Go back

Buy High, Sell Higher | Travis Prentice on Dispersion, Passive's Structural Risk and Why 52 Week Highs Don't Mean What You Think

59m 18s

Buy High, Sell Higher | Travis Prentice on Dispersion, Passive's Structural Risk and Why 52 Week Highs Don't Mean What You Think

The discussion highlights major market shifts that are more than temporary blips, with profound implications for investing. As a momentum investor, Travis Prentice emphasizes reacting to what works rather than predicting trends. The market shows extreme dispersion—semiconductors up 30% versus software down 23%—reflecting a broadening out beyond the Magnificent Seven, driven by AI’s capital-intensive nature and deglobalization. Momentum adapts flexibly, and recent evidence favors a more recent bias in look-back periods due to faster, more violent overreactions from factors like zero-dated options and FOMO. The rise of passive investing has redefined risk from capital loss to tracking error, masking real dangers as market-cap-weighted indexes become flow-driven and untethered from fundamentals. While passive has a role, overconcentration in a few stocks (e.g., 40% in seven stocks) builds hidden risk. The solution is a balanced portfolio blending active and passive exposures, combining momentum, quality, and value—factors that work at different times and are negatively correlated. Momentum’s adaptability and lack of emotional bias make it a key ingredient, especially alongside value, to navigate uncertainty and achieve resilient long-term outcomes.

Transcription

11503 Words, 63576 Characters

English
I think these are major shifts that aren't just a blip. I think they're kind of major moves that signify very big changes going on. And I think it has profound implications for how we invest. As an a momentum investor, you don't really care or you don't really think about what should be working. All you're doing is reacting to what's actually working. When Wall Street we have a really interesting characteristic that we take really good ideas and grown so big that they become less good ideas over the real risk hiding in plain sight, with the rise of passive and the fact that these companies have been bit up so much for so long and that you could argue whether how far away from fundamentals they are and in all women matter unless there's a change agent. And I think the change agent is AI. Welcome to Excess Returns. I'm Jack Forehand and today I am privileged to be joined by another factor investor. Travis Prentice, the CIO of Inform Momentum. Thank you. Thank you for coming back on. Yes, thank you for having me. Big fan of the podcast. Thank you so much. And yeah, I'm excited. We've done a wide variety of topics. Even if you're not a factor investor today, we're going to talk about, we've all been seeing this crazy dispersion behind the scenes in the market. We're going to talk about how Travis is seeing that from a factor investors lens. We're going to talk about passive investing. We're going to talk about Mike Green's work. We're going to talk about AI and the world of the world of AI. And then we're going to talk about a really great paper Travis wrote on 52 week highs is a momentum signal. So we've got a lot to get through you ready to go ready to go. Let's get to it. So I want to start with what I referenced first, which is we've been talking to a lot of different people like we just talked to Lizanne Saunders and she was referencing. We were talking about this idea like how is the S&P 500 held up this well despite everything going on and she was like, well, if you look behind the scenes, a lot of things haven't held up that well. It's sort of a different situation. We're seeing all kinds of craziness behind the scenes and an index that's not doing much. And I was just wondering like from the perspective of a factor investor who's seen behind the scenes, what stocks are moving and what's going on. I was wondering if you have any perspectives on like what we've seen in the recent market. Yeah, definitely. And I think I actually listened to Lizanne Saunders on the way on your podcast on the way to work this morning. So thank you. You're very quick. It just came out. I know. I'm a follower. So I get the notification. But no, she's fantastic. And I think she really hit on something that we're seeing as a momentum investor because obviously we're focused on what's working, what's trending, but also what's not, right? Because that's the opposite of owning the winners is avoiding the losers. And so yeah, the divergence has been extreme. And you have to you don't have to look any farther than the difference between the socks performance this year. You know, semiconductor performance and software. I was just looking at the numbers today. The socks is up 30% while the software like IGV, you know, the ETF of the software is down 23. So yeah, beneath this. That's crazy. Yeah, there's a lot of dispersion. And then from a factor standpoint, you see it in the returns to quality and growth. You're really seeing those styles really underperformed significantly, even the broader indexes. And this has to do with these extreme divergences. And also obviously some idiosyncrasies with quality itself. That's interesting. And we'll get into the quality stuff when we talk about software later. But yeah, it's been a reasonable euphurms to be a factor investor. Like I don't want to jinx myself because this is a, it's been such a long period where maybe not momentum as much for like valuings of other factors haven't been working and size hasn't been working. But we've sort of seen an environment where we've had a return to, you know, not mag seven leading everything. Yeah, yeah, exactly. And also value and momentum kind of became friends in the second half of last year. And through this. That's a rare occurrence, right? It's great when it happens, but it doesn't happen that often. Correct. It doesn't happen that often. It doesn't. Yeah. Particularly in the non-US side where value and momentum had to kind of some pretty good runs over the second half of last year and so far this year. But I think it also reflects the broadening out of markets that we've seen. Maybe besides March, let's put March aside for a second and we can get into March. But if you take March out, I think you've seen really a broadening out of the trade or what's working, you know, outside of just mag seven and tech and software. You're just really seeing a broadening out. You see the Russell 2000 outperforming large cap writes a small over large and value being a nice place because it's kind of the opposite of concentration. And so the value indexes themselves are a bit more diversified than certainly what you get in the SAP 500 as that and a Russell 1000 growth. So yeah, why disparages just the divergences between stocks industries, but also reflective of the indexes. If we use the indexes value and growth as kind of a proxy for some of the factors. And I know that's true for you, but for most factor investors, this idea of the rally widening out is so important because if we're selecting from a universe of stocks that's beyond the biggest stocks, and we're equal weighting our positions, which some factor investors do some don't. But if we're doing those things, we're automatically making a bet on smaller companies. And when like seven companies are driving the entire market, it's just hard for any factor to work other than size, which is not a large size, which is not a factor that actually works with the long term. So it's good to just see it spreading out at least and giving factors a chance here. Absolutely. And I think that's super important for value. Not so as important maybe for momentum because momentum kind of adapts to wherever, but I certainly think having a change in the marketplace. And I think look, I think there's massive shifts going on that are helping the broadening out trade and the value trade and the momentum trade. We can debate whether growth or quality, when that can come back, but I think this broadening out is really reflective of some major shifts going on. One is we're entering that AI disruption phase, and obviously ground zero for that is software. But also I think de-globalization, moving manufacturing back to the US and New York near Shoring. I think all of these things, the fact that AI as a technology is much more capital intensive and much, it needs a broader participation of different types of industries and companies to make it work, right? The AI build out. But also manufacturing come home, our self reinforcing trends, that kind of shifts all the action in the capital from just the mag seven and tech to a much broader participation of industries and sectors and styles. So I think all of that, all of what we're seeing in the market, these divergences are reflected those two seismic shifts, whereas most of my, I've been in the business for 30 years, but most of those 30 years has been rampant globalization and kind of this virtual software driven market. And I think we're just seeing areas of the market that have been kind of underloved coming back because of these major shifts going on in the economy globally. And what's good about that is in a unayarker to predict what's going to happen in the future, but those seem like things that are lasting to some degree. I mean, we've seen these fits and starts with things like this, but it seems like those have links maybe as we think beyond the next couple months. >> Totally. And I think we can get into this though. But because there may be the beginnings of a Megatron doesn't mean that you'll have, you'll have differences in terms of on a daily basis what's working or even on a monthly or quarterly basis. So I would think with all these evolutions happening and the pace of which they're happening, we would always just advocate for being kind of agnostic, but being, make sure you're exposed to styles in a balanced way. So having momentum, quality and value, I think, and having exposures to those over the long term, I think, align with kind of the level of uncertainty. But knowing that these premiums pay over the long term, but if you put them together, you're going to look smarter more often. >> That's that point you just made. Does this change when we think about this market, the index is kind of not doing much, you get all this crazy dispersion behind the scenes? Does that change the way you invested all? I mean, these factors are built for the long term. So maybe it doesn't really make too much of a difference. But does it change about how you think about markets or how you invest in anyways? >> No, not really. I mean, we're always an advocate. I mean, we're obviously a momentum investor. We're very focused on improving returns through momentum investing. However, if we think about it from a capital allocator's perspective as they're creating a diversified portfolio, I think it really underscores the fact because you see such extreme divergences between these factors to put together factors or exposures that work over the long term, but are negatively correlated or work at different times in different regimes in different cycles, right? And I think we're always an advocate from an allocation perspective to be in those premiums, like quality, value, and momentum that have shown empirically to work. But when we say work, that doesn't mean that it works month by month, quarter to quarter year by year. I mean, all of these factors have our regime dependent to a certain extent, and they all have risks with them. So when we say something works, it's on average, idealized excess return over the long term. That doesn't mean that they don't cycle. And I think this is a reminder in these markets like this that there is dispersion between factors and styles, which means, again, it just underscores the fact that you need diversification. But when we talk to most investors out there, they tend to be, and I'm generalizing here, but they tend to be biased or overexposed, the quality and value just typically. And most active managers are as well. And they're missing kind of the key ingredient, which is momentum. So I think what this is highlighting, at least in our conversations with investors, is that momentum is an important part of that balanced portfolio. And to your point, I mean, there's no factor that works better with value than momentum. And the great thing about momentum is momentum is not going to care about the fundamentals or what's going on in the news or the wars. It's going to buy what's going up. And there's times in the market where that is a really good thing to be doing because we can all get confused, but all this craziness going behind the scenes and we can be our own worst enemy. Absolutely. Momentum is, I mean, it's strength of momentum is its adaptability and flexibility like you suggested, but also that it's not emotional and it's agnostic. As a momentum investor, you don't really care or you don't really think about what should be working. So in that regard, it's a lot less emotional, a lot more flexible. And I think in these kind of environments, yeah, I think it definitely has a place, but it's also a good exposure to have because of that. So yeah, we're not trying to predict anything either. And I think that's a strong set of momentum. You're just reacting to what is rather than anything else. Just one more question on this before we get into the passive stuff. There's a lot of talk about this idea that the market moves faster now. Like the declines are faster. We go back up faster, the shifts between sectors are faster. Like is there anything you change in a momentum strategy for this to like you shorten your look back periods a little bit? Is there anything you change or you say like this is what's worked over the long term? Like we don't want to mess with this. Yeah, so at Inform Momentum Company, we've always favored a more recent-see bias to a momentum formation period or look back period. And we did some research on this. We called it back to the future, which kind of challenged the conventional 12 minus one, as we're all kind of familiar with is kind of the gold standard for how you measure whether a company has momentum or is outperforming, right? The last 12 months minus the most recent month. But we've found actually that we looked at a 40-year period and then we look at a sub-sample period of the last 20 years. And we found some pretty good evidence. The data suggests that actually a more recent-see biased momentum formation or look back period actually worked a bit better over the sub-sample of the most recent 20 years. So that does suggest that it behooves you to move a little bit quicker now, perhaps, than in a longer time period. So the 12 minus one over the last 40 years has worked pretty well. It kind of outperformed, but in the most recent, especially in US large cap, which is kind of interesting, it behooves you to have a more recent-see biased approach to when you're measuring that look back period. Do you think what I said is true? I mean, do you think the market has sped up? Do you think the shifts in the market has sped up? Or is that just also a recent-see bias where I'm just looking what's happening and not really remembering what happened in the past? Yeah, it's hard to tell. I mean, it's hard to quantify, but I would just say from a practitioner perspective of looking at these stocks every day. I think there's two main differences that we see. This could be a recent-see bias on our part because it's just observations. But I would say that we tend to see a little bit more of an amplitude or an overreaction to current trends. So momentum, we think, pays off because at the beginning of a trend, there tends to be an underreaction to the positivity of the information. But then ultimately, part of the payoff structure is that there's an overreaction at the end of the trend, like a blow off top or something like that. And so we see a much more violent overreaction these days, and that could be due to zero-dated options. It could be due to a FOMO. It could be due to a lot of behavioral things that are going on now. So we see much more of a violent overreaction rather than, I think that's the biggest thing we see, but I do think having a little bit quicker trigger or more a recent-see bias in momentum has proven to be a little bit better at the margin than kind of a 12-month score. I want to shift to passive investing because I know you've read Mike Green's work as much as I have, and it's been one of the most eye-opening things for me, like understanding what's going on behind the scenes. And so you wrote a paper about this. I believe it's called "Rist's Hiding and Plaint's Site." Yep. And you were talking about this idea that risk has been redefined a little bit in the world of passive investing. So can you talk about that? Yeah, sure. Yeah, big fan of Mike Green's work. I mean, he's really, and on your podcast actually really highlighting some of the market structure issues that occur because of the rise of passive. And I think we just have to understand and contemplate when we're talking about markets and factors and things of this nature, the fact that the growth of passive investing has been so massive, right? If we go back 25 years, there's very investments, but somewhere between 10 and 20 X in terms of assets under management. And now we're getting to the point in the US market structure where it's a majority of the assets are actually in "passive," which, as we know, is not totally passive, right? It's a strategy of market cap waiting. So that's actually a very deliberate decision that necessarily isn't the market. So I think the rise of passive is something that we have to understand in terms of market structure and how it affects stock action every day. The point I was trying to make in that paper and don't get me wrong, I think. Passive investing or index investing is not inherently flawed. So don't come after me on that, I think. I think there's a place for it. I think the problem becomes, is it too much of a good thing? I mean, are there structural issues that arise from it being so popular? In Wall Street, we have a really interesting characteristic that we take really good ideas and grow them so big that they become less good ideas over time. But my point in that was when we talk with investors, I think there's just a difference between how they're measuring risk now, which seems to be much more of a tracking error definition of risk. So how different am I than the S&P 500? The more risk they perceive, and my point was just to make that really risk is, I think, from a long-term investor, I think, if you look at an institutional investor, the biggest risk they have is actually loss of capital or not earning a return to make their commitments over the long-term. So I think there's been a change in that, which was replaced kind of that real risk, which is not an return or loss of capital versus how different am I, an IE tracking error. And I think with the rise of passive, this kind of, this changing definition of risk really massed real risk, which is, if you have an index that's because of the market cap waiting nature of it, and the fact that it's grown to be so big, and that allocates not on any fundamentals, right? It's just, is it a bigger market cap? It's going to get more capital. Then over time, you could see that divorcing, the index itself becomes more untethered to fundamentals, and it's just priced on flows, which is the point that Mike makes, which is totally valid. You can't argue that. And so that builds up risk over time, and since it's become so big, I think it's a risk that we have to think about. And so my point was, it's not a band in passive. I think passive has a role, but let's not go get over our skis and have like, that's going to be 500 right now, which is effectively maybe one bet. Entering the year was 40% in seven stocks and 35% in tech. Now, some of that's because of the fundamentals, these companies, but some of it, and maybe a majority of it is because of the flows have disproportionately helped those companies. They've gotten farther away from fundamentals, which poses a risk in and of itself. So we would just say, stay balanced with that too. I think there's a good blend of active and passive that can get you more resilient outcomes over time. To your point in tracking here, I always think about Jim O'Shaugh and his two points of failure. I don't know if you've heard of those, but the idea is like investors have two points of failure. One, they can sell when they're portfolio is down and panic and make their own decision. The other is they can sell when they're underperforming. And I have a feeling like through my career, I've found that second one is a much, much bigger risk to people. So people are using tracking errors and measure of risk. That's what's leading to their behavioral problems and leading to their mistakes. Yeah, absolutely. And I just think right now it's just amplified those risks are amplified just because of the how big passive has become and how concentrated these market cap weighted indexes have become. So I think and all of it doesn't matter. I don't think as long as as flows remain the same. But if we think about some of these seismic shifts that we talked about earlier in terms of, you know, AI being a much more capital intensive technology and also near-shoring and de-globalization or some form of that, that has a profound impact on these major companies that we all talk about, right? And so I guess all my point is that the risks are really important now to consider because of these massive shifts going on, which kind of highlight the real risk hiding in plain side, right? And in all women matter unless there's a change agent and I think the change agent is AI. Yeah, it's sort of arguing to clients about factor investing as a diversifier. And then like as a risk management tool because people think about passive as low risk, but as it gets more and more concentrated, you know, you don't have to abandon your passive, but having some of this other stuff on the other side can be a risk mitigator if this comes true of these big stocks, you know, lead the way down in the next decline or something like that. Well, absolutely. And it doesn't take much. And I think that's one thing Mike said too that I agree with is that since passive becomes so large, it doesn't take much of a rebalance a way to have some pretty hurtful results on a market cap weighted. strategy because what's driven large cap out performance, you can argue, I think it has a lot to do with the fact that it's just got a disproportionate amount of the assets going into the market, right? But if that reverses, then it's the other way is true. They'll get the disproportionate amount of the selling pressure, which should at the margin help smaller companies over big. So yeah, I think there's a lot of risks going forward with the kind of regime we've been on. I think as you know, Jack, the longer things go on, the more one way a trade has been, the more risk billed over time, right? And I think we can't argue that the rise of pacifists been kind of driving force in markets for the last 25 years and assets, some people think assets has increased 20X over that time. So it's all compressing the risk. How do you think about it from the perspective of how it affects a factor investor? I could argue that maybe the market's less efficient because people don't care. There's buying stocks in respect of their fundamentals. I could argue maybe it enhances momentum a little bit because these same stocks are getting driven up by this force. Like, have you thought about how it impacts the returns of factors? Yeah, I've thought about this a lot and I don't have really any concrete answers for you. I can see both sides of it. Because on one hand, you can see that allocating more to larger market cap companies is positive tailwind for momentum. But also the lack of dispersion, I think, hurts. When you have a one-way trade and a risk on environment, it's hard to differentiate in terms of momentum. But I also think that even a market cap weighted algorithm is kind of a weak form momentum strategy. You're not really getting a pure momentum strategy, obviously. So I don't know, I go back and forth, but I do think that just in terms of being an active manager, regardless of factor, I think it cross-sectional or dispersion between securities, I think creates a better playing field for all factors. There's differences in returns. It's not just one monolithic trade. The downside of a passive, I think, of the rise of passes has been, which I think is hurtful to factors, is that there just seems to be more code movement with securities or groups of securities rather than kind of idiosyncratic risk kind of comes down. So I think there's good and bad from a moment perspective, I guess. And I don't know where I come out. It depends on the day. Yeah, and I think people do misunderstand that we're momentum a little bit when they use it in this context. Like, when you talk to people about a momentum strategy, they're like, "Oh, at least not now, maybe like a year ago." They're like, "Oh, you just own the Mag Seven then." They've had lots of momentum, but we're defining momentum in the factor world by a very specific lookback period and performance, and we're using a very wide group of stocks. So a lot of times those stocks won't own the Mag Seven, even though they've done really well over, you know, it's as decade or something like that. Absolutely. Yeah. And I think the difference is that momentum is a discipline, right? Where you're constantly reorienting to strength. Then we can talk about rebalancing periods, but you're right. The lookback period matters. The implementation of a momentum strategy is paramount. So it's not a monolithic trade. And I think if you look at the last year or so, then the Mag Seven, there's only been two stocks, really, that have outperformed out of the seven. So that a momentum strategy will pick up on that, right? It's not just one Mag Seven trade. You're going to look at medium-term horizons and always be measuring what's outperforming and what's not. And so, you know, I think that is that flexibility and adaptability, again, is what, what, what, as long as it's done with discipline and you rebalance often enough, I think your position kind of no matter what may lead, because it's always shifting. A momentum strategy is a chameleon, right? It's just going to reflect what's working and move away from what's not. So I want to get to your paper is quality broken because this is really a good paper. And it's also something that all of us are thinking about right now, because as you alluded to earlier, the returns to quality have not been great recently. But before we get to that, can you just define, I think this is probably as the widest definition among factoring investors quality. It's like people say, you know, when you see it or warrant buffet owns those things or even when you get in the world of quants like us, like the definitions are all over the place. Like, how do you think about defining quality? Yeah, most of our research we're just, we're using, and just because of the repeatability through time, we use Fama French definition of quality, which is high operating profitability. So you take the top quintile of high operating profitability. So that's how we assess, you know, whether quality is not working or working or what have you. And I know there's a definitely obviously very different implementations or measurements of quality. And I think in this moment, actually, you can probably see some divergence between how people are defining quality because it's so important. So, you know, you hear the word modes used to, but I would imagine that if you have a more forward looking view of profitability, maybe you've done a little bit better because I think when we look at operating profitability or quality, it's kind of a backward looking metric, right? You're looking at what's been a high historic profitability. But I think if you think about like inflection of profitability, perhaps, you know, that might have done better. But, but certainly we've seen quality as a factor. Two things become negative, more negatively correlated with momentum in the most recent past in the history, but also really underperform the market in a pretty significant way recently. And so in that paper, we talk about quality and we actually, and don't get me wrong, we believe in quality over the long term. I think all the empirical data would suggest that that it's a pretty good source of excess returns, lower tracking error, good information ratio, risk adjusted returns. I think it's a really good exposure to have. But that doesn't mean that it doesn't go through cycles. And we're on a down cycle with quality now, having to do with kind of what we talked about in terms of AI infrastructure being necessitating a more maybe cyclical type companies like industrials, energy utilities. It's just another feature of this broadening out trade. And then on top of that, like all technology regimeships, kind of like the internet in the 90s, if we think about what AI is capable of and you're starting to see that now in terms of the agents and AI inference, then and the fact that it's coding pretty well. So the cost of coding maybe is becoming more of a commodity, so it's going down. So you think about that and hype historical profitability companies like software are kind of right for disruption. Like that's where the aim of AI is going to, right? Kind of like the middle man in the internet, in the internet days, right? You can skip the middle man and go right to the manufacturer. So profound changes, which I think implicate quality as a factor in the kind of the short term or medium term. Yeah, before we get into software, one of the interesting things that I've seen was some quality investors and some of these work factor investors, but this idea of focusing more on consistency of the business than the balance sheet. And that's allowed a lot of these tech names like the mag seven to become high quality companies because they produce really, really consistent results. So I think you've seen a lot of quality investors go into those, not that they don't have bad balance sheets or anything like that, but you have seen like that consistency become more and more a measure for quality investors out there, I think. Yeah, yeah, definitely. And look, I think, and I think Liz and Sauner's actually talked about it, which I totally agree with is it's not necessarily like I think she talked about good or bad, but we would always argue from a momentum perspective and a stock perspective, it's, it's what's the change? Is it negative or is it, is it improving or is it not improving? And I think that, I think with all factors is kind of something that we need to think about is that what's the rate of change? What's the second derivative? And so when you think about the world, not necessarily like, oh, a good company or a bad company, it's like, is it getting better? Is it getting worse? And so I think if you look at it, all the factors within that lens and quality being a great example now is, can we reasonably assume the consistency is getting better? Or do we, can we project all these cash flows out with a high degree of certainty now? Maybe not because of what's happening and changing in the market. So I would always think about these factors and we do at informed momentum is like inflection points and our thing is getting better or worse, not good or bad. Yeah, she said the same exact thing in the end of the year, she echoed exactly what you're saying. Software is really interesting to me because it's almost like if you had the before AI, if you had to make the perfect business, it's like high margin, consistent returns in a time. Like everybody was throwing like on the debt side, everybody was just throwing money at these companies because they seemed like the perfect business. And now like the flip of a switch, they're not. And it's just interesting to think about like a factor like quality, but also like all these people that held these businesses, it's a challenging time in your eye or not discretionary investors are going to try to figure this out. But it's just an interesting time when these businesses that had like the highest readings on a lot of these quality factors, just in a flip of a switch, it completely changes. Totally, totally. And that's why I think we talked about momentum and flexibility and adaptability and I think it's super important not to always look at things through a rear view mirror to think about what we think about quality going forward. So the trajectory of quality, the trajectory of profitability and I think software is a good example of a lot of different things, but one is not, you can't really predict how these things will evolve. But once you get some information that challenges your thesis and you think about the world in terms of expectations, stocks in terms of expectations, not historical. I think we can all probably agree that expectations have changed in terms of the business quality of software. And we get a lot of questions too. like we're not saying that software is going away. But it doesn't have to be that for software companies to underperform because of where they entered this with high expectations over allocation, like you suggested, where it's been like the hottest place to be. It doesn't, it's just about what's the change at the margin. And I think if you look at it that way, you can, well, that has implications for the valuation you're willing to pay. So you could be in an environment where software companies aren't going anywhere, they're going to be there, but they're probably not going to be as good as they were in terms of businesses. And this is why I like momentum so much, because you've got these people out there right now, like trying to argue the terminal value of Salesforce or whatever. It's like, it's we beyond what I can do it. It's like, let's just buy what's going up. But I think that's a great thing about momentum is it takes these hard, hard decisions in the market and sort of takes them out of your hands, having to make them yourself. Totally. And that's what I, that's why we love what we do is that we're, I'm not a technologist. I don't try to predict anything, but we look, we do think price is a signal, a price as information, right? So, I mean, that's our kind of basic philosophy, right, is that there is a signal in price. And so we look at what's happening in the market and then we seek to understand why. And I think that's just a much better way, because we can't predict anything. I mean, no one has a good record of predicting things with any degree of certainty, with any time out in the future and we certainly don't and we don't want to. So we're just again, yeah, unemotional and just react to what the trends are. And I think when you do that, you just, you avoid some of these major dislocations. But look, not to say that momentum doesn't have, it's a keely seal too. It has its own risks and we can run through those. But I think the risk and quality, the keely seal of quality is kind of what we've been talking about. Like what are you paying for that compounding, right, that business mode, what valuation are you willing to pay for that? But then I also think the keely seal for quality is, it's just, when you have these big technology shifts, it can be hurtful for quality. We saw the same thing in the late 90s with the internet and they don't, it's not, it's generally not a one time occurrence. In fact, it could be multiple years of quality not doing as well as it had. So we just got to be aware that these things, these factors are regime dependent and they are, there are some risks associated with all of them. I'm curious. I know you're a momentum investor, not coping with as much on quality, but this gets at a bigger issue in terms of when our factor strategy is not working. Like how do we think through that in terms of, is it a short term thing, is it a long term thing? Because a lot of the quality investors right now are thinking through, here are my quality criteria. This has completely blown up on me. What do I do? And I think most of the time we say, or if it works over the long term, we want to stay with it. And in this case, like I would think a lot of the things that define these software companies are good things, like they're things you want in the business. So it may not be a sign that there's something wrong with the quality factor. It may just be one of those short term things. So like, how do you think about that when you see something happening in the market, balancing that against sort of your long term evidence to your factor? Yeah. I think you've got to be open to evolving your factor. And I think we've seen a lot with in terms of how investors define value, I think, has been kind of a big discussion point over the last 10 or 15 years. And I think quality is the same way. I mean, you always got to evolve. I think your signal capture. But I always stick to your knitting, but understand that we need to always continuously improve. So I do think that you should be always introspective and look at quality and say, are we measuring it right? But I do think, look, quality will write itself. I think it will come back. It just may take time. And if you think about profitability for kind of looking at from an operating profitability perspective, historic perspective, well, over time, if what we're saying is correct in these mega trends, then profitability will inflect. It just might be in other areas of sectors and industries or countries or what have you. And so over time, if you're measuring profitability and there's changes in levels of profitability that the companies, then you should see less software over time and maybe more returns to hardware or physical infrastructure. And so profitability, you know, profitability will move. It's just slower moving than certainly a momentum strategy would be. And if any thoughts of the differences between now and the 90s, like we talk about this all the time in the podcast, like that situation, a lot of people just think that's going to repeat, you know, we've got text stocks leaving the market up that we're going to have a collapse and value is going to rain again and all that stuff. But obviously, interesting from the perspective of factors, I know you've looked at it a little bit in your writing, like, what do you think about the differences between the 90s period and what we're seeing today? Yeah, I mean, I was lucky enough. I don't know if it's lucky, but to see the boom in the bus of the 90s, but definitely I started my career in the late 90s. So I did see the highs and the lows of it. Look, I think there's a lot of corollaries. There's a lot of rhyming to it, but I think it's also different. And I'm not saying anything. You think controversial with that statement, but I do think AI, it's just more, it has a, it can potentially have a much larger impact than even the internet because I think it will diffuse into every sector in industry. Whereas the internet was, there were industries that were kind of, quote unquote, safe or not as impacted or didn't get the benefits of the internet. You know, so there was a little bit of, it wasn't as diffuse. It didn't go across so many sectors and industries. Whereas AI, I think it just every industry in sector is going to be changed somehow, either positive or negative or in between. So I do think this kind of narrative of like, boom bus, this kind of missing the point. It's like, well, first of all, we don't know when the boom and bus is going to happen. I think with the, when you look at backwards, you're like, oh, yeah, it was so inevitable, but at the time it was not. I think the timing of trying to time that is very difficult, but you can have two things be true that AI is going to be a profound change and maybe the cycle can extend longer. It doesn't have to be so binary of an outcome, you know, like it could actually be beneficial for some companies and not others. And there could be a lot of in-between things that happen because obviously we're trying to look in the future and trying to manage that unexpected. But I just think when people talk with certainty on things is when you should get concerned because no one knows and everything's always uncertain. And we will know 20 years from now what really is the case, but we can't, we don't have that benefit. Yeah. And to your point, I think I think Green Span's irrational exuberance speech was maybe 97. I think it's so many people at that point were like, this can't go on any longer. It's over. It's going to end any day. Like, there are two years of massive, massive research and he stocks before it end. Well, which just gets to the idea that this is impossible at the time. Yeah. Yeah. Looking also Amazon, one of the best companies, all right, one of the best success stories of all time was I remember being pan for a lack of profitability, right? And ended up being a very high quality business over the long term. So again, this kind of trajectory or looking at things at the margin, I think is super important. Because there will be some big winners out of this technology shift. And sometimes they're not led by the former leaders and they're always in and not be maybe high historical profitability companies will lead that. That's certainly not what we saw in the 90s either. So yeah, I think the narrative of like it boom bust is kind of misses the point to me a little bit, you know? Like, I think there's winners and losers and stocks and expectations and idiosyncratic risk matter too. I want to shift to your paper by high sell higher, which if you had to criticize Jackson Besting career, you would say a failure to do this is probably number one on the list. That's a value guy. I just can't do that. But nonetheless, it's an excellent paper. And you're talking about this idea of using the proximity of the 52 week highs and signals. So can you talk in general about what you're looking at in the paper? Yeah, definitely. Well, it's interesting that so the first part is that we've kind of always used a 52 week high as a reference point because I think it's important from a behavioral perspective with momentum. So sailing at reference points or benchmarks are always I think important. And we kind of got that through practice, you know, just looking at observing stocks. But the interesting part of that paper is we start out with the fact that, you know, Jackie just mentioned value. Here it is to a 52 week high. The data suggests that information coefficients across styles. So irrespective of whether you start with more men or not, 52 week high has a really good prediction in terms of looking out six months. So regardless of where we're applying it or what kind of style a 52 week high is, is an important signal. But in this paper, we talk about how we can use the 52 week high to improve momentum. But the basics of the paper was, hey, 52 week high is actually a pretty important benchmark in terms of evaluating momentum. It's not just how a company's performed or how much it's outperformed. It's also relevant to where it is in terms of a range or relative to a 52 week high, which we show in the paper actually explains a good portion of momentum and returns just with that single factor. And there's different ways to look at it, right? You referenced a few in the paper. Most people might think, oh, here's the percentage of the 52 week high you're done. But there's other ways to look at this. Yeah, yeah. We looked at three different measurements. And I have to give a shout out to some of the research done before us because, you know, we always do a literature review and look at what work's been done. And I think there's been some really good work, George and Wang in 2004. Wesley Gray and Vogel in 2016, I believe, in their quantitative momentum book had some pretty good data on this as well. So we kind of used some of those metrics. And then we found a more recent paper looking at 2000 or 2025 paper by bulltowison. We use three different measurements. So yes, we use a nearest to a 52-week high. We call it a position relative to its 52-week high. So just how close it is to a 52-week high. We looked at one called high-de price, which is just how far is it away from its low? So the higher away from its low, the better. And then we also looked at a range 52-week high, which includes where the company is positioned from a 52-week high basis, but relative to its high and low range over the last year. So where in the range is it? And we've actually found that from a risk-adjusted perspective, the range 52-week high was actually had the highest sharp ratios as a single factor. So the position 52-week high worked well too, but the range one definitely kind of outperformed all of them on a risk-adjusted basis across most selection universes. And then again, it takes into account where in the range is it? So the closer to the high of the entire range over the last year is actually a more salient reference point, perhaps. - How does this relate to your standard, 12 minus one momentum signals? Is it markedly different than the 12 minus one signal? Or is it very, very correlated? - I didn't think it's highly correlated, but our data suggests, and look, I always say when we look at back tests, and we look at data and research, I don't think we can always say anything definitively, but what the data suggests, and not only our research, but others, is that the 52-week high, and we did some nested sorts, and I won't get too technical on it, but we actually try to answer that question with first sorting on momentum, and then within that sort of 52-week high, and then vice versa to try to tease out, whether you get any more information outside of your 12 minus one momentum with 52-week high, and across most universes, we found that you don't gain any additional information that you don't get from the 52-week high in the 12 minus one. So in other words, the 52-week high is explaining, on its own, a lot of the momentum premium, and in fact, if you just took the top quintile of a range 52-week high strategy, you actually had much better risk-adjusted returns than a 12 minus one momentum strategy alone. And most of that was on the downside capture being better than your standard kind of 12 minus one price momentum strategy. So with this argued from replacing 12 minus one momentum with a 52-week high, or do you still be combining them together is probably the best way to go? - Well, I think you can make that argument, but I do think combining them is what we think is, leads to a better, not only risk-adjusted return than 12 minus one, but a better balance between upside capture and downside capture. So I think that if you were just to do an exclusionary, and just to arrange the 52-week high, it depends on the regime you're in, because it looks like that does much better on a risk-adjusted basis, because it has better downside capture, but a lower upside capture. And whereas if you combine the two, you get a good balance between, you're approaching sharp ratios of risk-adjusted returns. You're very close to just the range 52-week high, but you've got a better balance between upside and downside capture. So over long term, I think you got a better balance with combining the two. - Yeah, I've always had the saying, and then for my factor, investing, when you don't know, combine. - It seems to work pretty well, 'cause the second I take Christ the book out of my value composite, Christ the book's gonna have its biggest run like in history. And so when you're not sure, which one, I think averaging them out, when you're not sure, is probably a pretty good way to approach it. - I agree, and we saw the same thing with one of the research pieces we did on smooth sailing in terms of how a moment information period manifests itself, either smooth or continuous, like the frog and pan argument, or whether it's volatile or not. And we found the same things, like you can be exclusionary, and you're gonna probably be in a benefit on the downside capture, but I think using them in terms of portfolio construction and process is what we found in terms of up waiting less volatile momentum companies, and down waiting more volatile, kind of balances those upside downside captures a bit better. So yeah, we agree with combining things that gives you a little bit better of balance. - You've talked about already using this in strategy, but did this research change how you managed portfolio's all, or was this pretty much something you would already incorporate into what you're doing? - Yeah, we kind, I think we've incorporated it always, but I think what we did here in our research is be much more systematic about it, and actually measure it specifically, and then from a process perspective, embed it more systematically. So what I mean by that is that, now we're measuring all of these things, and we're continuously proving the signal capture, and are we looking at the right measurements, testing those, but then introducing in formality in terms of how we manage portfolio. So for the smooth sailing or the volatility of momentum, it's more of a portfolio construction adaptation, and then with the 52-EKI and some of the other work we've done, it just kind of confirms, but in a very mathematical way, kind of what we've seen from practice. So it's a bit of both confirming what you're doing and making sure that you're staying on top of, how things evolve and continuously improving, but also, yeah, can we get better, and how can we incorporate these findings into a process of not only stock picking, but obviously portfolio construction. - Is there anything interesting in when this works, and when it doesn't work relatively like a standard momentum? Like in terms of momentum reversal, is there different periods where it struggles? Was there anything you found interesting, from that perspective? - Well, I think what was most interesting about the range of 52-EKI, which I did it, and mostly all of the 52-EKI measurements was that it had better downside capture than momentum alone. That was really surprising to us. So over time, it's actually a risk mitigator to include a 52-EKI signal capture, which is totally counterintuitive. But I also think, and we can get into the reasons why, I think it's investor behavior, right? Because as Jack, as you kind of mentioned, it's like, well, no one wants to buy the highest price for something over the last year. So on average, if that's people's behavior, then you would think everything else being equal, that would be undervalued. So I do think there's some kind of a risk mitigation because of behavior and expectations. But I think what is the most surprising thing to us is that I think it's just countertuned to what just what most people think in terms of 52-EKI. So the advantage of buy high sell higher seems to be accurate. We're all trained on buy low sell high, but it may be the opposite is actually, essentially, a better. Yeah, to your point, if you told most investors, this stocks near 52-EKI, and that's the only thing you gave them, should I buy it or not, there is the absolute not. It's had its run, that I'm going to buy it. And it's just interesting that the opposite of that is true in the real world. Yeah, totally. And the fact that it's counterintuitive, I think is the reason why it works. It's so well, because if everyone agreed with something, there'd probably be no alpha there. But I would say that we haven't gone into exactly what that kind of portfolio would do in certain environments. So we haven't answered that question yet, but I would say in general with a momentum strategy, and I think 52-EKI would be the same, because it explains a lot of the momentum premium is that you would expect this signal or momentum not to do well when there's abrupt leadership changes in the market. So you go from winners to losers very quickly. Now, gradual changes is not a problem, but if it happens on one day, where leadership shifts or in very quick abrupt market reversals, generally after a downward trend when you get the early stages of a big up market, those are times where momentum tends to struggle. And I would expect 52-EKI to be the same. When you've been running a real world momentum strategy this year, is there anything interesting? I was always interested in, and I know we're a quance, we're not like deciding what's in there, but I'm always interested in what the momentum is picking up on. Obviously it doesn't have software right now, are there any areas that have been interesting in terms of what momentum's up on this year? - Yeah, I think, yeah, we are kind of talked about all the kind of broadening out theme, which I think momentum's picked up on. So relative to some other kind of rigid factors like a value or a quality depending, we picked up on materials doing well. So gold, silver, copper, all those types of companies, utilities have been kind of a different kind of momentum pick up recently. But again, it has to do with the AI buildout, right? Energy matters. And then I would say, lastly, as I mentioned, energy stocks really showing very strong momentum, whether it's natural gas, servicers, crude oil, servicers or exploration and production, we've seen an acceleration in momentum, kind of in the end of last year, beginning of this year, largely on kind of AI themes, but obviously with March and what happened with Iran, we kind of got another leg up. So right now, momentum's picking up on kind of that, that aha moment that we all had, that like, oh yeah, energy's still important, oil's still important, and it's a global market. So I think that aha moment, it's kind of helping those companies right now and momentum's kind of picking up on that. - Yeah, I think it's cool because it teaches people that momentum can be boring at certain times in terms of the types of stocks it's picking. It's not, people want to associate it with type-line growth companies, but there's times in the market where you don't want to own those companies. There's times where momentum exists and maybe they're more boring stocks. And that's something I think is a big misconception about momentum is that correlation people think between like high-flying growth and momentum. - Absolutely, totally. And there's reason for that because momentum and growth, if you look at the factor correlations, they tend to be positively correlated, but it's very mild. And there's also, as you point out, there's times where momentum's very much loaded on growth and there's times where momentum's very much not loaded on growth. And when it's not loaded, low to dawn growth actually is what creates the better premium. So again, that adaptability and flexibility is what momentum is strong suit. But yeah, I mean, momentum is as long as what's working is boring, momentum is going to be boring. How do you think about consistency in momentum? I know you've probably read Westprian, Jackville, those book. They show that at least in their research that consistent momentum was better than the biotech company. And just knows the drug and went way up. Do you find the same thing in your research? Yeah, generally, yeah. I mean, yeah, we find the more the more continuous a momentum formation period is and the less volatile, the better the risk adjusted returns are. And you can either apply that as an exclusionary filter or as a composite or as a as a as a signal and portfolio construction. And I think we look at it as like not necessarily exclusionary because you get a very kind of concentrated more concentrated portfolio with momentum if you do that. So we've chosen to again, to preserve that kind of upside down side balance. They use that knowledge in terms of how we construct our weightings of security. So we showed in another paper that if you upweigh the more gradual momentum companies, if you will, the more continuous less volatile, you can improve risk adjusted returns of the kind of the standard 12 minus one momentum alone. So we definitely our research is echoed that in terms of the general findings of that that the moment information period does matter. But we would much rather use it as a signal in terms of portfolio construction and waiting rather than exclusionary because we have found that in from an informed moment in perspective, biotech has been a good area for us in terms of excess returns and stock selection. And the fact that it's a large weight in microcaps and small cap, you don't really want to avoid it entirely. But you do want to understand in terms of the risk management, like how much how much weight do you want to put in those types of binary outcomes? I picked up something and reading some of your work that echo is an idea our friend Corey Hofstein has talked about a lot, which is this idea that it's not just how you rebalance your strategy. It's when you rebalance your strategy. And I think you've talked about this idea that that does matter in a momentum strategy. Am I right? Yeah, I mean, 2025 was probably the most stark example of that. And we did a study and this has more to do with timing. But it just shows how the difference that it could make. And we did a monthly or quarterly rebalance strategy, a momentum strategy, like a 12 minus one, the kind of your standard one. And all we did was vary the rebalancing calendar by a month. So if you did January and March versus February and May, last 2025, there was a thousand pace points difference to your return using the same measurement of momentum, the same everything. But you just varying it by one month in terms of a quarterly rebalance schedule. And obviously they have to do with like, if you're measuring like before the tariff tantrum and then the big, the big move up on the market on the, the pause of, of tariffs, you can imagine that if you measured momentum at the depths of despair in April versus one month later, you're going to get a very different outcome. Implementation does matter. And we, the way we do it and found over the long term, not all the time, but definitely not 2025, but over the long term, what we do is we rebalance every day incrementally, meaning that we move the portfolio when the signals move. So we don't wait for a calendar based rebalance. We kind of rebalance incrementally every day. And that way we think we capture over the long term more of the start of a trend and then less of the end of the trend are things that are breaking down. So, so we do it daily, but incrementally. So we're not making one decision. You know, we're not rebalancing 20% of the portfolio on one day, right? It's incrementally every day. And we move when the signals suggest us to move and we don't wait around for a calendar date. And we found that to be better over the long term. You referenced earlier this idea of reversals, which I think is something people will point out as one of the probably the major weakness of momentum strategies. Like, I'm just curious, if there have been, are there more reversals now, like you think about like when we talk to macro guests, they always talk about, you know, one tweet changes everything. Certain stocks are going up, certain stocks are going down based on one tweet. Like, do you see anything in the market in terms of more reversals or how momentum handles reversals or anything interesting there? Yeah, I'm not sure. I think it depends on how you measure momentum. So if you're a very short term measurement of momentum, then I think you can get a lot of reversals based on tweets and like whatever Trump may be saying on one day to the next. So yeah, I think how you measure it and whether you're measuring trend really or whether you're measuring noise, I think, you know, matters. So I think the time period that you measure momentum is super important. So not discounting what happens on a day, but it doesn't matter unless it reflects on the trend broader on a longer, you know, medium term basis at least. So I think the measurement period matters. But I do think from our perspective anyways, we think the highest expression of momentum investing is actually price signaling information or signaling something at the business that's positive or that's occurring that's positive. And so we're always focused on the intersection of yes, stocks that are doing well. So momentum, but intersected with business improvement. So fundamental momentum. And I think that intersection helps decrease the noise and the reversals that if you're acting on signals, but they're actually associated with information. I think you have a better chance of not having as many reversals. So do you use fundamental man your strategy or do you feel like that's reflected both lean price? No, we actually measure fundamental momentum as well. And that's going to be, you know, we use revision and surprise to help us do that. But no, we very firmly believe that it's that's the intersection. That's the highest expression of momentum investing is price again, reflecting fundamental improvement. So if you look at our panel of signal captured includes both kind of price-based signals like 52-EK and momentum scores obviously, but also fundamental momentum signals as well. And we think the confluence of those things give you a better chance of not having those reversals like you talked about, but also increase the amplitude and the duration of the outperformance. If there's actually a good business reason why it's occurring, right? It's not rocket science. It's just that, hey, you don't want to just purely chase price. We don't think, although, hey, look empirically, that does pretty well, but we think we can improve upon the risk adjusted returns with actually the intersection of business momentum and price. Well, this has been great. I really appreciate you taking the time. Unfortunately, you've answered our closing question and we have to come up with a new closing question, which we're the process of doing. But I did want to ask you, I always like asking people who are doing research. Is there anything interesting you're looking at right now, anything you're researching? Do you think might need to research in the future, anything like that going on right now? Yeah, I think right now we're at the point where we're going through our testing of signals to make sure we're measuring the right things in the right way. And it's actually, is there new signals? So right now, it's actually fundamental momentum signals. I think Novi Marx has done some pretty good work on that with the Sui. You're probably familiar with the SUE. But we want to look at our signal capture on the fundamental momentum side to see not only does that explain the momentum premium fully or and also is there a better way to measure these things. So that's kind of the next area of our research that we want to really refine. I mean, because we look at so many signals, we look at analysts revisions, but we look at the diffusion. So how many ups versus downs we looked at the magnitude? Same thing on surprise, but we also look at performance one day and three day after earnings report to actually measure whether it's a surprise. So there's so many ways to measure these things. And then that's the next area of our research that I think will be what least interesting to us. I don't know about it about anyone else, but just furthering on our understanding of momentum and seeking better results from momentum. And I think all of our research is in that regard where we know momentum works, but can we make it work better for investors in terms of the risk adjusted nature of it and to help in some of the challenging parts of momentum, right? Like so momentum crashes. If you can kind of really dampen down on the negative sides of the factor and amplify the positives, then I think better outcomes are in store for investors. So that's what our total focus is. Well, thank you again. I really appreciate you coming back on. Cool. Thank you. Thank you for tuning into this episode. If you found this discussion interesting and valuable, please subscribe on your favorite audio platform or on YouTube. You can also follow all the podcasts in the access returns network at excessforturnspod.com. If you have any feedback or questions, you can contact us at [email protected]. No information on this podcast should be construed as investment advice. Securities discussed in the podcast may be holdings of the firms of the hosts or their clients.

Podcast Summary

Key Points:

  1. The market is experiencing extreme dispersion beneath the surface, with sectors like semiconductors (up 30%) diverging sharply from software (down 23%), creating opportunities for factor investors.
  2. Momentum investing adapts to current trends without emotional bias, and a more recent look-back period (shorter than the traditional 12-minus-1) has proven more effective in recent years due to faster market shifts and violent overreactions.
  3. The rise of passive investing has redefined risk from loss of capital to tracking error, masking real risks as market-cap-weighted indexes become untethered from fundamentals and driven by flows.
  4. Seismic shifts like AI’s capital-intensive buildout, deglobalization, and near-shoring are broadening market participation beyond the Magnificent Seven, benefiting value, momentum, and small-cap strategies.
  5. A balanced portfolio combining momentum, quality, and value is recommended, as these factors are negatively correlated and work across different regimes, with momentum complementing value particularly well.

Summary:

The discussion highlights major market shifts that are more than temporary blips, with profound implications for investing. As a momentum investor, Travis Prentice emphasizes reacting to what works rather than predicting trends. The market shows extreme dispersion—semiconductors up 30% versus software down 23%—reflecting a broadening out beyond the Magnificent Seven, driven by AI’s capital-intensive nature and deglobalization.

Momentum adapts flexibly, and recent evidence favors a more recent bias in look-back periods due to faster, more violent overreactions from factors like zero-dated options and FOMO. The rise of passive investing has redefined risk from capital loss to tracking error, masking real dangers as market-cap-weighted indexes become flow-driven and untethered from fundamentals. , 40% in seven stocks) builds hidden risk.

The solution is a balanced portfolio blending active and passive exposures, combining momentum, quality, and value—factors that work at different times and are negatively correlated. Momentum’s adaptability and lack of emotional bias make it a key ingredient, especially alongside value, to navigate uncertainty and achieve resilient long-term outcomes.

FAQs

The major shifts include AI disruption, de-globalization, and near-shoring, which are broadening market participation beyond tech and mega-cap stocks.

A momentum investor reacts to what is actually working rather than predicting what should work, making the strategy less emotional and more adaptable.

Passive investing can cause indexes to become untethered from fundamentals due to flow-driven pricing, concentrating risk in a few large stocks.

These factors perform differently across market regimes, and combining them provides diversification and more resilient long-term outcomes.

Observations suggest more violent overreactions to trends, so a more recency-biased momentum look-back period has proven slightly better in recent years.

It shows extreme dispersion beneath the surface, with semiconductors up 30% and software down 23%, highlighting opportunities for factor investors.

Chat with AI

Loading...

Pro features

Go deeper with this episode

Unlock creator-grade tools that turn any transcript into show notes and subtitle files.