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Thoughts on the Market

Thoughts on the Market

De: Morgan Stanley
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Short, thoughtful and regular takes on recent events in the markets from a variety of perspectives and voices within Morgan Stanley.

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Episodios
  • The Risks of Private Credit's Software Exposure

    The Risks of Private Credit's Software Exposure
    Mar 2 2026
    Our Chief Fixed Income Strategist Vishy Tirupattur and U.S. Head of Credit Strategy Vishwas Patkar discuss the implications of private credit’s exposure to the software industry.Read more insights from Morgan Stanley.----- Transcript -----Vishy Tirupattur: Welcome to Thoughts on the Market. I am Vishy Tirupattur, Morgan Stanley's Chief Fixed Income Strategist. Vishwas Patkar: I'm Vishwas Patkar, Morgan Stanley's U.S. Head of Credit Strategy. Vishy Tirupattur: While potential disruption from AI has been a key driver for markets [in the] last few weeks, the focus of investor agenda has been in the software sector. On today's podcast, we will talk about software in the credit markets and its implications. It's Monday, March 2nd at 10am in New York. Vishwas, let's start by understanding how the exposure in software manifests in the credit markets. How does it compare to software, say, in the equity market? Vishwas Patkar: Yeah, so the software exposure in credit markets is large, and understandably that's why investors are closely watching what's happening with software in the equity market. But what's interesting and important for investors to note is the exposure in credit is very different from what it is in equities. So, for instance, a good chunk of exposure in the credit market is around private issuers. So, we estimate about 80 percent of companies are private in the whole sample set that we looked at. And that's largely a function of the fact that software is not a big part of the more liquid spaces like Investment Grade and High Yield. But it is heavily represented in the more opaque parts of the market, like leveraged loans, CLOs, and, you know, BDCs. So, our analysis found that about 25 percent of BDC portfolios are in software, closely followed by private credit CLOs. And leveraged loan market was about 16 percent. So, that's an important distinction to keep in mind versus the equity market. The second thing I would flag is – because the software sector grew a lot in the loan market through the LBO wave of 2020 and 2021, it has a weaker credit quality skew to it than the overall market. So about 50 percent of borrowers in the sector are rated B - or lower. So, that's the lowest rungs of the rating spectrum. Many of these software deals were underwritten with higher leverage than the broad market. And as a result of that you also have more front-loaded maturities in the sector, which brings the risks of refinancing, if some of this disruption persists. But Vishy, that's a nice segue to you. Over the past couple of years, you looked at the private credit market in depth and that's where I think the exposure we found is the highest in BDCs, you know, which is the public face of private credit. So, in your assessment, what is the risk of software to private credit, given all of the headlines that are popping up? Vishy Tirupattur: Public face of private credit – Vishwas, that's a great line. BDCs – business development corporations for those who are not familiar – are companies that invest in the debt of small and medium sized companies, sourced through non-bank channels. BDCs fund themselves through equity and debt issuance. So, if you look at the portfolios of BDCs to look at their exposure to software, there's a wide variation across the various BDC portfolios. What makes the assessment of these software risks in BDCs challenging is that many of these companies are private companies without the reporting obligations of public companies. So, no earnings reports, no 10-Ks or cues or broadly publicly available financials look at. So, in effect, these companies need to be re underwritten to evaluate which of these companies would be disrupted from AI; and which companies could actually benefit from AI and see their margins expand. So, in the context of BDCs, liability spreads are something we are watching closely. BDC liability spreads have widened but we think more needs to happen there. The clearing levels need to wait for the full resolution of the companies that benefit and that get hurt by disruption that is still awaited. So, we expect credit spreads of BDCs to remain volatile for some time to come. Vishwas Patkar: Okay. So, seems like this is a significant, or at least a non-trivial risk factor for credit markets, given the growth of the sector, leverage, the skew and quality. But Vishy, do you think this could be systemic for risk markets at large? Vishy Tirupattur: So, I do think that this is a significant risk, but I don't think it's a systemic risk. The amount of leverage in BDC is fairly small. About 2x is the kind of leverage. You compare that to the kind of leverage that existed in the financial system before the financial crisis – that’s orders of magnitude smaller risk. And also the linkage to the banking system comes through the back leverage provided to the non-bank lenders. But this leverage is substantially risk remote with very high ...
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    7 m
  • AI as New Global Power?

    AI as New Global Power?
    Feb 27 2026
    Our Deputy Head of Global Research Michael Zezas and Stephen Byrd, Global Head of Thematic and Sustainability Research, discuss how the U.S. is positioning AI as a pillar of geopolitical influence and what that means for nations and investors.Read more insights from Morgan Stanley.----- Transcript -----Michael Zezas: Welcome to Thoughts on the Market. I'm Michael Zezas, Morgan Stanley's Deputy Head of Global Research.Stephen Byrd: And I'm Stephen Byrd, Global Head of Thematic and Sustainability Research.Michael Zezas: Today – is AI becoming the new anchor of geopolitical power?It's Wednesday, February 27th at noon in New York.So, Stephen, at the recent India AI Impact Summit, the U.S. laid out a vision to promote global AI adoption built around what it calls “real AI sovereignty.” Or strategic autonomy through integration with the American AI stack. But several nations from the global south and possibly parts of Europe – they appear skeptical of dependence on proprietary systems, citing concerns about control, explainability, and data ownership. And it appears that stake isn't just technology policy. It's the future structure of global power, economic stratification, and whether sovereign nations can realistically build competitive alternatives outside the U.S. and China.So, Stephen, you were there and you've been describing a growing chasm in the AI world in terms of access to strategies between the U.S. and much of the global south, and possibly Europe. So, from what you heard at the summit, what are the core points of disagreement driving that divide?Stephen Byrd: There definitely are areas of agreement; and we've seen a couple of high-profile agreements reached between the U.S. government and the Indian government just in the last several days. So there certainly is a lot of overlap. I point to the Pax Silica agreement that's so important to secure supply chains, to secure access to AI technology. I think the focus, for example, for India is, as you said; it is, you know, explainability, open access. I was really struck by Prime Minister Modi's focus on ensuring that all Indians have access to AI tools that can help them in their everyday life.You know, a really tangible example that really stuck with me is – someone in a remote village in India who has a medical condition and there's no doctor or nurse nearby using AI to, you know, take a photo of the condition, receive diagnosis, receive support, figure out what the next steps should be. That's very powerful. So, I'd say, open access explainability is very important.Now, the American hyperscalers are very much trying to serve the Indian market and serve the objectives really of the Indian government. And so, there are versions of their models that are open weights, that are being made freely available for health agencies in India, as an example; to the Indian government, as an example.So, there is an attempt to really serve a number of objectives, but I think this key is around open access, explainability, that I do see that there's a tension.Michael Zezas: So, let's talk about that a little bit more. Because it seems one of the concerns raised is this idea of being captive within proprietary Large Language Models. And maybe that includes the risk of having to pay more over time or losing control of citizen data. But, at the same time, you've described that there are some real benefits to AI that these countries want to adopt.So, what is effectively the tension between being captive to a model or the trade off instead for pursuing open and free models? Is it that there's a major quality difference? And is that trade off acceptable?Stephen Byrd: See, that's what's so fascinating, Mike, is, you know, what we need to be thinking about is not just where the technology is today, but where is it in six months, 12 months, 24 months? And from my perspective, it's very clear. That the proprietary American models are going to be much, much more capable.So, let's put some numbers around that. The big five American firms have assembled about 10 times the compute to train their current LLMs compared to their prior LLMs, and that's a big deal. If the scaling laws hold, then a 10x increase in training compute to result in models are about twice as capable.Now just let that sink in for a minute, twice as capable from here. That's a big deal. And so, when we think about the benefit of deploying these models, whether it's in the life sciences or any number of other disciplines, those benefits could start to get very large. And the challenge for the open models will be – will they be able to keep up in terms of access to compute, to training, access to data to train those models? That's a big question.Now, again, there's room for both approaches and it's very possible for the Indian government to continue to experiment and really see which approach is going to serve their citizens the best. And I was really struck by just how focused the Indian ...
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    13 m
  • Oil Rallies on Fresh Uncertainty

    Oil Rallies on Fresh Uncertainty
    Feb 26 2026

    Our Global Commodities Strategist Martijn Rats discusses the geopolitical drivers behind the recent spike in oil prices and outlines four Iran scenarios.

    Read more insights from Morgan Stanley.


    ----- Transcript -----


    Welcome to Thoughts on the Market. I’m Martijn Rats, Morgan Stanley’s Global Commodities Strategist.

    Today – what’s fueling the latest oil market rally.

    It’s Thursday, February 26th, at 3pm in London.

    What happens when oil prices jump, even though there’s no actual shortage of oil? That’s the situation we’re in right now. Tensions between the U.S. and Iran have escalated again. Naturally, markets are paying attention.

    Over the past week, Brent crude rose about $3 to around $72 per barrel. WTI climbed into the mid-$60s. Shipping costs surged. And traders have started paying a premium for protection against a sudden oil spike – the levels we haven’t seen since the early days of the Ukrainian invasion.

    But here’s the key point: there’s no clear evidence that global oil supply has tightened. Exports are still flowing. Tankers are still moving. And some near-term indicators of physical tightness have actually softened. When oil is truly scarce, buyers scramble for immediate barrels and short-term prices spike relative to future delivery. Instead, those spreads have narrowed, and physical premiums have eased.

    This isn’t a supply shock. It’s a risk premium. In simple terms, investors are buying insurance. So what could happen next? We see four broad scenarios.

    Before I outline them though, here’s something we do not see as a core case: a prolonged closure of the Strait of Hormuz. Roughly 15 million barrels per day of crude and another 5 million of refined product moves through that corridor. A sustained shutdown would be enormously disruptive. But we think the probability is very low.

    Now coming back to our four scenarios. The first is straightforward. A negotiated settlement; conflict is avoided. Iranian exports continue and shipping lanes remain open. In that scenario, what unwinds is the geopolitical risk premium – which we estimate at roughly $7 to $9 per barrel. If that fades, Brent could drift back to the low-to-mid $60s, similar to past episodes where prices spiked on fear and then retraced once supply proves unaffected.

    Second, we could see short-lived frictions – shipping delays, higher insurance costs, temporary logistical issues. That might remove a few hundred thousand barrels per day for, say, a few weeks.. Prices could briefly spike into the $75–80 range. But balancing forces would kick in relatively quickly. For example, China has been building inventories at a steady pace. At higher prices, that stockbuilding would likely slow, helping offset temporary disruptions. That points to some further upside in prices – but then normalization.

    The third scenario is more serious, but still contained: localized export losses of perhaps 1 to 1.5 million barrels per day for a month or two. Prices would stay elevated longer, but spare capacity and demand adjustments could eventually stabilize the market.

    Now our last scenario is the more serious and considers a potential shipping shock. The real risk here isn’t wells shutting down – it’s shipping disruption. Global trade of crude oil depends on efficient tanker movement. If transit times were extended even modestly, effective shipping capacity could fall sharply, creating what amounts to a temporary tightening of about 2 to 3 million barrels per day – or about 6 percent of global seaborne supply. That is a logistics shock, not a production outage – but it would push prices toward early-2022-type levels, at least briefly.

    Now let’s zoom out. Beyond geopolitics, the fundamentals look weak. OPEC+ supply is rising, and our forecasts show a sizable surplus building in 2026. Even if some of that oil ends up in China’s stockpiles, a lot would still likely flow into core OECD inventories. Historically, when the market looks like this, prices tend to fall, not rise.

    Which brings us back to the central point. Oil isn’t rallying because the world has run out of barrels. It’s rallying because markets are pricing geopolitical risk. And unless that risk turns into actual, sustained disruption, insurance premiums tend to expire.

    Thank you for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.

    This podcast references jurisdiction(s) or person(s) which may be the subject of economic sanctions. Readers are solely responsible for ensuring that their investment activities are carried out in compliance with applicable laws.
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    5 m
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