52 Week Highs Momentum Signal Travis Prentice

TITLE: We Asked a Top Momentum Manager Why 52-Week Highs Are a Buy Signal, Not a Warning CHANNEL: Excess Returns DATE: 2026-04-24 URL: https://www.youtube.com/watch?v=NPrwWsbG2Rg ---TRANSCRIPT---

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. On Wall Street, we have a really uh interesting characteristic that we take really good ideas and grown so big that they come become less good ideas over time. The real risk hiding in plain sight, right, with with the rise of passive and the fact that these companies have been bit up so much for so long and they 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 is AI.

Welcome to Excess Returns. I’m Jack Forehand and today I am privileged to be joined by another factor investor uh Travis Prentice, the uh CIO of Informed Momentum Company, a second time guest on the podcast.

Yes, thank you for having me. Big fan of the podcast.

Thank you so much. We’ve got a wide variety of topics. We’re going to talk about 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. 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 in the world quality 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 I wanted to start with — we just talked to Liz Anne Saunders and she was referencing this idea like how has 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. We’re seeing all kinds of craziness behind the scenes and an index that’s not doing much.

Yeah, definitely. The divergence has been extreme. You don’t have to look any farther than the difference between the SOXX performance this year, semiconductor performance and software. The SOXX is up 30% while the software like IGV, the ETF of the software is down 23. Beneath the surface there’s a lot of dispersion. 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.

It’s been a reasonable year for a factor investor. Value and momentum kind of became friends in the second half of last year and through this.

That’s a rare occurrence, right?

Correct. Doesn’t happen that often. We’re seeing it now, particularly in the non-US side. But it also reflects the broadening out of markets that we’ve seen. If you take March out, you’ve seen really a broadening out of the trade or what’s working, outside of just mag 7 and tech and software. You see the Russell 2000 outperforming large cap. So small over large and value being a nice place because it’s kind of the opposite of concentration.

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, we’re automatically making a bet on smaller companies. And when seven companies are driving the entire market, it’s just hard for any factor to work other than size.

Absolutely. I think there’s massive shifts going on that are helping the broadening out trade and the value trade and the momentum trade. One is we’re entering that AI disruption phase. Ground zero for that is software. But also deglobalization, moving manufacturing back to the US and nearshoring. AI as a technology is much more capital intensive and needs a broader participation of different types of industries and companies to make it work — the AI buildout. But also manufacturing come home are self-reinforcing trends that shift all the action in the capital from just the mag seven and tech to a much broader participation of industries and sectors and styles. Most of my 30 years has been rampant globalization and this virtual software-driven market. 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.

Totally. I think these are major shifts that aren’t just a blip. With all these evolutions happening and the pace of which they’re happening we would always advocate for being agnostic but make sure you’re exposed to styles in a balanced way. So having momentum, quality, and value. Knowing that these premiums pay over the long term, but if you put them together, you’re going to look smarter more often.

Does this change the way you invest at all?

No, not really. From a capital allocator’s perspective, 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 and different cycles. When we say something works, it’s on average annualized excess return over the long term. That doesn’t mean they don’t cycle. When we talk to most investors out there, they tend to be biased or overexposed to quality and value, and they’re missing the key ingredient which is momentum. There’s no factor that works better with value than momentum. 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.

Momentum’s strength is its adaptability and flexibility, but also that it’s not emotional and it’s agnostic. As a momentum investor, you don’t really care what should be working. All you’re doing is reacting to what’s actually working.

Just one more question on this. There’s a lot of talk about this idea that the market moves faster now. Do you shorten your look back periods?

Yeah. So at Informed Momentum Company, we’ve always favored a more recency bias to a momentum formation period. We did some research called “back to the future” which kind of challenged the conventional 12-minus-1 as the gold standard. We looked at a 40-year period and then a subsample of the last 20 years and found that a more recency biased momentum formation period actually worked a bit better over the most recent 20 years. So that does suggest it behooves you to move a little bit quicker now. The 12-1 over the last 40 years has worked pretty well. But in the most recent, especially in US large cap, it behooved you to have a more recency biased approach.

Do you think the market has sped up?

It’s hard to quantify, but from a practitioner perspective I’d say there’s two main differences. We tend to see a little bit more of an amplitude or an overreaction to current trends. Momentum pays off because at the beginning of a trend there tends to be an underreaction to the positivity of the information but ultimately part of the payoff structure is that there’s an overreaction at the end of the trend like a blow-off top. We see a much more violent overreaction these days and that could be due to zero dated options, FOMO, behavioral things going on now.

I want to shift to passive investing because I know you’ve read Mike Green’s work. You wrote a paper about this called “risks hiding in plain sight.” You were talking about this idea that risk has been redefined a little bit in the world of passive investing.

Yeah, big fan of Mike Green’s work. The growth of passive has been so massive — if we go back 25 years, somewhere between 10 and 20x in terms of assets under management. 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. It’s a strategy of market cap weighting. So that’s a very deliberate decision that necessarily isn’t the market. Passive investing or index investing is not inherently flawed. The problem becomes is it too much of a good thing? On Wall Street, we have an interesting characteristic that we take really good ideas and grow them so big that they become less good ideas over time.

When we talk with investors, there’s 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. From a long-term 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. With the rise of passive, 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 allocates not on any fundamentals — it’s just is it a bigger market cap, it’s going to get more capital. Then over time you could see the index becoming more untethered to fundamentals and it’s just priced on flows, which is the point that Mike makes. So that builds up risk over time. The S&P 500 right now entering the year was 40% in seven stocks and 35% in tech. Some of that’s because of the fundamentals, but some of it and maybe a majority of it is because the flows have disproportionately helped those companies.

I always think about Jim O’Shaughnessy’s two points of failure. Investors have two points of failure. One, they can sell when their portfolio is down and panic. The other is they can sell when they’re underperforming. I’ve found that second one is a much bigger risk to people. People are using tracking error as a measure of risk. That’s leading to their behavioral problems and mistakes.

Yeah, absolutely. Right now it’s just amplified because of how big passive has become and how concentrated these market cap weighted indexes have become. All of it doesn’t matter as long as flows remain the same. But if we think about some of these seismic shifts — AI being a much more capital intensive technology, nearshoring and deglobalization — that has a profound impact on these major companies. Microsoft is probably a great example — it has a much more capital intensive future, free cash flow margins are going lower, incremental margins are probably going lower. The risks are really important now to consider because of these massive shifts going on which highlight the real risk hiding in plain sight with the rise of passive. These companies have been bid up so much for so long, and it all wouldn’t matter unless there’s a change agent — and I think the change agent is AI.

I’ve sort of been arguing factor investing as a diversifier, as a risk-management tool, because people think about passive as low risk but as it gets more and more concentrated, having some of this other stuff on the other side can be a risk mitigator.

Absolutely. And it doesn’t take much. Mike said too that since passive has become so large, it doesn’t take much of a rebalance away to active to have some pretty hurtful results on a market cap weighted strategy. What’s driven large cap outperformance has a lot to do with the fact that it’s just got a disproportionate amount of the assets going into the market. If that reverses then it’s the other way is true. They’ll get the disproportionate amount of the selling pressure which should help smaller companies over big.

How do you think about it from the perspective of how it affects a factor investor?

I’ve thought about this a lot and don’t have any concrete answers. On one hand allocating more to larger market cap companies is positive tailwind for momentum. But also the lack of dispersion hurts. When you have a one-way trade and a risk-on environment, it’s hard to differentiate. Even a market cap weighted algorithm is kind of a weak form momentum strategy. The downside of the rise of passive which is hurtful to factors is that there seems to be more co-movement with securities or groups of securities rather than idiosyncratic risk.

People misunderstand the word momentum a little bit. They’re like, “Oh, you just own the Mag 7 then because they’ve had lots of momentum.” But we’re defining momentum in the factor world by a very specific look back period and performance and we’re using a very wide group of stocks.

Absolutely. Momentum is a discipline where you’re constantly reorienting to strength. The look back period matters, the implementation of a momentum strategy is paramount. It’s not a monolithic trade. If you look at the last year or so, the mag seven — there’s only been two stocks really that have outperformed out of the seven, so a momentum strategy will pick up on that. A momentum strategy is a chameleon. 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.” Can you define quality?

Most of our research uses the FAMA-French definition of quality, which is high operating profitability. So you take the top quintile of high operating profitability. There’s very different implementations of quality. You hear the word “moats” used too. If you have a more forward-looking view of profitability, you maybe have done a little bit better because when we look at operating profitability or quality, it’s kind of a backward-looking metric. We’ve seen quality as a factor become more negatively correlated with momentum in the most recent past than the history. We believe in quality over the long term — lower tracking error, good information ratio, risk adjusted returns. But we’re on a down cycle with quality now having to do with AI infrastructure necessitating more cyclical type companies like industrials, energy, utilities. It’s another feature of this broadening out trade. Like all technology regime shifts, kind of like the internet in the 90s — if we think about what AI is capable of, the agents and AI inference, the fact that it’s coding pretty well, so the cost of coding is becoming more of a commodity. High historical profitability companies like software are kind of ripe for disruption. Like the middleman in the internet days — you can skip the middleman and go right to the manufacturer.

One of the interesting things I’ve seen with some quality investors is 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 7 to become high-quality companies because they produce really consistent results.

Yeah, definitely. 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? With all factors, what’s the rate of change? What’s the second derivative? Is it getting better or is it getting worse, not good or bad.

Software is interesting because if before AI you had to make the perfect business, it’s like high margin, consistent returns over time. Everybody was throwing money at these companies because they seemed like the perfect business. And now at the flip of a switch, they’re not.

Totally. It’s super important not to always look at things through a rearview mirror. Stocks in terms of expectations, not historical. Expectations have changed in terms of the business quality of software. We’re not saying 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 and overallocation. It’s just about what’s the change at the margin. So you could be in an environment where software companies aren’t going anywhere, but they’re probably not going to be as good as they were in terms of businesses.

This is why I like momentum so much because you’ve got these people out there trying to argue the terminal value of Salesforce or whatever. It’s like let’s just buy what’s going up. Momentum takes these hard decisions out of your hands.

Totally. I’m not a technologist. I don’t try to predict anything, but we do think price is a signal. Price has information. We look at what’s happening in the market and then we seek to understand why. The Achilles heel of quality is what valuation are you willing to pay for that compounding. But also 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 it’s not generally a one-time occurrence. It could be multiple years of quality not doing as well.

When our factor strategy is not working, how do we think through that — is it short-term or long-term? A lot of quality investors right now are thinking, “here are my quality criteria, this is completely blown up on me, what do I do?”

You got to be open to evolving your factor. How investors define value has been a big discussion point over the last 10 or 15 years. Quality is the same way. Always stick to your knitting, but understand we need to continuously improve. Quality will write itself. It will come back. It just may take time. If we’re correct in these mega trends, then profitability will inflect. It just might be in other areas — sectors and industries or countries. Over time, profitability will move, it’s just slower moving than a momentum strategy would be.

Differences between now and the 90s?

Lot of corollaries. Lot of rhyming. But I do think AI has a much larger impact than even the internet because it will diffuse into every sector and industry. Whereas the internet — there were industries that were quote unquote safe or didn’t get the benefits of the internet. Whereas AI, every industry and sector is going to be changed somehow. The narrative of boom-bust is missing the point. We don’t know when the boom and bust is going to happen. When you look backwards, you’re like “oh yeah it was so inevitable.” But at the time, it was not. You can have two things be true: AI is going to be a profound change and the cycle can extend longer. When people talk with certainty on things is when you should get concerned because no one knows.

Greenspan’s irrational exuberance speech was maybe 97. So many people at that point were like this can’t go on. There were two years of massive returns from these stocks before it ended.

Yeah. And Amazon, one of the best companies, was panned for a lack of profitability. Ended up being a very high quality business over the long term. The trajectory or looking at things at the margin 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.

I want to shift to your paper, “Buy High, Sell Higher.” If you had to criticize Jack’s investing career, you would say a failure to do this is probably number one on the list. As a value guy, I just can’t do that. Can you talk in general about what you’re looking at in the paper?

Yeah. We’ve kind of always used a 52-week high as a reference point because it’s important from a behavioral perspective with momentum. Salient reference points are important. Nearness to a 52-week high — the data suggests that information coefficients across styles, irrespective of whether you start with momentum or not, 52-week high is a really good prediction in terms of looking out six months. So regardless of where we’re applying it or what kind of style, 52-week high is an important signal. In this paper we talk about how we can use the 52-week high to improve momentum. The basics of the paper was that 52-week high is 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 returns just with that single factor.

There’s different ways to look at it.

Yeah. We looked at three different measurements. Shout out to research done before us — George and Wayne in 2004, Wesley Gray and Vogel in 2016 in their Quantitative Momentum book had some pretty good data on this. We also found a more recent 2025 paper by Boltousen. We used three different measurements. We use a nearness to a 52-week high — we called it a “position relative to its 52-week high.” 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. 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? We found that from a risk adjusted perspective the range 52-week high actually had the highest Sharpe ratios as a single factor. The position 52-week high worked well too but the range one outperformed all of them on a risk-adjusted basis across most selection universes. The closer to the high of the entire range over the last year is actually a more salient reference point.

How does this relate to your standard 12-1 momentum signals? Is it markedly different or correlated?

I think it’s highly correlated. We did some nested sorts to try to tease out whether you get any more information outside of your 12-1 momentum with 52-week high. 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-1. In other words, the 52-week high is explaining on its own a lot of the momentum premium. If you just took the top quintile of a range 52-week high strategy, you actually had much better risk adjusted returns than a 12-1 momentum strategy alone. And most of that was on the downside capture being better than your standard 12-1 price momentum strategy.

So would this argue for replacing 12-1 momentum with 52-week high?

You can make that argument. But combining them leads to a better risk adjusted return than 12-minus-1 and a better balance between upside capture and downside capture. If you were just to do range 52-week high, it depends on the regime — it 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 approach Sharpe ratios very close to just the range 52-week high, but you got a better balance between upside and downside capture.

I’ve always had the saying in factor investing — when you don’t know, combine.

I agree. We saw the same thing with our research on smooth sailing — how a momentum formation period manifests itself, smooth or continuous (the frog and pan argument) or volatile. Same thing — you can be exclusionary and you’ll probably benefit on the downside capture. But using them in portfolio construction by upweighting less volatile momentum companies and downweighting more volatile balances those upside-downside captures a bit better.

Did this research change how you manage portfolios?

We’ve kind of incorporated it always, but we became much more systematic about it. Now we’re measuring all of these things. For the smooth sailing or volatility momentum, it’s more of a portfolio construction adaptation. With the 52-week high, it just kind of confirms in a very mathematical way what we’ve seen from practice.

Anything interesting in when this works and when it doesn’t work relative to standard momentum?

What was most interesting about the range 52-week high — and mostly all of the 52-week high measurements — was that it had better downside capture than momentum alone. That was really surprising. Over time, it’s actually a risk mitigator to include a 52-week high signal capture, which is totally counterintuitive. I think it’s investor behavior. No one wants to buy the highest price for something over the last year. So on average, if that’s people’s behavior, then everything else being equal, that would be undervalued. The adage of buy high sell higher seems to be accurate. We’re all trained on buy low sell high but the opposite is actually better.

If you told most investors, “this stock’s near its 52-week high, should I buy it or not?” they’re going to say absolutely not.

Totally. The fact that it’s counterintuitive is the reason why it works so well, because if everyone agreed with something, there’d probably be no alpha there. With a momentum strategy and 52-week high, you would expect this signal not to do well when there’s abrupt leadership changes in the market. Gradual change 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.

When you’ve been running a real-world momentum strategy this year, what areas have been interesting in terms of what momentum’s picking up on?

The broadening out theme. We picked up on materials doing well — gold, silver, copper. Utilities have been a different kind of momentum pickup recently — has to do with the AI buildout, energy matters. Energy stocks really showing very strong momentum — natural gas servicers, crude oil servicers, exploration and production. We’ve seen an acceleration in momentum at the end of last year, beginning of this year, largely on AI themes, but obviously with March and what happened with Iran, it kind of got another leg up. Right now momentum is picking up on that aha moment we all had — oh yeah, energy is still important, oil is still important and it’s a global market.

Momentum can be boring at certain times in terms of the types of stocks it’s picking. People want to associate it with high-flying growth companies, but there’s times where momentum exists in maybe the more boring stocks.

Absolutely. Momentum and growth tend to be positively correlated but it’s very mild. There’s times where momentum is very much loaded on growth and times where momentum is very much not loaded on growth. When it’s not loaded on growth actually is what creates the better premium.

How do you think about consistency and momentum? Wes Gray and Jack’s book showed consistent momentum was better than the biotech company that just announced a drug and went way up.

Yeah, the more continuous a momentum formation period is and the less volatile, the better the risk adjusted returns. We’ve chosen to use that knowledge in terms of how we construct our weightings of securities. If you upweight the more gradual momentum companies — the more continuous, less volatile — you can improve risk-adjusted returns. We’d much rather use it as a signal in portfolio construction and weighting rather than exclusionary because biotech has been a good area for excess returns and stock selection, and it’s a large weight in micro cap and small cap.

I picked up something in your work that echoes an idea Cory Hoffstein has talked about a lot — it’s not just how you rebalance your strategy, it’s when you rebalance.

Yeah. 2025 was probably the most stark example. We did a study — we did a quarterly rebalance momentum strategy like 12-minus-1, and all we did was vary the rebalancing calendar by a month. If you did January and March versus February and May in 2025, there was a thousand basis points difference to your return using the same measurement of momentum, just varied by one month. If you measured momentum at the depths of despair in April versus one month later, you’re going to get a very different outcome. The way we do it — we rebalance every day incrementally, meaning we move the portfolio when the signals move. We don’t wait for a calendar-based rebalance. That way we capture more of the start of a trend and less of the end of the trend.

Are there more reversals now? Macro guests always talk about one tweet changes everything.

Depends on how you measure momentum. If you’re very short-term, then you get a lot of reversals based on tweets. The time period you measure momentum is super important. Not discounting what happens on a day, but it doesn’t matter unless it reflects on the broader trend on a longer medium-term basis. We think the highest expression of momentum investing is actually price signaling information at the business that’s positive. So we’re focused on the intersection of stocks doing well — momentum — intersected with business improvement, fundamental momentum. That intersection helps decrease the noise and reversals.

Do you use fundamental momentum in your strategy?

Yeah, we measure fundamental momentum as well. We use revision and surprise. We firmly believe the highest expression of momentum investing is price reflecting fundamental improvement. Our panel of signal capture includes price-based signals like 52-week high and momentum scores, but also fundamental momentum signals. The confluence of those things gives you a better chance of not having reversals, but also increases the amplitude and duration of the outperformance if there’s actually a good business reason why it’s occurring. You don’t want to just purely chase price.

Anything interesting you’re researching right now?

Right now we’re going through testing of signals on the fundamental momentum side. Novy-Marx has done some pretty good work on that with SUE. We want to look at our signal capture on fundamental momentum to see does that explain the momentum premium fully, and is there a better way to measure these things. We look at analyst revisions but we look at the diffusion — how many ups versus downs. We look at the magnitude. Same thing on surprise. We also look at performance one day and three day after earnings report to actually measure whether it’s a surprise. We know momentum works, but can we make it work better for investors in terms of risk-adjusted nature, and help in some of the challenging parts like momentum crashes. If you can dampen down on the negative sides of the factor and amplify the positives, then better outcomes are in store.

Well, thank you again. I really appreciate you coming back on.

Cool. Thank you. It was great being on.