The Potential Way Forward for the U.S.-Iran Standoff

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 look at an important shift in what the market wants to see from companies going forward.

It's Tuesday, August 11th at 11:30 am in New York.  

So, let’s get after it.

This week I am going back to our broadening thesis – but with a slightly different twist.

Earlier in the year, broadening was about beta. It was about the market moving beyond a narrow set of mega-cap winners and rewarding economically sensitive areas as the rolling recovery took hold.

In the last few episodes I’ve talked about how that phase is now over. And we’re moving from an early-cycle broadening into a mid-cycle quality rotation. In short, the market is no longer demanding just growth – but growth with durable earnings, strong margins, and free cash flow.

To be clear, the broadening in earnings is still very much alive. Russell 3000 median stock earnings growth is running at 15 percent, the strongest since 2021; while median sales growth is at 8 percent, the best since 2023. At the same time, 87 percent of S&P 500 companies are beating earnings expectations this quarter, and earnings revisions breadth has rebounded to 23 percent, with 76 percent of industry groups showing positive revisions breadth.

However, headline earnings are no longer enough for stock outperformance. The market is saying, ‘Show me the money’— and that’s exactly what should happen in a mid-cycle transition. When companies raise both earnings and free cash flow estimates, they are rewarded. When they only raise earnings and not free cash flow, the market is much less forgiving. Investors are no longer paying indiscriminately for growth. They want cash conversion.

This is also why I think AI adoption remains such an important theme. The market is increasingly rewarding companies that can demonstrate real efficiency gains from AI, not just talk about the open-ended opportunity in abstract terms.

That is a very different phase for the AI cycle. The first phase was about building the infrastructure. The next phase is about who uses it well. Companies that can translate AI adoption into better margins, better productivity, and better free cash flow should continue to be rewarded. In other words, AI is becoming less about the promise and more about the evidence.

That framework tells us where to be positioned. I continue to favor quality and AI adopters. Within Financials, I prefer large-cap Financial Services, particularly Insurance and Capital Markets exposed businesses, where earnings revisions are inflecting and our regime analysis remains supportive. Within cyclicals, I like Discretionary Goods, where the wallet-share shift from services to goods, improved pricing, and better earnings revisions all point to catch-up potential.

In Tech, I continue to prefer hyperscalers over semis. Semis can still participate tactically, especially after recent momentum unwinds, but the hyperscalers offer a better multi-month risk-reward. They have resilient core businesses, attractive relative valuation, and underappreciated optionality around AI-related ROI and adoption. Just as important, they are not only enablers of AI, but they are early adopters. They have the flexibility to spend less if the market becomes more demanding about capex discipline.

In terms of remaining market risks for this year, I’m still watching interest rates and oil very closely. A gradual rise in nominal yields alongside strong economic and earnings data is not necessarily bearish. In fact, historically, that has been one of the better environments for equities because it brings back my ‘run it hot’ theme. Stronger nominal growth supports revenues and earnings. The problem is not the level of rates. It is the pace of change. If back-end yields rise too quickly, the cost of capital becomes a headwind for stock valuations.

Bottom line, the broadening is still happening, but the market is raising the bar. Early-cycle beta is giving way to mid-cycle quality. Earnings are broadening, but free cash flow is also necessary to be fully rewarded. AI is still an important market driver, but the market wants measurable benefits and the leadership is becoming more selective within sectors rather than across them.

This shift may make the market feel less euphoric in the short term, but also healthier and more sustainable in my view. This is not a market that is simply chasing momentum any more.

It is starting to separate the companies that can simply talk about growth from the companies that can convert it into durable free cash flow and longer-term value.

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!

Jeff Adelson: Welcome to Thoughts on the Market. I'm Jeff Adelson, Morgan Stanley's U.S. Consumer Finance Analyst.

Jay Bacow: And I'm Jay Bacow, Co-Head of Securitized Products Research, also working at Morgan Stanley.

Jeff Adelson: Today, how AI could change the way Americans shop for, manage, and refinance their mortgages.

It's Monday, August 10th at 10am in New York.

The U.S. mortgage market is worth more than $14 trillion, and its performance ultimately depends on the choices millions of homeowners make. Today, refinancing still means shopping around, comparing offers, and working through a lot of paperwork. AI could make that process much easier, especially when rates begin to fall.

Jay, you led this work on our AI mortgage blue paper. What's the main way AI could change the mortgage market, and why does the borrower matter so much?

Jay Bacow: So we think the biggest change would be borrower adoption of using AI agents to manage their personal finance. An agent on your phone could just monitor mortgage rates, compare lenders, reduce the paperwork, and make homeowners more likely to refinance when the economics work.

Let's think about what that could be. Historically, only about 30 percent of borrowers that had the ability to lower their mortgage rate by a 100 basis points did so in a given year. When a borrower went to get a mortgage quote, less than half of them asked more than one lender for a quote.

That agent could go reach out to 30 lenders, ask for a variety of different mortgages, could upload all the documents, could do this all effectively instantaneously, present the homeowner with the best option. Allow the homeowner to effectively click a button and refinance. I think this could be pretty transformative for the mortgage market.

Jeff Adelson: Now, as we think about this transformation, Jay, mortgage investors still rely heavily on past refinancing behavior trends. If AI makes borrowers more likely to refi[nance] when rates fall, how could that change the way these investors value mortgage-backed securities?

Jay Bacow: Well, we all know that past performance is not indicative of future performance, and those models are likely to understate future prepayments. If you get a faster response, it's going to make mortgages more negatively convex.

That's going to make the durations shorten. It's likely to widen mortgage spreads by about 10 basis points in our base case. And now, if that base case were to happen and we get, let's call it 100 basis point rally in the future, we think that that could cause something like a 40 percent pickup in refinance volumes versus our current expectations of what refinance volumes would look like in that 100 basis point rally.

Jeff, you cover a lot of the largest mortgage lenders. What does this mean for their business model?

Jeff Adelson: So, it's pretty straightforward. More borrowers refinancing means more loans for the industry to originate. Today, we're still sitting below what I would describe as normalized levels of originations.

We're sitting at about $2 trillion of mortgage originations per year. As we think about normalized, we think that's somewhere in the order [of] around $2.5 trillion. So just that $600 billion alone could get us straight there.

We tend to think about this more in our bull case, where we could see something in the order of $3 trillion of originations or more, still below what we saw during the peak COVID years of about $4 trillion or more. But still pretty meaningful and material for the industry.

Now, for the scaled lenders, that can create meaningful operating leverage. Mortgage companies have historically had to hire aggressively when volumes rise, and then they've had to reduce headcount when the cycle turns. AI could allow them to process more loans with the same employee base, making their cost structures more flexible and reducing the need to rebuild capacity during every single refi[nance] wave.

But the earnings benefit we don't think will necessarily match the dollar benefit from volumes. If AI makes it easier for borrowers to compare offers and allows every lender to process more loans, then competition could intensify and pressure gain on sale margins. So the opportunity is a larger market and better productivity.

The key question for individual lenders is: how much of that volume can they capture without giving too much back through pricing?

Now, as we think about automation, Jay, it could bring in more loans, but could also intensify competition and reduce the profit lenders can earn when they originate and sell a mortgage. So, how should investors in your space weigh those two effects?

Jay Bacow: So, the mortgage investors are short the option to the mortgage homeowner of when they can refinance.

And if the mortgage homeowner is going to be more efficient about refinancing, the mortgage investor is going to need to get paid more for that. They're going to demand wider spreads, and they're particularly going to demand wider spreads where that option that they're shorting is worth more. That's generally how it's going to play out, but there's also other aspects as well.

That duration shortening, because the borrower's more likely to refinance, means that the investors that own that duration will need to buy some more duration against that. You're also going to see more demand for duration as rates rally. So it's going to be a bid for the low strike receivers, as our options experts will pay close attention to.

And then if we get a further rally, you also get a more of an impact across the consumer writ large. You can imagine a world where mortgage rates are substantially lower than they are right now. An agent could sit there and say, "Why don't you consolidate your debt between your credit card, your auto loan payments, maybe your student loan payments and your mortgage?" Allowing consumers to save more and then maybe spend that in the economy.

Jeff Adelson: If we maybe take it a step beyond refinancing, how could AI affect home sales, homeownership, and access to home equity?

Jay Bacow: So let's just go back to thinking about this agent that's on your phone that's looking at all the opportunities.

Traditionally, right now, most people are only calling up one lender, they're getting one quote. If your agent is looking at lots of different lenders and lots of different options, you're probably going to get more ability to take out a mortgage. So you're going to get an expansion of the homeownership rate.

That's going to create more demand for housing. As rates rally, you're going to get home sale activity picks up more than it used to, and people are also going to be more able to take advantage of the equity they have in their house. So, you're going to get more usage of second liens and HELOCs and cash-out refinance activity.

Once again, we think this is mostly going to happen three to five years down the road, but we're not really sure exactly how this is going to play out.

So Jeff, what would be some of the signs that people could look at to see if it's playing out in the three to five-year timeline that we're expecting – or slower, maybe even faster?

Jeff Adelson: Sure. So yeah, I mean, I think it's going to be similar to what we've already observed as consumers ourselves and what we're seeing with all the LLMs and AI tools we're adopting today. You should see some rapid advances in the ease of use and the adoption of these technologies from a forward-facing, client-facing perspective. What we all see in the websites, what we all see in the apps.

It should become easier for us to engage with the mortgage process, compare rates to actually step into the process. Whereas today, you still need to maybe speak with a bank officer, a loan officer, or a mortgage broker to get deeper into the process and actually better understand what your rate means today.

So that would be the first step. The second step would be closing speeds. The average originator today still takes about 40 to 45 days to close a mortgage. The biggest and largest originators that have invested the most in technology and AI today are closing at about, call it, 12 to 20 days. So, half the industry level. So, that should come down over time and make it much easier to actually apply and finish a mortgage.

And then quite frankly, the most obvious answer would just be at the given level of rates that are outstanding today, we should see a step up in the level of refi[nance] volumes. That would be the most obvious one. But that'll be the outcome of everything else we've talked about rather than the actual cause.

Jay Bacow: That makes sense. So faster refinancing, it's likely to make the mortgage market more responsive when rates fall and effects that are going to reach well beyond the borrower.

Jeff Adelson: That could mean higher volumes for lenders, quicker prepayments for investors, and wider swings across housing and rates markets.

Jay Bacow: Jeff, thanks for taking the time to talk.

Jeff Adelson: Great speaking with you, Jay.

Jay Bacow: And thank you all for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today.