Full Transcript: Liz Ann Sonders on the Outlook for 2026

Why Instability Matters More Than Uncertainty

Justin: Hi Liz Ann. Welcome back to Excess Returns.

Liz Ann: Hi guys. It’s a pleasure to be here. Thanks for having me on again.

Justin: One of your earliest mentors in the business and the legendary growth investor Marty, who I often reminded investors that the stock market is not a place for certainty. It’s a world of probabilities and not predictions, and that’s exactly why we like having you on to talk with us and our audience.

we really value your ability to kind of cut through the noise in the markets and help investors understand what’s really going on beneath the surface with sort of. Data grounded thoughts, sort of a, perspective of market history, and kind of respecting, the uncertainties that are always existing in the market.

So, I think this is gonna be a great conversation about what you and the team at Schwab are, are thinking about currently. And, how you’re advising and educating investors. Sure. So really looking forward to this conversation. Thanks, me too. one of the things that you’ve, I think written about recently is that you framed this year 2026, around the idea that the environment is not just only uncertain, but it’s fundamentally unstable.

And so I wanted to maybe start there and just have you walk us through sort of how you’re thinking about that and the distinction and, and, and why that matters for investors.

Liz Ann: Yeah, and I think it’s, it’s more than just a, a nuance in terms of the, the distinction between those two un words, uncertain and unstable.

I, I started thinking about that when, yeah, we hear it all the time, how often you hear the line markets hate, uncertainty, and I always chuckle inside my own head when I hear that, because I think. Is it ever certain, I, I’ve never woken up to the front page of the Wall Street Journal saying, we know everything, everything is certain.

So I, I think it’s the instability piece that is unique in this backdrop. It is, certainly as it relates to policy, as it relates to geopolitics, tariff related policy has been unstable, monetary policy. Has been unstable. We’ve had fits and starts in both of those. the, sometimes the messages we, we, we get, particularly from the administration, not, not to make this a political angle by any means that it can kind of come on a fly and.

I think there’s this tendency for knee-jerk reactions on the part of the investment community, and it’s this instability that makes this cycle a little bit different. And it’s leading, it’s in part leading to some of the bifurcation, some of the kha nature in this cycle, and I’m not sure that eases anytime soon.

Justin: Well speaking of the K shaped sort of bifurcation that you just mentioned, I mean, one of the, you guys had a really interesting chart and we’ll sort of put it in the podcast here.

and sort of visually looking at sort of what the drivers are. That are driving this kha sort of bifurcation in our economy and, and among consumers and people. So can you just talk to that a little bit?

Liz Ann: Sure. And, it, it’s, maybe even gotten an overused descriptor of the environment, but I think the use of that letter is very descriptive and I think people in general understand what you mean.

And there’s so many levels and layers of it. Probably the most commonly discussed is the K shape. among consumers, so high income consumers versus low income consumers, and, and there’s, there’s threads and tangents of that, separation. That bifurcation too, because not only do are high income consumers.

In a better income situation that’s stating the obvious, but they tend to be, the asset owners. And we’ve had this massive, asset appreciation via the markets. And that tends of course, to accrue more so to the benefit of higher income folks, certainly the asset owners. It’s also the case that within the inflation data there is a.

Very widespread between the price of discretionary items and the price of non-discretionary items. So wants versus needs. And of course, low income people spend a disproportionately large percentage of their take home on those non-discretionary components, so stickier inflation there tends to accrue.

Not to the benefit of lower income people. You can look at services versus manufacturing. We have been in a manufacturing recession for quite some time now. If you use the ISM manufacturing index as a proxy for that, just still plumbing below 50, pretty consistently, much stronger. Backdrop and growth on the services side of the economy.

You can go into the CapEx part of the cycle. There’s an easy differentiation there, AI versus non ai. You see it in the labor force. You see it in bifurcations in terms of where job growth has been most robust. It’s in those non-cyclical areas. Of the economy. So, healthcare and education, leisure and hospitality is where the job growth has been in the more cyclical areas.

It’s where the job growth has been, weakest or in many cases in negative territory. And that, of course, has translated into a lot of bifurcations within the equity market too. I think we could see. Some narrowing of some of these wide dispersions, but I don’t think 2026 is going to be a year where we revert to some sort of normal looking cycle as it relates to those divergences.

Justin: Yeah, that’s what I was gonna ask. It’s like what could kind of bring that, bring some of these back in line or closer to each other? Like, I don’t know if, maybe like a wide, just specifically with stocks, maybe a widening market where there’s less concentration in the top performing names or.

You know, maybe some of these manufacturing sectors sort of start to pick up as some of the Trump stuff works out. So, I

Liz Ann: dunno your thought on that. I, I think we’re more likely to see some convergence and already are, in terms of market behavior. I think we’re less likely to see a lot of convergence on the economic side of things as it relates to the K shape we.

We’ve had a view, and we expressed it in our 2026 outlook, which we published in the beginning of December, that this broadening out trade, which really only started to kick in on the latter part of 2025, we do believe that that has legs. That’s not to say that will happen in a linear fashion, meaning.

Equal weight performing well relative to cap weight, small caps performing well relative to, large caps, international as a beneficial diversifier in terms of global equities. We think all of those have legs, but that doesn’t mean the outperformance is going to be. Every week, every month, every quarter.

I still think that there is that sort of embedded desire to go back into prior leadership names, I think will have pops of strength. That really harken back to when things were much more concentrated and less broad last year. But in the aggregate and in a broader sense, I think all of those, trends have legs.

And I, I’ve been having kind of fun with, with, just, sayings and, and phrases. I, I think, the recommendation of diversification, whether it was. In international markets relative to just domestic equity exposure, whether it was down the cap spectrum, whether it was outside of just everything in tech communication services meant you had to say, I’m sorry, a lot now, I think the recommendation around diversification, and, and based on an expectation of continued breath improvement and, and continued.

Strong performance by international means, now you have the ability to say you’re welcome a little bit more often. So I, I, I am optimistic that this broadening out, could persist. The last thing I’d say though is given the run that small caps have had, there’s been a bias in performance. To some degree down the quality spectrum.

So unprofitable stocks within the Russell 2000, outperforming the profitable stocks. Over the past year or so, I would not lean into a continuation of that. To use trader lingo, I think you wanna fade the unprofitable segments of small caps and lean into higher profitability.

Justin: I like, you’re welcome.

Better than I’m sorry, but, I guess with inflation, and this next one I wanted to ask you, I think you’ve, you’ve written about that, more of the inputs into the way that inflation is being calculated is more based on impute, imputed data. Right, right. And, how should, how do you think investors should interpret the data when the measurement itself is becoming a little bit less reliable on hard data?

Liz Ann: Well, I, I would say that that, translates into other areas as well, including a lot of labor market statistics. And it’s not just a function of limited resources, more imputation meaning, more estimating of, of inputs to, an inflation metric like the consumer price index. But we also have a lot of data that we get.

on the economy, broadly on the labor market specifically, that is driven by surveys and survey response rates have dropped pretty significantly. Even within an organization like the Bureau of Labor Statistics, their establishment survey, their household survey response rates are, significantly lower.

Just the response rates of. Companies providing that data, at least in the early phase of the three month window that the BLS collects data for jobs response rate down there, the job opening and labor turnover survey response rates down there. The ISM pmi, same problem. And then you add to it more recently the government shut shutdown and just the data desert that that represented.

I think what that’s brought about, which is maybe beneficial when you think about. Some of the concerns of the efficacy of the data for any number of those reasons that we already, mentioned. I think parallel sources of data have come more into the spotlight. That was certainly case during the government shutdown ‘cause we weren’t getting the, official government data.

So that elevated the importance of a metric like A-D-P-A-D-P decided to take advantage of that, and now they issue weekly readings on payrolls, not just. Monthly readings. You’ve got LIO Labs doing labor market work, Carlisle group doing labor market work. There’s alternate measures that are becoming a little bit more popular in terms of getting reads on inflation, sort of real economy on the ground kind of measures.

I think that’s the environment in which we’re gonna live for a while. So that you’ve got these parallel sources of data as a bit of a check and balance, to the official data that might be suffering from the, the vagaries of, of the aforementioned issues with response rates. And, having to estimate a lot more than we did in the past

Justin: probably makes your job a little bit harder ‘cause you have a little bit more sources to turn to.

Liz Ann: Exactly. But that’s okay. Drink from the fire hose.

Justin: One of the, on inflation. I think you’ve kind of voiced this idea that it’s gonna be difficult for the fed to get inflation sustainably below. It’s. Sort of 2% target. So what’s sort of impacting that view of yours?

Liz Ann: I, I think we’re just in a different secular backdrop relative to the so-called era, defined as a great moderation, which went from the mid nineties or so to the early part of the pandemic.

Call it to the. You know, through 2001, before we had the pandemic driven spike in inflation that began in 2022 and all the forces that were in play during that great moderation era, which helped to bring and keep inflation low and also bring about an environment of very low inflation volatility. So massive globalization, China joining the WTO and basically flooding the world with cheap and abundant access to.

Manufactured, goods, you had a massive energy boom in the United States with, shale and fracking, putting us in a position to be relatively energy independent. those forces, for the most part are kind of in the rear view mirror. I, I, I don’t know that I wanna label the current environment deglobalization, but there’s more concern about diversification of supply chain.

There is a bit more sort of French shoring and near shoring. gone are the days of what began in 2001 when China joined the the WTO. So I think that doesn’t necessarily mean an elevated level of inflation as far as the eye can see, but probably more volatility inflation. And I’ve been saying that I think we may be in a secular backdrop now that looks a little more.

Like what I’ve been calling the temperamental era from the mid sixties to the mid 1990s, with the exception of this not being akin to the 1970s, era, but that 30 year period, you had more inflation volatility, more economic volatility, had shorter cycles, you had bigger upswings in growth, but you had more frequent, recessions.

Again, I think there’s more differences than similarities in terms of an A component of that era being the 1970s, but I think we could be an environment where we have a bit more inflation volatility. Maybe the simplest way to think about this in the context of the Fed’s 2% inflation target is that. For much of the great moderation, you could almost think of 2% as the ceiling in the range.

Now I think we may wanna think of 2% as the floor in the range and, and that has not just implications obviously for monetary policy, but of probably the most important distinction between those two eras as the relationship between bond yields and stock prices in the temperamental era from the mid sixties.

The mid nineties, almost the entire time, bond yields and stock prices moved in the opposite direction because when bond yields were moving higher in that era, as an example, it was often because inflation had reared its ugly head again, and the implications that had for monetary policy, negative for equities and vice versa when yields were coming down.

Fast forward to the great moderation period. Yields were generally keying off. Growth, not inflation. So yields going up because growth is improving without the attendant concern about inflation. That’s sort of nirvana for equities. Now we’re kind of in this transition period where we’ve had these bouts of that inverse relationship, positive relationship.

I think we’re gonna settle to something that maybe looks slightly more like the temperamental era than the great moderation era.

Jack: That chart you have, which we have up right now, is, is very, very eyeopening. Like, intuitively that the stock bond correlation has changed, but when you see it in this chart, like how long it’s markable, it’s markable, how long is the other, yeah.

It is truly remarkable. And, yeah, maybe we’re gonna see more back and forth, I guess is your idea Yeah. The, the

Liz Ann: epitome of sort of secular eras. I, I think for now anyway, we’re probably, it’s almost like the environment is figuring out what it looks like. And in the short term, that’s a function of whether bond yields are keying off the inflation side of things or the growth side of things, and that’s what leads to that changing relationship with what stock prices do.

Jack: And I think one of the things a lot of us are trying to figure out is, is this, two to 3% inflation. Okay. Like, how, how serious should we be about getting back to 2% and how okay is it for the economy if we just kind of live in this two to 3% range?

Liz Ann: I think it’s probably okay. I think significant swings, that becomes, trickier that if we were to develop an actual, an unstable inflation backdrop where the swings were more dramatic, that obviously.

Makes the Fed’s job a lot more difficult. But if we settled in closer to, 3% ish? Relative to 2% ish, yeah, I think the, I think the market can handle it. I think the economy can handle, I have to remember that the 2% inflation target really just kind of happened almost by accident. And it was sort of arbitrary.

There was a, speech given by I think one of the central bankers in New Zealand who mentioned it, and a bunch of the other global central banks said, that sounds about right. Let’s, let’s use it. And, that, that’s, a, a little bit of a funny take on it. But that’s not far from the truth.

And, and not, I don’t think the Fed is going to do any kind of formal change to the 2% target. But they can use their language to express maybe a comfort level with a, to handle on inflation. but, I, I think, I, I think that we’re, we’re likely to just, we’re gonna be settling in, I think, into a higher range.

Jack: It’s funny how many, much, many of these numbers we rely on in markets, like when, when you think about where they came from, they came from like this random place. Sure. Like, a lot of people probably have no idea where the 2% target came from and don’t, we’re reliving a random walk down

Liz Ann: Wall Street, a random walk down monetary policy street.

Jack: So thinking about the other side of the Fed’s mandate, the labor market, that, that’s been something they’ve been focusing more and more recently and you talked in your outlook about it being both a headwind and a tailwind right now. Yeah. Can you talk about that?

Liz Ann: Yeah, so I, I, I, first of all, it depends on what component of the, the labor market you’re looking at.

And, and I’m going beyond just the data we get in the monthly jobs report. So if you look at the weekly metric that is unemployment claims, initial unemployment claims continue to be incredibly. Low. That is obviously a, a, a tailwind in that it represents not a lot of firing in this backdrop. The headwind comes though also in some data that we get.

Every week with initial unemployment claims, which is continuing claims. So people who have initially filed for unemployment insurance now continue to be receiving that. That is an example of the low hiring kind of backdrop. So it’s becoming more difficult for the few people that have been laid off to find jobs in, in short order.

You’re seeing that. Within the Jolts data, in, in terms of things like the, the hires rate, the, the quits, rate, I, I think that’s likely to persist and, and represent some cross currents within the labor market. You’ve also got the immigration piece of this and the massive compression in immigration, which is really changing the backdrop from a labor force perspective.

We have to remember that. labor force growth is driven by, or overall economic growth is driven by labor force growth and productivity. We’ve really compressed labor force growth. Therefore, there needs to be a higher reliance on productivity. So far, so good with the aggregate productivity statistics Absolutely.

Through the roof, so we benefit there. But that very weak immigration flow also wreaks havoc on some of the data. Makes it difficult to do sort of apples to apples historic comparisons. whether it’s, how the unemployment rate is calculated and how there’s sometimes the unemployment rate can go up.

But it can be for the right reason if you’ve got more entrant coming into the labor force. So we’ve really gotten a wrinkle thrown into this data, and of course it’s additive to the government shutdown problem with getting data on time and accurate data, that immigration piece of it. You really have to kind of fine tooth comb a lot of these labor market indicators.

The other sort of headwind and tailwind is that. The compression in the labor force means you’ve lowered the supply of labor, which in turn lowers the economic demand associated with that labor. So you’ve gotta look at both the supply side of things and how that works into the data, but also the demand side of things and how that works into consumption type metrics.

Jack: On the limited hiring part, do you have any thoughts on how much of that is ai? Like if you talk to people right now who have kids coming outta co going, coming outta college and trying to get jobs, that seems to be one of the weakest parts of the labor market right now, and some people argue that is where you would see the biggest impact of ai.

Do you have any thoughts on how a AI is impacting all this?

Liz Ann: Yeah, I mean, it is hard to quantify. I haven’t seen anybody that’s attempted to do that with any kind of precision other than using anecdotes, anecdotes and making assumptions, which, which I do too. And I think it is a component of it. And that’s because I think the way to think about ai, and we always say that more broadly, but I think.

More often than not, when we’re talking about ai, we’re talking about large language models and the work that they can do that maybe human beings had to do in the past. And I think one of the better descriptors of what an LLM represents inside a company is, it’s sort of the same concept, is when you hire an intern, they can do a lot of the grunt work that nobody really wants to do.

But you gotta check their work. you can’t just say, here’s a project and then just assume that the deck they’re gonna put together, the, the proposal they’re going to put together is gonna be accurate. There is that hallucination rate. So, I do think it probably. Has come into play as it relates to the need to hire a lot of, young whipper snappers to come in and do a bit more of the grunt work.

But I don’t think it’s the, I don’t think it’s the full story. I, I think there’s, because of this instability and the benefits that have accrued to companies and the productivity and there maybe their, their profit margins and their labor force growth, that I think it, it provides a window during which companies can sort of.

Take a breath, take a breath from a robust hiring standpoint and take a breath from long-term high cost CapEx. Outside of ai, one of the clear bifurcations within the economy, AI related CapEx, non related CapEx, I don’t think that will last for an extended period of time. I don’t worry about ai. Now, speaking more broadly, eliminating li lots of jobs.

I think at this stage, AI is a replacement of tasks, not really a replacement of occupations, and I think that’s an important distinction.

Jack: It’s, it’s something I struggle with a lot, like thinking about AI’s impact on the overall economy. You’ve got so many different things that in play, like its, its role in productivity, it’s role to potentially replace jobs.

Like, to your point, it may just make people more efficient. I think it’s just really hard. Even like the best economists right now seem to be struggling with thinking about. Like, what does this mean at an overall economic level?

Liz Ann: Not only that, but, in the, in the context of AI boom, which is only a few years old, I’ve been, I’ve been saying that there’s sort of three Cs to define the, the phases of it.

The first C was the create phase. That was the hyperscalers, basically the. The, the inventors of, of ai. Then I think we have been in more recently the, the catalyze phase of ai. that’s the build out of AI and the infrastructure associated with the data centers and energy usage. Now, I think we’re also shifting to a focus on the cultivate part of ai.

That’s where it’s broader, that’s where it’s every company, every industry, every sector. Is we’re they’re, they’re speaking more openly and with more data behind how are we using this? How do we see it benefiting, whether it’s broader productivity trends or what it means for both the size and the cost of our labor force.

That in turn leads to, the possibility of profit margin, stability. Even in light of the tariff term turmoil in potential impact on the profit margin story. So we’re still trying to put as much meat on the bones of this as we can, but that’s going to take, time. It’s just we, there’s nobody that can truly quantify this, yet, but we are starting to see it in a very broad sense in the numbers like the non-farm productivity numbers.

Jack: One of the things you touched on in the outlook is something I think a lot of us have been thinking about, which is none of us feel as good as things are doing right? Like the stock market’s doing re really well, like the economy’s doing better than people think it is. Mm-hmm. Or at least for, for some people it is.

And like, but sentiment has been horrible. Right? Like, why, why do you think that’s been occurring?

Liz Ann: So I think, some of it is the nature of how we, we get information., the, the news tends to be, negative. We, we often tend to go down negative rabbit holes on, on social media. but I think it’s also the, the.

Perceptions around the labor market, just less confidence in maintaining that that job, the quits rate coming down dramatically is an expression of that. When the quits rate was high, it meant a lot of confidence in finding a new job. We know the payroll statistics are really weak, even though that has a lot to do with immigration, it still filters into the, the psyche.

so, and it’s not just as it relates to how the consumer feels relative to the actual hard data or how investors feel relative to what the actual market is doing. You see that more broadly in the soft data versus the hard data. All the survey-based data has been persistently weaker than the actual hard economic data.

And that’s the same case in the stock market. And this is where it gets really fascinating because I’m a, I’m, I’m. Coming up on 40 years, doing this. And, and, you mentioned in the, the intro the fact that I, started in this business working for the late great Marty’s Weg, who was a pioneer in investor sentiment data analysis.

He invented the PCA ratio, he coined the term, the trend is your friend. He, he, he, the, don’t fight the fed was kind of his thing. And, and he did tremendous amount of work on sentiment. What I learned. Under his tutelage is that it’s really important to bucket sentiment in either attitudinal measures of sentiment or beha and behavioral measures of sentiment, because at times what.

An investor might be saying is entirely different than what they’re doing, but that has really, really gone to the extreme in the last several years. In 2022, the last bear market year that we had, you might remember we had the first big, whoosh down into the the June lows. And an interesting thing happened on the way to those June lows.

The most popular measure of attitudinal sentiment is A A I I, American Association of Individual Investors. They’ve been doing their weekly survey since the mid 1980s, and in the lead into that first low in June, that weekly survey went to a record high percentage of bears and a record low percentage of bulls.

And again. That survey’s been around since the mid eighties, so higher percentage of bears than the immediate aftermath of the crash of 87, the entire two and a half year bear market associated with the bursting of the Interbu internet bubble, the entire global financial crisis period. COVID, we’ve never seen an extreme like that bearishness yet.

Interestingly, A A I I. Also tracks on a monthly basis what those same members that voted in the survey have are doing with their money. So they track equity exposure at that time of a record, high percentage of Bears equity exposure was only 1% off an all time high. A perfect example of what they’re saying and what they’re doing are entirely different, things, and that we’re not quite at that extreme, but I think.

Maybe because of the speed with which we get information, how bombastic that information can often be. The advent of social media as a, as a vessel for communicating that and the bombast in the extremes there. We get much sharper, shorter term swings in attitudes than we do in the actual underlying data, and it’s hard for me to think of an environment where we dramatically narrow the gap between those two.

Jack: Yeah, it is interesting to think about, like when I talk to investors, like they’re doing exactly what you said, which is they’re very, very worried about this stuff, but they’re not doing anything in their portfolio about it. So I don’t know if it’s because people have become more accustomed to this and better at managing their emotions, or, I don’t know what it is, but you’re right.

I mean, it’s not, there’s two separate things going on here. Well,

Liz Ann:, Jack, what I also think it is, has to do with who the power players are in this market right now. the, the retail trader has become such a powerful force, and I. I wanna differentiate between retail trader and individual investor.

So retail trader is basically the cohort born out of the pandemic. They skew younger, they skew mail, they’re the reason why the betting markets are going through the roof and why there’s so much focus on, on short term timing and, and the acronyms of, FOMO and BTD and Yolo and hoddle, and. On any given day or week, they can represent, a third plus of trading volume.

I, I’m not suggesting that they’re living under a rock and are paying no attention to the macro backdrop. It just doesn’t tend to be as front and center in their, their mindset into what drives their. Investment decision making into what drives their, their, to some degree gambling. So they, they just have the, the ability, good or bad, to kind of drown out that more macro oriented news that still filters into the psyche of your more traditional individual investor.

Jack: On the hard versus soft data. Do you have any feeling as to how this resolves? I mean, can, can this stay separated for forever, for a long period of time? Like if the hard data stays good, does the soft data eventually come around? Like, I don’t know if there’s an answer to this, but do you have any feeling that it might resolve?

Liz Ann: I think the most likely, if we’re going to have convergence, I think most likely it’s gonna happen in both directions that we, assuming we don’t see a real. Faltering in the labor market. I I, and we don’t see a, a huge spike back up in inflation. I think time will heal some of the wounds that show up in that soft economic data such that you could start to see a pickup in attitudes about the economy.

And in turn, I think that. Given the late cycle nature of the backdrop, we could see a, a bit of softening. So, a, a, a convergence but in both directions as opposed to soft, just fully catches up to heart or hard via recession, catches down to soft.

Jack: One of the things we’ve been seeing in the overall data is we’ve had less, and probably less length in the recessions, but also I think that misses it to some degree because beneath the surface we’ve had all these rolling recessions in different sectors, right?

Yep. Like, what do you think causes that?

Liz Ann: I, I think it started, with COVID and that was, a somewhat obvious initial phase to this, because when the world went into lockdown mode. Everything shut down what we then still had access to and the demand was fueled. In addition to the access to from stimulus, and that was the good side of the economy.

So we went on, we, we were in, both a, a goods and services, really fast tumultuous recession, courtesy of the pandemic and the lockdowns. Then, even though we were still in lockdown, but the stimulus kicked in, we were able to avail ourself. Of, of goods, and goods that were, certainly practical at the time.

you know, Peloton bikes and Lululemon casual clothes and zoom equipment, et cetera, et cetera. So we, we kind of had this role from. The entire economy be in, being in sort of depression mode to then this huge lift that came out on the good side of the economy. In turn, we went from, deflation in goods when everything shut down to then ultimately what was hyperinflation in goods.

We just had a later. Sort of downturn both on the services side, but a later pickup in services. It took until we had vaccines and we could truly open the global economy back up, that you then entered a period of pent up de pent down demand on the good side and pent up demand on the services side that caused goods inflation to go from, high single digits.

Ultimately down into deflation territory. Yet we had the offsetting surge and the services side of inflation services Inflation has rolled over, which is good news, especially the shelter related components. But now in large part courtesy of tariffs, we’ve got what was goods. Deflation has now accelerated and we’re back into goods inflation territory.

So. Those two things. Moving in the the opposite direction. We have the tariff impact. You’ve had strength in areas, where companies are just not impacted, by, by tariffs versus those that are more directly impacted. large companies versus small companies, especially as it relates to that tariff impact.

Large companies can be more nimble. they can figure out how to adjust supply chains so that they’re importing goods from. Lower tariff countries. As a reminder, by the way, this is a tangent, but this isn’t remarkable to me. back in the, the march, april time period last year, I was at a, a, a client event and speaking to a large group of individual investors, and I decided to just quickly define how tariffs work.

you know, tariffs, notwithstanding the shorthanded headlines of tariffs on China, tariffs on Mexico. Or what at times are utterances, literally out of the administration saying, China’s paying us more in tariffs than ever before. Or Mexico’s paying us more in tariffs, whatever, fill in the blank of the country.

Tariffs are paid by the US companies. And the reason why I think that’s remarkable is I do that at every event that I do. And every single time I had people come up to me and say, I had no idea that’s how tariffs worked. I thought China was actually paying the tariffs on China. So. There was a tangent, but I think an important one, because it still blows my mind that there’s not really a, a full understanding of how, tariffs work, but that’s come into play in terms of that differential between the soft data and the hard data and why confidence has been compressed.

Are you impacted by tariffs? Are you not impacted, by tariffs? And, and that part of the unstable story, is less unstable than it was. 10 months ago, but, not yet in anything that we might define as a stable backdrop.

Jack: Do you think this dynamic of less recessions overall in these rolling recessions, do you think that changes as we get further and further from the pandemic, or do you think that’s something that’s kind of with us for a while now?

Liz Ann: I think it, it, it becomes less extreme than we’ve seen in recent years, but I. The, the drivers of different parts of our economy are so different right now relative to when we were more of an industrial economy, more of a manufacturing economy, and things were a bit more linear. You could rely on the various leading indicators.

I, I’ve had a visual that I’ve shown in the past of sort of labeled dominoes, the order of things faltering. Part of the reason why leading economic indicators, the LEI in particular, is so dominated by. Financial components like the yield curve, like credit spreads, like the s and p 500. The economic components are mostly manufacturing is, that’s in a normal cycle, how things have unfolded.

You see it showing up in the financial variables. You see a blowout in credit spreads. access to credit gets tighter. Stock markets a leading indicator. It tends to sniff out problems. You see weakness there first. It then translates into weakness on the manufacturing side of the economy that.

Ultimately topples dominoes into the services side of the economy, such that at the end of that, you’re in a classic recession that has hit the entire economy all at once. I, I think there are so many different drivers right now. We’ve got traditional manufacturing, that traditional industrial, part of a sec, the sector, but then we’ve got the, the high tech innovation that has different drivers with different timeframes associated with.

So I think the rolling nature actually could persist. I don’t think that means no more recessions. but I think it probably elevates the likelihood that a true full-blown economic recession, as we know them probably is, is not. That just proceeded by, but maybe is necessitated by some sort of actual crisis or, particularly within the financial system or some serious plumbing system problem within the financial system.

Otherwise absent that, yeah, I think the rolling nature of different pockets getting hit and being helped at different times, I think that’s also part of this new era we’re in.

Jack: To your point you made on tech, we do a monthly show with Jim Paulson and he, he has this term, he’s come up with the no shaped economy, and what he’s referring to is we have this huge sector in tech, which is way less economically sensitive.

Right. And so how does that impact this whole thing? Like tech, if you, if you invent the, his point was if you like invent the iPhone, you don’t, you’re not that concerned about what’s going on in the economy. You’re probably gonna do pretty well. So. It’s interesting how that dynamic plays into this whole thing.

Liz Ann: Yes. No question about it. But that what you don’t wanna do is, is get trapped into thinking that there’s zero cyclicality to a sector like that. And it’s not at all at the mercy of, of cycles. There are, there are excesses that happen, obviously even in segments of the economy that are, are booming and that you have to go through.

Periods where you correct those excesses. The, the internet was a game changer. It didn’t go away, but we still had a two and a half year bear market because of the bursting of that bubble. AI is here to stay. It’s not going anywhere. It’s transformative. But that doesn’t mean we might not get to a point if.

Maybe we’re already there and that explains part of the reason for the relative underperformance of many of the prior leaders. The fact that, we have no longer the mag seven, we have the lag five and the mag two that I, that there, there are still corrective phases that are necessary. The good news is, is in keeping with the rolling nature of this.

It can happen underneath the surface of the market as well, where you get sort of individual bear markets by virtue of the process of rotation. So last year, s and p was up, I think 16%, for the calendar year 2025. The average member within the s and p 500. Had a maximum drawdown of negative 27%. It just wasn’t a 27% drop all at once in the index.

It just happened via process of rotation. The NASDAQ was up even more than that last year, but the average member within the NASDAQ had a 52% maximum drawdown last year. It just happened to spread out over time and via a process of rotation, very different from the bottom falling out all at once. I think that kind of backdrop could persist.

Jack: I wanna shift to the Fed, ‘cause we’ve talked about the labor market, we’ve talked about inflation, and it seems like for the first time in a long time, they’ve got pretty much a pretty strong push and pull in both directions. Yep. Coming from both of those right now, like how do you think about the position they’re in?

Yeah.

Liz Ann: You know, we, we used to have at Schwab, the wonderfully talented cartoonist. I mean, he was a graphic artist expert, and we used him for a number of different things, but he was also an expert, cartoonist. JP Morgan figured that out and snatched him from us. and I’m sure he is doing a fabulous job, over there.

I’m glad they, they, they understood his talent. But, every year in the past when we would do our outlooks, we would come up with ideas for a cartoon. And, and his name is, Carlos Gary. And if Carlos had still been with us, I was thinking, okay, what kind of cartoon would I have Carlos, draw. And I was, it was sort of a mixed metaphor cartoon.

I thought, I wanna have Jerome Powell sitting in a car that shaped like a pickle, but it’s wedged between a rock and a sign. That says hard place. so I know it’s mixed metaphors, but you’re absolutely right. The Fed operates with a dual mandate, and right now. The, the mandates are not sending completely disparate signals, but certainly at times in the past year or so, that has been the case, which is why we’ve had this, these fits and starts.

You know, a year plus ago, the Fed launched into an easing campaigns. They actually cut by 50 basis points initially, then 25. Then they had to put themselves in timeout because of, coming tariffs. Then they, recently went back down, back into easing mode, and I think right now they’ve probably put themselves in a timeout.

again, so I, I, I think there are those fits and starts that are still likely to be with us right now. You know, we’ve had. Some better labor market data claims are low. The unemployment rate came down. Not great payroll data. So that’s a mixed bag. You know, the latest inflation readings have come down. So I think it’s kind of a common thread message right now from the mandates probably don’t do anything and that’s what the market is betting on, at this point.

But I think we could find this year where we have periods where. Each mandate is sending a different message, and that helps to explain why. Never before have we seen such a wide dispersion in the, the members of the, the Fed and the Federal Market Committee and their views on the trajectory of economic growth where the appropriate, fed funds rate, will be at the end of this year, the end of next year, long term, and why there’s.

Likely to continue to be more dissents. And the most recent case was dissent in favor of both lower rates and higher rates. So, that is, again, back to that sort of unstable, descriptor. I, I, I think that it’s, it’s not a very clear path the Fed is on right now.

Jack: And, and to your point about the sense the other day I asked, I wanted to ask the Fed.

I was thinking like, ‘cause we’re gonna, we’re gonna have a new chairman who’s potentially gonna have an easing bias or we probably gonna have a new chairman. I, I was thinking like, has a fed chairman ever dissented? so I asked Chad GBT about it and I guess the answer is in the modern era, no.

Liz Ann: No.

Jack: and I, and I do wonder if that’s a possibility, maybe going forward, I think there’s lots.

Liz Ann: Of possibilities., you, you had Senator Tillis come out and say that if there isn’t a backing down on the subpoena of Powell, that he, with might withhold the vote to, to bring on a new Fed chair. So. Now we’re, we’re all on chat, GPC saying, well, what exactly would that mean? And Okay.

Does, does, Powell stay, as, show, chair Pro temporary? we, we don’t know. the one overarching thing that we’ve been saying to investors in an environment where people are rightly so concerned about any meaningful threat to the independence of the Fed is that the C in FOMC. It stands for committee not chair.

It’s 12 votes that go into monetary policy decisions. So you can have sway over the chair, but that doesn’t mean you have sway over all 12 voting members, and I’m not. Gravely concerned about this sort of threat to independence in a practical sense. Like will it actually result in monetary policy decisions happening solely based on political pressure?

Jack: So we talked about AI earlier, but I, I wanted to ask you about this, this CapEx boom, which, which you referenced earlier, but it’s, it’s something like all of us are thinking about because it’s, it’s just so unprecedented and we’re trying to think about it in context of, I, I guess a lot of different contexts.

You know, is all this spending gonna eventually be worth it? How is this changing, the biggest companies in the world? I’m wondering if you have any thoughts on that in general?

Liz Ann: Yeah. And, very important caveat. I’m not, I’m not an analyst, I’m not a tech analyst. I’m not a tech expert. Anything that goes wrong technologically in my world, I unplug it and plug it back in.

It’s usually solves the problem. So that usually works, by the way. Yeah, it usually works. And so, keep that in mind as a, as a caveat. Um. I, I often get questions like that with, with a direct comparison to the late 1990s, or asking about are there, are there scary similarities? And, and, just in, in terms of a general heightened level of enthusiasm toward, a new innovation.

Yeah, of course there’s similarities. but I, I think there are more differences, part of which is that so far. The spend has largely tracked the demand curve. The spend back in the late nineties was not tracking an existing demand curve. It was tracking the prospects for demand down the road. So that was an important disconnect.

Also, the. the profitability part of the equation was pretty much nil back in the late 1990s, and as a result of no denominator in the PE equation, you had silly valuation metrics that were invented, like, price to eyeballs. we all know what happened that. Burst in spectacular fashion, although the internet, didn’t go away.

there was also the circular financing, vendor financing is what it was called. But again, the backdrop of that was, build it and they will come. I think the difference now is there is still that circular financing, but it’s not a build it. They will come, it’s they’re here and they want this now.

Now, that doesn’t mean that you shouldn’t have. Any concerns about this, that this will just continue to, to boom without any potential dislocations? The, this boom so far has been largely financed out of earnings, out of cash flows. But if you, if you use the, the Mag seven as a proxy or as a cohort, it’s not the best AI proxy.

I mean, Tesla’s not really a direct AI company, but for lack of a better cohort that everybody knows about. Let’s talk about the the max seven free cashflow growth for that cohort. Less than two years ago was running it more than 60% year over year. Now we’ve had three quarters in a row where that’s been in slight negative territory, which is why there’s more focus on debt finance deals and some of the.

Perceived perils of that. And you’ve seen in, I only mention individual companies here just to, frame it. I’m not an analyst. I don’t cover stocks. I’m not recommending one way or another. But, you saw what happened in Oracle in the stock and credit default swaps. And so there are concerns creeping in about, have we gone too far?

Do we have to be concerned about. You know, lower quality debt financing, in this, the circularity of this, the valuation issues are always there. and they, they can be kind of corrected over time. I don’t. At, at this point I’m not worried about some impending kind of valuation related crash.

You know, we’ve already seen the underperformance now relative to the s and p of, five of the, the Mag seven over the past year, and that’s persisted into this year. So you see some of that price depreciation while you still have decent. Denominator earnings and you, you can sort of ease a valuation problem without something terribly calamitous.

But I think the valuation issues part and parcel of why we’re seeing this broadening out, and it’s that whole, create to catalyze, to cultivate the, the three Cs that I touched on. I, I think that we’re now. More in the cultivate phase where it’s a broader approach to AI and what it means and how does it work and how companies are, are using it.

So I, I think we could have these rolling, corrections and pullbacks that might be valuation related or just too much sentiment froth. But I think it can happen in a, in a fairly. Kind of controlled way at this point. So notice I didn’t use the other B word bubble. I, I think that we may be still a little bit too early to declare that this might be more of a 1997 kind of environment than a 1999.

Justin: But that is the ironic thing, is that the, the exact qualities that those big tech companies, had very high free cash flow asset light, like the move into AI has kind of. Put a damper on the exact things that, investors were rewarding those companies for. Right.

Liz Ann: Which is why I think you had a situation erupt like you did in Oracle.

So there, there is maybe a, a heightened amount of sensitivity and, and you see that when you and we’re, we’re now just starting earning season. You, you have seen that in the past year in an environment where aggregate earnings have been strong. What we’ve also witnessed is earnings misses get disproportionately punished.

Even relative to double beats where a company beats on both top line and bottom line, I think that backdrop is going to persist. So I think the punishment is, could still be, fairly malignant just happening on a kind of company by company, basis as opposed to, baby out with the bath water.

Justin: Now speaking of earnings, you had this chart in your outlook where you showed sort of the price of the s and p 500. Well actually the pe, the forward PE ratio, and then sort of this up into the right line of forward earnings estimate. So earnings have actually been, quite strong coming off of that low in the spring of last year.

So just talk to that a little bit.

Liz Ann: Yeah. So, the first half. To, to, to just make very generic references to certain parts of the year. First half-ish of last year was an era of significant valuation expansion, certainly the early part of the year into the peak in, in mid-February. And then you had the near bear market between mid-February and early April.

But then we had the massive surge off those, intraday lows on, on April 9th and that initial surge off the April lows. Like was the case in the beginning of the year, those were periods of excessive valuation expansion. So earnings were still growing, but multiples were going up at a much sharper clip than earnings.

Then starting at about the August period of time, we actually started to see kind of a flat trend in multiples. The good news being that earnings, the earnings trajectory continued to rise, so you could have made the case. Back in, say the August period of time, and I’m sure we, we said it at some point, boy, we’re at that point, given how stretch valuations are, where earnings are gonna have to do more of the market’s heavy lifting.

Well, so far earnings have heated that call and have been doing more of the, the markets heavy lifting. So we are getting that improvement. But it all. There’s also an explanation embedded in there as to why we’re seeing a broadening out. I think one of the mistakes investors make is that they look at snapshots in time and they do level comparison.

So, the earnings growth rate of the Mag seven or the tech sector, or the combination of tech and comp services, whatever categorization you wanna use, is still quite a bit sharper than the earnings growth rate of, the S and PX. Whatever cohort you’re talking about. And that’s true at a snapshot in time, but it’s the direction of travel that matters too.

And a year and a half ago you had, for the Mag seven, you had about a 60% earnings growth rate, but that has been decelerating. And now we’re in environment where the other 4 93, or again, you know. SPX Tech EXCOM services, you can cohort this a million different ways. We’re on an upward trajectory for sort of the other part of the market.

At any snapshot in time, you’re gonna see still a level differential in favor of the techie AI oriented names. But as I often remind investors. Especially as it relates to connecting the dots between what’s going on in earnings and what’s going on in the stock market, or what’s going on in economic data and what’s going on in the stock market.

It’s human nature for us to think in. Was it good or was it bad? Was it stronger? Was it weak? That snapshot in time, what’s the level, the reality is that the market focuses on more on was it better or was it worse? So better or worse often matters more than good or bad. And I think that comes into play and probably will continue to come into play, in terms of the earnings outlook.

All that said, we can talk about valuations till the cows come home. I have another chart that I often show, it’s a scattergram and it looks at the forward pe. Over time, over the history of the s and p 500 at any point in time and what the subsequent one year return was for the s and p. And it’s a negative correlation, but it’s like negative 0.0 something.

I mean, it’s, it’s, it’s essentially no correlation. You can have a high starting point PE and the market can still rip higher a year later. You can have a low starting point PE and if you’re in the throes of a bear market, like in oh eight and into oh nine, it doesn’t matter that the market gets cheap.

You’re still at a bear market. So valuation is just a terrible market timing tool. There isn’t a great market timing tool. If there was, I’d have it, but, but it, it doesn’t tell you what the market’s going to do

Justin: if you were to try to sort of summarize the areas of the market. And when I’m, I’m thinking like, from a Morningstar style box perspective.

Value growth, large cap, small cap, and or thematic base things. I know last time we had you on, we were talking about quality a little bit. Mm-hmm. So for like the next, 12 to 18 months, what areas within that broad range of sleeves of equities would you be? You know, more favorable on today.

Liz Ann: I think it’s not about areas, it’s more about factors. So I think for now, anyway, gone are the days of being able to make monolithic investment. decisions where that sort of tide of whatever it is, a sector or a theme like AI kind of lifts all boats associated with that. I, I think that factor-based research is essential right now, and I would apply it across all 11 sectors.

I’d apply it in growth to growth indexes if you’re using those as a source for ideas to value indexes, large cap, small cap, and I, I’ll go old school here with the collection of factors that I think. Makes sense. I think it’s a garp type of environment. I think you wanna have a mix of both growth oriented factors, so positive earnings revisions on a going forward, basis, stability or, and or growth in profit margins as a key component of that positive earnings surprises.

So those would be the growth oriented. Factors of note. Then the more value oriented factors, which are of the both traditional variety. So price to book, price to sales, but also balance sheet oriented factors, especially if we’re an environment where the Fed is back in hold mode and they’re not gonna ease as aggressively as, the market might’ve thought less than a year ago.

You want to look for high interest coverage, healthy balance sheets where you have fairly low debt or if you have debt, you’ve got the cash flows, to, to cover interest. you’re not a zombie company. So, again, to use that old school acronym of growth at a reasonable price, I think that’s the way to think about factors more so than just quality because so many firms now do analysis on factors and they’ll establish baskets based on factors and.

The quality factor is sometimes its own individual factor. Sometimes it’s kind of a collection of factors, and I’m not sure it really. Tells you about what the characteristics are. It depends on how you define. It’s too broad a descriptor. I think you wanna be a little bit more specific in the collection of factors and then apply that screening, so to speak everywhere.

Don’t then just say, okay, I’m only gonna apply it to these two attractive sectors. I think in an environment of lower correlations and wider dispersion, which safer maybe spikes in volatility that we might get this year, I think we’re in a backdrop with generally lower correlations and more dispersion leading to opportunities to apply factor-based analysis across the spectrum from a cap, from a style, from a sector perspective.

Justin: I love it. We started with a reference to Marty Wag and we sort of ended here with Garp and I’ll, I’ll throw in reference to Peter Lynch. Mm-hmm. And in the middle we had you Lizanne. So thank you very much. We really appreciate it. My

Liz Ann: pleasure. Thanks for having me.