Factor Frenzy: What's driving the volatility beneath the surface?

Kristian Kerr (00:00):

Welcome to Market Signals. I'm Kristian Kerr, head of macro strategy at LPL, and I'll be your host this week. Well, we're coming off a bit of a volatile stretch in the equity market. The NASDAQ 100 dropped more than 4.5% last week. And on Friday alone, we saw the biggest single day point drop in its history. And that was really on the back of the short reversal and the momentum factor. Today we're talking about factors, because when you look past the headline index moves this year, there's been a lot going on underneath the surface. And a big part of that story is what's happening in the equity factor universe. So to help us break it all down, I'm joined by my colleague Tom Shipp. Tom is LPL’s head of equity research and our in-house expert on all things factor related. So I couldn't think of a better person to help us make sense of what's been driving these moves. Tom, how are you? Welcome to Market Signals.

Thomas Shipp (00:43):

Thanks, Kristian. Happy to be here and yes, absolutely a pretty wild tape we've seen year to date, not even halfway through, but there is a lot to talk about, a lot to unwind, and this is where factors can really help explain and dissect risks for you. So I'm happy to talk about it.

Kristian Kerr (01:01):

Totally agreed. Really good to have you on some big moves in the last few days, and I think a lot of it can be attributed to what we've been seeing in factors. So some of the extremes we're seeing on the quant factors side really. But you know, before we get into that, let's take a step back, maybe set the stage. So Tom, can you give the audience an overview of what factor investing is and how it's been growing in importance over the last few years?

Thomas Shipp (01:24):

I'd say so factors have a pretty long academic history, but definitely, like you said, in the more recent years, it's become very prevalent to look at factor risk, to look at factor exposures, to maybe invest solely in a specific factor exposure. But what are factors? It's really just characteristics, right? Different risk factors or characteristics within an equity portfolio. I mean, there's factors across different asset classes, but here we're talking equity factors and that was really where the original research had been done. The easiest way to think about it is that you have a bunch of different characteristics such as value or quality or momentum or volatility. And those characteristics can really explain things. You may have a portfolio of stocks that looks diversified across different sectors, but the number one thing, and why I think it's really relevant today is that these factors can help explain where you may have correlated risks that you don't know about, right? You have sector diversification, but you're actually all loaded up on beta and momentum. So at a high level, I would just say factors are simply characteristics that explain what risks you're taking in your portfolio beyond just market risk.

Kristian Kerr (02:42):

So they're really like isolated variables, right? That are driving things. That's another way to think about it.

Thomas Shipp (02:47):

So if you put on your stats hat, right? You go beyond a single linear regression and you start thinking about a multi-factor regression that says, Hey, these are multiple different things that are explaining the outcome of the portfolio.

Kristian Kerr (03:02):

All right. Thanks for that. So let's get into the meat of this conversation. This year has been really interesting. We started the year with this big rotation, right out of the gates, away from the Magnificent Seven into things like small cap and value. And that really was the big theme up until the conflict in the Middle East kicked off. There was then a little bit of what I would call a classic risk off. And then from the end of March, we got this absolutely historic rally over two months that was led by a really small subset of stocks. So Tom, can you walk us through what's been happening from a factor perspective during all this? What's been working? I think what's been going on in the equity factor space is really significant and has been a big part of the story that the index has largely masked.

Thomas Shipp (03:49):

It's been pretty wild since around March 30th, let's call it end of March, the news flow from the conflict in Iran started to shift from live kinetic war to ceasefire talks, with peace talks seemingly right around the corner. And what I think is really funny about the market in 2026 is that the market itself has a very short attention span and it's an analog for society writ large, I guess. But the market almost wanted to stop focusing on the war, stop focusing on oil flows and the Strait of Hormuz, and the story went right back to the prevalent theme of the last three years, AI and AI CapEx. And one of the things that started to drive that was earnings, right?

Thomas Shipp (04:40):

I've spoken on this topic with Jeff Bookbinder and others on this pod, the earnings were fantastic coming out of the tech sector and the AI trade writ large. So those things started working again. And when I say working, it was pretty dramatic. The spread between your high momentum stocks, your high beta stocks, your high volatility stocks and their counterparts of low momentum, low volatility, et cetera. I don't have the exact numbers in front of me, but I think the high beta factor is up about 50% since the bottom in March, while low-volatility has not really worked at all. It's been those factors really explaining what's going on in the market, and it's really just been everybody crowding into the same theme, the same thing at one time.

Thomas Shipp (05:34):

And that's really where I think the factors can start to help folks understand what risk they may be taking when they're buying into both semiconductors, AI data center, build out beneficiaries of AI — it looks more and more like it's all the same trade. And that's really where you can have risks in the market and risk in your portfolio without maybe realizing it. But I'll also say that there's a large part of the market that I think wants to take that risk and is fully aware of doing so. But I do think there's likely a large cohort of active managers who are diversified on paper but probably have a lot of that risk in their portfolio as well. Maybe they know it, maybe they don't. There's a difference between those folks and the ones who are going all in — whether retail or hedge fund focused — knowing full well they're taking that bet.

Kristian Kerr (06:32):

Yes, they may be taking a factor bet without realizing it. Right. There are a lot of participants in the market doing that. But you hit on a good point on the AI side — there is a bit of circularity within AI. You touched on it a little, but how much of that AI circularity do you think is really driving all these factor moves we've been seeing, particularly over the last year or so?

Thomas Shipp (07:01):

I think there's the circularity aspect. I'll go a little broader and then we can dive into the circularity. It's really the same theme — there's all this money flowing into building data centers and building out compute to help companies adopt AI and drive all this productivity that's supposedly right around the corner. And there's all this demand for these tools right here right now, but nobody's really paying for it yet. So there's a lot of different things going on with that. And I think when it comes to factors and how we can think about that, it's useful to look at the correlation of, say, momentum or beta with a factor that you usually want the low end of — investment intensity, or CapEx to sales.

Thomas Shipp (07:52):

So how much capital is being spent relative to your sales. It's just a characteristic of a stock that tells you how much a company is investing. And typically from a long factor or a long history of performance, you typically see low CapEx to sales, low investment intensity as a winning factor, right? But in the recent tape, that's been flipped on its head. The more companies are spending, the better they're doing. And that comes back to that circularity — all this money is coming into these stocks, it's then rotating through to the semiconductor stocks, the infrastructure stocks, then those big spenders are raising debt, raising equity, and goes on and on. And look, we've seen this movie before. So I think it's one of those things that investors just need to keep an eye on and have an understanding of it, particularly from a tactical standpoint of, we know that beta and momentum factors in particular can have pretty violent unwinds. But you've got this big thematic macro trend driving the earnings revisions, which is keeping the momentum factor working. And that's where the circularity shows itself the most.

Kristian Kerr (09:18):

Basically, the point is there could be crowding, and when you get extreme crowding there tend to be at a minimum tactical unwinds, and potentially something more. I did want to circle back on something — you mentioned the equity market wanting to look past the events in the Middle East. And clearly that's been the case in the equity market, but it hasn't been the case in the bond market. Bonds have been, for the most part, trading in lockstep with crude prices. So from a factor lens, how does the macro backdrop play into it? Things like rates, inflation expectations, growth surprises, and obviously the geopolitical backdrop — there are a lot of factors that are more rate sensitive. How do you think about it from the broader macro lens?

Thomas Shipp (10:15):

In general, a lot of the core factors that folks look at and focus on are extremely sensitive to the macro backdrop, right? If you have a low inflation, high growth, low interest rate environment, that is fuel for momentum and beta factors on the long end. Just given that you've got a lot of growth companies that have long duration of their cash flows, right? You've got a market that is going to pay up for that growth because of lower interest rates. And so generally, when those conditions are more benign and there is no growth scare, those factors will do quite well. On the flip side, in a higher rate environment or higher inflation, you're going to see more strength in quality and value, right?

Thomas Shipp (11:15):

A value stock typically is cheap. So therefore you're not paying for long duration cash flows. You're paying a lower multiple, meaning you're not discounting a bunch of potential earnings into the future. And in terms of quality, in an inflationary environment, you want to lean on quality because quality companies are typically not economically sensitive and have stable cash flows, right? So you can count on your Walmart for example, or whatever to have those consistent cash flows kind of regardless of the economic market. So the macro backdrop typically matters quite a bit, right? And you can even go back to the CapEx to sales, your investment intensity in a higher rate environment, you're generally going to have a harder environment to invest capital as a company. And so you would typically think that higher rates, higher inflation, a uncertain macro backdrop would kind of hurt all the factors that have been working this year. But that's not the case because the one macro theme and trend overpowering all of that is AI.

Kristian Kerr (12:29):

That makes sense. And good reminder though, that the macro does matter even though we get in these regimes where it just seems to be focused on one or two factors that are really driving things, but that can very easily change, right? And maybe we're starting to see the beginnings of that with the employment data we got on Friday. Who knows. But it is a good reminder. But let's talk a little bit more about momentum. The moves in momentum have just been extraordinary recently. Last I looked, momentum performance was at the 90th percentile on a five-year look-back. What does that setup tell you? Are we at risk of seeing a bigger unwind in momentum stocks? And what would cause the current factor regime to change and momentum to stop working? Tom, before getting into that, could you quickly define what the momentum factor is? I think it's a little misunderstood.

Thomas Shipp (13:27):

It's misunderstood because there are generally a few ways to explain it. The most popular and most commonly used — and the basis of the original academic paper on momentum — was looking at simple price returns over the last 12 months, excluding the most recent month. So you call it 12-minus-one. That is the most commonly used momentum factor calculation. All that's basically saying is winners continue to win, right? So if your stock has been winning, it tends to continue to win. There are a few behavioral reasons behind that. When it comes to company performance, you'll get some good news, a bunch of investors flock to that good news, and they buy the stock and bid it up.

Thomas Shipp (14:21):

But news generally, and this is something you would expect to become an anomaly that gets arbitraged away more quickly in a fast news environment. But if you just throw more news, there's just more fuel for that. So you typically have investors that might be slow to react or slow to buy in, whatever it may be. And that's one reason why momentum has tended to persist. So you're generally thinking about price performance when, when looking at momentum, but there are business and economic momentum factors that you could look at with a individual company, whether that's earnings revisions, right? We tend to look at earnings revisions and define them as their own thing, but it's really just a sentiment factor, right?

Thomas Shipp (15:14):

Of momentum sentiment. You'll see that used as another definition of momentum, or it can be integrated in, and then you have shorter-term momentum, right? A three-month, six-month, what have you. But generally we look at 12-minus-one momentum. And to think about how it's worked and how these things tend to reverse over time: From a portfolio construction standpoint, or when thinking about a factor composite, I like to look at momentum blended within other factors because it can smooth the transition from one regime to another. I've never been a huge proponent of focusing solely on momentum. As a fundamental investor with a penchant for quant, I tend to mix things.

Thomas Shipp (16:11):

Completely ignoring fundamentals or valuation is a tough ask for me. That said, to answer your question on what could cause this regime to change or what are the risks inherent in momentum: I think the easiest way to think about it is as momentum continues to work, right? More and more people pile in and more and more people are chasing that momentum, and eventually there's no one else left to buy. Everyone is on the same side of the boat. That's how I think about momentum unwinds and the risk inherent in a really stretched, really crowded momentum factor.

Kristian Kerr (16:50):

The crowding effect, I think is impossible to ignore. That tends to be how these things reach their crescendo. That was a great overview on momentum, by the way. I also think there's an element here of the market structurally has changed, particularly over the last 10 to 15 years with passive, with buybacks becoming bigger and bigger. And I think that adds fuel to the momentum effect. There are buyback-related factor risks and things like that, but I think that structural dynamic has played at least some role in momentum doing so well over these multi-year timeframes. Quick follow-up: what are some indicators we should be watching more closely for signs of a potential factor rotation or regime change?

Thomas Shipp (17:43):

I tend to think about it rather simplistically. There's obviously a lot of great research and data around crowding and how extended some of these stocks within a momentum basket have gotten. I also like to look at the correlation between market returns, momentum returns, and other related factors like beta or volatility. And then think about it at the individual name level — without naming any names — a name or theme that is very much in trend right now. When there's good news and the stock doesn't react — because a big piece of momentum is that expectations can get so lofty that even good news isn't good enough.

Thomas Shipp (18:44):

A quarterly earnings print just isn't good enough anymore. They beat, they raised guidance, they did everything you'd expect — and the same things that two, three, or four quarters ago were causing that stock to skyrocket just don't work anymore. Those are the signals. One instance may not signal a regime shift, but when you see it repeatedly across several names within the trend, that's a sign. And the moves downward can be violent. Even just last week we saw what could potentially be the start of an unwind — it could just be a blip, but the drawdown we saw was pretty drastic.

Kristian Kerr (19:34):

That's interesting. So news failure is one big thing to watch for, and seeing it across more than one name within the factor — that's a key signal. Great. Outside of momentum, when you look across the factor landscape, what's the cleanest message you're getting right now? Are we at a point where the dispersion across factors is creating some opportunities?

Thomas Shipp (20:05):

I think so. There's been a lot to unpack here, as we talk about quite a bit. There's your AI basket and that has all the factors that are explaining the AI basket, right? And there's a bunch of different ways to slice up that basket. You have your hyperscalers, you have your semiconductors within semiconductors, you have memory versus high compute. Then there's your non-AI bucket. If you're not in the AI basket, you're not in it — it's a pretty clean bifurcation. One thing I've been thinking about is the AI-at-risk bucket — companies that may be disrupted by AI. Software names have been a notable negative beneficiary of that dynamic.

Thomas Shipp (20:55):

What I've been thinking about is the AI-insulated type of business — names where, whatever happens with AI, whether it's everything everyone says it could be or just another step change in technological advancement, these companies may not be impacted one way or the other. So when thinking about that AI-insulated basket, if you can sort out those opportunities, you can then ask: have some of these names been thrown out as if they're AI-at-risk or a disrupted industry? You can sort by identifying stocks that are not in the AI basket but that we believe are AI insulated and have low momentum.

Thomas Shipp (21:45):

Low momentum may actually mean that their valuation looks attractive because they've sold off, and then you can look at a quality factor. Those are the opportunities we're looking for while individually looking at any names within those momentum buckets that may have gotten a bit stretched beyond any realistic expectations. To answer your question simply — yes, there are absolutely opportunities. You don't necessarily need to find a new name or a new investment. You could just take your current portfolio and adjust it to incorporate some risk management.

Kristian Kerr (22:32):

The path forward — whether on AI or anything else — won't necessarily be linear. There will likely be some steps along the way, and factors can probably take advantage of that, right?

Thomas Shipp (22:48):

Yes, absolutely. That's one of the primary ways we like to leverage factors in our work here at LPL — to help us quickly identify what the data is telling us.

Kristian Kerr (23:04):

All right. So we covered a lot of ground today. Tom, as we close, let me ask you this from a risk management perspective, what's the biggest mistake you think investors could be making right now when it comes to factor exposure?

Thomas Shipp (23:20):

I touched on this before, and I'll preface by saying that some investors are intentionally taking this risk — going all in knowing full well what they're doing. But I think the biggest mistake folks could be making is thinking they're more diversified and less correlated across their portfolio than they really are. Because they're not. Maybe they're at benchmark weights on the traditional AI names, but they've been buying other businesses with high earnings revisions and think, "I've got exposure across a bunch of different risks." But when you really break it down and run some cross-factor correlations, the risk is all coming from the same place. It's the same trade. And I think that's the big risk.

Thomas Shipp (24:07):

And ultimately that's what drives these momentum unwinds — once everyone in the market is in the same trade, even unknowingly, and it starts to break down, stops get hit, risk management kicks in, and it just continues to unwind from there. That's the biggest mistake folks are making in this market right now, and it can be explained through factor analysis. And compute and software have enabled a wide range of investors — from retail and wealth management advisors all the way up to institutional investors — to access these tools. It used to be the domain of hedge funds and big institutions to have access to these risk models. But now a lot of people can do what I like to think of as an x-ray or a checkup — looking at what factors you're exposed to relative to your benchmark or on an absolute basis, and what the correlations are. So you can get a much better understanding of how concentrated your bets may be without even realizing it.

Kristian Kerr (25:20):

Know your position, know what you own — always timely advice. Yep. Alright, I think we can wrap things up there. Some great insights today. Tom, really appreciate you taking the time to stop by this week. And thank you to everyone for listening. Please be sure to join us again next week for another episode of Market Signals. And until then, bye for now.