A Policymaker’s View of Financial Stability
At Georgetown University’s McDonough School of Business Psaros Center for Financial Markets and Policy, Washington, D.C.
乔治城大学麦克多诺商学院 Psaros 金融市场与政策中心，华盛顿特区
Thank you, Reena.
谢谢你，瑞娜。
It is an honor to be back at Georgetown and at the Psaros Center.
很荣幸回到乔治城和普萨罗斯中心。
1 I have spent a significant amount of time on and around this campus, including when I served as a congressional intern early in my career.
1 我在这个校园及其周围度过了大量时间，包括在我职业生涯早期担任国会实习生时。
Perhaps in fate's way of foreshadowing, one of the topics I researched that summer was the Glass-Steagall Act.
也许是命运的预示，那年夏天我研究的主题之一就是《格拉斯-斯蒂格尔法案》。
Turns out that it was handy to learn about at a young age.
事实证明，在年轻的时候学习是很方便的。
Financial stability is a focal point of my attention at the Board of Governors, since I serve as chair of the Board's Committee on Financial Stability.
由于我担任理事会金融稳定委员会主席，金融稳定是我在理事会关注的焦点。
Allow me to start by saying that the financial system remains resilient, supported by strong balance sheets among households and businesses and high capital levels across the banking system.
首先请允许我说，在家庭和企业强劲的资产负债表以及整个银行体系的高资本水平的支持下，金融体系仍然具有弹性。
Earlier this month, the Fed issued the most recent version of our semiannual Financial Stability Report.
本月早些时候，美联储发布了最新版本的半年度金融稳定报告。
That report affirmed the system is resilient, while also noting some of the same risks and vulnerabilities we have seen in recent reports.
该报告肯定了该系统具有弹性，同时也指出了我们在最近的报告中看到的一些相同的风险和漏洞。
My remarks will center on three areas of vulnerabilities: asset valuations; the structural shift in lending to private companies, away from traditional bank loans and toward private credit arrangements; and the growing role of hedge funds as investors in the U.S. Treasury market.
我的讲话将集中在三个脆弱领域：资产估值；对私营企业贷款的结构性转变，从传统的银行贷款转向私人信贷安排；对冲基金作为美国国债市场投资者的作用日益增强。
Finally, I will turn to a longer-term issue—the potential for the use of generative artificial intelligence (AI) in financial market trading that could both increase and decrease financial stability.
最后，我将转向一个更长期的问题——在金融市场交易中使用生成人工智能（AI）的潜力，它既可能增加也可能降低金融稳定性。
Let's begin by putting financial-system vulnerabilities into context.
让我们首先了解一下金融体系的脆弱性。
The Federal Reserve promotes financial stability in order to support the achievement of its dual mandate of promoting maximum employment and price stability.
美联储促进金融稳定，以支持实现其促进就业最大化和价格稳定的双重使命。
That is, achieving maximum employment and price stability depends on a stable financial system.
也就是说，实现就业最大化和价格稳定取决于稳定的金融体系。
We know from history, whether from the distant past—the Great Depression—or from the recent past—the Great Financial Crisis or the Great Recession—that financial crises typically lead to large job losses and high unemployment.
我们从历史中知道，无论是从遥远的过去（大萧条）还是从最近的过去（金融危机或大衰退），金融危机通常会导致大量失业和高失业率。
2 However, given the complexity of the financial system, it is sometimes hard to see the connection between the system and everyday life.
2 然而，鉴于金融体系的复杂性，有时很难看出该体系与日常生活之间的联系。
Living and teaching in Michigan during the Great Recession, I saw firsthand how the financial system's fragility contributed directly to job losses.
大衰退期间，我在密歇根州生活和教学，亲眼目睹了金融体系的脆弱性如何直接导致失业。
One example is how the default of Lehman Brothers contributed, via a chain of events, to declines in employment in Michigan.
一个例子是雷曼兄弟的违约如何通过一系列事件导致密歇根州就业下降。
Lehman's failure in September 2008 led a money market fund to "break the buck"—the fall in the value of its assets meant it could no longer redeem shares for the $1 that investors expected to receive—prompting a run on the funds.
2008 年 9 月，雷曼兄弟的倒闭导致货币市场基金“跌破一美元”——资产价值的下跌意味着它无法再以投资者预期收到的 1 美元赎回股票——从而引发了基金挤兑。
In turn, the funds pulled back from riskier assets, including asset-backed commercial paper.
反过来，这些基金从风险较高的资产中撤出，包括资产支持的商业票据。
But the major auto finance companies depended on that commercial paper to finance loans to consumers; hence, they came under stress.
但主要的汽车金融公司依靠商业票据为消费者提供贷款；因此，他们面临着压力。
3 With less credit available, auto sales plummeted, and Michigan was hit very hard.
3 由于可用信贷减少，汽车销量直线下降，密歇根州受到了严重打击。
Many people—including some of my family members, my students' and colleagues' family members, friends, and neighbors—lost their jobs and experienced significant hardship.
许多人——包括我的一些家人、我的学生和同事的家人、朋友和邻居——失去了工作并经历了巨大的困难。
The Michigan unemployment rate exceeded 14 percent in 2009, while the national unemployment rate peaked at 10 percent in 2009.
2009年密歇根州失业率超过14%，而2009年全国失业率达到10%的峰值。
Correspondingly, foreclosures more than tripled in Michigan between 2006 and 2010, and home values in Michigan sank 33 percent over the same period.
相应地，2006 年至 2010 年间，密歇根州取消抵押品赎回权的数量增加了两倍多，同期密歇根州的房价下跌了 33%。
I tell this story, not because I fear we are on the brink of a financial crisis, but because I think it is worth emphasizing why resilience of the financial system matters for the real economy—a point I have made since writing my dissertation—and for everyday Americans' lives.
我讲这个故事，不是因为我担心我们正处于金融危机的边缘，而是因为我认为值得强调为什么金融体系的弹性对实体经济（这是我在写论文后提出的观点）和美国人的日常生活很重要。
A stable and resilient financial system supports employment and stable prices and ensures families and businesses can function effectively in the economy.
稳定和有弹性的金融体系支持就业和稳定的价格，并确保家庭和企业能够在经济中有效运作。
That is why policymakers work diligently to understand the functioning of the financial system and is one reason we publish a financial stability report twice a year.
这就是政策制定者努力了解金融体系运作的原因，也是我们每年两次发布金融稳定报告的原因之一。
And, of course, the story emphasizes the need to maintain resilience in the financial system.
当然，这个故事强调了保持金融体系弹性的必要性。
Asset Valuations With that background, allow me to turn to the financial system vulnerabilities I consider to be most salient currently, beginning with asset valuations.
资产估值 在此背景下，请允许我谈谈我认为目前最突出的金融体系漏洞，首先从资产估值开始。
When we evaluate asset valuations, we do not look at the actual levels of asset prices.
当我们评估资产估值时，我们不看资产价格的实际水平。
Rather, we look at their levels relative to fundamentals and whether their levels relative to fundamentals are high by historical standards.
相反，我们关注的是它们相对于基本面的水平，以及它们相对于基本面的水平按照历史标准是否很高。
4
4
As noted in the Financial Stability Report, our assessment of asset valuations is that they are, on the whole, elevated relative to historical benchmarks in a number of markets, including equity markets, corporate bond markets, leveraged loan markets, and housing markets.
正如《金融稳定报告》中指出的，我们对资产估值的评估是，总体而言，资产估值相对于许多市场的历史基准有所上升，包括股票市场、公司债券市场、杠杆贷款市场和房地产市场。
To be sure, this is not investment advice.
可以肯定的是，这不是投资建议。
Indeed, it is neither my role nor my desire to offer any comment on the merits of different asset valuations.
事实上，对不同资产估值的优点提出任何评论既不是我的职责，也不是我的愿望。
Our role at the Fed is to simply observe that expected compensation for risk is low relative to history—and that might revert, stay low, or even go lower.
我们在美联储的作用是简单地观察预期风险补偿相对于历史水平较低，并且可能会恢复、保持较低水平，甚至更低。
And situations of elevated valuations are quite common.
而且估值升高的情况也很常见。
Asset valuations have been stretched many times since the 2009 trough.
自2009年低谷以来，资产估值已多次上涨。
I consider any potential financial system vulnerability through the lens of how it might constrain the Federal Reserve's ability to attain its dual-mandate goals of maximum employment and price stability.
我从以下角度考虑任何潜在的金融体系脆弱性：它可能会如何限制美联储实现就业最大化和价格稳定双重使命目标的能力。
Currently, my impression is that there is an increased likelihood of outsized asset price declines.
目前，我的印象是资产价格大幅下跌的可能性有所增加。
However, given the system's overall resilience, I do not see the kinds of weaknesses that played out so painfully in the Great Recession, and, thus, I do not see potential asset price declines as posing risks to the financial system.
然而，考虑到该体系的整体弹性，我并不认为大衰退期间会出现如此痛苦的弱点，因此，我不认为潜在的资产价格下跌会对金融体系构成风险。
Private Credit Another potential vulnerability worth watching is the growth of private credit.
私人信贷另一个值得关注的潜在脆弱性是私人信贷的增长。
Fed staff estimate that, over the past five years, private credit has roughly doubled.
美联储工作人员估计，在过去五年中，私人信贷大约增加了一倍。
Whenever we observe such rapid growth in credit over such a short period of time, it draws our attention.
每当我们观察到信贷在如此短的时间内如此快速增长时，都会引起我们的注意。
I use the term private credit to describe loans to privately held businesses that originate from nonbank entities .
我使用私人信贷一词来描述来自非银行实体的向私人企业提供的贷款。
Privately held businesses are companies without publicly traded stock that generally lack access to public capital markets for debt or equity finance.
私营企业是指没有公开交易股票的公司，通常无法进入公共资本市场进行债务或股权融资。
The growth in nonbank lending to privately held businesses has increased credit access.
向私营企业提供非银行贷款的增长增加了信贷准入。
As a result, private businesses that have difficulty securing a loan from a bank can continue to grow their businesses with loans from private credit providers.
因此，难以从银行获得贷款的私营企业可以通过私人信贷提供商的贷款继续发展业务。
In one of its simplest forms, private credit involves a straightforward intermediation chain.
私人信贷最简单的形式之一涉及直接的中介链。
Investors with very long investment horizons and no particular need for liquidity invest in a private credit vehicle, such as a private credit fund or business development company (BDC), which then extends loans to private businesses.
投资期限很长且对流动性没有特别需求的投资者投资于私人信贷工具，例如私人信贷基金或业务发展公司（BDC），然后由这些工具向私营企业提供贷款。
Such investments are usually locked up or ineligible for redemption for five to seven years, or even longer.
此类投资通常被锁定或无资格赎回五至七年，甚至更长时间。
At its best, private credit vehicles conduct due diligence and monitor the loans on behalf of the investors.
在最好的情况下，私人信贷工具代表投资者进行尽职调查并监控贷款。
Private credit vehicles tend to have a strong incentive to monitor these loans and can flexibly respond to emerging distress.
私人信贷工具往往有强烈的动机来监控这些贷款，并能够灵活应对新出现的困境。
This careful monitoring is important, because private businesses are not subject to the same public scrutiny—auditing and disclosure standards—as their public counterparts.
这种仔细的监控很重要，因为私营企业不像公共企业那样受到同样的公众监督——审计和披露标准。
This model has the potential to enhance financial stability and expand economic growth, since it matches longer-maturity loans with longer-term funding and allows firms to get the financing they need on favorable terms.
这种模式具有增强金融稳定性和扩大经济增长的潜力，因为它将较长期限的贷款与长期融资相匹配，并允许企业以优惠的条件获得所需的融资。
Default rates have also been low and returns high.
违约率也很低，回报率也很高。
Nonetheless, we should expand the lens and inspect this funding vehicle more closely.
尽管如此，我们应该扩大视野，更仔细地审视这一融资工具。
We have also seen more complex intermediation chains involving more leveraged players, such as banks and insurance companies, emerge in recent years.
近年来，我们还看到涉及更多杠杆参与者（例如银行和保险公司）的更复杂的中介链的出现。
5 Some private firms may also have multiple sources of funding.
5 一些私营企业也可能有多种资金来源。
The increased complexity and the interconnections with leveraged financial entities create more channels through which unexpected losses in private credit could spread to the broader financial system.
复杂性的增加以及与杠杆金融实体的相互联系创造了更多渠道，私人信贷的意外损失可以通过这些渠道扩散到更广泛的金融体系。
What do recent trends in the sector suggest about the potential for such losses and financial stability risks?
该行业的最新趋势表明此类损失和金融稳定风险的可能性如何？
I do not currently see the potential for private credit to contribute to an unexpected credit crunch in the same way that the asset-backed commercial paper market did in 2008.
我目前并不认为私人信贷有可能像 2008 年资产支持商业票据市场那样导致意外的信贷紧缩。
However, it is well worth keeping a close eye on developments here.
然而，非常值得密切关注这里的事态发展。
Default rates remain low, but they are a backward-looking measure and could also reflect increased usage of payment-in-kind arrangements, or PIKs; loan amendments; and distressed exchanges.
违约率仍然很低，但这是一种向后看的衡量标准，也可能反映出实物支付安排（PIK）的使用增加；贷款修改；以及苦恼的交流。
Recent private business bankruptcies in the auto sector also revealed unexpected losses and exposure across a broad range of financial entities, including banks, hedge funds, and specialty finance companies.
汽车行业最近发生的私营企业破产事件也揭示了银行、对冲基金和专业金融公司等一系列金融实体的意外损失和风险敞口。
Should we expect to see more?
我们应该期待看到更多吗？
There are some reasons to interpret the recent failures as outliers.
有一些理由将最近的失败解释为异常值。
I do not assess the current risks from private credit to be a threat to financial stability.
我不认为当前私人信贷的风险对金融稳定构成威胁。
The businesses that failed recently may have been more exposed to changes in trade and immigration policy, made more use of off-balance sheet financing, or been of poorer credit quality than other private businesses.
最近失败的企业可能更容易受到贸易和移民政策变化的影响，更多地利用表外融资，或者信用质量比其他私营企业较差。
Therefore, it is difficult to infer general lessons from these specific cases.
因此，很难从这些具体案例中得出普遍的教训。
Yet, history teaches us a lesson here.
然而，历史在这里给了我们一个教训。
The likelihood of observing additional cases like those recently in the news increases when size of exposure and level of complexity in these arrangements are not transparent, when a sector experiences periods of rapid growth, and when these arrangements have not been through a full credit cycle (boom and bust).
当这些安排的风险规模和复杂程度不透明、某个行业经历快速增长时期以及这些安排尚未经历完整的信贷周期（繁荣和萧条）时，观察到类似最近新闻中的其他案例的可能性就会增加。
Accordingly, I will continue to focus on ensuring that we understand developments in this sector and how these lending arrangements are evolving over time.
因此，我将继续致力于确保我们了解该领域的发展以及这些贷款安排如何随着时间的推移而演变。
Hedge Fund Footprint in Treasury Markets Another vulnerability I am following carefully is the footprint of hedge funds in the U.S. Treasury market.
对冲基金在国债市场的足迹 我仔细关注的另一个漏洞是对冲基金在美国国债市场的足迹。
This footprint has grown substantially over the past few years and recently just exceeded its previous, pre-pandemic peak.
在过去几年中，这一足迹大幅增长，最近刚刚超过了之前的大流行前峰值。
My focus relates to the potential for transmitting stress to the U.S. Treasury market, which is critical to the functioning of our financial system.
我关注的重点是向美国国债市场传递压力的可能性，这对我们金融体系的运作至关重要。
The U.S. Treasury market is the largest and most liquid financial market in the world.
美国国债市场是世界上最大、流动性最强的金融市场。
Treasury securities, by serving as a source of safe and liquid assets, enable the efficient and stable flow of capital across the global financial system.
国债作为安全和流动资产的来源，使资本在全球金融体系中高效稳定地流动。
The Treasury market averages around $900 billion in transactions per day, with transactions on high-volume days around $1.5 trillion per day in recent years.
美国国债市场平均每天交易额约为 9000 亿美元，近年来交易量高的日子每天交易额约为 1.5 万亿美元。
6 The smooth operation of U.S. Treasury markets is also critical for the transmission and implementation of monetary policy.
6 美国国债市场的平稳运行对于货币政策的传导和实施也至关重要。
Hedge funds' holdings of Treasury cash securities—that is, Treasury bills, notes, and bonds—have increased from representing about 4.6 percent of total Treasury securities outstanding in the first quarter of 2021 to representing 10.3 percent in the first quarter of this year, just above its pre-pandemic peak of 9.4 percent.
对冲基金持有的国债现金证券（即国库券、票据和债券）已从 2021 年第一季度占已发行国债总额的约 4.6% 增至今年第一季度的 10.3%，略高于大流行前 9.4% 的峰值。
7 This represents significant growth in the scale of liquidations that could result, if hedge funds were to sharply reduce their Treasury positions because of changing market conditions.
7 这表明，如果对冲基金因市场条件变化而大幅减少其国债头寸，则可能导致清算规模大幅增长。
We witnessed such an episode at the start of the pandemic during the "dash for cash" when sales of Treasuries by a broad range of market participants increased dramatically and all at once.
我们在疫情爆发之初的“现金抢购”时期目睹了这样的一幕，当时广泛的市场参与者出售的国债突然大幅增加。
8
8
The sensitivity of hedge fund Treasury positions to shifting market conditions depends on the Treasury trading strategies that hedge funds are pursuing.
对冲基金国债头寸对市场条件变化的敏感性取决于对冲基金所追求的国债交易策略。
Staff analysis suggests that the vast majority of hedge fund Treasury positions involve relative value trading strategies, of which there are many types.
工作人员分析表明，绝大多数对冲基金国债头寸都涉及相对价值交易策略，其中有多种类型。
These trades exploit relative price differences between related securities—pairs or combinations of Treasury cash securities, Treasury derivatives, or interest rate derivatives.
这些交易利用相关证券（国债现金证券、国债衍生品或利率衍生品的配对或组合）之间的相对价格差异。
To be sure, outside of episodes of stress, relative value trades substantially improve the efficiency and liquidity of Treasury securities and related markets.
可以肯定的是，除了压力事件之外，相对价值交易大大提高了国债和相关市场的效率和流动性。
Yet, during episodes of stress, the unwinding of crowded positions in such trades could magnify instability in these markets.
然而，在压力时期，此类交易中拥挤头寸的平仓可能会加剧这些市场的不稳定。
Relative value trading strategies typically share key features that create potential Treasury market vulnerabilities.
相对价值交易策略通常具有造成国债市场潜在漏洞的关键特征。
9 For example, relative value trades are highly leveraged to amplify returns from small price differentials, with these trades generally funded with repo that is shorter term than the maturity of the trade, resulting in maturity mismatch.
9 例如，相对价值交易的杠杆率很高，以放大小价差带来的回报，这些交易通常由期限短于交易期限的回购协议提供资金，从而导致期限错配。
As a result, these strategies are exposed to significant funding risks that could arise from instability in repo markets.
因此，这些策略面临着回购市场不稳定可能产生的重大融资风险。
Relative value trades that involve derivative contracts—such as the cash-futures basis trade and the swap-spread trade—are further exposed to margin calls when additional liquidity is required to satisfy increased minimum margin requirements.
当需要额外的流动性来满足提高的最低保证金要求时，涉及衍生品合约的相对价值交易（例如现金期货基差交易和掉期价差交易）会进一步面临追加保证金的风险。
Such adverse funding shocks can result from episodes of market volatility or from moves in relative prices that are disadvantageous to the trade.
这种不利的资金冲击可能是由于市场波动或对贸易不利的相对价格变动造成的。
Sudden funding shocks can then prompt an unwinding of hedge fund positions, resulting in significant Treasury security sales and the potential for market liquidity strains.
突然的资金冲击可能会促使对冲基金头寸平仓，导致大量国债抛售，并可能导致市场流动性紧张。
Increased volatility and losses due to changes in relative prices can also lead hedge funds to choose to exit trades for risk-management reasons, also resulting in large Treasury security sales.
相对价格变化导致的波动性和损失增加也可能导致对冲基金出于风险管理原因选择退出交易，从而导致大量国债出售。
10 All of these features of relative value strategies can make Treasury market liquidity conditions—and, in the extreme, market functioning—more vulnerable to stress.
10 相对价值策略的所有这些特征都可能使国债市场的流动性状况（在极端情况下，市场运作）更容易受到压力。
Note that it is not inevitable that episodes of market volatility will induce an unwinding of relative value trades and, indeed, instances of one of these trades unwinding are rare.
请注意，市场波动事件并非不可避免会导致相对价值交易平仓，事实上，其中一项交易平仓的情况很少见。
As you know, the swap-spread trade—a relative value trade between Treasury securities and interest rate swaps—experienced an unwinding during April's heightened market volatility, because the relative prices of securities at the core of the trade moved in ways that became unfavorable to the trade.
如您所知，掉期价差交易（国债和利率掉期之间的相对价值交易）在 4 月份市场波动加剧期间经历了平仓，因为作为交易核心的证券的相对价格变动对交易不利。
Nonetheless, other relative value trades remained fully intact.
尽管如此，其他相对价值交易仍然完好无损。
This was especially notable for the cash-futures basis trade, reflecting the fact that conditions in repo markets remained orderly throughout the episode.
这对于现金期货基差交易尤其值得注意，反映出回购市场的状况在整个事件中保持有序的事实。
11 Notwithstanding, the paucity of sizable relative value trade unwindings remains a potential impetus for market liquidity strains.
11 尽管如此，大规模相对价值贸易平仓的缺乏仍然是市场流动性紧张的潜在推动因素。
AI Use in Financial Services The potential implications of rapid advancements in AI for financial stability constitute my final topic today.
人工智能在金融服务中的应用人工智能快速进步对金融稳定的潜在影响构成了我今天的最后一个主题。
Just as the scientific revolutions in chemistry and biology brought both life-saving medicines and more potent weapons, the recent advancements in AI have prompted forecasts that run the gamut from utopia to doomsday.
正如化学和生物学领域的科学革命带来了拯救生命的药物和更强大的武器一样，人工智能的最新进展也引发了从乌托邦到世界末日的各种预测。
How do theory and limited evidence inform us thus far about the potential impact of AI on financial stability?
迄今为止，理论和有限的证据如何告诉我们人工智能对金融稳定的潜在影响？
To structure our thinking, I would like to briefly consider one aspect of this question: the use of AI in algorithmic trading in financial markets and the implications for financial stability.
为了构建我们的思维，我想简要考虑这个问题的一个方面：人工智能在金融市场算法交易中的使用以及对金融稳定的影响。
Certainly, sophisticated computer-driven trading algorithms are not new.
当然，复杂的计算机驱动的交易算法并不新鲜。
Traders have been using machine learning and other advanced statistical tools for decades.
数十年来，交易者一直在使用机器学习和其他先进的统计工具。
Trading in many important financial markets is now heavily reliant on algorithms.
许多重要金融市场的交易现在严重依赖算法。
12 But the adoption of generative AI in trading is different and brings new challenges.
12 但在交易中采用生成式人工智能则不同，并带来了新的挑战。
Unlike pre-programmed algorithms with limited flexibility, generative AI is able to quickly review large amounts of data and then autonomously deploy trading strategies that could be opaque to humans.
与灵活性有限的预编程算法不同，生成式人工智能能够快速审查大量数据，然后自主部署对人类来说可能不透明的交易策略。
Used without careful testing and human oversight, generative AI may create risks that are difficult to monitor or mitigate.
在没有仔细测试和人工监督的情况下使用生成式人工智能可能会产生难以监控或减轻的风险。
The use of generative AI in trading may also improve on current algorithmic trading activity, especially if the less rigid models prove able to adjust in ways that stabilize rather than destabilize prices.
在交易中使用生成式人工智能也可能会改善当前的算法交易活动，特别是如果事实证明不太严格的模型能够以稳定而不是破坏价格稳定的方式进行调整。
There is early evidence for both.
两者都有早期证据。
Correlated trading and herding Researchers are only starting to study whether the use of generative AI in trading leads to more or less correlated trading.
相关交易和羊群效应 研究人员才刚刚开始研究在交易中使用生成人工智能是否会导致或多或少的相关交易。
Nonetheless, research so far offers some useful insights.
尽管如此，迄今为止的研究提供了一些有用的见解。
Theory and empirical evidence show that independent but simultaneous actions by high-frequency trading (HFT) algorithms in response to a common signal can indeed generate excess volatility and mispricing, thereby reducing market efficiency.
理论和经验证据表明，高频交易（HFT）算法响应共同信号而独立但同时采取的行动确实会产生过度波动和错误定价，从而降低市场效率。
13 Not all algorithms are created equal.
13 并非所有算法都是一样的。
Studies have also shown instances when correlated trading by HFTs improved price discovery without increasing volatility.
研究还表明，高频交易的关联交易在不增加波动性的情况下改善了价格发现。
14 Research also shows widespread use of popular arbitrage strategies helped eliminate mispricing across fragmented markets.
14 研究还表明，流行套利策略的广泛使用有助于消除分散市场中的错误定价。
15 In other words, correlated trading by algorithms can, at times, also benefit market quality and efficiency.
15 换句话说，通过算法进行的关联交易有时也有利于市场质量和效率。
A recent experimental study by Fed economists demonstrates that algorithmic strategies relying on generative AI may also be less prone to herding behavior—by which I mean ignoring private information and imitating others—than human traders.
美联储经济学家最近的一项实验研究表明，与人类交易者相比，依赖生成式人工智能的算法策略也不太容易出现羊群行为（我的意思是忽略私人信息并模仿他人）。
In this experiment, the AI agents were less influenced by the cognitive biases that sometimes drive human investment decisions.
在这个实验中，人工智能代理受到认知偏见的影响较小，而认知偏见有时会驱动人类投资决策。
16
16
Collusion, market manipulation, and concentration Researchers have also pointed to the risk that generative AI could engage in collusion and market manipulation, rigging the system to favor those employing the technology.
共谋、市场操纵和集中研究人员还指出，生成式人工智能可能会参与共谋和市场操纵，操纵系统以偏向那些使用该技术的人。
Recent theoretical studies find that some AI-driven trading algorithms can indeed learn to collude without explicit coordination or intent, potentially impairing competition and market efficiency.
最近的理论研究发现，一些人工智能驱动的交易算法确实可以在没有明确协调或意图的情况下学会串通，这可能会损害竞争和市场效率。
17 However, others observe that the possibility of collusion rests on the assumption that all traders use very similar algorithms.
17 然而，其他人观察到，共谋的可能性取决于所有交易者都使用非常相似的算法的假设。
They argue that algorithmic traders have strong incentives to differentiate their trading strategies, because noncollusion can be highly profitable when others collude.
他们认为，算法交易者有强烈的动机来区分他们的交易策略，因为当其他人共谋时，非共谋可以带来高额利润。
18 Thus, according to these views, the likelihood of tacit algorithmic collusion arising in real-world financial markets is very small.
18 因此，根据这些观点，现实世界金融市场中出现默认算法共谋的可能性非常小。
Beyond collusion, there is also the troubling possibility that AI trading systems could learn to manipulate markets.
除了串通之外，人工智能交易系统还可能学会操纵市场，这种可能性也令人不安。
A recent theoretical study shows that self-learning, profit-maximizing algorithms can unintentionally discover spoofing strategies—that is, placing large orders they never intend to execute just to create false impressions of market demand.
最近的一项理论研究表明，自学习、利润最大化的算法可能会无意中发现欺骗策略，即下达他们从未打算执行的大订单，只是为了制造对市场需求的错误印象。
19 Potentially, some new AI systems could operate with greater opacity, execute more complex trades, and better hide manipulative intent than old-fashioned dishonest human traders.
19 与老式不诚实的人类交易者相比，一些新的人工智能系统可能会以更大的不透明度运行，执行更复杂的交易，并更好地隐藏操纵意图。
Additionally, there are growing concerns that results obtained from complex AI models may be difficult to explain or rationalize by human experts—the "black box" problem.
此外，人们越来越担心从复杂的人工智能模型获得的结果可能难以由人类专家解释或合理化——“黑匣子”问题。
20 The inability to fully audit trades executed by algorithms makes surveillance by trading venues and regulators more challenging.
20 由于无法全面审核算法执行的交易，使得交易场所和监管机构的监控更具挑战性。
The good news here is that major electronic trading platforms are also rapidly adopting advanced machine learning techniques to detect market manipulation and collusive behavior.
好消息是，主要电子交易平台也在迅速采用先进的机器学习技术来检测市场操纵和串通行为。
21 Thanks to improving surveillance capabilities, AI technology could ultimately strengthen market integrity and enhance market liquidity.
21由于监控能力的提高，人工智能技术最终可以加强市场诚信并提高市场流动性。
Trading venues are also taking steps to mitigate the risk stemming from the "black box" problem associated with AI-enabled trading algorithms.
交易场所也在采取措施减轻与人工智能交易算法相关的“黑匣子”问题带来的风险。
For example, the Chicago Mercantile Exchange (CME) recently reminded its members that they must be able to fully explain and reproduce any decisions or actions taken by their algorithms on the CME market.
例如，芝加哥商品交易所（CME）最近提醒其会员，他们必须能够充分解释和重现其算法在 CME 市场上采取的任何决定或行动。
22 Such initiatives may limit the deployment of generative AI and other stochastic algorithms for direct trade execution on major trading venues.
22此类举措可能会限制生成式人工智能和其他随机算法在主要交易场所直接执行交易的部署。
Last but not least, the debate is also growing as to whether the adoption of generative AI in trading algorithms may increase concentration due to high investment barriers (as seen with one liquidity provider using 25,000 GPUs and building billion-dollar infrastructure) or decrease concentration by democratizing access to sophisticated capabilities previously limited to large institutions.
最后但并非最不重要的一点是，关于在交易算法中采用生成式人工智能是否会因高投资壁垒而提高集中度（正如一个流动性提供者使用 25,000 个 GPU 并建设数十亿美元的基础设施所见），还是通过使以前仅限于大型机构的复杂功能民主化而降低集中度，这一争论也日益激烈。
23
23
Taken together, areas to watch carefully have emerged, as well as potential ways we will benefit from this new technology.
总而言之，需要仔细观察的领域已经出现，以及我们将从这项新技术中受益的潜在方式。
Conclusion Back to my broader themes, the financial system remains resilient.
结论 回到我更广泛的主题，金融体系仍然具有弹性。
Yet, vulnerabilities from elevated asset values, growth and complexity in private credit markets, and the potential for hedge fund activity to contribute to Treasury market dislocation warrant attention.
然而，资产价值上升、私人信贷市场的增长和复杂性以及对冲基金活动可能导致国债市场混乱带来的脆弱性值得关注。
These emerging vulnerabilities also occur against a backdrop of very significant technological change.
这些新出现的漏洞也是在非常重大的技术变革的背景下出现的。
These innovations may ultimately improve financial stability but also involve transitions and potential challenges that may require thoughtful and deliberate navigation.
这些创新可能最终会改善金融稳定性，但也涉及可能需要深思熟虑的转型和潜在挑战。
My focus going forward will be on working with my colleagues to navigate these opportunities and vulnerabilities to ensure the financial system remains strong and resilient.
我未来的重点将是与我的同事合作，驾驭这些机遇和脆弱性，以确保金融体系保持强大和弹性。
1.
1.
The views expressed here are my own and are not necessarily those of my colleagues on the Federal Reserve Board or the Federal Open Market Committee.
这里表达的观点是我自己的观点，不一定是我在美联储委员会或联邦公开市场委员会的同事的观点。
Return to text
返回正文
2.
2.
Financial crises can also lead to deflation, which can have further feedback on the financial system due to deflation leading to increases in the real burden of debt that can, in turn, prompt business (and household) bankruptcies, reducing their spending and production.
金融危机还可能导致通货紧缩，通货紧缩可能对金融体系产生进一步的反馈，导致实际债务负担增加，进而促使企业（和家庭）破产，减少其支出和生产。
This reduced economic activity can then lead to layoffs and further declines in prices—that is, a deflationary spiral.
经济活动的减少可能导致裁员和价格进一步下跌，即螺旋式通货紧缩。
This process occurred in the U.S. in the 1930s after the Great Depression and also occurred in Japan in the 1990s after their banking crisis.
这个过程发生在20世纪30年代大萧条之后的美国，也发生在20世纪90年代银行业危机之后的日本。
For summaries of these two episodes, see John C.
有关这两集的摘要，请参阅 John C.
Williams (2009), "The Risk of Deflation," FRBSF Economic Letter 2009-12 (San Francisco: Federal Reserve Bank of San Francisco, March).
Williams (2009)，“通货紧缩的风险”，FRBSF 经济快报 2009-12（旧金山：旧金山联邦储备银行，3 月）。
Return to text
返回正文
3.
3.
See Ralf R.
参见拉尔夫·R.
Meisenzahl (2017), "Auto Financing During and After the Great Recession," FEDS Notes (Washington: Board of Governors of the Federal Reserve System, June 22).
Meisenzahl (2017)，“大衰退期间和之后的汽车融资”，FEDS 注释（华盛顿：美联储系统理事会，6 月 22 日）。
Return to text
返回正文
4.
4.
See Tobias Adrian, Daniel Covitz, and Nellie Liang (2015), "Financial Stability Monitoring," Annual Review of Financial Economics , vol. 7 (December), pp.
参见 Tobias Adrian、Daniel Covitz 和 Nellie Liang (2015)，“金融稳定监测”，《金融经济学年度评论》，第 1 卷。 7（12 月），第 17 页。
357–95.
357–95。
Return to text
返回正文
5.
5.
See Jose Berrospide, Fang Cai, Siddhartha Lewis-Hayre, and Filip Zikes (2025), "Bank Lending to Private Credit: Size, Characteristics, and Financial Stability Implications," FEDS Notes (Washington: Board of Governors of the Federal Reserve System, May 23); and Sydney Carlino, Nathan Foley-Fisher, Nathan Heinrich, and Stéphane Verani (2025), "Life Insurers' Role in the Intermediation Chain of Public and Private Credit to Risky Firms," FEDS Notes (Washington: Board of Governors of the Federal Reserve System, March 21).
参见 Jose Berrospide、Fang Cai、Siddhartha Lewis-Hayre 和 Filip Zikes (2025)，“银行向私人信贷贷款：规模、特征和金融稳定性影响”，FEDS 注释（华盛顿：美联储系统理事会，5 月 23 日）； Sydney Carlino、Nathan Foley-Fisher、Nathan Heinrich 和 Stéphane Verani (2025)，“人寿保险公司在风险企业公共和私人信贷中介链中的作用”，FEDS 注释（华盛顿：美联储系统理事会，3 月 21 日）。
Return to text
返回正文
6.
6.
Financial Industry Regulatory Authority (2025), "Treasury Daily Aggregate Statistics" (accessed November 17, 2025).
金融业监管局 (2025)，“财政部每日汇总统计数据”（2025 年 11 月 17 日访问）。
Return to text
返回正文
7.
7.
Hedge funds' Treasury holdings data can be found on the Board's website: https://www.federalreserve.gov/releases/efa/efa-hedge-funds.htm .
对冲基金的国债持有数据可在委员会网站上找到：https://www.federalreserve.gov/releases/efa/efa-hedge-funds.htm。
The market value of privately held Treasury debt can be found at https://www.dallasfed.org/research/econdata/govdebt .
私人持有的国债的市场价值可以在 https://www.dallasfed.org/research/econdata/govdebt 上找到。
Return to text
返回正文
8.
8.
See Daniel Barth and R.
参见 Daniel Barth 和 R.
Jay Kahn (2025), "Hedge Funds and the Treasury Cash-Futures Basis Trade," Journal of Monetary Economics , vol. 155 (October), 103823; Mathias S.
Jay Kahn (2025)，“对冲基金和财政部现金期货基差贸易”，《货币经济学杂志》，卷。 155（十月），103823；马蒂亚斯·S。
Kruttli, Phillip J.
克鲁特利，菲利普·J.
Monin, Lubomir Petrasek, and Sumudu W.
Monin、Lubomir Petrasek 和 Sumudu W.
Watugala (2025), "LTCM Redux?
Watugala (2025)，“LTCM Redux？
Hedge Fund Treasury Trading, Funding Fragility, and Risk Constraints," Journal of Financial Economics , vol. 169 (July), 104017; and Andreas Schrimpf, Hyun Song Shin, and Vladyslav Sushko (2020), "Leverage and Margin Spirals in Fixed Income Markets during the Covid-19 Crisis," BIS Bulletin 2 (Basel, Switzerland: Bank for International Settlements, April).
对冲基金国债交易、融资脆弱性和风险约束，《金融经济学杂志》，卷。 169（七月），104017； Andreas Schrimpf、Hyun Song Shin 和 Vladyslav Sushko (2020)，“Covid-19 危机期间固定收益市场的杠杆率和保证金螺旋”，BIS 公告 2（瑞士巴塞尔：国际清算银行，4 月）。
Return to text
返回正文
9.
9.
See Emil N.
参见埃米尔·N.
Siriwardane, Adi Sunderam, and Jonathan Wallen (2025), "Segmented Arbitrage," The Journal of Finance , vol. 80 (5), pp.
Siriwardane、Adi Sunderam 和 Jonathan Wallen (2025)，“分段套利”，《金融杂志》，卷。 80 (5)，第 80 页。
2543–90; and Jefferson Duarte, Francis A.
2543–90；和杰斐逊·杜阿尔特、弗朗西斯·A.
Longstaff, and Fan Yu (2007), "Risk and Return in Fixed-Income Arbitrage: Nickels in Front of a Steamroller?" The Review of Financial Studies , vol. 20 (3), pp.
Longstaff 和 Fan Yu (2007)，“固定收益套利的风险与回报：压路机前的镍币？”金融研究评论，卷。 20 (3)，第 177 页。
769–811.
769–811。
See also Ayelen Banegas and Phillip Monin (2023), "Hedge Fund Treasury Exposures, Repo, and Margining," FEDS Notes (Washington: Board of Governors of the Federal Reserve System, September 8).
另请参阅 Ayelen Banegas 和 Phillip Monin (2023)，“对冲基金国债风险敞口、回购和保证金”，FEDS Notes（华盛顿：美联储系统理事会，9 月 8 日）。
Return to text
返回正文
10.
10.
See Kruttli, Monin, Petrasek, and Watugala, "LTCM Redux?
请参阅 Kruttli、Monin、Petrasek 和 Watugala，“LTCM Redux？
Hedge Fund Treasury Trading, Funding Fragility, and Risk Constraints"(see note 8).
对冲基金国债交易、资金脆弱性和风险约束”（见注释 8）。
Return to text
返回正文
11.
11.
See Roberto Perli (2025) "Recent Developments in Treasury Market Liquidity and Funding Conditions," remarks at the 8th Short-Term Funding Markets Conference, Washington, May 9.
请参阅 Roberto Perli (2025)“国债市场流动性和融资条件的最新发展”，在 5 月 9 日于华盛顿举行的第八届短期融资市场会议上的发言。
Return to text
返回正文
12.
12.
See Andrei A.
参见安德烈 A.
Kirilenko and Andrew W.
基里连科和安德鲁·W.
Lo (2013), "Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents," Journal of Economic Perspectives , vol. 27 (2), pp.
Lo (2013)，“摩尔定律与墨菲定律：算法交易及其不满”，《经济展望杂志》，卷。 27 (2)，第 27 页。
51–72; and Maureen O'Hara (2015), "High Frequency Market Microstructure," Journal of Financial Economics , vol. 116 (2), pp.
51–72；和 Maureen O'Hara (2015)，“高频市场微观结构”，《金融经济学杂志》，第 1 卷。 116 (2)，第 116 页。
257–70.
257–70。
Return to text
返回正文
13.
13.
See Robert A.
参见罗伯特 A.
Jarrow and Philip Protter (2012), "A Dysfunctional Role of High Frequency Trading in Electronic Markets," International Journal of Theoretical and Applied Finance , vol. 15 (3), 1250022.
Jarrow 和 Philip Protter (2012)，“电子市场中高频交易的功能失调”，《国际理论与应用金融杂志》，卷。 15（3），1250022。
Return to text
返回正文
14.
14.
See Alain P.
参见阿兰·P.
Chaboud, Benjamin Chiquoine, Erik Hjalmarsson, and Clara Vega (2014), "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of Finance , vol. 69 (5), pp.
Chaboud、Benjamin Chiquoine、Erik Hjalmarsson 和 Clara Vega (2014)，“机器的崛起：外汇市场的算法交易”，《金融杂志》，卷。 69 (5)，第 69 页。
2045–84; and Evangelos Benos, James Brugler, Erik Hjalmarsson, and Filip Zikes (2017), "Interactions Among High-Frequency Traders," Journal of Financial and Quantitative Analysis , vol. 52 (4), pp.
2045–84；和 Evangelos Benos、James Brugler、Erik Hjalmarsson 和 Filip Zikes (2017)，“高频交易者之间的互动”，《金融与定量分析杂志》，卷。 52 (4)，第 52 页。
1375–402.
1375–402。
Return to text
返回正文
15.
15.
See Albert Menkveld and Bart Zhou Yueshen (2019), "The Flash Crash: A Cautionary Tale about Highly Fragmented Markets," Management Science , vol. 65 (10), pp.
请参阅 Albert Menkveld 和 Bart Zhou Yueshen (2019)，“闪电崩盘：关于高度分散市场的警示故事”，《管理科学》，第 1 卷。 65 (10)，第 65 页。
4470–88; and Dobrislav Dobrev and Ernst Schaumburg (2016), High-Frequency Cross-Market Trading and Market Volatility," Federal Reserve Bank of New York, Liberty Street Economics (blog), February 17.
4470–88；以及 Dobrislav Dobrev 和 Ernst Schaumburg (2016)，高频跨市场交易和市场波动”，纽约联邦储备银行，Liberty Street Economics（博客），2 月 17 日。
Return to text
返回正文
16.
16.
See Anne Lundgaard Hansen and Seung Jung Lee (2025), "Financial Stability Implications of Generative AI: Taming the Animal Spirits," Finance and Economics Discussion Series 2025-090 (Washington: Board of Governors of the Federal Reserve System, September).
请参阅 Anne Lundgaard Hansen 和 Seung Jung Lee (2025)，“生成式 AI 的金融稳定性影响：驯服动物精神”，财经讨论系列 2025-090（华盛顿：美联储系统理事会，9 月）。
Return to text
返回正文
17.
17.
See Álvaro Cartea, Patrick Chang, Mateusz Mroczka, and Roel Oomen (2022), "AI Liquidity Provision in OTC Markets," Quantitative Finance , vol. 22 (12), pp.
请参阅 Álvaro Cartea、Patrick Chang、Mateusz Mroczka 和 Roel Oomen (2022)，“OTC 市场中的 AI 流动性供应”，《量化金融》，第 1 卷。 22 (12)，第 22 页。
2171–204; and Winston Wei Dou, Italy Goldstein, and Yan Li (2025), "AI-Powered Trading, Algorithmic Collusion, and Price Efficiency," NBER Working Paper Series 34054 (Cambridge, Mass.: National Bureau of Economic Research, July).
2171–204；以及 Winston Wei Dou、Italy Goldstein 和 Yan Li (2025)，“人工智能驱动的交易、算法合谋和价格效率”，NBER 工作论文系列 34054（马萨诸塞州剑桥：国家经济研究局，7 月）。
Return to text
返回正文
18.
18.
See Laura Veldkamp (2024), "Discussion of 'AI-Powered Trading, Algorithmic Collusion, and Price Efficiency,'" NBER Summer Institute 2024: Asset Pricing, Cambridge, Mass., July 11–12.
请参阅 Laura Veldkamp (2024)，“关于‘人工智能驱动的交易、算法共谋和价格效率’的讨论”，NBER 2024 年夏季学院：资产定价，马萨诸塞州剑桥，7 月 11-12 日。
Return to text
返回正文
19.
19.
See Álvaro Cartea, Patrick Chang, and Gabriel García-Arenas (2025), "Spoofing and Manipulating Order Books with Learning Algorithms," available at: https://ssrn.com/abstract=4639959. Return to text
请参阅 Álvaro Cartea、Patrick Chang 和 Gabriel García-Arenas (2025)，“利用学习算法欺骗和操纵订单簿”，网址为：https://ssrn.com/abstract=4639959。返回正文
20.
20.
See Alessio Azzuti, Wolf-Georg Ringe, and H.
参见 Alessio Azzuti、Wolf-Georg Ringe 和 H.
Siegfried Stiel (2022), "Machine Learning, Market Manipulation and Collusion on Capital Markets: Why the 'Black Box' Matters," University of Pennsylvania Journal of International Law , vol. 43 (1), pp.
Siegfried Stiel (2022)，“机器学习、市场操纵和资本市场共谋：为什么‘黑匣子’很重要”，宾夕法尼亚大学国际法杂志，卷。 43 (1)，第 43 页。
79–135.
79–135。
Return to text
返回正文
21.
21.
See Pedro Gurrola-Perez and Kaitao Lin (2024), "An Analysis of Market Manipulation Definitions round the World," working paper (London: World Federation of Exchanges, June).
请参阅 Pedro Gurrola-Perez 和 Kaitao Lin (2024)，“世界各地市场操纵定义的分析”，工作论文（伦敦：世界交易所联合会，6 月）。
Return to text
返回正文
22.
22.
See the CME Group's "Market Regulation Advisory Notice" at https://www.cmegroup.com/content/dam/cmegroup/notices/market-regulation/2024/07/CME-Group-RA2403-5.pdf. Return to text
请参阅芝商所的“市场监管咨询通知”：https://www.cmegroup.com/content/dam/cmegroup/notices/market-regulation/2024/07/CME-Group-RA2403-5.pdf。返回正文
23.
23.
See Anna Irrera and Justina Lee (2025), "Billionaire Trader Alex Gerko's XTX to Build €1 Billion Data Hub," Bloomberg, January 22.
请参阅 Anna Irrera 和 Justina Lee (2025)，“亿万富翁交易员 Alex Gerko 的 XTX 将建立 10 亿欧元的数据中心”，彭博社，1 月 22 日。
Return to text
返回正文