Thoughts on the Market

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

  1. 2h ago

    4 Market Signals Ahead of the Midterms

    As investors look toward the U.S. midterm elections, the biggest question is what could change. Our Head of U.S. Public Policy Research Ariana Salvatore outlines the signals worth watching.  Read more insights from Morgan Stanley. ----- Transcript -----   Ariana Salvatore: Welcome to Thoughts on the Market. I'm Ariana Salvatore, Head of U.S. Public Policy Research at Morgan Stanley.  Today, I'll be talking about the upcoming 2026 midterm elections.  It's Wednesday, September 30th, at 10am in New York.  As the elections inch closer, investors are increasingly asking about potential ramifications. We just put out a deep dive covering our expectations, and we arrive at four key takeaways.  The first, midterms are unlikely to change the core executive-led policy agenda. As we've been noting for some time, a lot of the policy uncertainty that markets have dealt with since the beginning of 2025 has actually come from the executive branch rather than Congress.  Tariffs, trade policy, deregulation, immigration, and export controls are all variables that are going to remain within the White House's authority. So even if control of Congress changes, we don't think investors should assume that those parts of the policy agenda simply go away. Where Congress actually matters more is on fiscal policy. But even there, the range of outcomes is relatively narrow.  The main differences revolve around the timing of scheduled SNAP and Medicaid cuts, defense spending, and how future government funding and debt limit negotiations evolve.  So, that's our first takeaway. Midterms can change the mechanics of governing, but probably not the broader direction of the executive agenda. That means policy uncertainty, at least across those vectors I mentioned, is likely to stay high.  Takeaway number two, we'd be careful about treating the midterms as a direct signal for the 2028 presidential election. Historically, what we see is the issues that dominate a midterm don't necessarily translate to the next presidential race.  Looking at the six midterm-to-presidential cycles since 1994, the top-ranked issue changed in five of them. And the issue that ultimately proved decisive in the presidential election was actually already visible at the midterm in only two of the six cases. What elections can tell us, however, is where some of the policy fault lines are beginning to form.  We're watching four debates in particular in that context: the fiscal and Social Security debate, individual tax landscape, restrictions on data center development, and healthcare. In our view, across those variables, the useful signal isn't simply which party wins more seats. It's which versions of these policies are beginning to gain traction with voters and within the parties themselves.  That actually brings us to takeaway number three. AI is one area where the midterms could matter, but mainly through data center policy rather than broad AI regulation.  We think it's important to separate those two issues. So first, on data centers, we do see midterms as a catalyst. And that's because many of the most important policy levers sit at the state and local level: permitting, siting, grid interconnection, large load electricity rates, and tax incentives. So that means that the governorships, utility commissions, and state legislatures can actually have a much more immediate effect on the pace and the location of the build-out than Congress itself.  In that vein, our base case remains a conditional build-out, meaning the expected level of AI CapEx can continue. But likely it's going to increasingly concentrate in locations where developers can address concerns around things like electricity costs, infrastructure, water, and community impacts.  Broader AI safety regulation is different. Here, we think government configuration actually matters less, and that's because we see comprehensive federal legislation as pretty unlikely in the near term, absent a high salience event or incident. So congressional control is not necessarily the key driver.  And finally, takeaway number four: for markets, we see more micro implications than macro ones. For equities, the composition and cohesion of the congressional majority can matter for individual sectors. Congress that's able to negotiate changes to scheduled SNAP or Medicaid cuts, for example, could have implications for consumer and healthcare companies.  AI related sectors could also respond to changes in expectations and sentiment pertaining to data center restrictions. For rates, the key question is whether the election produces fiscal outcomes that materially change expected deficits.  United Republican control would be the only outcome preserving reconciliation as a potential vehicle. Divided government, conversely, would narrow the scope for new legislation and put more emphasis on funding and debt limit negotiations. And for the dollar, our strategists see the transmission mechanism running primarily through U.S. yields and the growth outlook rather than the election itself.  So, bottom line, we don't think the 2026 midterms are likely to produce a wholesale change in the policy or macro backdrop. But there will be important lessons to pick up along the way.  Thanks 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.

  2. 1d ago

    China’s $12 Trillion Manufacturing Upgrade

    Our China Industrials Analyst Sheng Zhong explains how AI, robotics and a major investment cycle could transform China’s manufacturing base and its role in global supply chains. Read more insights from Morgan Stanley. ----- Transcript ----- Sheng Zhong: Welcome to Thoughts on the Market. I’m Sheng Zhong, Morgan Stanley’s China Industrials analyst.  Today – how AI and automation are transforming China’s factories, and what that could mean for global manufacturing.  It’s Tuesday, September 29th, at 3 PM in Hong Kong. For decades, Made in China has been shorthand for scale, speed, and low-cost manufacturing. Now the story is shifting toward something more ambitious: using technology, productivity, and industrial know-how to shape not just what gets made, but how it gets made.  We call this transition Industry 5.0. Industry 4.0 was about connecting machines and digitizing production. Industry 5.0 goes a step further, using AI to improve how factories schedule production, manage quality, and maintain equipment.  China is starting from a position of enormous scale. It represents roughly 28 percent of global manufacturing value-added and covers all 666 industrial subcategories defined by the United Nations. There are already more than 30,000 basic-level smart factories and more than 100 million connected industrial devices.  That industrial base also gives China a strong platform for robotics. Traditional industrial robots generally perform fixed tasks. Embodied AI could make machines more flexible, allowing them to gain new capabilities through software and updated models. That could effectively turn some physical labor into software-upgradable capital.  And the numbers give you a sense of how quickly this could scale. China could go from selling about 8 million robots a year in 2025 to 29 million in 2030, and 76 million by 2035. That’s roughly a ninefold increase in annual sales in just a decade.  Scaling robotics and AI across such a large manufacturing base will require a lot of capital. We estimate Industry 5.0 could generate about $12 trillion USD of incremental industrial investment in China from 2026 through 2035. Around $5.5 trillion USD would go toward factory upgrades, including robotics, smart equipment, and software, while roughly $6 trillion USD would support new industrial capacity.  But that investment cycle is likely to build gradually. We expect industrial capex growth of about 4 to 5 percent annually in 2026 and 2027, before accelerating toward 6 to 7 percent from 2028 as excess capacity is absorbed, technology bottlenecks ease, and AI adoption broadens across factories.  If that investment translates into higher productivity, the economic impact could be meaningful. By 2035, China’s industrial profit margin could rise to 8 percent from roughly 5 today. Industry 5.0 could lift China’s potential GDP level by around 3.5 percent, helping cushion some of the drag from an aging population. And China’s share of global manufacturing value-added could increase from about 28 percent to 30 percent.  And those changes would not stop at China’s borders. Final assembly can shift to new locations, but the supplier networks, machinery and production know-how behind it are much harder to replicate. We estimate only around 40 percent of China-to-U.S. exports can be readily substituted.  That means China’s role may increasingly extend beyond exporting finished goods to supplying the equipment, components and industrial systems used to make them elsewhere. That is the move from Made in China toward Made by China.  Thanks 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.

  3. 2d ago

    The Stock Market’s Bad Breadth

    Fewer companies have been driving equity market gains in 2026. Our CIO and Chief U.S. Equity Strategist Mike Wilson looks at what investors should make of the narrowing rally as the year enters its final stretch.  Read more insights from Morgan Stanley. ----- Transcript ----- Mike Wilson: Welcome to Thoughts on the Market. I'm Mike Wilson, Morgan Stanley’s CIO and Chief U.S. Equity Strategist.  Today on the podcast I’ll be discussing the Market’s Bad Breadth. It's Monday, September 28th at 11:30 am in New York.  So, let’s get after it. The market is up this year. That's the good news. But over the last six weeks, I've been watching something that’s giving me pause. This rally has been carried by a shrinking group of stocks. More than half of the Russell 3000 is at least 20 percent below its June highs and the S&P 500 forward multiple has fallen to 19 times, close to a new low for the year. Meanwhile, earnings growth is still running in the mid-teens for the median stock and revisions breadth is approaching cycle highs for the S&P 500.  That is not complacency. It is a market that has already done a lot of work to price higher energy costs, a tighter Fed, AI disruption, questions around returns on capital, and geopolitical risk.  Last week on the podcast, I noted that this is classic mid-cycle behavior. Earnings are absorbing lower valuations, and quality is taking the baton from the early-cycle winners. Groups that have led powerfully from the rolling-recession trough have been among the weakest areas recently: Autos, Semis, and short-cycle Industrials.  That is what tends to happen when the cycle matures and the Fed turns less friendly. The market stops paying for high beta. And starts rewarding free cash flow, stable margins, operating efficiency, and earnings that are still being revised higher. That is why I continue to favor large-cap quality, particularly asset-light, services-oriented, and fee-based businesses. Having said that, there is still one problem to resolve. Breadth improved through most of the summer even as crude and yields moved higher. The deterioration came after Jackson Hole. That’s when markets began discounting a more hawkish Fed reaction function. The percentage of S&P 500 stocks above their 200-day moving average fell from roughly 75 percent to below 50 percent, while the index held up much better.  That divergence cannot persist forever. Either breadth catches up to price, or the index comes down to meet breadth. If bond volatility does not settle down soon, it could spill over into equity vol and we would see the S&P 500 price come down about 5 or 10 percent.   Frankly, I would welcome it. A final index-level correction is often how a multi-month correction beneath the surface ends. There has been a lot of focus on the Fed’s recent pivot to rate hikes. However, the two-year yield is already above the level implied by the Fed’s projections. To me this suggests the bond market has been leaning too hawkish in the near term.  The bigger uncertainty is how the new Fed Chairman approaches liquidity and the balance sheet. He is more of a monetarist than his predecessors, and markets are still trying to understand what that means in practice.  My expectation is that the Fed ultimately provides liquidity if financial conditions tighten too far. But markets may test that resolve first. Bond volatility, funding stress, and whether equity volatility follows are the key signals. If those pressures ease, breadth can catch up and drive the market higher. If they do not, the index probably has more correcting to do. There is also a new, constructive story developing for investors: AI adoption is moving from promise to practice. Companies with higher AI adoption are seeing stronger margins and earnings trends, but consensus still assumes many of those benefits fade in the out-years.  We think that’s too conservative. Productivity gains tend to compound, not immediately disappear. Earnings momentum is broadening from enablers to adopters, while adopter valuations have reset to more attractive levels. That supports a barbell approach – own select enablers where earnings durability justifies the premium, but increasingly own adopters where improving fundamentals are not yet fully reflected in expectations. Bottom line, the market is not ignoring risk. It has priced the risks through lower valuations, weaker breadth, and major leadership rotations. What remains unresolved is the gap between a resilient index and a much weaker average stock.  The answer is that we probably see breadth improve and the index level come in before a surge to new all time highs. That’s why, I still want to overweight large-cap quality, but use October weakness to add to riskier stocks.  The market may need one more uncomfortable adjustment. But that may be exactly what sets up a stronger finish to the year. I will be here to guide you.   Thanks for tuning in; I hope you found it informative and useful. Let us know what you think by leaving us a review. And if you find Thoughts on the Market worthwhile, tell a friend or colleague to try it out!

  4. 5d ago

    AI Meets the Physical Economy

    Morgan Stanley Research analysts Michelle Weaver, Ravi Shanker and Dave Arcaro discuss two industrial inflection points: how long it will be before autonomous trucking becomes a reality and why power infrastructure is racing to keep up with AI-driven demand. Read more insights from Morgan Stanley. ----- Transcript ----- Michelle Weaver: Welcome to Thoughts on the Market. I'm Michelle Weaver, Morgan Stanley's U.S. Thematic and Equity Strategist. Ravi Shanker: I'm Ravi Shanker, Morgan Stanley's U.S. trade transportation analyst Dave Arcaro: And I'm Dave Arcaro, Morgan Stanley's Utilities, Power & Clean Energy analyst. Michelle Weaver: Today, what we learned at Morgan Stanley's Industrials Conference about the changing economics of autonomous trucking and the increasingly tight power market supporting the AI build-out. It's Friday, September 25th at 10am in New York. Now, I know we're all on the road taking meetings post-conference, so the audio might sound a little bit different, but we wanted to bring you the latest from our annual Industrials Conference that recently concluded in Laguna Beach, where two themes really stuck out. The growing physical infrastructure demands behind AI, particularly power, and the shift in autonomous trucking from proving the viability of the technology to commercializing it at scale. Ravi, after roughly a decade of development, you've said autonomous trucking is entering a critical 12 to 18-month period ahead of serial commercial production. What's changed, and why is the debate shifting from whether the technology works to whether it can be commercialized at scale? Ravi Shanker: I think for 10 years the industry has been focused on making the technology work. but with players like Aurora now putting up almost half a million miles of fully driverless revenue-generating operations, on public highways in the U.S., day and night, rain and shine, for different customers. With people like Kodiak, also running, several trucks, in revenue-generating service, for customers like Atlas, I don't think there is much debate on the technology itself. And so, I think the debate is now moving from does this work to can this work for me? Where the next steps are going to be dotting i's and crossing t's on the path to actually pressing these trucks into commercial service rather than having to prove that it works in the first place. Michelle Weaver: Your research suggests that autonomous trucking can deliver roughly a 20 percent lower cost per mile, while higher utilization could be an even bigger source of value. What are the key assumptions behind that math? And what still needs to happen operationally for fleets to capture those benefits? Ravi Shanker: Yeah, so we recently updated our TCO math, on autonomous trucks and published a North American insight, where we revised and revisited our views on autonomous trucking with a lot of proprietary data, in there as well. And part of that new TCO math, again, I think revisited some of the changes in the split of operating costs of trucking over the last several years. First of all, I'll kind of throw a huge disclaimer out there that your mileage may vary, right? Because, depending on who you are as a trucker, if you're public or private, small or large, dry van or reefer, heavy or asset light, long haul or short haul, your split of costs are going to be slightly different. But we started out, by looking at the ATRI's national average. And labor accounts for 35 to 40 percent of the P&L of the average trucker. So, when you take the driver out and substitute that with an autonomous driver, if you will. Even after paying the autonomous technology company roughly 85 cents a mile, for the autonomous operation, you will still save a significant amount of money. Versus the 40 percent of the roughly $3 per mile that it costs for labor today. In addition to that, fuel is another third of your cost structure. And there, an autonomous truck should be anywhere from 13 to 22 percent more fuel efficient. We have taken the low end of the scale to be conservative. And then you layer on insurance savings, maintenance savings on top of that. Even if you add some incremental costs, either for human drayage at both ends or for the truck itself being more expensive – we believe you will save about 20 percent per mile versus a human driver today. And I'll point out that the unit economic savings are only about a-third of the total savings with the utilization benefit driving another two-third savings on top of that. Michelle Weaver: But there, there still seems to be a notable disconnect between how much freight carriers and shippers think can be automated and how much of the network may actually be suitable to be automated. What's the industry potentially underestimating? Ravi Shanker: Yeah. We have seen this in our conversations. Again, part of our report was conducting detailed surveys and in-depth interviews with a lot of our coverage companies. And I will say that there still needs to be a lot of education, of how these trucks work, where they work, what the unit economics are going to be out there. There's still a lot of misinformation. For instance, there's this big perception that you still need human drivers at both ends of an autonomous truck move because these trucks can only operate on a highway. And here's where our AlphaWise analysis, comes in. I think it's the first of its kind analysis where we use geolocation data to pinpoint 10,000 plus of the largest commercial facilities belonging to the hundred largest commercial shippers in the U.S. And we found out that the average [00:05:00] commercial facility is less than two miles away from the nearest ramp point. And these trucks can comfortably do seven to 10 miles, if not longer, off a highway on main roads to get to their end destinations. So, I think you just need a lot of education in the industry. And that is part of the dotting of i's and crossing of t's that we think the industry needs to do in the next 12 months before we see the start of serial commercial production next year. Weaver: Thanks, Ravi. I want to bring Dave into the conversation here, and that question of turning demand into real world capacity brings us naturally to power, where the challenge is also increasingly about physical infrastructure and execution. Dave, coming out of Laguna, you describe management commentary across power equipment as notably positive. What surprised you most about what you heard on demand bookings and project activity? Arcaro: Yeah, absolutely. What surprised me most was probably how consistent the commentary was across companies, across large frame turbine providers and the smaller, on-site power equipment players, the new entrants and the more mature companies in the market. Very consistent feedback. All very positive. And I would say also what surprised me too was the lack of disruption across the board. You know, we all see the headlines about data center moratoriums, political pushback, community challenges that really, it seemed, to increase the risk of data center execution and delays out in the market. But at least with the power equipment companies, they're just not seeing it. You know, in terms of the feedback that we heard from management teams across the board at Laguna, they review project timelines actively with their customers, and that's all still intact. We haven't seen any changes in bookings or slot reservations for equipment deliveries. Still seems to be a very stable and very strong backdrop across the board. Weaver: One of the broader conference themes was the availability of power is becoming a bottleneck for AI infrastructure. How are equipment shortages, longer wait times, and customers planning further ahead affecting pricing? And how far ahead can the industry see? Arcaro: Yeah, we are seeing equipment companies booking out orders farther and farther. The large frame gas turbines, to give you a couple examples, from companies like GE Vernova, they're now in conversations to contract turbines for 2031 and 2032. Smaller equipment companies like INNIO, who make, smaller scale engines for data centers, they're in conversations with customers and taking reservations into 2029 and 2030. So, what we heard from the conference as well was that utilities, which is a big customer for this equipment, they're looking out farther and farther now into the 2030s. That's new and that's a surprisingly long time in terms of how far they're looking out. And we're also hearing data centers looking out toward the end of the decade, you know, late 2020s in terms of trying to secure their power equipment in advance. We would still consider it very much a seller's market. Pricing has been rising, and companies at the conference gave further indications that it's likely to keep rising, what looks like into the 2030s from here. We just haven't seen any signs of softening yet, really regardless of the company or the equipment type that they're selling into the market. So still farther and farther out that we're seeing visibility into the order flow, and with that is also coming firm and even rising prices into the 2030s. Weaver: Investors often frame the power debate as electricity from the grid versus smaller power sources built on-site at data centers. Based on what you heard at Laguna, how should investors think about the balance between those two approaches? Arcaro: Yeah, it's an interesting dynamic. When you talk to utilities and some of the large frame turbine companies, they all say that all this data center demand is going to the grid. Eventually, it's all going to go to the grid. When you talk to the smaller equipment manufacturers and the power as a service providers, they say nobody wants the grid. They see long-term opportunities to sell, on-site power equipment and contract it with their end customers for 15 to 20 years, and we're seeing evidence of that. So, I think, it'll stay It's an ongoin

  5. 6d ago

    The Global Diesel Problem

    Diesel is at the center of an international supply squeeze, with prices rising to historic highs. Andrew Sheets and Martijn Rats unpack why this industrial fuel matters far beyond the pump. Read more insights from Morgan Stanley. ----- Transcript ----- Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Global Head of Fixed Income Research at Morgan Stanley.  Martijn Rats: And I'm Martijn Rats, Head of Commodity Research at Morgan Stanley.  Andrew Sheets: Today, the secret life of diesel and why there's so much attention on it.  It's Thursday, September 24th at 2pm in London.  Diesel is a fuel that I think a lot of investors may be aware of but not familiar with, so to speak. It's often the other price that you see when you're driving down the road.  But Martijn, it's incredibly important for the industrial side of the economy and unusually disrupted by current geopolitical events. And so, I'd like to really start at the top, or technically the middle of the barrel, so to speak.  What is diesel and what makes it so special?  Martijn Rats: Yeah. When people talk about diesel at the moment, they really talk about sort of three things combined. They talk about outright diesel, as well as jet fuel and also heating oil.  These are effectively part of the same pool of molecules coming out of the refinery. And so, when you look at that sort of pool of molecules, you talk about the things that fuel trucks, trains, ships, tractors in agriculture, excavators, generators, home heating. It is a molecule that has a tremendously broad range of applications.  It's really the fuel of the industrial economy.  One of the characteristics of diesel is that it has very high energy density. In contrast to, say, gasoline, electrifying the uses of diesel is harder because it carries so much punch.  Andrew Sheets: And why has there been so much on diesel recently, given the current energy disruption in these geopolitical events?  Martijn Rats: Yeah. So, the global refining system normally processes about 85 million barrels a day of crude oil and from that, it makes a range of products. Diesel is at the heart of it. But it's only one of many.  At the moment, we are short in terms of refinery runs, i.e., the amount of crude that refineries process to the extent of about somewhere between 4 to 5 million barrels a day. So, 4 to 5 million barrels a day on a base of 85, you're talking about 5 to 6 percent. That may not sound like a lot, but in the world of commodities, where prices really depend on relatively small changes, that is actually a very large amount.  That sort of 4 or 5 million barrels a day of refineries that are currently not running, they are fifty-fifty, either in the Middle East or in Russia. In the Middle East, it is a story of the Strait of Hormuz and refineries locked behind the strait, and they can't export their products. Some of them are also damaged, although information on that is hard to find.  And then the other half that is out is in Russia, where they are effectively taken out by Ukrainian drone attacks.  In total, that's sort of 4 to 5 million barrels a day of refining capacity that is not running. 40 percent of their output would typically be diesel, so we are missing something like 1.5 million barrels a day of global diesel supply, all into the seaborne market.  Now, I mentioned the seaborne market because the seaborne market is the traded market where traders buy and sell cargoes to each other. And that is where, from a physical market perspective, price formation takes place.  The global seaborne diesel market is an 8 million barrel a day market. And so given that all of the supply we're missing is also into the seaborne market, the comparison to make is to say that we're missing about, sort of, close to 1.5 million barrels out of an 8 million barrel a day traded…  Andrew Sheets: A pretty large percentage, yeah.  Martijn Rats: Absolutely. That is very, very large, and that is hard to offset. Every other refinery around the world that can run is running flat out. The margins are all-time highs. So, there's a lot of incentive to run very hard. But nevertheless, it's left the market very, very tight.  Andrew Sheets: So, that tightness in the market shows up via price. And just talk us through a little bit about what has happened to the price of diesel and its related fuels. You know, I think a lot of listeners are probably more familiar with the price of gasoline. They're more familiar with the barrel of oil that's often the quoted benchmark in the market.  But what has been happening to these diesel prices?  Martijn Rats: Yeah. So, the way to really tell that story is to look at what we call the crack spread. So, making a barrel of refined product, including diesel, of course, you start with crude oil. So, the price of crude oil impacts the price of the refined product. So, quite often we focus more on the uplift from the price of crude to get to the price of the refined product, and we call that the crack spread.  Under normal conditions, say a year ago, crude was $70, and then the price of diesel was another $20 on top of that. And so, you got to diesel being 70 plus 20 is $90 per barrel. At the moment, crude is higher. Crude is about $100 per barrel. Crude has rallied. But the increment on top of it has spiked.  So, a couple of days ago we got to all-time high nominal term diesel prices over $200 per barrel. So, we're now having a situation that is [$]100 for crude plus another [$]100 to get to the diesel price. So, the crack spread is something that normally lives in a range of, like when the diesel market is weak, maybe sort of $8, $9, $10. When the market is normal, close to $20. If it's very strong, $25 to $30.  Now, that incremental crack spread is $100 per barrel, and that is something that we've not seen before. It is stronger than it was in 2022, when we also had a moment of a severe diesel crisis. Didn't last very long in 2022, but the crack spread got to sort of $60, $70 per barrel. So, that highlights the extent to which the price of diesel has rallied.  Andrew Sheets: So, Martijn, you mentioned this crack spread. You know, I think if we all go back to our organic chemistry, this is the refineries literally cracking a barrel of oil down into constituent distillates and other pieces.  But given those very high prices for diesel, why don't the refiners just refine more? Why aren't the incentives increasing production? What's getting in the way of that?  Martijn Rats: Yeah. That's just a matter of like the physical reality of the system.  So, when you build a refinery, you often quite think about two things. What crudes are available to me. So, if you're in the United States, you have U.S. shale crudes, or you have crude from Mexico, Canada. And based on those, you then also think about, you know, what is my consumption, where I am likely to be. And based on that, you build a certain configuration – that converts the crudes that you can buy into the products that your specific customer set might need.  You fix the configuration of the refinery at the time you build it. And once it's built, there is a little bit of flexibility to say, "Oh, well, maybe at the moment I make a little bit more diesel and a little bit less gasoline," and change the – what we call the yield of these products. Like a little bit within, you know, a few percentage points range.  But that flexibility is small, so the only thing you can do to make more diesel is to run the refinery at 100 percent utilization. That is currently where we are. That has already happened. And then you put in the crude that you buy, you get the products for which your refinery is then designed, and that's it. There are no other…  Andrew Sheets: You can’t just turn a big dial that says more diesel.  Martijn Rats: No. You can't say, "Oh, well, I don't like my naphtha output this week, so let's not make any naphtha for the chemical industry. Let's only make diesel." It's not contained in the barrel of crude and the kits that you have – takes many years to rebuild and probably very expensive. So you're kind of then stuck. I mean, it is what it is.  Andrew Sheets: So Martijn, where is this leaving the global story? You know, if we think about just the relative price of this. Again, you mentioned it's an incredibly important fuel for agriculture, for industry… What's it looking like kind of across the major regions?  Martijn Rats: Yeah. Look, it leaves a very tight market at the moment. I mean, it's relatively straightforward.  The price of diesel depends very heavily on how the geopolitics of the Middle East and Russia sort of play out. So, in terms of the traded price that you see on the screen every day, it swings around very heavily with how the market foresees the future with regards to these two conflicts.  So, one week things flare up, the price of diesel rallies. The following week the market feels a bit more optimistic maybe around a deal, so then things sort of sell off. So, we have to live with that sort of geopolitical sort of reality. But other than that, those who can afford it pay a high price to effectively erode demand amongst sets of consumers who cannot afford these higher prices.  You see a substitution, for example, what I thought was very interesting last week. Some of the train companies in the United States were talking about a truck-to-train substitution of very high levels of cargo loads on trains because simply the diesel on trucks is too expensive. So, you see those behavioral changes come through.  Andrew Sheets: But that point about demand destruction is really important because, you know, a point that you've made over many years is this idea that the solution to higher prices is higher prices. That that reduces the demand for the fuel, that helps these markets recorrect.  And yet, you know, we're hitting prices in diesel that are near all-time high

  6. Sep 23

    The Unexpected Investment Case for AI Safety

    Tighter AI safety requirements could reshape the pace of AI investment. Ariana Salvatore and Michael Zezas dig into why the spending may shift toward more compute, not less. Read more insights from Morgan Stanley. ----- Transcript ----- Ariana Salvatore: Welcome to Thoughts on the Market. I'm Ariana Salvatore, Head of U.S. Public Policy Research at Morgan Stanley.  Michael Zezas: And I'm Michael Zezas, Deputy Global Head of Research at Morgan Stanley.  Ariana Salvatore: Today, we'll be talking about AI safety and regulation.  It's Wednesday, September 23rd, at 10am in New York.  We put out a note last week on AI frontier capability gain and the associated safety risks.  Those have been in focus in recent weeks, and as a result, we've gotten a number of questions about the path forward for government regulation.  So today, Mike and I are going to get into some of the newest developments, where we think things are headed, and how the midterms could shape that path.  Michael Zezas: Yeah, and this is pretty important because the concern is that if AI safety scrutiny increases, it's going to slow everything down. You might have less CapEx, fewer model releases, and there's all sorts of downstream effects for the pace of U.S. growth and investment strategy in equities and throughout the AI investment theme.  But Ariana, you and the team landed in a bit of a different place and are arguing that a bigger focus on AI safety could end up being a tailwind to compute spend rather than a brake on it. Can you break that down for us?  Ariana Salvatore: Sure. So, the way we see this playing out, is there are five potential states of the world. Some include industry self-policing; some include the prospects for heavier government intervention. Across all of them, as you mentioned, we actually think this is a pretty big tailwind to compute spend and CapEx more broadly.  That's because as the labs integrate greater safety monitoring infrastructure, we think that spend is only going to accelerate, especially as LLM capabilities increases at a nonlinear rate. Similarly, on the regulation front, we think there are a few things that prevent something like a large comprehensive AI regulation bill from coming to fruition.  We think there's really three, kind of, key obstacles to something like that happening.  The first is the politics. So, the president himself has said he's against some sort of large-scale regulation. The second is the procedure. So mechanically speaking, there would need to be a legislative vehicle for this sort of thing to ride on. That's hard to see emerging in the very near term. And the third is precedent.  So, historical precedent here tells you that usually regulation is catalyzed by some sort of high salience event. That's why our framework for government reaction here hinges on two components: incident salience, as I just mentioned, and instrument availability. Instrument availability basically reflects the extent to which the government already has a tool that it can pull in this direction.  So, that's how we think about it going forward. That doesn't mean all policy action is off the table, but that supports our expectation for higher CapEx, higher compute spend over the coming years.  Michael Zezas: Right. So, the idea is that the spending continues and the things that would otherwise limit that spending, you don't see as real plausible policy options at the moment. And can you break this down a little bit more? Because I know there's a lot of different proposals floating around Washington, D.C. from policymakers right now.  What are you paying attention to?  Ariana Salvatore: We don't expect an overarching AI regulatory authority in the near term. Now, importantly, we also don't expect sweeping open weight model regulation. The reason for that is threefold. First of all, we think the U.S. is keen on maintaining this managed stability relationship with China.  We've written about the expectations around the U.S.-China summit. That's kind of a delicate balance that we think is likely to persist. So, overly restricting open weights models might throw a little bit of a wrench into that equilibrium that we see. So that's the first reason.  The second reason is diffusion. We think the U.S. administration wants to see the proliferation of open weights models. We know that companies are using some sort of hybrid of open and closed weight. So, to the extent that, you know, banning these models would slow adoption, we don't think that's in the interest of the administration.  And the third reason is purely mechanical. It's really hard to enforce these sorts of restrictions. Once a model weight is published online, it can be really hard to clamp down exactly who and where it's going to.  Obviously, companies can download them, customize them, et cetera. So, the enforcement picture here is also really challenging. That being said, we do think that the executive can continue to lean in and, sort of, make some incremental adjustments or changes on the regulatory front. But we think it's likely less severe than some of the proposals you're seeing in Congress right now. Things like the Kill Switch Act, for example, which basically mandate that companies can maintain an ability to shut down models at a moment's notice, right? If a certain threshold is crossed.  So, that's something that we see as less likely to come to fruition. But again, setting safety standards, guardrails, all of that from the administration we think is possible in the near term. Michael Zezas: What about some of the pushback that would at least appear to be rising at the state and local level around construction of data centers?  Is that something that you think might materially slow the industrial build-out and the CapEx levels around AI?  Ariana Salvatore: So far, what we've seen is that AI safety risks are not the top of the priority list when it comes to data center pushback, right? So, things like environmental concerns, affordability – those tend to be the main vectors of the opposition.  That being said, we've gotten the question, right, to your point, of does this, sort of, risk focus mean that the data center backlash is likely to grow? We think that it could, but at the same time, we think this is a highly idiosyncratic issue, meaning that this is something to pay attention to on a very granular level.  Certain states and localities will be the ones to really administer these restrictions, and we think in the aggregate, hyperscalers are going to be able to continue to mitigate. We've already seen these mitigation measures employed. We're still constructive on AI CapEx this year and next, because overall, we see the build-out really becoming more of a conditional build-out.  So, that means contingent upon some of these concessions, maybe it's more expensive in certain areas. But overall, we don't think that the concerns around safety are going to derail that story.  Michael Zezas: So, then when it comes to data centers, the conditions that might be being put on their construction at the state and local level, for the most part – those building out the data centers have been willing to make those concessions, so it hasn't slowed that much. Is that fair?  Ariana Salvatore: That's right, and it really depends on where the pushback is coming from, right? So, in some cases, you're seeing communities push back on things like water usage, right? And we're seeing the hyperscalers come out and respond and say explicitly, you know, how much water they're using in some of these operations. Google is proposing a regulatory framework, so that's something that they're mitigating through that lens.  In another example, you've got local communities pushing back on just, sort of, disruptions to quality of life, and you're seeing companies like Meta announce a fund to engage more locally there. So, it really is different. There's no one-size-fits-all solution here. But yes, I agree with you that overall, we don't think this is going to meaningfully constrain the build-out.  Michael Zezas: Got it. So, it seems like the idea here is that the secular trend around AI development is going to continue in your view. Is there any way that you think the midterm elections or the outcome around that might change your thinking?  Ariana Salvatore: So, I think the midterms will be important for sentiment, but when it comes to the actual policy path, we don't think they're the main driver, and there's two key reasons for that.  The first is obviously the president is not changing until 2029. So, the fact that President Trump still has to be involved in any capacity – if we were to see a bill emerge from Congress to us gives a little bit of clarity on what that bill could actually look like. And so ultimately, whatever comes to fruition will have to be a product of collaboration between Democrats, Republicans in Congress, and the president. So, that's a pretty much a constant.  The second reason I would say is because, as I kind of alluded to earlier, you tend to see government response when there's a high salience event. And in that case, it doesn't really matter what the government configuration is if it's reactionary.  When you think back to things like the pandemic, we saw the CARES Act. In 2008-2009, you saw the ARRA. Those are all efforts that were produced in a divided government. And so, in that vein, we basically think that you need to see some sort of event catalyze a response.  The key driver is not going to be government configuration. It's going to be the salience of that event specifically.  Michael Zezas: Okay, got it. So, the guidance to investors on the back of all of this is what?  Ariana Salvatore: So, the thematic recommendations from our team are intact, right? So, what we were talking about is basically we see these all converging towards a tailwind to CapEx and a tailwind to compute supply.  So, in t

  7. Sep 22

    Why Central Banks Are Raising Rates Again

    Central banks are turning more hawkish as inflation risks increase. Our Global Chief Economist and Head of Macro Research Seth Carpenter explains what that means for the Fed, ECB and Bank of Japan. Read more insights from Morgan Stanley. ----- Transcript ----- Seth Carpenter: Welcome to Thoughts on the Market. I’m Seth Carpenter, Morgan Stanley’s Global Chief Economist and Head of Macro Research. Today, I’m going to talk about all the movement we’ve seen in central banks and how it’s changing our forecasts.  It’s Tuesday, September 22, at 10 a.m. in New York.  Over the past two weeks, our economists here at Morgan Stanley have revised their outlooks for the Fed, the ECB, and the Bank of Japan to include more rate hikes.  Each economy faces different challenges, but all three central banks have arrived at roughly the same conclusion: growth has remained remarkably resilient despite all of the shocks hitting the global economy. And renewed energy-price pressures have increased the risk that inflation proves more persistent than they had previously expected.  The clearest example—and our biggest revision here—is the Fed.  Now for much of this year, we had actually thought the Fed might avoid hiking interest rates altogether. But in addition to this increase that we just saw at the September FOMC meeting, we now expect two additional rate hikes—in December and in March that will bring the terminal rate up to 4.25 to 4.5 percent.  While Chair Warsh has highlighted the inflationary implications of higher energy and commodity prices, for me, the more important signal was the assessment that policy is not sufficiently restrictive.  So in our view, the Fed appears to be reassessing not just the inflation outlook, but the amount of restraint that is required to bring inflation sustainably back to target.  But even with all of that said, we’re still looking at this shift as more of a recalibration of policy for the Fed rather than a fundamental shift in policy. And so the market may have—just may have—overestimated how much hiking is left.  But the shift does have clear and important market implications.  Our rate strategists expect investors to pull forward additional tightening expectations in the near term, while increasingly questioning how long policy can remain at restrictive levels before growth starts to slow. But more broadly, the Fed now appears a bit more sensitive to energy-driven inflation pressures, and that strengthens the case for a firmer dollar.  Over recent months, rising energy prices have supported the euro because investors have seen the ECB respond more aggressively than the Fed. That maybe former asymmetry could be changing.  Our foreign-exchange strategists therefore continue to favor dollar strength, particularly against the yen.  Now Europe does face a similar inflation challenge to the Fed, though through a different mechanism.  The renewed rise in natural-gas and other energy prices has led our economists to revise up their inflation forecast materially and, therefore, to add in another ECB rate hike in December.  But we have got to keep in mind that it is not energy prices all by themselves that have changed the outlook.  Economic activity in the euro area has also proven to be much more resilient than we had anticipated. And that reduces concerns that an additional modest tightening of policy would derail growth.  And so if you take it all together, the ECB is increasingly focused on preventing higher energy costs from feeding into broader inflationary dynamics.  Now Japan might seem different, but the underlying story is really surprisingly similar.  For decades, the BoJ’s challenge was generating inflation. But now policymakers are now increasingly concerned about the possibility that inflation will overshoot its target.  After the BoJ’s hike last week, we expect it to raise rates to 1.5 percent in December and then raise rates further, to about 1.75 percent, in March.  Like the Fed and the ECB, the BoJ faces an economy that has absorbed tighter financial conditions much better than had been expected. And yet, unlike the Fed and the ECB, our strategists believe that markets have become too aggressive in pricing the eventual destination of rates. And that creates scope for expectations to be revised lower over time.  As a result, while Japanese rates may continue to rise gradually, our foreign-exchange strategists still expect a broader trend of yen weakness to emerge once temporary positioning effects fade.  So the common thread across all three of these central banks that I’ve discussed is that, while the energy shock has changed the inflation conversation, the resilience in growth has further changed the policy conversation. And so for investors, next year is probably going to be characterized by higher policy rates and a stronger dollar than markets expected at the beginning of the year.  Well, thanks for listening. And If you enjoy the show, please leave us a review and share Thoughts on the Market with a friend or colleague today.

  8. Sep 21

    Market Resilience Isn’t Complacency

    Our CIO and Chief U.S. Equity Strategist Mike Wilson discusses why quality stocks, strong earnings and price momentum support his view that the bull market remains intact. Read more insights from Morgan Stanley. ----- Transcript ----- Welcome to Thoughts on the Market. I'm Mike Wilson, Morgan Stanley’s CIO and Chief U.S. Equity Strategist.   Today on the podcast I’ll be discussing the ongoing mid-cycle transition.  It's Monday, September 21st at 11:30 am in New York.   So, let’s get after it.  The S&P 500 is near record highs. That’s despite rising energy prices, two wars running in parallel and AI safety concerns back in the headlines. Meanwhile central banks are tightening. On paper, that's a lot of reasons to be nervous. So are investors just being complacent? I don't think so.  More than 40 percent of the Russell 3000 has fallen at least 20 percent since June, while the S&P 500’s forward price earnings multiple has fallen back to 19 times, which is almost 20 percent lower than a year ago. At the same time, median stock earnings growth is running around 15 percent, and revisions breadth is back near cycle highs. Falling valuations alongside strong earnings growth is not complacency. It is the definition of a classic mid-cycle transition.  That distinction matters because mid-cycle markets tend to frustrate almost everyone. The index can remain resilient while much of the market corrects. Earnings can stay strong while multiples fall. And leadership can change without the bull market ending.  Last week’s Fed meeting fits squarely into that framework. The 25-basis-point hike was largely priced, so the real information was Chair Warsh’s willingness to follow through on his commitment to fight inflation. Recent core inflation data were firmer than expected, but the details were not uniformly hot.  Some of the upside was concentrated in a handful of categories, shelter remained soft, and tariff pass-through appears to be fading. That gave the Fed room to act without forcing investors to assume we are heading into another 2022-style tightening campaign.  In my view, the hike can enhance credibility. If investors believe the Fed is acting early enough to contain inflation, a higher policy rate can reduce uncertainty and term premium rather than automatically driving long-term financing costs higher.  But the rate hike is not my concern. A few additional hikes over the next year are unlikely to end this bull market if earnings remain strong. The bigger unknown is how a Warsh-led Fed approaches the balance sheet, money supply, and credit growth. His philosophy has historically leaned more monetarist than prior Fed chairs. However, we still don’t know how aggressively he will apply it – or how much influence he will have over the rest of the committee. That matters because the private economy is using more capital, and an overly restrictive approach to liquidity could become more consequential than the policy rate itself.  This is one reason I continue to favor large-cap quality. High free-cash-flow yield, low accruals, and operating-efficiency factors are leading, while the high-sales-per-employee factor has been one of the strongest recent performers. That also aligns closely with our preference for AI adopters rather than the enablers.  Price momentum is not disappearing. But its composition is changing toward quality, services-oriented, asset-light, and fee-based businesses. That is exactly what should happen during a mid-cycle transition.  The near-term swing factor remains energy prices. Another meaningful rise in crude or refined products would put upward pressure on the expected policy path, long-end yields, and bond volatility in an unhealthy way. It would also arrive during a period when midterm-election seasonality often produces a 5 to 10 percent index correction.  In a worst-case near-term scenario, the S&P 500 could trade near 7100, but I would view that as a tactical correction within the bull market – not a change in our fundamental views. Either way, I remain convicted in our 8,000 year-end price target.  The bottom line is that this market is behaving exactly like a mid-cycle market should: valuations are compressing, earnings are carrying the load, and leadership is moving toward quality. The index may look calm, but plenty of concern has already been priced at the stock level.  The mistake would be confusing resiliency with complacency—and missing the rotation taking place in plain sight.  Thanks for tuning in; I hope you found it informative and useful. Let us know what you think by leaving us a review. And if you find Thoughts on the Market worthwhile, tell a friend or colleague to try it out!

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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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