回美国，同时增加全球流动性。 从历史上看，寻求防范通货膨胀和货币贬值的投资者已经转向黄金、政府债券和房地产。 如今，比特币提供了另一种选择——一种不受政府控制的、流动的、分散的价值存储方式。帕克认为，美国和外国投资者都会转向比特币，尽管原因不同。 帕克表示，“在美国，比特币可以作为对冲美元疲软和通货膨胀的工具，而在国外市场，它可以提供一种逃避当地货币贬值的方法。” “记住我的话：10 年期国债收益率将会下降——无论需要付出什么代价，”帕克表示。“在美元走弱和美国利率下降的背景下，美国的风险资产可能会超出预期。因此，值得拥有的资产是比特币。” 尽管一些人认为抛售只是暂时的反应，但另一些人认为这标志着更深层次的经济变化，可能会重塑加密货币在全球金融中的作用。 恐慌性抛售还是根本性转变？ Bitlayer Labs 联合创始人 Kevin He 认为，最近的市场下跌主要是反应过度，但他警告称，其长期影响取决于更广泛的经济状况。 “从短期来看，这看起来像是市场反应过度。但从长远来看，其影响将取决于加密货币市场如何与全球经济环境互动。” 他指出，如果贸易紧张局势升级为经济衰退，机构可能会减少对加密货币等高风险资产的敞口，但比特币也可能吸引更多的避险需求。 “如果贸易战引发全球经济衰退，机构可能会减少对加密货币和科技股的投资，从而导致持续的流动性压力。但如果通胀恶化或资本管制收紧，加密货币可能会吸引避险资本流入，尤其是稳定币和某些 DeFi 资产。” Foresight Ventures 的投资合伙人薛敏也认为，此次抛售是一种情绪反应，而不是经济长期低迷的迹象。 “市场通常与主流金融部门同步发展。比特币最近跌至 91,000 美元，充其量只是一种下意识反应。这场最新的惨败并不是通往令人恐惧的加密货币寒冬的大门。” 虽然短期波动占主导地位，但专家认为，关税可能会引发加密货币市场的结构性转变，从采矿动态到流动性流动。Changelly 研究主管 Daria Morgen 认为，特朗普的经济政策可能会推动更多投资者转向去中心化资产。 “作为一种不受政府控制的技术，加密货币可以成为对冲经济和政治不稳定的手段。具有讽刺意味的是，加密货币的采用可能不是因为直接支持，而是为了躲避政策驱动的波动而加速。” Ghaf Capital 创始合伙人 Rahul Suri 警告称，更高的运营成本可能会将小型矿工挤出市场，从而影响网络安全和交易费用。 “如果关税保持不变，而矿工继续面临运营成本上升，我们可能会看到市场情绪发生持久变化。挖矿成本增加可能会导致交易费用增加，阻碍创新，并加剧长期的看跌趋势。” 然而，一些人认为比特币的挖矿网络将会适应。Yellow Network 董事长 Alexis Sirkia 指出，从历史上看，大型矿工能够搬迁或适应新的经济条件。 “虽然任何额外的硬件要求可能会给小型矿工带来压力，但大型机构规模的矿工可以适应并保持盈利能力。” 他还指出，成本上升可能导致比特币的盈亏平衡价格上涨，从而可能设定新的价格底线。 “我们看到传统金融市场和加密货币之间的融合日益加深，这表明关税等宏观经济事件将比前几年更直接地影响数字资产。” 接下来会发生什么？ 关税对加密货币的影响仍在显现，但几个关键趋势正在显现。 短期波动可能存在，比特币将对更广泛的市场不确定性做出反应。但是，如果通胀上升或全球流动性收紧，加密货币可能会成为对冲经济不稳定的手段。 虽然长期前景依然强劲，但过度杠杆的交易者和那些押注立即反弹的交易者应该谨慎行事——宏观经济冲击仍可能重塑竞争环境。

别介意比特币的波动性极高。一些家长看得更远，选择投资加密货币，而不是传统的 529 大学储蓄计划，希望尽管有风险，也能获得更高的回报。 据彭博社报道，越来越多的家庭将比特币作为对冲通胀的工具。12 月份通胀情况进一步恶化，消费者价格同比上涨 2.6%。这一涨幅高于 11 月份的 2.4%。 赌注是，比特币是一种比传统 529 计划等传统储蓄账户具有更强长期增长潜力的资产。 这些家长认为，随着时间的推移，比特币可能会产生更好的效果。 你可能还喜欢：本周值得关注的顶级加密货币：Litentry、Flare、Pi Network CryptoCoinToss 是一个深入探讨加密货币投资各个方面的博客，它也有类似的看法。据一篇博文称，比特币的通货紧缩性质是父母将其作为替代储蓄工具（例如国家支持的 529 计划）的有力理由。 为什么？尽管 529 大学储蓄计划可以帮助个人节省教育费用，并具有一定的税收优惠，但它也存在缺点。资金必须严格用于与学校相关的费用（即学费、书籍、食宿）。如果高中毕业生希望使用这些资金创业或出国旅行，则提款将面临 10% 的罚款和税款。 此外，529 资产可能会降低获得助学金的资格，尤其是如果由祖父母拥有的话。各州的具体规定各不相同，有些计划提供的税收优惠比其他计划更好，而高费用可能是一个缺点。尽管存在这些限制，529 计划仍然是大学储蓄的热门选择。 Upromise 上发布的一篇博客概述了使用加密货币进行大学储蓄对经济援助和税收的影响。比特币和其他虚拟货币在 FAFSA 表格上被视为资产，这意味着必须报告它们，并且会影响经济援助资格。 如果出售后获得收益，利润将计入调整后总收入，从而可能减少援助。 尽管比特币很有吸引力，但理财顾问警告不要全押。与 529 计划不同，比特币投资不提供免税的教育费用提款，而且其价格波动可能使其成为短期学费需求的风险赌注。 尽管如此，一些家长仍在寻找平衡——维持传统的 529 计划，同时将部分储蓄分配给比特币，以期获得长期收益。 随着机构对比特币的采用不断增加，以及交易所交易基金（ETF）等新投资工具的出现，使用加密货币进行大学储蓄的争论可能会愈演愈烈。 特朗普会改变529计划吗？ 只有少数几所美国学校（纽约国王学院和宾大沃顿商学院）接受比特币支付学费，其他几所国际机构也接受。但是，学生贷款不能直接用比特币支付，需要持有者先出售他们的加密货币，这会产生税收后果。

Solana, the popular layer-1 network, is seeing strong network activity that may help its price jump to $200 and above. Solana (SOL) was trading at $147.25 on Wednesday, just below last week’s high of $156. It has jumped by over 52% from its lowest level this year. Third-party data indicates that Solana’s network is performing well, and significantly outperforming Ethereum(ETH) in several key metrics. According to Nansen, Solana processed over 410 million transactions in the last seven days, representing a 10% increase from the previous week. This uptick likely occurred as top meme coins in its ecosystem, such as Fartcoin, Dogecoin, Bonk, and Official Trump, all surged.  You might also like:Can SOL price rise to $500 as Solana meme coins surge? The spike in transactions led to a 22% increase in fees collected by the network, generating over $9.3 million in that period. In contrast, Ethereum handled over 8.6 million transactions during the same timeframe, making Solana 47 times more active. It also generated $4.45 million in fees, significantly less than Solana during this period. This divergence has been consistent over the last 30 days, with Solana processing 1.58 billion transactions compared to Ethereum’s 36 million. TokenTerminal data shows that Solana’s network fees have jumped to over $400 million so far this year, while Ethereum has made $241 million. Solana is also beating Ethereum in other numbers. For example, its decentralized exchange protocols have handled over $68 billion in volume in the last 30 days, while Ethereum’s ones processed $56 billion.  Solana price technical analysis SOL price chart | Source: crypto.news The daily chart shows that Solana bottomed at $94.87 earlier this month as concerns about its meme coin ecosystem rose. It then recovered and moved to a high of $156.55 last week. SOL remains above the important support level at $121, the lowest level from June, July, August, and September of last year. It has also moved above the 50-day and 25-day Weighted Moving Averages. It is currently forming a bullish flag pattern, characterized by a tall flagpole followed by consolidation. This pattern often leads to a strong breakout. If that happens, the short-term outlook turns bullish, with an initial target at the psychological level of $200. Such a move would represent a 32% increase from the current level. A drop below the support at $121 would invalidate the bullish outlook. You might also like:XDC Network unlocks omnichain interoperability with LayerZero integration

随着美国证券交易委员会在唐纳德·特朗普总统的领导下采取新的做法，发行人正在重新考虑将质押作为以太坊交易所交易基金的一部分。 在加密货币交易所交易基金申请热潮中，美国证券交易委员会已承认另一项尝试，即将质押重新引入为现货以太坊 (ETH) 交易所交易基金的组成部分。 Cboe BZX Exchange 代表 21Shares 为该公司的 21Shares Core Ethereum ETF 提交的一份文件称：“发起人代表信托质押的以太币将完全由信托拥有的以太币组成。” 你可能还喜欢：专家：现货以太币 ETF 并非行业所认为的利好 去年，当发行人提交在美国国家交易所上市和交易以太坊基金的申请时，将质押纳入交易所交易基金的讨论被广泛讨论。 在前主席 Gary Gensler 领导的美国证券交易委员会反对这一想法后，人们对以太坊质押将被允许进入交易所交易基金的预期有所减弱。该机构工作人员指示所有潜在的以太坊现货交易所交易基金发行人从其申请中删除与质押相关的语言。 该指令与 Gensler 的立场一致，即权益证明代币应归类为证券，并且权益证明服务必须在该机构注册才能合法运营。 詹斯勒的离职和特朗普总统重返华盛顿标志着美国证券交易委员会的做法发生了转变。该机构的加密货币工作组由代理主席马克·乌耶达 (Mark Uyeda) 建立，最近与 Jito Labs 和 Multicoin Capital 会面，讨论以太坊 ETF 的质押问题。 这些讨论的结果尚不清楚。不过，该机构已承认至少有两份文件征求公众意见，以决定是否允许以太坊质押进入华尔街 ETF。上周，纽约证券交易所 Arca 提议批准 Grayscale 的以太坊交易所交易基金套件中的质押，这表明该机构正在重新推动将质押纳入受监管的投资产品。 阅读更多：加密货币工作组与 Jito、Multicoin 讨论 ETF 质押事宜

Disclosure: The views and opinions expressed here belong solely to the author and do not represent the views and opinions of crypto.news’ editorial. The fall of Mantra (OM), the native token of the layer-1 real-world asset blockchain Mantra, shook the crypto market on April 13. Within hours, the asset saw its market cap plunge from over $6 billion to around $500 million. You might also like:AI is creating a new class of entrepreneurs, and you’re either in or out | Opinion In a market already scarred by billion-dollar collapses, the collapse of Mantra’s native asset proved yet again that hacks aren’t the only enemy to the industry—crypto has been crippled by negligence. The team behind Mantra blamed “forced liquidations” for the 90% token crash, which is only half of the story.  As more data surfaces, it’s becoming clear that the collapse wasn’t just a case of unfortunate timing or high market volatility. It was a preventable disaster that had many catalysts, like overleveraged positions, weak liquidity, and various gaps in its automated risk management systems. Ironically, artificial intelligence, the technology that crypto evangelists have been praising over the last three years, could have predicted, flagged, and even prevented this crash, had it been implemented properly. AI-driven liquidity stress testing The problem with traditional financial stress testing is that it is designed for stable, regulated markets and conventional assets like stocks and bonds, where extreme volatility is rare. Cryptocurrencies, on the other hand, operate in a different reality where wild price swings and sudden liquidity crashes are pretty common and part of the market game. Legacy risk frameworks that rely on historical patterns fail to capture these shocks. AI-driven stress testing offers a dynamic alternative. Instead of relying on static historical data, machine learning models adapt to real-time conditions, analyzing market sentiment, on-chain metrics, and liquidity patterns. A new method called kurtosis-based stress testing focuses on reducing the risk of extreme outlier losses, precisely the “fat tail” events that characterize crypto market failures. This technique can help firms in “less predictable, high-impact” events like the recent Mantra and the 2022 Terra (LUNA) crashes. During the Terra collapse in 2022, traditional risk models failed because they didn’t anticipate how quickly a stablecoin de-peg could spiral into a $60 billion wipeout. The research shows that portfolios designed to reduce extreme risk swings delivered a 491% return with the kurtosis model, beating the simpler ‘buy-and-hold’ approach at 426% and even outperforming those built around traditional Sharpe ratio strategies, with a 384% return. A high kurtosis value indicates a higher probability of extreme volatility. In crypto, these events aren’t anomalies—they’re part of the landscape. Mantra’s exposure to thin weekend liquidity and token concentration could have been flagged well in advance with AI-powered stress testing methods, offering stakeholders a window to act before catastrophe struck. Tracking and flagging movements with AI Blockchain’s transparency is its greatest strength, yet monitoring millions of transactions manually is impossible. This is where AI excels. Autonomous AI agents can continuously scan on-chain activity and flag unusual patterns that might indicate impending market manipulation, all without the need for human involvement. In Mantra’s case, blockchain data analyzed after the crash revealed telling signs. Just days before the collapse, a wallet linked to Laser Digital reportedly transferred 6.5 million OM tokens to another wallet, which then sent them to OKX, where they were liquidated. An AI monitoring system could have detected these movements in real time, issuing immediate alerts to exchanges, regulators, and the broader community. AI agents can distinguish routine market behavior from potential manipulations since they don’t just track transactions but also build behavioral profiles across wallet networks.  Predicting order book vulnerabilities Perhaps the most direct way AI could have prevented the Mantra crash is through sophisticated order book analysis. Order books reveal the true health of a market, but their complexity demands more than just surface-level analysis. Deep learning models, particularly Convolutional Neural Networks and Long Short-Term Memory networks, have proven to deliver promising results in forecasting price movements based on order book data. One study found that temporal CNNs can predict Bitcoin (BTC) price shifts with up to 76% accuracy. AI-driven analysis of market depth would have highlighted the risk of significant slippage from large sell orders—conditions ripe for a cascading price collapse. Consequently, these models could have exposed Mantra’s fragility by identifying dangerously thin order books during weekend trading hours.  With the help of AI and deep learning models, crypto firms can implement dynamic safeguards like circuit breakers triggered by sharp price drops and structural weaknesses in liquidity to flag or prevent situations similar to Mantra. Building a resilient crypto ecosystem with AI While blockchain technology promises decentralization and transparency, it remains vulnerable without advanced AI-powered risk management systems that can process millions of transactions and flag suspicious patterns. The collapse of high-profile assets like Mantra and Terra has proven the need for these systems. Financial institutions with crypto exposure must prioritize dynamic stress testing frameworks that integrate both on-chain and off-chain data. Real-time transaction monitoring, powered by AI agents, needs to be the standard practice for exchanges and liquidity providers. Continuous order book analysis is also crucial to anticipate slippage risks and prevent manipulation-driven crashes. At this point, crypto companies are having a hard time catching up to the global regulations, with every region having its own set of limitations. Sometimes, regulatory frameworks take years to be negotiated and assessed properly. The Markets in Crypto-Assets Regulation (MiCA), for example, was proposed in September 2020 and was officially adopted on May 31, 2023, but was still incomplete—some rules for stablecoins were announced in June 2024, and provisions for crypto-asset service providers were announced in December 2024.  Despite the sensitivity of these regulations, they still fail to encapsulate the complexity, speed, and volume of data that define blockchain ecosystems today. Consequently, regulators are left with rules designed for yesterday’s problems. Instead of imposing blanket and one-size-fits-all restrictions that stifle innovation, AI-powered tools can also help regulatory bodies with more effective oversight. Government agencies can focus on detecting manipulation patterns and systemic risks without compromising decentralization principles to ultimately make timely and accurate decisions. From prediction to prevention The Mantra crash wasn’t inevitable. Most of the tools and techniques that could’ve predicted it already exist, but what’s missing is the industry’s will to implement them. Companies need to start integrating advanced and more complex risk management into broader enterprise frameworks rather than treating it as a separate domain. Investing in cross-functional expertise spanning quantitative modeling, blockchain infrastructure, and compliance isn’t just a luxury anymore; it’s a necessity to protect market integrity. Crypto firms should benchmark against emerging global standards like MiCA and Basel crypto frameworks and leverage both on-chain analytics and real-time exchange data for comprehensive monitoring. The projects, exchanges, and institutions that embrace these methodologies will gain both competitive advantage and community trust. Most importantly, they can build a crypto ecosystem where innovation thrives without the constant threat of market manipulation and catastrophic crashes. The question is no longer if AI should be integrated into crypto risk management, but how soon the industry is ready to embrace it before the next crisis unfolds, and more investors are hurt. This isn’t just about protecting individuals, but also the reputation of the whole ecosystem. Every major collapse, hack, and rug pull hurts the public’s trust in the crypto market. This allows the regulators to push for stronger regulations. AI can complement the decentralized ecosystem and help identify bad actors, detect systemic vulnerabilities, and separate credible builders from those exploiting the system.  Read more:Open-source AI isn’t the end-all game—Bringing AI onchain is | Opinion Ahmad Shadid Ahmad Shadidis the Founder of O.XYZ, an ecosystem with a mission to build the world’s first sovereign superintelligence, and the Сo-Founder of IO.net, a Solana-based decentralized infrastructure provider (DePIN). Being a trailblazing entrepreneur and a serial founder at the intersection of web3 and AI, Ahmad is renowned for transforming ambitious ideas into world-changing ecosystems. As the mastermind behind IO.net, Ahmad led the company to a stunning $4.5 billion valuation in under a year. He personally invested $130 million in O.XYZ, which demonstrates his commitment to redefining AI for the benefit of society rather than corporate interests.