Inside the AI Debt Surge

欢迎收听《市场观点》。

Welcome to Thoughts on the Market.

我是卡罗琳·坎贝尔，摩根士丹利资产支持证券策略师。

I'm Carolyn Campbell, Morgan Stanley's Asset-backed Securities Strategist.

我是维什瓦斯·帕特卡尔，摩根士丹利企业信贷策略负责人。

And I'm Vishwas Patkar, Morgan Stanley's Head of U.

美国区。

S.

企业信贷策略。

Corporate Credit Strategy.

今天，我们聊聊固定收益市场如何为人工智能建设提供资金支持。

Today, how fixed income markets are helping fund the AI buildout.

现在是纽约时间6月18日，星期四上午10点。

It's Thursday, June 18 at 10AM in New York.

我们直接开始吧，维什瓦斯。

Let's get right into it, Vishwas.

我们俩之前都上过这个播客，聊过信贷市场如何为人工智能基础设施建设提供融资。

We've both come on this podcast before to talk about how credit markets are financing the AI build out.

过去十个月，可以说，进展的速度、广度和深度都超过了我们最初的预期。

And over the last ten months, I think it's fair to say that things are faster, broader, deeper than we perhaps expected initially.

如今，这笔投资已经覆盖了投资级公司债、高收益贷款，以及一系列证券化产品。

This investment now spans investment grade corporate bonds, high yield loans, and a range of securitized products.

从你负责公司信贷的角度来看，为什么人工智能基础设施现在对投资者这么重要？

From your seat in corporate credit, why does AI infrastructure matter so much to investors right now?

这在我们和客户的讨论中是个热门话题。

This is a big talking point in our client discussions.

有意思的是，不到一年前，我们才第一次写文章讨论这个话题，当时就指出信贷市场能填补高达1.5万亿美元的融资缺口。

It's also telling that less than a year ago, we wrote about this topic for the first time, identifying a $1,500,000,000,000 financing gap that credit markets could help bridge.

那时候，数据中心债务根本不是投资者关注的重点。

At that time, data center debt was not something that investors were really focused on.

可现在不到一年过去，这已经成为你我各自领域里最核心的主题。

Yet less than twelve months forward, this, I think, is the number one theme dominating both your and my market.

我觉得它之所以重要，主要体现在三个关键方面。

And why it's important, I would say, is across three key vectors.

首先是规模问题。

First, just the scale.

今年到目前为止，与AI相关的债务发行总额已接近2500亿美元。

So if you look at overall AI related debt issuance so far this year, we're close to 250,000,000,000.

预计今年剩余时间里，这个数字还会翻倍，2026年AI债务融资总额将达到约5000亿美元。

For the balance of the year, we expect that number to double, so about 500,000,000,000 of total AI debt financing for 2026.

其次，交易的复杂性也越来越突出。

Increasingly, the second vector, think, is around the complexity of deals.

最初，AI融资主要集中在普通的投资级公司债券，但现在已扩展到高收益市场中的项目融资模式。

So initially, while AI financing was dominated by vanilla investment grade corporate bond deals, we are now seeing that broaden out into project finance style deals in the high yield market.

在不同信用类别中，芯片融资的活动明显增加了。

We have seen an uptick in chip financing, across the different credit silos.

这对投资者来说很重要，因为要在这些不同选项中发现价值，需要深厚的信用分析能力。

And that's important for investors as identifying value across these different options does require deep credit expertise.

第三，随着这个投资周期持续推进，我们也要留意风险的积累——不只是从整体上对算力需求的担忧，还要关注这些不同结构中的细微差别，比如数据中心建设或芯片融资方面，投资者都需要密切跟踪。

And third, as this investment cycle rolls along, it's also important to be cognizant of risks that are building, not just from a very broad top down sense around the demand for compute, but also what are some of the the nuances in these different structures, whether it is in data center construction or is in chip financing that investors will need to monitor.

正是基于这三个方面，我们认为数据中心债务融资的重要性正在不断提升。

So it's across these three themes that we think data center debt financing is is gaining importance.

目前，AI基础设施的底层需求非常强劲。

Now the underlying demand for AI infrastructure is very strong.

但这并不意味着所有与此主题相关的债券都天然具有吸引力。

That doesn't necessarily mean that every bond tied to this theme is automatically gonna be attractive.

正如你提到的，今年有高达五千亿美元的供给，而且各种结构之间的复杂性也很高。

And as you mentioned, 500,000,000,000 of supply for the year, a large amount of complexity between the structures.

信用投资者应该如何看待这些不同结构中的各类风险呢？

How should credit investors think about the various risks within these different structures?

在投资级市场，情况相对简单一些。

So in investment grade, the story is a bit simpler.

我们已经看到无担保的超大规模云服务商发行了债券。

So we have had unsecured hyperscaler bond issuance.

半导体公司也发过债，还有一些我们称之为私人模式的数据中心交易。

We have had issuance from semiconductor names, and then we've had some what we call private style data center deals.

但绝大多数融资仍然来自超大规模云服务商的投资级债券。

But the vast majority still comes from hyperscaler investment grade rated bonds.

在这个市场里，我们更关注的不是基本面，因为基本面本身就非常强劲，而超大规模云服务商也是我们见过的信用资质最好的公司之一。

For this market, our focus is less on fundamentals because fundamentals are very strong, and then hyperscaler are some of the more most creditworthy companies that we've seen in the history of the market.

我们更看重的是供给的规模。

Our emphasis more is on just the quantum of supply.

今年到目前为止，美元市场上的超大规模云服务商债务发行量已经超过一千亿美元。

So year to date, we have had north of $100,000,000,000 of hyperscaler debt in the dollar market.

其他货币区的发行量也超过了五千亿美金。

We've had north of $50,000,000,000 being issued in other currencies.

如果看整个投资级市场，今年的供给比去年增长了近百分之二十五。

If you look at the overall investment grade market, supply is up almost 25% versus last year.

这和我们今年创纪录发行量的判断是一致的。

That's consistent with our call for a year of record issuance this year.

而且如果往前看，把发行数据和我们的资本支出预测对上，明年很可能再次创下新高。

And increasingly, if you look forward and map these issuance numbers to our CapEx estimates, where we could very much be on track for another record to be hit hit next year.

所以投资级市场的关键问题并不在于这些公司的基本面或具体交易。

So the the issue of the investment rate market is not around the fundamentals of the companies or or these deals.

真正的问题在于供应量，我们认为这最终会考验市场的承接能力。

It's more about the quantum of supply, which we think eventually will test the demand capacity of this market.

我们对投资级市场的基本判断类似于1997到1998年，当时信贷开始推动商业周期。

And our base case for the the investment grade space is similar to 1997, 1998, where credit was starting to finance the business cycle.

利差温和走阔，投资级债券可能跑输其他风险资产。

Spreads widened modestly, and IG could underperform other risk assets.

但从更长的时间维度看，利差依然处于历史低位。

But over a longer time horizon, spreads still look historically very low.

那在投资级以下的非投资级信用领域呢？

Now what about further down the credit spectrum into the noninvestment grade portion?

AI相关的发行在非投资级这部分情况如何？

What about that part of the issuance spectrum for AI?

是的。

Yeah.

我们在非投资级市场，尤其是高收益领域看到的情况截然不同。

So what we're seeing in the sub investment grade space, especially in high yield, is very different.

在那里，数据中心融资的增长主要体现在数据中心建设的项目融资交易上。

There, the growth in data center financing has happened around project finance deals for data center construction.

很多情况下，这些融资来自加密矿企，它们实际上提供的是我们所说的‘快速供电’解决方案。

In many cases, these have come from crypto miner companies that effectively provide what we call speed to power solutions.

我们也看到一些新兴云服务商发行了无担保债券，不过规模相对较小。

We've also had some unsecured issuance from neo clouds, although that's relatively small.

这个领域从去年秋天几乎为零，已经增长到今年的四百亿美元。

But this sector has expanded from effectively $0 around the fall of last year to about $40,000,000,000 this year.

我们预计到2026年底，还会再有两千亿美元的发行量。

We expect to see another $20,000,000,000 of issuance by the end of twenty twenty six.

这些项目融资交易为普通信贷投资者提供了有趣的多元化选择。

And the way they fit into this whole ecosystem is these project finance deals, we think, are interesting diversifiers for regular credit investors.

这些项目确实带有建设风险，尤其是在前两三年，数据中⼼还没正式投运的时候。

They do come with construction risks, especially initially for the first two to three years till the till the data center is up and running.

但反过来，它们往往附带很多结构性保护和债权⼈保障，这在⾼收益市场的⼤多数情况⾥是看不到的。

But on the flip side, you do get a lot of structural enhancements and and creditor protections, which is something you don't see in the in the vast majority of the of the high yield market.

所以我认为，投资者在评估这类交易时，需要转变思路，重点关注资产层面的风险——这和⼤多数信⽤市场交易的⽅式有很⼤不同，后者主要是投资者熟悉的⽆担保公司层级风险。

So I think a cree shift in the framework that investors have to do for these deals is focus on asset level risk, which is, again, I I think a big divergence from how the the vast majority of the credit market trades, which is largely unsecured corporate level risk that investors have been used to.

明白了。

Alright.

你刚提到了建设风险。

You just brought up construction risk.

你认为这是当前⾼收益投资者⾯临的最⼤风险吗？

Do you think that's the biggest risk facing the high yield investors today?

是的。

Yes.

对⾼收益项目来说，建设风险确实是投资者最关注的核心问题，因为要记住，很多债务发行⽅都是⾸次借款，过去在建设⽅⾯几乎没有经验。

I think for the high yield deals in particular, construction risk is the dominant vector that investors are focused on because it's important to remember a lot of the the debt issuers are are first time borrowers, and they have a limited track record of of construction in the past.

所以你可能会看到工期延误，还有成本超支这类问题，这些都会影响市场对整个行业，或者至少对某些债券交易的情绪。

So you could see potential delays, and things like cost overruns that can affect sentiment on on the sector or at least on on on specific bond deals.

这一点在下半年尤其值得关注，因为去年宣布的那些项目，第一批交付日期就要到了。

And this will be especially important to monitor going into the second half of the year as we have some of the the first delivery dates coming up for the the deals in the sector that were announced last year.

话虽如此，尽管有些租户有终止合同的权利，但如果延误超过180天，我们认为，鉴于电力供应的结构性限制，这些终止权不太可能被实际行使。

That being said, you know, even though some of the tenants have termination rates, if delays go beyond 180, our view is that given the structural power constraints, these termination rights are unlikely to be exercised.

所以，虽然建设里程碑会影响市场情绪和短期估值，但我们把任何短期波动都看作是入场机会。

So while construction milestones can affect sentiment and short term valuations, we would look at any blips, as as buying opportunities in the space.

明白了。

Alright.

卡罗琳，我把话题抛回给你。

So, Carolyn, let me throw this back to you.

建设风险对整个企业信贷市场，尤其是高收益投资者来说，确实非常重要。

So construction risk, clearly very important for the corporate credit market, especially for high yield investors.

那么，ABS投资者或者商业抵押贷款支持证券的投资者会关心这个问题吗？

Is that something ABS investors or commercial mortgage backed investors care about?

那这些资产类别在哪些方面和公司信用债不同呢？

And in what other ways are these asset classes different from corporate credit?

明白了。

Okay.

首先，最大的区别在于，证券化产品的资产都是已经稳定的。

So first and foremost, the biggest difference is that in securitized products, the assets are stabilized.

它们已经在产生现金流。

They're cash flowing.

而且已经投入运营了。

They're online.

在我们的领域里，根本不存在建设阶段的风险。

We don't have that first factor of construction risk in our space.

第二个重要区别是，在高收益债和投资级债市场，我们看到的基本都是单园区、单租户的数据中心。

The second biggest difference is while in high yield and IG, we've mostly seen or we've entirely seen single campus, single tenant data centers.

但在证券化发行中，主流产品都是多租户、多资产、跨区域的交易。

In securitization issuance, it's mostly multi tenant, multi asset, multi regional deals that that have come to market.

所以风险特征完全不同。

And so it's a very different risk profile.

因此，投资者关注的不只是这一份租约背后的租户是谁、终止率有多高，而是整个计算基础设施的整体环境如何。

And as a consequence, investors are focused not just on who is behind this one single lease and what are the termination rates, but what does the landscape look like in general for compute?

这对空置率和租户更替率又有什么影响？

How does that affect vacancy and churn rates?

最后，发行方本身也不一样。

And then lastly, the issuers themselves are different.

你提到了那些加密公司。

You talked about the crypto companies.

它们更多是做数据中心建设的，而证券化产品里的发行方，大多是已经经营了五到二十年的老牌企业。

You get a little bit more of the data center data center construction, whereas in securitized products, these are companies that have been around for five, ten, twenty years.

它们习惯于管理庞大的资产组合，少则几十个、多则上百个租户。

They're accustomed to managing a fleet of assets, dozens if not hundreds of tenants.

总的来说，它们的业绩记录比信贷市场里那些发行方要扎实得多。

They've got a little bit more of a track record for the most part than the types of issuers we're seeing in the credit market.

所以，你这个市场在建成后，更侧重于计算需求的主题，以及AI投资周期的走势，而企业信用市场则主要受数据中心建设带来的施工风险影响。

So your market post construction, more leverage to the the thematic of demand for compute and how the AI investment cycle is playing out versus the corporate credit market, which is largely exposed to construction risks as the data centers get built out.

这确实是一个非常重要的区别。

So that's a very important difference.

不过话说回来，两个市场都有一个共同点：基本面都挺健康，但供给量也很大。

That being said, one theme that ties, both our markets are just healthy fundamentals, but at the same time, heavy supply.

我之前提到过，这种状况如何影响我们对投资级市场的看法。

So I talked about how we see that affecting our view on investment grade.

同样的这种张力，在证券化产品里又是怎么体现的呢？

How is that same tension showing up in securitized products?

正如你所说，基本面确实非常强劲。

So exactly as you said, the fundamental story is very strong.

我们目前没看到资产表现有任何下滑，短期内也不预期会有恶化。

We don't see deterioration in performance of the assets either that has happened yet or that we expect to come in the near term.

所以这本质上是个技术面驱动的故事。

So it really is a technically driven story.

我们预计这个领域的供应量大约是每年三千亿美元。

Supply in this space we're forecasting at around 30,000,000,000 for years.

虽然绝对规模小一些，但对一个供应预期已经很高的市场来说，这个量还是相当大的。

So smaller in magnitude but relatively large for the market that has very elevated supply expectations.

因此，整个市场的利差都出现了走阔。

And so as a consequence, we've seen spreads back up across the space.

我们认为，跨资产的比较会帮助限制利差进一步扩大，因此今年余下时间，结构性信用产品整体上仍有投资价值。

We do think that some of the cross asset comparisons will help keep spreads, contained from here, and so we do see value in securitized credit across the stack for the rest of the year.

明白了。

Alright.

你提到了跨资产比较，我们之前也讨论过各自市场的基本面差异，以及预期的发行规模。

So you brought up the cross asset comparison, and so we've we've discussed the fundamental differences in our market, how much issuance we we expect.

不过，最后从实际操作的角度说，如果我们要给投资者建议，该从哪里寻找相对价值，用什么框架来评估不同机会，你是怎么看的？

But, you know, just to end on a commercial note, for if we are advising investors on where is the best relative value and what's the framework for comparing opportunities, how do you think about that?

在整个生态体系里，你觉得哪里最有价值？

What what what where do we see value across the ecosystem?

我觉得，这可能是当前关注这个领域的投资者面临的最大问题。

I mean, I think this is probably the biggest question that investors that are looking at this space are facing today.

如果我们只看数据中心支持的资产，我认为主要有两个方面。

And there's if we're thinking just about the data center backed assets, I think there are two main things.

一个是资产本身，我们关注的是地理位置、租户、互联能力，以及这种资产支持多种用途的灵活性。

One is the asset itself, where we're focused on things like the geography, the tenant, the interconnectivity, the flexibility of this asset for multiple uses.

另一个是交易结构本身，包括资产背后的杠杆水平、现金流状况，当然还有期限长短。

And then the second is on the structure of the deal itself, how much leverage is being raised against the asset, how cash flowing is it, and then, of course, the duration as well.

但这个问题确实很好，由于这个领域太复杂，要相互比较真的非常困难。

But it's a it's a great question, and because of the complexity of this space, it can be really hard to compare one to the other.

是的。

Yeah.

虽然这么说可能有点避重就轻，但我认为投资者正在逐步建立一套分析框架，因为这类交易出现得太快了。

And at the risk of providing a non answer, I I very much think investors are in the process of coming up with a framework because these deals have come very quickly.

对大多数信贷投资者来说，这还是一个全新的领域。

This is a new sector for most credit investors to analyze.

但我们可以很有把握地说，这正在模糊企业信贷和证券化信贷之间的界限。

But I think what we can say with a high degree of certainty is this is blurring the lines between corporate credit and securitized credit.

所以，这为我们今后在这一话题上加强合作开辟了更多可能性。

So, you know, this this opens up more avenues for us to collaborate on this topic going forward.

好的。

Alright.

今天我们就聊到这儿吧，这种跨领域的合作很有意义。

That's a great place for us to leave it today with that nice cross collaboration.

Vishwas，非常感谢你抽出时间来交流。

Vishwas, thank you so much for taking the time to talk.

Carolyn，和你聊得很愉快。

Great speaking with you, Carolyn.

也感谢大家的收听。

And thanks for listening.

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