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

[00:00:00] 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 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.

[00:00:20] On 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. The real risk hiding in plain sight with the rise of passive and the fact that these companies have been bid up so much for so long. And you could argue whether how far away from fundamentals they are. And it all wouldn't matter unless there's a change agent. And I think the change agent is AI.

[00:00:48] 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 Informed Momentum Company, a second time guest on the podcast. Travis, 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 got 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 investor's lens.

[00:01:15] 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 equality in the world of AI. And then we're going to talk about a really great paper Travis wrote on 52-week highs as 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 Liz Ann Sonders and she was referencing, we were talking about this idea, like how is the S&P 500 held up as well, despite everything going on?

[00:01:43] 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 seeing behind the scenes, what stocks are moving and what's going on. I'm just 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.

[00:02:09] 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.

[00:02:38] I was just looking at the numbers today. The socks is up 30 percent while the software like IGV, you know, the ETF of 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 underperform significantly, even the broader indexes.

[00:03:03] And this has to do with these extreme divergences and also obviously some idiosyncrasies with quality itself. It's interesting. And we'll get into the quality stuff when we talk about software later. But, yeah, it's been a reasonable year for us to be a factor investor. Like, I don't want to jinx myself because this is it's been such a long period where maybe not momentum as much, but like value and some 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.

[00:03:30] Yeah, yeah, exactly. And also value and momentum kind of became friends in the second half of last year. And 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. And but we're seeing it now, particularly in the non-US side, where value and momentum had 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.

[00:03:59] 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. Where you're really seeing a broadening out and you see the Russell 2000 outperforming large cap, right? It's 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 S&P 500,

[00:04:26] as that and Russell 1000 growth. So, yeah, why disperses the divergences between stocks industries, but also reflective of the indexes? If we use, you know, the indexes value and growth is kind of a proxy for some of the factors. And I know that's true for you, but for most factor investors like 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.

[00:04:53] 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 like large size, which is not a factor that actually works, you know, over the long term. So it's good to 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,

[00:05:22] 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, you know, and obviously ground zero for that is software. But also I think deglobalization, you know, moving manufacturing back to the U.S.

[00:05:51] and near nearshoring. 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.

[00:06:19] So I think all of that, all of what we're seeing in the market, these divergences are reflected in those two seismic shifts. Whereas, you know, 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.

[00:06:45] And what's good about that is that you and I aren't going 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 legs maybe as we think beyond the next couple of months. Totally. 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. And I think, you know, we can get into this, though.

[00:07:14] But, you know, because there's maybe the beginnings of a megatrend 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, you know, 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.

[00:07:38] Anyway, 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. Like, does this change? You know, when we think about this market, you know, the index is kind of not doing much. You got all this crazy dispersion behind the scenes. Does that change the way you invest at all? I mean, these factors are built for the long term, so maybe it doesn't really make too much of a difference.

[00:08:07] But does it change about how you think about markets or how you invest in any way? No, not really. I mean, we're always an advocate. I mean, we're obviously a momentum investor, so we're very focused on improving returns through momentum investing.

[00:08:21] 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 and different regimes and different cycles.

[00:08:47] 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 are regime dependent to a certain extent, and they all have risks with them.

[00:09:13] So when we say something works, it's on average annualized 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.

[00:09:33] 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 to 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.

[00:10:04] 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 by all this craziness going on behind the scenes, and we can be our own worst enemy. Absolutely. Momentum is, I mean, its strength of momentum is its adaptability and flexibility, like you suggested, but also that it's not emotional and it's agnostic.

[00:10:29] As 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. 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.

[00:11:00] 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? Do you shorten your look back periods a little bit? Is there anything you change or do you just say, like, this is what's worked over the long term? Like, we don't want to mess with this.

[00:11:22] Yeah, so at Informed Momentum Company, we've always favored a more recency bias to a momentum formation period or look back period. And, you know, 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.

[00:11:49] But we found actually that we looked at a 40-year period and then we look at a subsample period of the last 20 years. And we found some pretty good evidence. The data suggests that actually a more recency biased momentum formation or look back period actually worked a bit better over the subsample of the most recent 20 years. So that does suggest that it behooves you to move a little bit quicker now, perhaps, than in, you know, a longer time period.

[00:12:16] 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 U.S. large cap, which is kind of interesting, it behooved you to have a more recency 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 recency bias where I'm just looking at 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.

[00:12:41] 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. And this could be recency 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.

[00:13:10] 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.

[00:13:34] But I do think having a little bit quicker trigger or more recency 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 like one of the most eye-opening things for me, understanding what's going on behind the scenes. And so you wrote a paper about this. I believe it was called Risk Sighting in Plain Sight.

[00:13:59] 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. And 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.

[00:14:26] If we go back 25 years, there's varying estimates, but somewhere between 10 and 20x in terms of assets under management. And now we're getting to the point in the U.S. market structure where it's a majority of the assets are actually in quote-unquote passive, which as we know is not totally passive. It's a strategy of market cap weighting. So that's actually a very deliberate decision that necessarily isn't the market.

[00:14:53] 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, look, 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, meaning are there structural issues that arise from it being so popular?

[00:15:21] You know, 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 different, the more risk they perceive.

[00:15:50] And my point was just to make that really risk is, I think, from a long-term investor, I think, if you look at like an institutional investor, the biggest risk they have is actually loss of capital or not earning a return, right, to make their commitments over the long term. So I think there's been a change in that, which has replaced kind of that real risk, which is not earning a return or loss of capital versus how different am I, i.e., tracking error.

[00:16:16] And I think with the rise of passive, this kind of, this changing definition of risk really masks real risk, which is if you have an index that because of the market cap weighting nature of it and the fact that it's grown to be so big and it allocates not on any fundamentals, right? It's just, is it a bigger market cap? It's going to get more capital.

[00:16:38] 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 abandoned passive.

[00:17:04] I think passive has a role, but let's not go get over our skis and have like the S&P 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.

[00:17:32] 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'Shaughnessy's 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 their portfolio is down and panic and make the wrong 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 error as a measure of risk.

[00:18:01] Like 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 how big passive it's 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 flows remain the same.

[00:18:24] But if we think about some of these seismic shifts that we talked about earlier in terms of AI being a much more capital intensive technology, and also nearshoring and deglobalization or some form of that, that has a profound impact on these major companies that we all talk about, right? The Mag7, as Microsoft's probably a great example of it, is that it looks like it has a much more capital intensive future, i.e. free cash flow margins are going lower.

[00:18:54] Incremental margins are probably going lower. And so I guess all my point is, 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 sight, right? With the rise of passive and the fact that these companies have been bid up so much for so long. And you could argue whether how far away from fundamentals they are. And it all wouldn't matter unless there's a change agent. And I think the change agent is AI.

[00:19:25] Yeah, I've sort of been arguing to clients about factor investing as a diversifier to them, 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 if you and it doesn't take much. And I think that's one thing Mike said, too, that I agree with is that since passive has become so large,

[00:19:53] it doesn't take much of a rebalance away to active to have some pretty hurtful results on a market cap weighted strategy. Because what's driven large cap outperformance, 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.

[00:20:19] So, yeah, I think there's a lot of risks going forward with the kind of regime we've been on. And I think, as you know, Jack, like the longer things go on, the more one way a trade has been, the more risks build over time, right? And I think we can't argue that the rise of passive has been kind of a 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.

[00:20:51] How do you think about it from the perspective of how it affects a factor investor? Like, I could argue that maybe the market's less efficient because people don't care. They're just 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.

[00:21:14] And because on one hand, you can say that, you know, allocating more to larger market cap companies is, you know, positive tailwind for momentum. But also the lack of dispersion, I think, hurts. You know, when you have a one-way trade and a risk-on environment, it's hard to differentiate, you know, in terms of momentum. But I also think that even a market cap weighted algorithm is kind of a weak form momentum strategy.

[00:21:44] It's not really getting like 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. Like, there's differences in returns. It's not just one monolithic trade.

[00:22:09] So the downside of a passive, I think there's just of the rise of passive has been, which I think is hurtful to factors, is that there just seems to be more co-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 momentum perspective, I guess. And I don't know where I'd come out. It depends on the day. Yeah, and I think people do misunderstand the word 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.

[00:22:38] They're like, oh, you just own the MAG-7 then because they've had lots of momentum. But like, 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-7, even though they've done really well over the past 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.

[00:23:07] 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-7, there's only been two stocks really that have outperformed out of the seven. So that momentum strategy will pick up on that, right? It's not just one MAG-7 trade. You're going to look at medium-term horizons and always be measuring what's outperforming and what's not.

[00:23:31] And so, you know, I think that is that flexibility and adaptability, again, is 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.

[00:23:56] 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 into that, can you just define – I think this is probably the widest definition among factor investors, quality. It's like people say, you know, when you see it or Warren Buffett 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?

[00:24:17] 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 obviously very different implementations or measurements of quality.

[00:24:42] 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 moats used too. But I would imagine that if you have a more forward-looking view of profitability, you maybe have 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 high historic profitability.

[00:25:10] But I think if you think about, like, inflection of profitability, perhaps, you know, that might have done better. But certainly we've seen quality as a factor. Two things. Become more negatively correlated with momentum in the most recent past than the history. But also really underperformed 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.

[00:25:39] 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.

[00:25:55] 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 more maybe cyclical-type companies like industrials, energy, utilities. It's just another feature of this broadening out trade.

[00:26:13] And then on top of that, like all technology regime shifts, 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 it's becoming more of a commodity, so it's going down. So you think about that. And historical profitability companies like software are kind of ripe for disruption.

[00:26:42] Like that's where the aim of AI is going to, right? It's kind of like the middleman in the internet days, right? You can skip the middleman and go right to the manufacturer. So profound changes, which I think implicate quality as a factor in kind of the short-term or medium-term. Yeah, before we get into software, one of the interesting things I've seen with some quality investors, and some of these weren't factor investors, but this idea of focusing more on consistency of the business than the balance sheet.

[00:27:10] And that's allowed a lot of these tech names, like the MAG-7, 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 have bad balance sheets or anything like that, but you have seen that consistency become more and more a measure for quality investors out there, I think. Yeah, yeah, definitely. And look, I think Liz Ann Saunders actually talked about it, which I totally agree with.

[00:27:35] 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 what's the change? 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 or is it getting worse?

[00:28:04] 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 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, it's like inflection points and are things getting better or worse, not good or bad?

[00:28:33] Yeah, she said the same exact thing in the interview. She echoed exactly what you're saying. And software is really interesting to me because it's almost like if you had to, before AI, if you had to make the perfect business, it's like high margin, consistent returns over time. Everybody was throwing on the debt side. Everybody was just throwing money at these companies because they seemed like the perfect business. And now at the flip of a switch, they're not. And it's just interesting to think about a factor-like quality, but also all these people that held these businesses, it's a challenging time, and you or I are not discretionary investors who are going to try to figure this out, thankfully.

[00:29:03] But it's just an interesting time when these businesses that had 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 rearview mirror, to think about what do we think about quality going forward, right? So the trajectory of quality or the trajectory of profitability.

[00:29:28] 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.

[00:29:56] 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 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.

[00:30:22] 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 way beyond what I can do and it's like let's just buy what's going up. I think that's a great thing about momentum is it takes these hard, hard decisions in the market and it 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.

[00:30:48] I don't try to predict anything, but we look – we do think price is a signal. Price has 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.

[00:31:17] 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 its Achilles heel too. It has its own risks and we can run through those. But I think the risk of quality, the Achilles heel 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?

[00:31:47] But then I also think the Achilles heel for quality is – it's just when you have these big technology shifts, it can be hurtful for quality. And 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.

[00:32:17] I know you're a momentum investor, not focused 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 is completely blown up on me. What do I do? And I think most of the time we say, all right, 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 a business. So it may not be a sign that there's something wrong with a quality factor.

[00:32:46] It may just be one of those short-term things. But how do you think about that when you see something happening in the market, balancing that against sort of your long-term evidence for your factor? Yeah. I think you've got to be open to evolving your factor. And I think we've seen a lot 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.

[00:33:14] And, but 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 right itself. I think it will come back. It just may take time. And if you think about profitability, if we're kind of looking at it from an operating profitability perspective, historic perspective, well, over time, if what we're saying is correct

[00:33:43] in these megatrends, 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 profitabilities at 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. Ein perfekter Frühlingstag. All of them!

[00:34:13] Sonne! All of them! Park! All of them! Picknick! Und so viele Polen! Shop Apotheke sagt Tschüss Allergie und Hallo Frühling. Hier findest du alles, um unbeschwert durch die Allergiezeit zu kommen. Als Neukunde sparst du sogar 10% ab 35 Euro Bestellwert. Mit dem Code NEU10. Du hast ein E-Rezept? Einfach Shop Apotheke App runterladen und direkt einlösen. Gutschein-Bedingungen auf shop-apotheke.com slash Gutscheine. Do you have any thoughts on the differences between now and the 90s?

[00:34:43] 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 tech stocks leading the market up and we're going to have a collapse and value is going to reign again and all that stuff. But I'm just interested from the perspective of factors. I know you 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 and the bust of the 90s. But definitely, I started my career in the late 90s. So I did see the highs and the lows of it.

[00:35:12] 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 don't know, I'm not saying anything 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 and industry. Whereas the internet was, there were industries that were kind of, quote unquote, safe or not

[00:35:41] as impacted or didn't get the benefits of the internet. 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's just every industry and 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 bust is kind of missing the point. It's like, well, first of all, we don't know when the boom and bust is going to happen. I think with the, when you look at backwards, you're like, oh yeah, it was so inevitable.

[00:36:10] But at the time it was not. I think that 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.

[00:36:36] And 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'll 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 Greenspan's irrational exuberance speech was maybe 97. I think it's so, so many people at that point were like, this can't go on any longer. It's over. Or, you know, it's going to end any day like you.

[00:37:06] There were two years of massive, massive returns to these stocks before it ended. It just gets to the idea of this is impossible to time. Yeah. Yeah. Look, and also Amazon, one of the best companies, right? One of the best success stories of all time was I remember being panned for a lack of profitability. Right. And it 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.

[00:37:34] And sometimes they're not led by the former leaders and they're always, and not be maybe high historical profitability companies will lead that. That's certainly not what we saw in the, in the nineties either. So yeah, I think the narrative of like a boom bust is kind of misses the point to me a little bit, you know, like I think there's, there's winners and losers and, and, and stocks and expectations and idiosyncratic risk matter too.

[00:38:03] I want to shift to your paper, buy high, sell higher, which if you had to criticize Jack's investing 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, but nonetheless, it's, it's an excellent paper. And you're talking about this idea of using the proximity of the 52 week high as a signal. So can you just talk in general about what you're looking at in the paper? Yeah, definitely. We, we, well, it's interesting that, so the, the first part is that we've kind of always used a 52 week high as a, as a reference point, because I think it's important from a behavioral

[00:38:32] perspective with momentum. So salient reference points or benchmarks are always, I think important. And we, we, 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, Jack, you just mentioned value nearness to a 52 week high. The data suggests that information coefficients across styles. Uh, so irrespective of whether you start with momentum or not, 52 week high is a really

[00:39:00] 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 a, is an important signal. Um, and, but in this paper, we talk about how we can use the 52 week high to improve, uh, momentum. Uh, but, but the, the basics of the paper was, Hey, 52 week high is actually a pretty important benchmark in terms of evaluating momentum.

[00:39:26] 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, um, a range or relative to a 52 week high, which we show in the paper actually explains a good portion of momentum returns just with that single factor. And there's different ways to look at it, right? You referenced a few of 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.

[00:39:53] 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, we always do a literature review and look at what work's been done. And I think, uh, um, there's been some really good work. Um, George and Wang in 2004, uh, Wesley Gray and Vogel, uh, in, in, in 2016, I believe in their quantitative momentum book had some pretty good, um, data on this as well. So we kind of, we use some of those, um, metrics.

[00:40:22] Um, and then we found a more recent paper, uh, looking at, uh, 2000 or 2025 paper by Bolthausen, but, uh, we use three different measurements. So yes, we use a nearness to a 52 week high. We called 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 to price, which is just how far is it away from its low. So the bet, the higher away from its low, the better. And then we also looked at a range 52 week high, which, which includes where the company

[00:40:51] is positioned, uh, 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, uh, definitely kind of outperformed all of them on a risk adjusted basis across most selection universes.

[00:41:18] And then again, again, it, 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, you know, 12 minus one momentum signals? Is it, is it markedly different than the 12 minus one signal or is it very, very correlated? I think it's highly correlated. Um, but I mean, our, our data suggests, and, and look, I always say when we look at like

[00:41:44] back tests and we look at data and research, um, I don't think we can always say anything definitively, but the, but, but what the data suggests, um, in not only our research, but others is that, um, the 52 week high, and we did some nested sorts and I won't get too technical on it, but we actually tried to answer that question with first sorting on momentum and then within that sort on 52 week high and then vice versa to try to tease out whether

[00:42:09] you get any more information, uh, outside of your 12 minus one momentum with 52 week high. And across most universes, we found that you don't gain any, any, 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, um, strategy, you

[00:42:38] 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 would this argue for replacing 12 minus one momentum with a 52 week high, or do you still think combining them together is probably the best way to go? Well, I think you can make that argument. Um, but I do think combining them is what we think is, um, leads to a better, not only risk

[00:43:05] adjusted return than 12 minus one, but a better balance between upside capture and downside capture. Um, so I think the, if you were just to do an exclusionary and just do range 52 week high, um, 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. Whereas if you combine the two, you get a very, you get a good balance between, um, you're approaching sharp ratios of risk adjusted returns.

[00:43:34] 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 in, for my factor investing, when you don't know combined, um, it seems to work, it seems to work pretty well. Cause you know, like the second I take price to book out of my value composite price, the books can have its biggest run like in history. And so like when you're not sure which one, you know, I think averaging them out when you're not sure is probably a pretty good way to approach it. I agree.

[00:44:02] And we saw the same thing with, um, one of the research pieces we did on smooth sailing in terms of the, how a momentum formation period, uh, manifests itself, like either smooth or continuous, uh, you know, like the frog and pan, uh, argument or whether it's volatile or not. And we found the same things that you can be exclusionary, uh, and you're going to probably be in a benefit on the downside capture. But, but, but, but I think using them in terms of portfolio construction process is what we

[00:44:29] found in terms of up weighting less volatile momentum companies, uh, and down weighting more volatile, uh, 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 your strategy, but did this research change how you manage portfolios at all? Or was this pretty much something you had already put incorporated into what you're doing? Yeah, we kind of, I think we've incorporated it always, but I think what we, I think what

[00:44:58] 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, you know, we're continuously proving the signal capture and are we looking at the right measurements, testing those, but then, um, introducing in formality in terms of how we, we manage portfolios. So for the smooth sailing or the volatility of momentum, it's more of a portfolio construction,

[00:45:28] um, adaptation. And then with the 52 week high 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 in terms of confirming what you're doing and making sure that you're staying on top of how, you know, how things evolve and continuously improving, but, but also, uh, yeah, can we get better and how can we incorporate these findings, um, into, uh, a process of not only stock picking, but obviously portfolio construction.

[00:45:58] Is there any interest, anything interesting in when this works and when it doesn't work relatively like a standard momentum, like in terms of momentum reversals, the different periods where it struggles. Was there anything you found interesting from that perspective? Well, I think what was most interesting about the range 52 week high, which I didn't and, and all of, and mostly all of the, the 52 week high 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 be, to include a 52 week high signal capture,

[00:46:27] which is totally counterintuitive. Um, 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, then you would think everything else being equal, that would be undervalued. So I do think there's some kind of a risk mitigation, uh, uh, because of behavior and expectations.

[00:46:51] Um, but I think, uh, what, what is, uh, the most surprising thing to us, uh, is that I think it's just counterintuitive to what just what most people think, um, in terms of 52 week high. So the adage of buy high, sell higher seems to be accurate. Um, you know, we're all trained on buy low, sell high, but it may be the opposite is actually, it's actually a better. Yeah. Yeah. To your point, if you, if you told most investors, this stock's near its 52 week high, and that's the only thing you gave them, should I buy it or not?

[00:47:21] They're going to say, absolutely not. You know, it's, 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 so well, because if, if everyone agreed with something, there'd probably be no alpha there. But I would say that I, we haven't gone into exactly what that kind of portfolio would do, uh, in certain environments. So we haven't answered that question yet, but, but I would say in general with a momentum

[00:47:50] strategy, and I think 52 week high 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, uh, abrupt leadership changes in the market. So you, you know, you go from winners to losers very quickly. Now, gradual changes is not a problem, but, but if it happens on one day, right? Where leadership shifts or in very quick, abrupt market reversals, generally after a, a,

[00:48:15] a downward trend, when you get a, the early stages of a big up market, those are times where momentum tends to struggle. Um, and I would expect 52 week high 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 quants, we're not like deciding what's in there, but I'm always interested in like what the momentum is picking up on. Like, obviously it doesn't have software right now. Are there, are there any areas that have been interesting in terms of what momentum's picking up on this year?

[00:48:41] Yeah, I think, um, yeah, we are kind of talked about all the, uh, the, the kind of broadening out theme, which I think momentum's picked up on. So, um, relative to some other kind of rigid factors, like a value. Or, or, uh, quality depending. Um, you know, we picked up on materials doing well. Um, you know, so gold, silver, copper, all those, you know, types of companies. Um, utilities have been kind of a different kind of momentum pickup recently. Um, but I'll, again, it has to do with the AI build out, right? Energy matters.

[00:49:11] And then I would say, uh, lastly, as I mentioned, energy, uh, energy stocks, um, really showing very strong momentum, you know, whether it's a natural gas, uh, servicers, uh, crude oil servicers or, or exploration and production. We've seen, um, uh, an acceleration in momentum kind of in the end of last year, beginning of this year, uh, largely on kind of AI themes. But obviously with March and what happened with Iran, it kind of got another leg up.

[00:49:38] So right now momentum's picking up on kind of that, that aha moment that we all had that like, oh yeah, energy is still important. Oil is still important. And it's a global market. So I think that aha moment, it's kind of helping those, those companies right now. And momentum's kind of picking up on that. Yeah. And 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. Like it's not, people want to associate it with high flying growth companies, but there's times in the market where you don't want to own those companies. There's times where momentum exists in maybe the more boring stocks.

[00:50:05] 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 is very much not loaded on growth. And when it's not loaded on growth actually is what creates the better premium.

[00:50:32] So again, that adaptability and flexibility is, is, is the, is what is momentum strong suit. But yeah, I mean, momentum, as long as what's working is boring, momentum is going to be boring. How do you think about consistency and momentum? I know you've probably read a Westbury and Jack Vogel's book. Like they, they show that at least in their research that, you know, consistent momentum that was better than the biotech company just announced the drug and went way up. Like, do you find the same thing in your research? Yeah, generally. Yeah.

[00:51:00] I mean, um, 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, um, or as a composite or as a, uh, as a signal in portfolio construction. And I think we look at it as like, um, not necessarily exclusionary because you get a very kind of concentrated, more concentrated portfolio with momentum if you do that.

[00:51:28] Um, so we've chosen to, again, to preserve that kind of upside downside balance, um, that use that knowledge in terms of how we construct our weightings of security. So, um, we showed in another paper that if you up weight the more gradual momentum companies, if you will, the more continuous, less volatile, um, you can improve risk adjusted returns of, of the kind of the standard 12 minus one momentum alone.

[00:51:54] So we definitely, our research has echoed that, uh, in terms of the general findings of that, that the momentum formation period does matter. Um, but we would much rather use it as a, a, a, a signal in terms of portfolio construction and weighting rather than exclusionary, because we have found that in, in, from an informed momentum perspective, biotech has been a good area for us in terms of, of excess returns and, and stock selection.

[00:52:20] And the fact that it's a large weight in micro cap and small cap, you don't really want to avoid it entirely, but you do want to, uh, 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 in reading some of your work that, uh, echoes 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.

[00:52:49] I mean, 2025 was probably the, the most stark example of that. And we did, we did a study that we, and, and this has more to do with timing, uh, but it just shows how the difference that it could make. And we did a, a monthly or a 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 paces

[00:53:19] points difference to your return using the same measurement of momentum, the same everything, but you just varied it by one month in terms of a quarterly rebalance schedule. And obviously that had to do with like, if you're measuring like before the tariff tantrum and then the big, the big, um, move up on the market, uh, uh, on the, um, the pause of, of, of tariffs 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 outcomes.

[00:53:49] Implementation does matter. And we, the way we do it and found over the longterm, not all the time, but definitely not 2025, but over the longterm, what we do is we rebalance, um, 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, uh, every day.

[00:54:14] And that way we think we capture over the longterm 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 longterm.

[00:54:42] 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, Oh, I'm just curious if there've 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. Like certain stocks are going up and certain stocks are going down based on one tweet. Like the, 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.

[00:55:09] 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 from one day to the next. So yeah, I think that 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.

[00:55:39] At least. So I think the measurement period matters. But I do think from, 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.

[00:56:04] 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 momentum in your strategy or do you feel like that's reflected mostly in price? No, we actually measure fundamental momentum as well. I mean, that's going to be, you know, we use revision and surprise to help us do that.

[00:56:34] 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 capture, it includes both kind of price-based signals like 52-week high 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

[00:56:58] 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, 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.

[00:57:26] Unfortunately, you've answered our closing question and we have to come up with a new closing question, which we're in the process of doing. But, but I did want to ask you, I always like asking people who are doing research, like, is there anything interesting you're looking at right now? Anything you're researching, anything 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 a new signal? So right now it's actually fundamental momentum signals.

[00:57:56] So I think Novi Marks has done some pretty good work on that with the SUE. You're probably familiar with the SUE. But, you know, we, you know, 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, 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, cause we look at so many signals. We look at, you know, analysts revisions, but we look at the diffusion.

[00:58:25] So how many ups versus downs? We looked at the magnitude, same thing on surprise, but we also look at, you know, 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 at least interesting to us. I don't know about it, about anyone else, but, 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

[00:58:55] 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, what our total focus is. Well, thank you again. I really appreciate you coming back on. Cool. Thank you. It was great being on. Thank you for tuning into this episode.

[00:59:21] 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 XS Returns Network at xsreturnspod.com. If you have any feedback or questions, you can contact us at xsreturnspod at gmail.com. 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.