In this episode of The Acquirer’s Podcast Tobias, chats with Corey Hoffstein. He is a co-founder and Chief Investment Officer at Newfound Research. Founded in August 2008, Newfound Research is a quantitative asset management firm based out of Boston, MA. During the interview Corey provided some great insights into:
- The Robust Equity Momentum Index
- The Agnostic Case For Value
- Value Investing Indices Are Not All Created Equally
- Tesla Is A Living Example Of Soros’ Theory Of Reflexivity
- Diversify Your Diversifiers
- Embracing Process Diversification
- Compliment Your Asset Allocation Strategy With Robust Equity Momentum
- Is Momentum Set For A Comeback?
- Are Different Factors Creeping Into The Value Basket?
References in this podcast:
Should I Stay or Should I Growth Now? (Flirting with Models)
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Corey Hoffstein: Let’s do it.
Tobias Carlisle: Hi, I’m Tobias Carlisle. This is the Acquirers Podcast, my special guest returning, the first return guest, on the Acquirers podcast, Corey Hoffstein, my very good friend. He’s the co-founder and CIO of Newfound. It provides both research and manages assets. We’re going to be talking about his collaboration with Gestalt, what’s the firm name, ReSolve and the Robust Equity Momentum Index, and we’re going to talk about Corey’s recent paper on value investing, “Should I Stay or Should I Growth Now?” I love a Clash reference. We’ll be talking to Corey right after this.
Announcer: Tobias Carlisle is the founder and principal of Acquirers Funds. For regulatory reasons, we will not discuss any of the Acquirers Funds on this podcast. All opinions expressed by podcast participants are solely their own and do not reflect the opinions of Acquirers Funds or affiliates. For more information, visit acquirersfunds.com.
Tobias Carlisle: Hey Corey, how are you doing?
Corey Hoffstein: Toby, doing great. Thanks for having me on a second time. I feel privileged to be the first repeat.
Tobias Carlisle: I had Jake Taylor, he’s now come on as a host and my Value After Hours show. But you guys were the very first Guinea pigs, unfortunately for you. So I did promise to get you back after I’d had almost a year of practice. I think we recorded February 8th last year.
Corey Hoffstein: Yeah, I think, I think we’re going to hit almost perfectly on the year here.
The Robust Equity Momentum Index
Tobias Carlisle: I’ve gone about a week early, but I think it will be live around about that date. So you’ve created a new index, Robust Equity Momentum Index. This is mostly a value podcast, I need to start from first principles. Let’s talk about what is momentum.
Corey Hoffstein: So momentum is a really basic quantitative signal. At its core, the idea of momentum is that securities or assets that have recently outperformed their peers will continue to outperform their peers in the short-run, and those that have underperformed their peers have a higher likelihood of continuing to underperform over the short-run. And obviously, all the craftsmanship and nuances in how you measure that and build a portfolio around that idea, But, that is the core idea of the quantitative signal. It’s very much tied to behavioral concepts as to why or why not that works, why such a simple concept can work.
Corey Hoffstein: But what you do see is from an efficacy perspective, it can be applied across individual securities, across-asset classes. It works in commodities, currencies, fixed income, equities, equity indices. So that gives you a lot of confidence that this type of signal, despite being rather trivial to implement, has a strong level of robustness to it.
Tobias Carlisle: When I think of momentum, you’ve got a great post on your site, which I read before I met you, you’ve had it on that site for a few years now, It was 200 Years of Momentum. When I think of momentum, I think of Cliff Asness, I think he may have been one of the first to codify momentum in relation to equities. My recollection of what he had done was he was looking at the… It’s a 12-month momentum lookback and then you don’t examine the most recent month. What’s the rationale for that? How does that work?
Corey Hoffstein: Yeah, so momentum, what’s really interesting, the academic studies for momentum actually go way, way back. I think the earliest was in the 1920s there were later studies in the 1960s but really I think what you saw was the growth of efficient market theory really pushed momentum aside. I think momentum got very much caught up in this idea of technical analysis, which was really poo-pooed on, especially by people who were doing more fundamental analysis, taking on that Graham and Dodd type mentality.
Corey Hoffstein: So what you saw was a lot of the more price-based quantitative signals really didn’t get a lot of attention until the early nineties. So really the seminal paper here was done by Jagadish and Tippmann, I believe it was 1992, might’ve been 1994, and they did look at a variety of different lookback periods.
Corey Hoffstein: So one of the ones that came out of the paper as being very strong was this idea of twelve minus one, so you’re going to look at the prior 12 months skipping the most recent one. And the reason that they do that and do it very particularly in the space of individual security selection is because what they intended to see was in the very short-run, securities actually exhibit mean reversion.
Corey Hoffstein: So if you saw a very, very strong performance in the most recent month, it actually had a higher likelihood of reverting over the short-term. So by focusing really on that twelve minus one, you were looking for more persistent pass momentum, ignoring the most recent returns that had a higher likelihood of mean reverting and… towards those securities that had a higher likelihood of persisting in that performance.
Diversify Your Diversifiers
Tobias Carlisle: I’ve had Adam Butler on the show, who’s Gestalt at ReSolve and you’ve been on previously as well, talking a little bit about momentum. One of the things that I learned from both of you guys is to try to sort of be a little bit less strict about those look-ahead periods or to be less governed by what the back tests says specifically and sort of to take more of an ensemble approach to that. So, what is the problem really that you’re trying to solve with the Robust Equity Momentum Index?
Corey Hoffstein: Yeah, so I think if we take a step back, for us at Newfound, we’re very, very much focused on active risk management. Our view is that for investors who are trying to achieve an outcome in their financial plan, consistency in returns is really important. And so what you tend to see for most investors, the way they try to de-risk their portfolio over time is by introducing more fixed income. That’s been the plan for the last 30 years and it’s worked very well.
Corey Hoffstein: The potential problem that we see today is that as you add more fixed income into your portfolio, you’re not really introducing more diversification. You’re just really explicitly de-risking. So if you move from a more equity-dominant portfolio to a more fixed income-based portfolio, at this point where interest rates are, you’re moving into an asset class that has a very, very low forecasted real return.
Corey Hoffstein: So as you get towards retirement and you’re using fixed income to try to manage risks, the risk you’re introducing is that you might actually live longer than expected and you may therefore outgrow your portfolio with the ability…
Tobias Carlisle: I hope so, that’d be a great risk.
Corey Hoffstein: Oh, it’s a great risk until you’re out a money and then it’s a real big problem at the end of life. What we’re really pounding the table about is saying, the answer for us is diversification, that all risk management should be centered around diversification. We just really think you need to rethink diversification more holistically. It’s not just what are we investing in, but it’s how are we making those investment decisions and even when are we making those investment decisions.
Corey Hoffstein: So to go to the how, there’s absolutely nothing wrong with strategic asset allocation. It works really, really well in certain market environments. But if you’re using, let’s say, US treasuries as your primary means of managing risk in your portfolio, a rising interest rate environment can be a difficult environment for you to do well in or a prolonged low interest rate environment can mean that you miss out on a tremendous amount of portfolio growth opportunity.
Corey Hoffstein: So what we’re ultimately trying to do is say not that tactical, which is an approach that we focus on heavily, is better, not that alternatives are or not that buying puts as a means of managing risk is necessarily better, but they all just happen to work, be effective and ineffective in different market environments and that we should really think about diversifying the way in which we manage risk. Diversify our diversifiers in other words.
Corey Hoffstein: So what we wanted to bring to market, and doing this with Resolve, which I think is a really unique collaboration as far as products in the market go. But with this index, what we wanted to say was, well, how can we apply a lot of these momentum and trend-following ideas to equity market exposure to help investors potentially manage those big left-tail risks can be associated with equities, especially where equities tend to be the primary source of risk in most investor portfolios.
Collaboration With ReSolve
Tobias Carlisle: You stepped ahead a little bit there. It’s funny, I think about you and ReSolve as philosophically aligned and I’ve learned a great deal from both of you guys. So how did the collaboration come about and why work together?
Corey Hoffstein: So Newfound Research, my firm, we’ve been helping power and running our own tactical strategies going back to 2008 so we were originally a research firm outsourcing the actual asset management to other asset managers. Around 2013, we started offering her on separately managed accounts, mutual funds in 2014. So this idea of tactical equity, trend-following momentum has been near and dear to our hearts, something we have practiced and researched for a very long time now.
Corey Hoffstein: The team up at ReSolve came upon a lot of the same conclusions completely independently and both of us have been large proponents of publishing research, found each other through the research and I think ultimately formed a mutual respect for the research learned from each other, help push each other in a very strong way. And I think that’s somewhat unique in what’s historically a competitive market environment to have that collaboration.
Corey Hoffstein: This really came about because what we saw post-2008 was a large number of people who really did want to adopt this tactical mentality, really focus on proactive risk management. And our friend, Meb Faber, I think was a large influence there with the paper he wrote showing that you could just use something like a simple 10-month moving average and just look at it the end of every month. A gentleman named Gary Antonacci wrote a very influential paper and wrote a book. I believe he just used 12-month returns and evaluated every month.
Corey Hoffstein: Adam, the CIO at ReSolve and I really were hitting our hands on the table about saying, yes, we believe these styles work, but if you’re only going to look with one signal, making a big all-in, all-out decision and only look at one point in the month, you’re taking on a tremendous amount of specification risk. So we think the style works, but the way you’re specifically implementing the style can make it so that you actually underachieve what you’re trying to accomplish.
Corey Hoffstein: So there was this big debate about simplicity versus complexity. More complexity obviously can potentially make something more fragile. But we argued, if you get too simple, it becomes too fragile. And I think what ultimately ended up happening was Q4 2018 was a big wake up call for a lot of people who were implementing these, very simple “do it yourself” approaches where they saw that for some of these signals, they rode the market all the way down to December 31, 2018, the signal turned off, then they missed all of January and some of them even February. So it put them well behind what they were trying to accomplish and I think that was ultimately an eye-opener.
Corey Hoffstein: They had to experience it and say, “okay Corey, okay Adam, I understand what you’re saying that maybe we don’t just want to use one signal in evaluate once a month. Maybe we want to do all these different approaches to measuring trend and momentum together, use this ensemble, measure more frequently, make smaller tweaks, act more like a dimmer switch than a light switch. So there was a lot of demand that we got from people saying, “but that’s too much work for me to do. Can you put this into a strategy for us?”
Corey Hoffstein: So ReSolve received the inbound requests I received the inbound requests, we ultimately said, you know, does it make sense for us to come to market with competitive products or does it make sense for us to collaborate, share some ideas, and help support the index together? And ultimately we chose the latter because we thought it was going to be a more powerful solution.
Embracing Process Diversification
Tobias Carlisle: So what does the index actually do? How are the decisions made? How is it implemented?
Corey Hoffstein: The index starts with a really simple decision tree. So we’re going to start at the very beginning by asking a very simple question: do global equities look like they have a positive trend or a negative trend? And I’m very generic with that question, right? I’m not going to talk about how we implement it.
Corey Hoffstein: If it has a positive trend, that means we want to be invested in the equity market. Then what we’re going to do is we’re going to look at three regions. The three regions are going to be US equities, foreign developed, and emerging markets, and we’re going to look at their momentum and choose to invest in the region with the strongest momentum. Again, for a moment, just being very generic about how we ask that question.
Corey Hoffstein: If we see a negative trend on the other hand in global equity markets, well then we want to divest and move to a position of safety. So what we’re going to then do is look at short-term US treasuries and intermediate-term US treasuries and choose to invest in the one that has the strongest relative strength or momentum.
Corey Hoffstein: Now if we follow that really simple decision tree through the path, we’d actually end up with just one recommendation, right? So right now US equities look like they’re in a positive trend. Sorry, global equity look like they’re in a positive trend. US equities have the greatest relative strength, the decision tree would be would say, be all in on US equities. But I was very generic in how I ask those questions. When it actually comes to implementing those with a model, how you measure momentum, how you measure trends in general can actually lead to different outcomes.
Corey Hoffstein: So the real sort of fundamental problem that you face when trying to implement this is, let’s say, Toby, you have the decision tree and you say you’re going to implement it using 12 months of history. I’m going to look at the 12-month returns. And I say, well I actually think 9 months is the secret. We both think they look the same over the long-run, we think that there’s efficacy to the system, but I actually end up with different recommendations than you end up with. Well that’s sort of confusing because they’re both in theory trying to tap into the same thing, momentum and trend, it’s just we ended up with different answers.
Corey Hoffstein: So the solution we came up with was to say, well why make that choice at all? There are times where the 12-month might be right. There are times where a 200-day might be right. There are times where 36 weeks might be right. So rather than making this very specific choice, why not create a decision forest where we plant all these trees, right? Each tree represents one very specific way of measuring trend and momentum. It gives you one very specific answer as to what you should invest in and then what we do is we look at the whole forest and we allocate in proportion to the number of votes received. So if US equities get 50% of the votes, they would be 50% of the portfolio.
Corey Hoffstein: So the idea in doing so is to try to embrace process diversification. Recognize that we think trend and momentum work as styles over the long-run, but we don’t know in the short-run which particular implementation will work best. So we want to diversify our risk as to how we’re actually measure those questions.
Tobias Carlisle: So when you’re implementing it, it’s not through individual equities, you’re looking at indices, you’re looking at the top level of the S&P 500, for example, is that in a trend or does it have momentum. Is that right?
Corey Hoffstein: Yep, that’s right. So we are looking at this as more of an asset allocation decision and there’s really two-fold reason. One, because again, what we’re really trying to do is from a major muscle movement perspective, tried to create a portfolio that can manage that risk of prolonged and significant drawdowns in those equity markets. So the individual security selection there is less important than just being exposed or not exposed or that beta exposure.
Tobias Carlisle: Right.
Corey Hoffstein: But from a philosophical perspective, there’s actually, I think a strong argument that that sort of cross-asset allocation is more ripe for opportunity than individual security selection. That when you think of the way assets are managed worldwide, especially in pensions and endowments, they tend to come up with very strategic policy portfolios and they don’t have a lot of active risk allocated to cross-asset decisions.
Corey Hoffstein: So they’ll say, we want 30% of our assets in US equities and then they’ll pick managers who go into US equities and try to make active decisions about what securities to pick, but there’s no one really out there meaningfully arbitraging cross-asset decisions. So we think there’s far more opportunity for differentiated performance in those cross-asset decisions than there is in the individual security selection itself. Especially on the risk management side.
Tobias Carlisle: How many signals are you using? Are you allowed to talk about them?
Corey Hoffstein: Yeah. Yeah, absolutely. And the index methodology is fully documented, so anyone who wants a deep dive on the index methodology, they can find that on the index webpage… in terms of measuring trend and momentum, but then we have a variety of what we call different lookback periods. Everything from very, very short-term, one, two month type periods to longer term, 18-month.
Corey Hoffstein: And then we also vary what we call the sampling frequency. So are we looking at a 200-day moving average versus a 40-week moving average versus a 10-month moving average? They’re all kind of the same span, but depending again on which data points are included, you can actually come up with different answers. So the grand total is actually something close to 30,000 individual trees being planted, which sounds like an overwhelming number.
Corey Hoffstein: But the reality is the benefit of being a quant is that there’s no more marginal effort and doing the 30,000 versus the 29,999. And it may have very, very, very little impact in terms of you think of the marginal benefit… including it either, it’s just more computational power, so we might as well include it.
Compliment Your Asset Allocation Strategy With Robust Equity Momentum
Tobias Carlisle: How should somebody implement the index in the portfolio?
Corey Hoffstein: So this is where I think a lot of people have gotten into trouble over the last decade. So after 2008, we witnessed a huge uptick in the demand for these types of strategies and a lot of people use them to replace equity exposure. And I think then you get a 10-year bull market and people get frustrated because a strategy like this really is not necessarily going to outperform in a bull market environment. You would hopefully expect 70 to 80% of the up capture and then maybe try to only get 40 to 50% of the down capture in those more prolonged bear markets.
Corey Hoffstein: What we think is a far more effective way of implementing this type of strategy is truly thinking about it as a compliment to a strategic asset allocation. So we benchmark it to a 60/40 which we think is sort of the alternative way in which people try to manage risk. And we think that that benchmark should not only inform the long-term risk and return profile of the strategy, but we think it should also inform where assets should be funded from. And I don’t think people think about that a lot from a benchmarking perspective, but I think it’s a really important aspect of benchmarking.
Corey Hoffstein: So what does that mean? Well, if I want to have a 10% slice of my portfolio be tactical and I’m benchmarking that tactical portfolio to 60/40, then I should actually sell 6% of my global equities and 4% of my fixed income to allocate to a strategy like this. And the reason why that can work is because then now, the strategy acts as sort of a tactical pivot in the portfolio that in a strong bull market, instead of being a 60/40, that tactical pivot has the opportunity to tilt you more towards like a 70/30. And then if it goes the other way, where markets start to sell off instead of being a static 60/40, that tactical pivot can now de-risk the portfolio to something like a 50/50. I think, again, the benefit there is you’ve also constrained how tactical you’re going to be.
Corey Hoffstein: So again, our view here is not that tactical is better than strategic, it’s that they do well in different market environments and we want to think about ways of integrating them for a client so that they can create more consistent outcomes and their financial plan has a higher probability of being achieved.
Tobias Carlisle: Yeah, that’s really clever. How do folks learn more about that if they’re interested in it?
Corey Hoffstein: Yeah, so they can go to our website, thinknewfound.com, we have a very specific index page for this index. So the index ticker is actually NRROMOT. I’ll send a link to you and you can hopefully share under the podcast page, make it a little easier for people.
Tobias Carlisle: I’ll stick it in the show notes.
Corey Hoffstein: And there’s all sorts of resources, webinars. I’ll have this podcast up there of course, index methodology, back-tested fact sheets, everything you could hopefully need in an evaluation of of the index and the strategy.
The Agnostic Case For Value
Tobias Carlisle: That sounds great. Oh man, you’ve got to help out long suffering value, guys. I’m looking for any kind of a cool drink of water in a long desert of underperformance of value. There are a couple of great things on your website that I love checking out pretty regular. I always look at the equity style dashboard. You’ve got a really great representation of what value has done, what size has done, what momentum has done, what people are actually investing in to implement those. Looking back over one year and three years, I think it’s a fantastic resource and I go there very regularly.
Tobias Carlisle: I also love your blog. So anytime you mention value, because I always think of you as your agnostic to any of the styles. So I want to see what are the guys who are agnostic, think about this thing that I’m a Jihadi in. So I loved your paper, “Should I Stay or Should I Growth Now?” What was the paper about?
Corey Hoffstein: Well, I should start by saying, I actually came up with a paper title before I came up with the paper.
Tobias Carlisle: Sometimes that happens, right? Now I got to write it.
Corey Hoffstein: It hit me in the shower and I was like, well now I have to write a paper about this. So we are not value managers, but that doesn’t mean that value doesn’t influence our process. In some of our tactical mandates, we take a sector-base approach to accessing the equity markets very specifically and equal sector weight approach tends to serve as our strategic basis.
Corey Hoffstein: And when you look over the last three, five, ten years, you’ve seen that basic equal sector weight approach has tracked the value premium very closely, did very well 2000 through 2007, 2008, did decently up until about 2011, 2013, and then basically has been a drag on portfolio performance ever since and very steep since 2018. So tracking value very closely. So it is one of these interesting things that while we don’t pick value securities, when you look at the market one way, you can actually be influenced by these other factors, what I consider to be these unintended bets.
Corey Hoffstein: So for us, we wanted to take a look at saying, well, if we know that value is a factor that we’re hitting unintentionally, value in size to a certain degree, when is this pain going to end? Right? We continued to report that this has been a drag on performance year, after year, after year at a certain point. After hitting your head against the wall that many times you have to ask, should we just do it differently?
Corey Hoffstein: So ultimately, what the paper wanted to look at was saying, how can we try to measure the cheapness of value? Is value out of favor for a good reason or do we think it’s been oversold? There are a number of papers that have been written recently, QMA wrote one, Research Affiliates wrote a great one, Rob Arnott wrote a great one. Excuse me, Cliff Asness wrote a great one, Rob wrote the Research Affiliates one. All written in the 2018-2019 period.
Corey Hoffstein: For me it was trust but verify. I wanted to take a look myself. And very specifically what I wanted to look at was separating a little bit the difference between the academic implementation of a factor and the way an investor might look at a factor. So you mentioned we have this style dashboard. One of the things that’s really important to me is saying it’s not fair to me, as a quanta, to say, hey, by the way, values out of favor. This is the way I implement it. It is this long/short academic portfolio. And by the way, the way you’re going to access it through ETFs looks nothing like that. So my research isn’t even relevant to the way you’re going to buy this factor.
Corey Hoffstein: So what I wanted to do was try to replicate some of those ETF methodologies. What I would consider to be version one and version two methodologies, and we can talk about that and just simply ask, is value cheap? Does it look cheap historically? Has it been oversold relative to both the market and growth portfolios? And the idea of being, if it does look historically cheap, that there might be strong tailwinds that we can expect going forward as we would get a a reversion to fair valuation.
Tobias Carlisle: When you say oversold, you’re not using that in the technical sense of… I don’t know. I don’t actually know how that’s calculated, but that’s one of the overboard, oversold, like an RSI indicator or something like that?
Corey Hoffstein: Yeah, I mean relatively oversold, right? So if we think that prices are set at the margin by demand from investors that if investors are issuing value stocks for growth stocks, they’re going to relatively trade those down. You know, instead of buying value stocks, they’re buying growth stocks, which is going to increase the price of growth stocks and disfavor value stocks. So it’s really more of a relative spread. And then really what we’re trying to look for there is how does the price of buying that basket compare to the fundamentals you get and how is that tracked over time?
Tobias Carlisle: I thought it was a really interesting paper and it did sort of remind me a little bit of, or it looked a little bit at, Cliff Asness’ paper, which I thought was a particularly good one. Where he said, if we’re talking about the value factor strictly that’s price-to-book, it hasn’t worked for a really long period of time. Lots of folks who’ve looked at the reasons why. There’s various arguments, one is sort of that the world has moved away from a tangible asset to an intangible asset world.
Tobias Carlisle: Another one is just that buybacks have reduced the efficacy of the signal because companies that are very good tend to buy back a lot of stock and some of them have got negative book values.
Tobias Carlisle: Which McDonald’s is an example, it’s a very good company that has lots of free cashflow, buys back a lot of stock. So there’s no money invested in any more because it’s all been paid out, which is a great business and ultimately one you’d like to own. But it’s misclassified by price-to-book.
Tobias Carlisle: But then Cliff moved on and he said that’s not the way that it’s implemented for the most part. No value quant is using price-to-book or none who was still going anyway.
Corey Hoffstein: Right.
Tobias Carlisle: The implementation is look at flow, look at a variety of different metrics and he found that that improved performance pretty materially. But you still top out in 13, 14, 15 somewhere around there. Then they said his AQR’s implementation without actually telling us exactly how they did that. But you can imagine that it’s probably closer to what every other quant value guy is doing when they’re looking at everything. They’re looking at the health of the company, health of the balance sheet, strength of the cash flows, the valuation, various other things like that. So that’s what I took from your paper too, that you were looking at what is a more realistic implementation of it. Is that a fair assessment?
Value Investing Comes In Many Flavors
Corey Hoffstein: Yeah, I mean, I think to your point, this is something we were chatting about before we started recording. We can talk about value as a style, but the way you implement it, again, it’s so meaningful to your conclusion. So price-to-book, that just very generic academic definition, peaked out in 2007. Most composite models that might do price-to-book and plus price-to-forward earnings, and enterprise value to sales might be included in there. Those get you to 2013-2014.
Corey Hoffstein: When you start including other craftsmanship concepts, so you’re going to look at the quality of the balance sheet. You might look at cross-industry signals instead of cross-market signals, so you might be sector neutral or industry neutral, has certainly helped you more in technology, for example. Different sort of portfolio construction. I mean, some of the signals that someone like an AQR might even use would be looking at, but we’re not just going to look cross-industry, we’re going to actually look at valuations of suppliers, economically linked companies, not just what the GIC tell us. Or they might have their own definitions.
Corey Hoffstein: And you see that some of those craftsmanship things using momentum for example, to keep you from buying losers, deferring purchases. DFA implemented that a couple of years ago. Those sorts of things kept a lot of value people at least in the game until late 2017, early 2018 and then since then it’s just been a loser for, it seems, everyone. Which is really interesting because again, it ties back to your considerations on your experience with value is very much tied to the specific choices you make of how you implement the concept.
Corey Hoffstein: Again, I should mention here, we’re very much talking about systematic value. I know there’s a lot of people who fight with you online in particular about what does value mean. We’re talking about the quant value sematic value here.
Value Investing Indices Are Not All Created Equally
Corey Hoffstein: And so what I wanted to look at was really what I considered to be value 1.0 indices and these are really indices that got popular, well they’ve been popular for a long time, but products started coming out around them in the early 2000s.
Tobias Carlisle: That’s a broad one, like a Russell.
Corey Hoffstein: Exactly. This would be like a Russell 1000 value. And I think what’s really unique, well not unique, what’s really interesting, at least, about these indices is that the way they’re defined is they’re defined to break up the universe between value and growth. So if I were just to say, what does value mean? Well, value would mean I’m hopefully buying things that are priced cheaply versus their intrinsic value.
Corey Hoffstein: But that’s not actually the way that these Russell, S&P, MSCI indices are defined. What they say is, well, if we’re going to break up the world between value and growth, so what they’re going to do is they’re going to rank stocks on both value and growth simultaneously. So growth, they’re going to look at a number of metrics, price-to-value, price intrinsic value measures book value or again, enterprise value-to-sale, something like that.
Corey Hoffstein: Then they’re also going to look at growth measures, revenue growth, earnings growth, internal growth rates, Roe, that sort of stuff. And they’re going to simultaneously rank and they’re going to say value is the stuff that loads very heavily on the value metrics, but very poorly on growth metrics. Right? So think about what you’re buying there in that index. You are buying stuff that is very cheap, but probably cheap for a good reason because it’s not growing.
Corey Hoffstein: Then you go the other side of the scale which is we’re going to buy growth, which is growing very quickly high on the growth metrics but low on the value metrics, which is basically saying, yeah, we’re buying stuff that’s growing a lot, but it’s super expensive. Which you would sort of say like, well that just sounds like fair value then, right? It’s cheap but contracting, growing but expensive, it’s all sort of fair value. But that’s how those original value indices worked.
Corey Hoffstein: So the question of, is that cheap, is a very different question than a lot more of these smart beta products that have come out, more concentrated. And again, I think they keep improving every year where you’re not just looking at simultaneously ranking, you’re just asking on an absolute perspective like is this thing cheap? And if it’s cheap we’re going to include it without any consideration really, or maybe there is some consideration of quality and growth, but it’s not simultaneously split. So you end up with with subtly different answers to the question of is value cheap based on how you’re going to implement value.
Tobias Carlisle: And then the implementation that AQR takes, which is probably using as many signals as possible that are value-related signals, trying to drive it, perhaps more the way that a value investor would do it. In the sense that it’s not enough for it to be cheap on a book value basis, it needs to be generating free cash flows. The cash flows need to be actually turning into cash, piling up on the balance sheet being used to buy back stock. There needs to be some other considerations of health and that helps you perform, but it only helps up to a point.
Tobias Carlisle: One thing from, from Rob Arnott, and I thought Rob Arnott’s paper was very good and when I say it’s very good, it agrees with me, it’s basically my definition of it, And Cliff’s is in the same boat. I guess the question that every value investor wants to know is what drives the underperformance and when does it turn around or what do you look at to see, am I just going insane here buying value stocks when I can just go and buy a Tesla or something else that seems to be growing at a very high rate regardless of the valuation?
Corey Hoffstein: Yeah. What’s really interesting to me is, again, a lot of that actually ties back to how you’re constructing the portfolio. So those value 1.0 indices that I talked about tend to take very heavy sector bets. So you even if you use a composite, a lot of them will use a composite of different value scores, they tend to load very heavily on financials, be very underweight technology. So you can actually track the value premium over time by just looking at technology minus financials or financials minus technology. I think you had Lawrence Hamtil on the podcast a little while back.
Tobias Carlisle: Right.
Corey Hoffstein: I know this is an area that he has explored really in depth, right? But if you were to look at a more sector or industry neutral implementation of value, that would no longer be the case. You wouldn’t be having this big sector bet that’s driving the premium. So what makes this sort of era, this particular point in time, unique is it’s okay, I can accept that value underperformed technology for the last decade and that’s why value 1.0 indices have stopped working.
Corey Hoffstein: But when you start looking at someone like an AQR or a QMA who tends to neutralize those industry and sector bets and look at cross-industry valuations, well this now seems like a… situation. Because a lot of what the evidence shows is that these valuations, relative valuations between growth and value, are at historical highs. Not all time highs, right? This is not 2000.
Corey Hoffstein: But when you look at price-to-book, enterprise value-to-sales, price-to-earnings, forward earnings especially, you see that the love for value has definitely dissipated and those relative ratios of those fundamental measures are at decade highs. They’re not as high as some prior dislocations, but they certainly are cheaper today, at least on a relative perspective than they were five, six, seven years ago.
Corey Hoffstein: And it’s accelerated in the last year, so I think there’s certainly an argument that this is no longer just a sector issue, that this looks a lot more like a risk appetite issue that investors have just said, “we’re done with this.” And I think what’s really interesting about that in particular, I did this study, I not only looked at these relative ratios to say, well, how cheap is it versus growth? How cheap is it versus the market?
Corey Hoffstein: But I wanted to look on an absolute basis and say, well, how much are we going to get paid to hold this trade? If I’m going to buy value, assuming prices don’t change, is there a good carry argument? So I tried to back out the shareholder yield expectations and that’s another area where you see shareholder yield for value has accelerated versus growth over the last couple of years. So I think on a relative basis, you can at least say the attractiveness of what you’re going to get paid for making this trade is a lot higher today than it was five, six, seven years ago.
Tobias Carlisle: One of the great points that Cliff makes in his is that while we might not be at 2000-type extremes yet, there really aren’t any other analogs out there. So you’re either proceeding onto a 2000 extreme at this point or we’re turning around and it’s becoming a more normal environment for value where there is some sort of premium for holding value stocks. What do you think about that?
Corey Hoffstein: Yeah, I mean, I think the interesting thing about the market is the unexpected can always happen. So would we bet on another 2000 occurring? Well it’s still close enough in the rear view mirror that I think people are aware of it and are hyperaware of valuations. But on the other hand, at a certain point after a decade of growth just working, you can start to see the appetite for growth continuing. So I think there is an opportunity for this to potentially continue to extend.
Sin A Little
Corey Hoffstein: I think Cliff has always been very proactive in saying tactical timing can work, but it’s not necessarily an all-in or all-out decision.
Tobias Carlisle: Sin a little.
Corey Hoffstein: Right, sin a little. So if you’re going to start doing this trade, I think it can make sense to leg into it slowly. You can also dollar cost average into it. It doesn’t have to be an all-in or all-out decision, which is more of a market timing decision, right? You can say, hey, as value stays cheap, if I’ve got a blend of growth and value, I’m going to tilt every month another percent or two towards value and as long as it’s staying cheap, I’m going to do that.
Corey Hoffstein: And then if it reverts, great, you can take the trade off. So that way you’re not getting into trouble putting it on today and it underperforms for another three years. You can sort of build that position over time. And especially as it gets more extreme, you can keep building that position. So I think there’s opportunities for a little bit of craftsmanship and the implementation of taking a little bit of a tactical bet, if people feel like value is truly oversold at this point.
Tobias Carlisle: That’s a spooky thought, Corey. You’re making me think that it’s Halloween telling me that value’s going to underperform for another three years.
Corey Hoffstein: Anything’s possible, my friend.
Tobias Carlisle: Value was getting pretty stretched, I thought by May, June, July last year. And then I think 827 was the various different metrics that I look at that was about as wide as it got. And then it did start closing up, value started outperforming a little bit overgrowth or glamor, or however you want to describe it, until September 9, which was the best day for value since 2000 basically and then the worst day for momentum since an equivalent date. Followed by September 10, which was not quite the same Five or Six Sigma event. It did seem to sort of outperform through the end of last year, the last quarter and a bit of last year.
Is Momentum Set For A Comeback?
Tobias Carlisle: But then we’ve had this January, it turns out, we haven’t seen the end of January yet, but we’re close to it. I saw somebody on Twitter yesterday said this is the best month for momentum since the beginning of the millennium. And it’s good to see those momentum guys, we might never again. Do you think that when you see something like that, does that mean the momentum trades back on, that kind of volatility towards momentum?
Corey Hoffstein: You know, what’s really interesting about the momentum trade is it is a complete chameleon trade, right? The turnover in a purely implemented momentum portfolio. So maybe not the ETFs you might buy, but the true sort of quant active definition is going to be so high that momentum can look like all quality stocks one day, all low-vol stocks, it could be defensive, it could go high beta, it could go plow and devalue.
Corey Hoffstein: So I think at least what’s interesting to me is looking at sort of those changing correlations between what does momentum look like. You could actually look at the underlying holdings overlap, which is always telling. But you can also look at sort of what is it tilting into. And so this idea of momentum being either implemented as a pure factor, trying to isolate it from all the other exposures it had or thinking about it as a chameleon factor. It allows momentum to sort of potentially continue to persist.
Corey Hoffstein: It’s always interesting when things hit extremes. New extremes are particularly interesting, but I’m always hesitant to ever fade anything. Again, I’ll defer to Cliff, who any smart thought I’ve had he’s had 20 years prior and vocalized it for a lot longer. I think he said it’s always at the 150th percentile that you want to start taking action, which is sort of a quant joke, because it stops at a hundred.
Tobias Carlisle: Right.
Corey Hoffstein: But the point being just because something makes a new extreme, things can always get more extreme. So I think where things will get particularly interesting for value is when you start to see the momentum trade start to correlate with value. And so if you start to see value get some legs, then what could really create a tailwind behind not just multiple compression and reversion, multiple reversion, and not just the tailwinds of higher shareholder yield from earning that trade, but getting momentum, could really accelerate that and continue that trend a lot longer and it sort of becomes a self fulfilling prophecy.
Tobias Carlisle: Yeah, that’s interesting. I’d never thought about that like that before. What’s momentum loading on now? Do you have any sense of that?
Corey Hoffstein: So I’m not sure what it’s loading on positively. Over the last decade, what’s been really interesting is the negative leg of momentum. So if we think of what you buy is the stuff that’s been outperforming, what you avoid is the stuff that’s underperforming. The negative leg has been really heavily correlated to high beta stocks. So risky stocks. And the argument there has basically been, the market was so afraid of post-2000, so afraid post-2008 that anything that looks slightly risky, people were just getting rid of. And then once it started to sell off, well that just made it riskier and people would get out of it and faster. So there’s been this huge correlation on the negative side that high beta and low momentum had been highly, highly correlated post-2008.
Corey Hoffstein: On the positive side of the trade, you have seen it sort of oscillate, but more recently, at least in the last year, it’s been heavily correlated with low vol. The overlap, what’s interesting is the holdings overlap hasn’t necessarily been there, but from an actual performance perspective, looking at the residuals of those factors, they’ve been pretty decently correlated.
Are Different Factors Creeping Into The Value Basket?
Corey Hoffstein: So Toby, because I run my own podcast I’m going to take over here and I flip the script on you. So let me ask you this, because I know you run a number of value portfolios and I know you run some long/short portfolios as well. As you’re looking for opportunities and screening opportunities, how has that composition changed? I mean, have you noticed loadings from different factors sort of creeping into the value basket or creeping into sort of your short basket?
Tobias Carlisle: Yeah, I tend to be unconstrained, so I don’t take the equal weight implementation just because I think that there is some additional alpha in weighting towards sectors. There are no free lunches, the quid pro quo for that is that it can extend the underperformance. But the things that I have noticed, so on a sector basis, I lean more heavily towards financials on the long side. And then the short side tends to be names that have… I would call it a calorie list growth. While the revenue line might be quite robust, it doesn’t seem to fall through into the flows, the balance sheet looks terrible, the cash flows are highly negative and it’s not necessarily growth cash flow. It’s just not flowing through from the revenues.
Tobias Carlisle: So I make a distinction between a high-growth company. A high-growth company will grow at a negative cashflow because they’re reinvesting, they’ve got financing cash flows, they’ve got reinvestment cash flows that are negative to build the next asset that you’re going to get the next bit of growth out of your investing in, that’s negative cashflow. I’m not looking at that sort of thing.
Tobias Carlisle: I hate to bash Tesla all the time, but Tesla I think is something like the poster child for it, where the top line does seem to be reasonably healthy. I think there are some questions about how some of the top line is being achieved. The revenue line, the growth is great but the cash flows and the earnings, if anything, they’d become worse every time more cars are sold and at some stage it has to be something other than a metal bender to achieve that. So it sort of looks more like a software as a service type business.
Tobias Carlisle: The portfolio as a whole though, it looks it’s a little bit the reverse of your momentum observation in the sense that the value stuff tends to be higher beta at the moment, which is unusual and it’s not something that I’ve seen a lot of before. It has tended to be lower beta stocks through most of my career, but for the last few years there have been higher beta names and they certainly behave that way too. Once they’re in the portfolio, they continue to exhibit those properties up and down. Although, there’s a lot more down than up.
Corey Hoffstein: Is it high beta in that the… security itself or is there sort of a high amount of volatility in the underlying fundamentals too?
Tobias Carlisle: No, it tends to be… Well, it’s a little bit of both. There are some cyclical names in there that do have some. I don’t think you’d measure it necessarily as beta because the cycle is longer. The cycle is not quarter to quarter, the cycle is two or three or four or five years. And the question is can these companies continue to earn what seemed to be very good earnings?
Tobias Carlisle: But no, it’s security beta, it’s security price’s beta. So they just seem to be more volatile. And some of them I don’t really understand why they’re so volatile relative to the underlying fundamentals, because the fundamentals seem to be pretty consistent. It’s more investor expectations about what every every quarterly print sort of means for the business. And it’s a violent move up and down.
Tobias Carlisle: I don’t really understand why. In some senses, I don’t really want to try and figure it out because I think sometimes that can be a little bit misleading. You decide on some answer for why something is behaving the way that it is and then it’s just not right and you’re continually clouded by that thought. I don’t want to bash on Tesla because it’s entirely possible that Tesla is something that I would roll out of and not really think about one way or the other.
Corey Hoffstein: Well Tesla is sort of an interesting one and it’s fun to talk about it. I’ve got no position in Tesla, no view on Tesla. But you can sort of look at stocks in a couple of ways. You can say, hey, this is the present value of all future cash flows, right? And Tesla, I think people sort of look at in a very binary nature, this thing is a fraud that’s going to zero, in which case the price of the security is zero or you’ve got something that’s going to be world-changing. Not a lot of people are in the middle, right? And so when you have two groups fighting, that should a lot of volatility.
Corey Hoffstein: Then you’ve got this other idea of a stock is ultimately, at the end of the day, the equity value of a company is a call option on the assets, or the debt holders that have been paid.
Tobias Carlisle: Right.
Corey Hoffstein: Well you would then say if assets have a high degree of volatility to them or the forecaster assets, well then you would expect that the option should have a high value.
Tobias Carlisle: Right.
Corey Hoffstein: Right? Because you’re floored at, okay, you can only lose 100% but you can make an infinite amount. So that call option gets more valuable. So if you say, hey, Tesla has a lot of intrinsic volatility to the business, well then the price of the security should go up, which is sort of an interesting way to think about it.
Corey Hoffstein: And then the third, which I know people try to quantify this, I’d be curious if you’ve looked at this, but you start to look at the actual market impact of participants and things like short squeezes.
Tobias Carlisle: Sure.
Corey Hoffstein: Which we should say, hey, in an efficient market, none of this should really happen. But we know efficient markets require a set of assumptions that aren’t realistic. I mean, you end up in scenarios where the shorts might be right, but they can be squeezed to death and you can see this balloon inflate way further than people can ultimately stay on. So it makes it difficult to arbitrage the price to the right point. Right? Especially when you have such rabid disagreement. I mean do you have any idea what the borrow is on Tesla recently?
Tesla Is A Living Example Of Soros’ Theory Of Reflexivity
Tobias Carlisle: It’s come down because that price section which has been so aggressively positive has just meant that the short interest has come down commensurately, so it’s actually pretty reasonable at the moment. I think Tesla is a living example of Soros’ theory of reflexivity.
Corey Hoffstein: Absolutely.
Tobias Carlisle: And it’s a really funny one too because I don’t know if you’ll recall Josh Brown last year said something like, Tesla’s a better short at, I think it was 299 rather than 399 roughly, I forget the exact numbers. I 100 percent agreed with him on the way down. And the reason is it got down to around $200. It is still a metal bender, it does still need money to build cars and factories for them to grow.
Tobias Carlisle: Their growth isn’t costless, it’s not a software it’s a service business that has marginal growth of virtually zero costs. They have to build factories and factories are expensive. So they have to find the money, do a big capital raising at $200 stock, you get diluted and you’re in a little bit of trouble there. Now that it’s at wherever it is now, I wouldn’t want to guess because I’d be 10% behind where it is. $600 or $700 or something like that.
Corey Hoffstein: Yeah, I was going to say, I haven’t checked, but they blew through the $420 funding secured, right.
Tobias Carlisle: Blew through. It went through 500, so I don’t even know where it is. It could be $600 or $700. But now it is actually a better long because they could do a very serious capital raise at this level.
Corey Hoffstein: Right.
Tobias Carlisle: I used to give that as this is the path not taken, a different future, where instead of tweeting “the funding’s secured at $420,” Musk goes and says… Takes whatever the $5 billion that seems to have been genuinely offered at some stage and just does a little capital raise at a $60 billion valuation. That’s an entirely different story.
Tobias Carlisle: As it turns out, it doesn’t matter because he has well and truly blasted through that number.
Corey Hoffstein: Yeah. Well, the counter argument to your point though is that yes, it dilutes the Tesla shareholders, but there may be people more willing to participate in a raise at $200 than at the valuations today because they are getting a poor deal.
Corey Hoffstein: So the dynamics of a market always make these things so difficult, but it’s such a fascinating stock to watch just for the sheer fun. It’s like watching a sporting event.
Tobias Carlisle: You remember the Volkswagen squeeze? It’s in that kind of a realm. I don’t know what’s driving it now. It’s beyond my comprehension, I have no idea. So I think it’s a short squeeze. It’s one of those, once they get some momentum folks who are just looking at the price trajectory and ignoring the fundamentals and saying this is something that does have very serious upward price momentum. And so maybe you’d buy this and if you look ahead periods only a month or so, that’s probably a good trait. I don’t know.
Corey Hoffstein: Yeah. And I’d be interested to see as it starts to raise market cap, lose market cap, what that does for index deletions, additions, where it falls, what sort of capital ends up just getting placed into it because of that situation.
Corey Hoffstein: I mean, a perfect example was our friend, Jake, pointed out, what was it, Beyond or Impossible. I think it was Beyond got included in a whole bunch of value portfolios.
Tobias Carlisle: Right.
Corey Hoffstein: Which clearly not a value stock, but just the way these things are are systematically defined. And I know very few people go read the index documents and I do go through them, but if you’re missing certain metrics, you get assigned the median a lot of times in the universe.
Tobias Carlisle: Of your sub-sector, industry sector, that’s right.
Corey Hoffstein: So it made Beyond look like a value stock.
Tobias Carlisle: The food.
Corey Hoffstein: It’s interesting to think about how there can be some systematic flows that occur for all the wrong reasons. And then once you get included in there and then there’s all the biweekly deposits that go into retirement accounts that can just strategically buffer.
Tobias Carlisle: Right.
Corey Hoffstein: To me, there’s some interesting structural effects that can occur, especially with systematic strategies that may be well-defined at a stylistic level, but poorly defined at a very specific security level.
Tobias Carlisle: Right. Exactly. I couldn’t agree more at that execution level is… And that’s one of the things that I’ve learned, particularly from you and from the ReSolve guys, is that there’s a massive difference between the explanation of even very broadly value or momentum or something like that. And then at the implementation level, there’s such a vast difference between the performance. Even your paper on timing luck I think was excellent.
Corey Hoffstein: Right.
Tobias Carlisle: It’s something that if you do enough back tests, it’s something that you see. But it’s something that I’d never really focused on before until you wrote that paper or until we discussed it. It’s just the difference between, so if you rebalance and you capture that March 2009 low, if you don’t rebalance around that data, if you even wait, I think it was the September rebalance might’ve been the worst ones.
Corey Hoffstein: August, September. Yeah.
Tobias Carlisle: You missed that huge opportunity for that rebound. Right? You just didn’t reallocate back into equities from an asset allocation perspective. It really changed. I know one of the original papers written by Blitz and van Vliet, and I’m blanking on the third author’s name from Robeco, they looked at the Research Affiliates methodology. And the sector loadings that they saw for the different rebalanced states were so different.
Tobias Carlisle: I think it was right post-2009 that March rebalance, they would have loaded heavily into financials and if they had waited another three months, it was a totally different sector allocation, which yeah, you start saying, okay, your choice of… really does, especially in these markets where security valuations are changing in relative rank very, very quickly. You can end up with a totally different portfolio composition, especially if you’re building it systematically and you’re not building in all these constraints or ways to address these problems that lead to totally divergent outcomes.
Tobias Carlisle: I couldn’t agree more. I think we’re coming up on time now, Corey. So a few things that folks should go and listen. I love your blog. I think it’s blog.newfound.
Corey Hoffstein Yeah, blog.thinknewfound.com or people can just search for the phrase Flirting with Models, which I can’t say without laughing.
Tobias Carlisle: You got some pushback from iTunes when you tried to get the… They saw your picture and they said, this guy’s surely flirting with models.
Corey Hoffstein: There’s a lot of disappointed reviewers, I’ll just leave it at that. Quant podcasts was not what they were expecting.
Corey Hoffstein: That’s great. But yeah, blog is there and then you can also go to the podcasts searching the same phrase.
Tobias Carlisle: And your Twitter account is excellent too. What’s your handle there?
Corey Hoffstein: Thank you. Twitter account is @choffstein.
Tobias Carlisle: Choffstein. So folks want to see the Robust Equity Momentum Index, just one more time that link, I’ll put this all in the show notes.
Corey Hoffstein: Yep. So they can go to thinknewfound.com/NRROMOT and that’ll take them right to the NRROMOT index page.
Tobias Carlisle: Perfect. That’s great. Corey Hoffstein, thank you very much.
Corey Hoffstein: Thanks for having me on again, Toby. Really enjoyed chatting.
Tobias Carlisle: Absolutely.
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