美联储主席凯文·沃什将于7月14日就加息辩论出席国会听证

TheNewsCryptoPublished on 2026-06-23Last updated on 2026-06-23

Abstract

美联储主席凯文·沃什将于7月14日出席美国众议院金融服务委员会的听证会,向国会首次评估美联储的货币政策。此次听证会正值联邦公开市场委员会会议前夕,投资者密切关注其证词,以获取有关通胀状况与利率政策的线索。 当前,投资者和政策制定者的焦点已转向个人消费支出价格指数,这是美联储衡量通胀的关键指标。分析师预计5月份PCE通胀环比上涨0.5%。近期的通胀预测已促使部分金融机构调整政策展望,例如美国银行目前预测美联储将在9月、10月和12月的会议上各加息25个基点,这与早前认为今年政策将保持不变的预测形成对比。 市场预测显示,对美联储7月加息的预期概率约为25%,但9月加息的可能性已超过50%。尽管市场普遍预期7月会议不会采取行动,但对下半年利率走高的定价正在增加。在沃什准备国会作证之际,市场持续聚焦通胀趋势、经济数据及利率预期,以判断未来的政策路径。

美联储主席凯文·沃什将在众议院金融服务委员会前评估央行的货币政策。听证会定于7月14日举行,距离联邦公开市场委员会(FOMC)会议仅剩数周。这将是沃什在即将到来的听证会上首次向国会评估美联储的货币政策。

联邦法规要求美联储主席每年两次向国会汇报货币政策。预计沃什还将出席参议院银行委员会的另一场听证会。由于政策制定者持续密切关注美国经济中的通胀状况,投资者们正等待着沃什的证词。外界预期,委员会成员将就经济形势征求他的意见。

通胀数据仍是焦点

与此同时,投资者和政策制定者已将注意力转向个人消费支出价格指数,这是美联储用来衡量通胀的指标。分析师预计,5月份的PCE通胀环比4月上涨0.5%。近期的通胀预测已促使一些金融机构重新审视其货币政策展望。美国银行目前预测,美联储将在三次会议上以每次25个基点的幅度加息。该机构预计美联储将在9月、10月和12月的联邦公开市场委员会会议上进一步加息。此前的预测曾认为美联储将在全年保持政策措施不变。

市场消化进一步加息预期

预测市场继续显示出对美联储未来举措的不确定性。据估计,美联储在7月采取行动的概率约为25%。尽管投资者继续预计美联储在即将到来的7月会议上不会有所行动,但市场正越来越多地消化今年晚些时候利率上升的预期。

根据CME FedWatch的数据,市场认为美联储在9月收紧政策的可能性超过50%。投资者继续分析现有的经济数据,以评估进一步的政策动向。在沃什为出席国会做准备之际,市场持续关注通胀趋势、经济状况以及利率预期。

重点加密货币新闻:
英国央行在2027年推出前软化最终框架中的稳定币规则

标签区块链加密货币美联储美国国会美国众议院

Trending Cryptos

Related Questions

Q美联储主席凯文·沃什将于何时在哪个国会委员会就货币政策作证?

A美联储主席凯文·沃什将于7月14日在众议院金融服务委员会就货币政策作证。

Q根据美国银行的最新预测,美联储可能在哪些会议上加息?

A根据美国银行的最新预测,美联储可能在9月、10月和12月的联邦公开市场委员会会议上加息。

Q目前市场预期美联储在7月份加息的概率大约是多少?

A根据预测市场的估计,目前市场预期美联储在7月份加息的概率约为25%。

Q美联储衡量通胀的主要指标是什么?五月份该指标预计将如何变化?

A美联储衡量通胀的主要指标是个人消费支出价格指数。分析师预计,五月份该指数将比四月份上涨0.5%。

Q除了众议院金融服务委员会,沃什主席还预计将在哪个委员会出席听证会?

A除了众议院金融服务委员会,沃什主席还预计将在参议院银行委员会出席另一场听证会。

Related Reads

You Use Claude and Codex Every Day, but Meta Has Restricted Internal Use

In May, Meta imposed internal restrictions on its engineers regarding the use of Claude Code and Codex, two widely used AI programming tools. Despite being a major client, Meta's guidelines, still in effect, prohibit these external models from being used for specific tasks to prevent potential "escalations with partners." The core concern is "distillation"—the risk that outputs from Claude or Codex could inadvertently contaminate the training data and evaluation processes for Meta's in-house AI coding assistant, MetaCode. If MetaCode is trained or evaluated using data generated by these external models, it risks learning their capabilities rather than developing its own, blurring the line of intellectual origin. The restrictions are precise: engineers cannot use the external models to generate test questions, debug source code, or suggest test cases. AI-generated content is also barred from environments accessible to MetaCode. However, AI can still assist with peripheral tasks like workflow setup and code organization, provided all outputs are manually reviewed. This caution reflects a broader industry dilemma. While distillation is a common technique, using a competitor's model output for training raises legal and ethical questions about the ownership of derived capabilities. Contractual terms from companies like OpenAI and Anthropic explicitly forbid using their outputs to build competing products, putting enforcement power in the hands of rivals. The move is also financially motivated, as Meta seeks to reduce its hefty internal AI spending, estimated in the billions this year. Meta's policy illustrates the delicate balance companies must strike: leveraging powerful external AI tools while safeguarding the integrity and independence of their own AI development. As AI systems increasingly help build other AIs, distinguishing the origin of capabilities becomes a fundamental challenge for the entire industry.

marsbit2h ago

You Use Claude and Codex Every Day, but Meta Has Restricted Internal Use

marsbit2h ago

Why Do We Need an AI Content Perspective Today?

The article "Why Do We Need an AI Content Perspective Today?" explores the complex and often contentious integration of AI into the cultural and creative industries, particularly film and television. It begins with the cancellation of Amazon's AI-generated animation "Punky Duck," highlighting the ethical debates surrounding AI content. AI's rapid advancement is transforming video production, enabling cost-effective, full-length AI films (e.g., "RAPHAEL," "Dreams of Violets") while sparking industry resistance over issues like "synthetic actors." The core debate has shifted from whether to use AI to how to use it responsibly. The article analyzes why AI's entry into film is uniquely unsettling. It distinguishes between "cultural fast food" (short-form, fast-paced content like micro-dramas) and "cultural main courses" (traditional, long-form film/TV). AI currently excels at the former, matching its fragmented narratives, shallow emotional needs, and free-to-consumer models. However, venturing into the latter challenges the human-centric essence of storytelling—creativity, emotional depth, and the unique value of human labor and experience. While AI can generate massive volumes of content and lower costs, it risks devaluing human creativity, leading to homogenized output, and creating unfair competition through potential intellectual property infringement. Its efficiency also amplifies content safety risks, making preemptive governance crucial. To counter these risks, the article proposes establishing clear boundaries guided by a human-centered AI content perspective. It outlines four principles: 1) Amplify, rather than displace, human creative space; 2) Respect and protect human creative output; 3) Ensure human creative control and responsibility remain paramount; and 4) Guarantee transparency and traceability in AI creation. The conclusion emphasizes that humans must act as the "helmsmen" of technology, steering AI development to enhance, not replace, the core human values at the heart of cultural expression.

marsbit2h ago

Why Do We Need an AI Content Perspective Today?

marsbit2h ago

Trading

Spot

Hot Articles

What is $BANK

Bank AI: A Revolutionary Step in the Future of Banking Introduction In an era marked by rapid advancements in technology, Bank AI stands at the intersection of artificial intelligence (AI) and banking services. This innovative project seeks to redefine the financial landscape, enhancing operational efficiency, security measures, and customer experiences through the power of AI. As we embark on this exploration of Bank AI, we will delve into what the project entails, its operational dynamics, its historical context, and significant milestones. What is Bank AI? At its core, Bank AI represents a transformative initiative aimed at integrating artificial intelligence into various banking operations. This project harnesses the capabilities of AI to automate processes, improve risk management protocols, and enhance customer interaction through personalised services. The primary objectives of Bank AI include: Automation of Banking Functions: By leveraging AI technologies, Bank AI aims to automate routine tasks, reducing the burden on human resources and enhancing efficiency. Enhanced Risk Management: The project utilises AI algorithms to predict and identify risks, thereby fortifying security measures against fraud and other threats. Personalisation of Banking Services: Bank AI focuses on offering tailored financial products and services by analysing customer data and behaviours. Improving Customer Experience: The implementation of AI-driven solutions, such as chatbots and virtual assistants, aims to provide users with more human-like interactions, revolutionising the way customers engage with banks. With these goals, Bank AI positions itself as a crucial player in rendering banking more efficient, secure, and user-centric. Who is the Creator of Bank AI? Details regarding the creator of Bank AI remain unknown. As such, no specific individual or organisation has been identified in the available information. The anonymity surrounding the project's inception raises questions but does not detract from its ambitious vision and objectives. Who are the Investors of Bank AI? Similar to the project's creator, specific information regarding the investors or supporting organisations of Bank AI has not been disclosed. Without this information, it is challenging to outline the financial backing and institutional support that might be propelling the project forward. Nevertheless, the importance of having a robust investment foundation is pivotal for sustaining development in such an innovative field. How Does Bank AI Work? Bank AI operates on several innovative fronts, focusing on unique factors that differentiate it from traditional banking frameworks. Below are key operational features: Automation: By applying machine learning algorithms, Bank AI automates various manual processes within banks. This results in reduced operational costs and allows human workers to redirect their efforts towards more strategic activities. Advanced Risk Management: The integration of AI into risk management practices equips banks with tools to accurately predict potential threats such as fraud, ensuring that customer information and assets remain secure. Tailored Financial Recommendations: Through continuous learning from customer interactions, the AI systems develop a nuanced understanding of user needs, enabling them to offer tailored advice on financial decisions. Enhanced Customer Interactions: Utilizing chatbots and virtual assistants powered by AI, Bank AI enables a more engaging customer experience, allowing users to have their queries resolved quickly, thus reducing wait times and improving satisfaction levels. Together, these operational features position Bank AI as a pioneer in the banking sector, establishing new benchmarks for service delivery and operational excellence. Timeline of Bank AI Understanding the trajectory of Bank AI requires a look at its historical context. Below is a timeline highlighting important milestones and developments: Early 2010s: The conceptualisation of AI integration into banking services began to gain attention as banking institutions recognised the potential benefits. 2018: A marked increase in the implementation of AI technologies occurred when banks started using AI tools like chatbots for basic customer service and risk management systems for improved security handling. 2023: The sophistication of AI continued to advance, with generative AI being introduced for more complex tasks such as document processing and real-time investment analysis. This year marked a significant leap in the capabilities afforded to banks by AI technology. 2024-Current Status: As of this year, Bank AI is on an upward trajectory, with ongoing research and developments poised to further enhance capabilities in banking operations. Continued exploration of AI applications hints at exciting developments yet to come. Key Points About Bank AI Integration of AI in Banking: Bank AI focuses on adopting artificial intelligence to streamline banking processes and improve user experiences. Automation and Risk Management Focus: The project strongly emphasises these areas, aiming to shift the burden of routine tasks while enhancing security frameworks through predictive analytics. Personalised Banking Solutions: By harnessing customer data, Bank AI enables tailored banking services that cater to individual user needs. Commitment to Development: Bank AI remains committed to ongoing research and development efforts, ensuring its adaptability and ongoing relevance as technology continues to evolve. Conclusion In summary, Bank AI exemplifies a crucial step forward in the banking industry, leveraging artificial intelligence to reshape operational paradigms, enhance security, and promote customer satisfaction. Despite gaps in information surrounding the creator and investors, the clear objectives and functional mechanisms of Bank AI provide a strong foundation for its ongoing evolution. As AI technology continues to advance and merge with the banking sector, Bank AI is well-positioned to significantly impact the future of financial services, enhancing the way we understand and interact with banking.

172 Total ViewsPublished 2024.04.06Updated 2024.12.03

What is $BANK

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of BANK (BANK) are presented below.

活动图片