Hello, and welcome to another episode of the Odd Lots Podcast. I'm Joe Wisn't Thal and I'm Tracy Hallaway. Tracy, you know, one of the things that we discussed a fair number of times but also maybe before. It's just sort of the I guess you would say permanent state of crisis that you might call it in so called value investors. Yes, it's been. It's certainly been a long running theme, hasn't it. And I feel like we've done quite a few episodes on it at this point, but didn't exactly turn things around for value investors either. No, definitely not. And I think, like you know, there's really two strands that tend to emerge in our conversations, and I would characterize them is this one is that there is some like cyclical element to value investing in this cycle, it just hasn't turned around yet. So it's like we have this sort of long multiple expansion. It's kind of low growth fed driven economy that sort of creates this permanent bid for growth companies at the expensive value week GDP growth, etcetera. Just like certain industries aren't going to thrive in that environment. And then I would say the other half is that no, the problem is that we are not good at defining value in their people sort of take a more accounting approach and say traditional measures of the stocks cheapness, like say price to book value. It just these measures don't work in a world where so much value is intangible. Right. This is the idea that as companies, well the sort of successful companies nowadays, are investing a lot, they're investing a lot in things like their brands and other intangible assets that just aren't captured by price to book value. And so a company that's positioning itself for a really good future performance might not actually look that way if you're just glancing at, you know, something like price to book you know, like it's sort of a joke, and I think we've talked about it with Michael Mobison last year Jared Witdard. But it's like you can rescue value investing if you call Netflix of value stock, or if you call Facebook a value stode, and someone would say, Okay, these companies don't have like big like factories that can easily be measured. But if you could somehow like put a number on the value of the Facebook network as an asset, then you couldn't, then you could theoretically imagine a world in which had some traditional value screen Facebook comes up right. I mean, the thing that still makes me uncomfortable about value stocks is that you're you're still investing in something on the basis that the market has some how mischaracterized its future, which I think you touched on this with with your two narratives. But I think in the current environment, where we talk a lot a lot about flows based investing, a lot of momentum trading things like that, it feels like the market is quite consistently directing capital to you know, a few firms, and then it just keeps doing that and those firms get overvalued and overvalued and overvalued. And if you're not in that cycle, I don't know. I just feel like it's unlikely that you're going to get back in it. And the longer it takes you to get in, the more you're sort of losing out in terms of valuations. But anyway, sorry, I'm going on a tangent. No, No, it's great, And I mean, and the other thing, and I think it's sort of related to your point, is you know, it's nice to say like, okay, like there's some intangible value that we if we could only measure it at Netflix or Facebook or whatever it is, but it seems hard to know in advance that is there. And so it's like, okay, if you have some like factory, then you can at least say, okay, this exists, and historically speaking, it will uh, you know, we would project it over the next ten years. It's going to throw up this cash and that's a good value. It feels like with a lot of these sort of like backing into the value approach that it's very much easier to say in retrospect or expose factor, oh, this turned out to be a very valuable asset that they have, which is sort of nice, I guess from maybe an intellectual standpoint, but it doesn't really help you like pick stocks today, which is what people to really care about these discussions. It's great to say, Okay, the Facebook network is worth a lot of money, but you know, I wish you had told me that six years ago. No, but it does help a lot of different investment companies come up with different strategies and factors to come up with different definitions of value that always work when they're back tested against historical data. Right. So I guess the question is that sarcasm. I don't know my sarcasm is coming through on the podcast, but I got it crazy. But I guess the thing we're looking for is the approach that works in advance, that's not just back tested and some you know, some approach that can help us identify the sort of deeply under a company intervalue companies today using some something whether it's a metric, whether it's a screen, whether it's some other intangible measure, something that doesn't just help us rationalize the past, but can you know, help help me retire a few years earlier. Yeah, and also maybe even explain why value investing as it's you know, commonly understood has performed so badly for so long. Absolutely all right, So I'm very excited. We're going to be speaking with someone today who may be able to help move this forward, whose work consists of sort of solving this problem. An investor, so obviously someone who wants to do more than just explain the past but produce good returns going forward. We're going to be speaking with Rafael Rassindez. He is the co founder of Applied Finance Capital Management, which has looked at some of these problems and try to identify where the traditional and value investing framework has gone wrong. So, Rafael, thank you very much for joining us. Great to be here. So I'm curious, I mean, uh, you know, I always like to look for validation after our introest But that general framework of sort of the two stories that people tell about value investing, how does that comport with how you see the world right now and how you see this sort of ongoing debate. Great, great question. So as you, as you know through some of our exchanges, applied finance focuses on valuation. I think to some degree the term value has been hijacked historically with with the advent of the release of the FAMA French three factor model back in ninety two and the creation of this quote value factor, otherwise known as the book to price ratio. I think the term value has really been hijacked because book to price, at the end of the day, is really nothing more than a cheapness metric, as are all the price to something measures. It's measuring the price of a stock in relation to some fundamental variable, whatever that variable is, or even composites of that variable. But it doesn't necessarily relate to the worth of a stock, and I think that fundamentally is where things have really tended to diverge or go off the rails to some degree. In investing finance, the focus has been on cheapness, and there hasn't been enough attention paid to understanding intrinsic value through more complete valuation approaches, which is what we've specialized in since n SO Applied finance has been in existence since nineteen ninety five. But we were chatting before we started recording the podcast, and you mentioned that your current area of focus is something that grabbed your interest because of a big debate that was happening in the nineties seventies. Could you maybe explain that a little bit? Sure? Sure, so, let me just provide a little historic background on how we are where we are today. If you think about how finance has evolved, you know, in the sixties you had a lot of theoretical work on the CAPTEM model, which was really exciting, and then in the early seventies you started to see this basically this brand new field of finance created by Eugene Fama, which is empirical finance, and he did amazing work testing and kind of formulating the efficient market hypothesis and ushering a whole new era of scientific method applied to finance, so to speak. And I think prior to that, for the most part, university level finance focused on net present value and a lot of security analysis. And in a great paper that Farmer wrote, I believe it's titled you know, My Memories and Finance, or something to that extent, he essentially says, you know, when I arrived at Chicago, finance consisted of classes essentially teaching people to pick stocks, and in in an efficient market world, there's not a lot of value to having so many people specialized in that. And what we saw in the seventies was this birth of mean variance finance, where computer methods and data availability allowed for incredible study of properties of stock prices, testing of hypotheses of you know, a lot of the mainstream thoughts back then we're biased stock just because it's going up. So a lot of efficient market tests focused on momentum investing, which is kind of ironic given the crave of momentum investing now you know, thirty years later, fifty years later, um. And ultimately it drove security analysis to a large degree out of finance, and you see a lot of security analysis of courses now being taught in accounting departments. And what we tried to do had applied finance when we started in was essentially try to link this notion of mean variance finance and security analysis. And we did that through systematically constructing security analysis rules to process data on companies and then ultimately linking that the output of that those reformulated income statements and balance sheets from accounting data into more of an economic framework through the calculation of an economic margin, which essentially is a firm's return on investment less it's cost a capital. We linked that with expected capital growth, risk, and competition to value a company. And so we did this work from the seventies to ninety five, kind of a twenty five year what I'll call an observation window. And I think, Tracy, going back to one of your statements you made earlier about back testing, it'd be fun to get into that. It'll a little bit more depth later, but so I'll call it an observation window rather than an evidence window. I think there's a big distinction between the two. And beginning in nineteen we began calculating intrinsic value estimates. First for US companies on an ad hoc basis, i'd say monthly and quarterly. When we were early on in our company development, we were doing a lot of corporate consulting work. We didn't have the full uh infrastructure of personnel to handle calculating what i'll call productions of intrinsic value consistently. By the company had grown, and we began calculating these intrinsic values monthly, and from through today we continue doing that. Now we do it globally on twenty thousand companies every week. But what's interesting is back test observations versus evidence. Since ninety eight, these have all been live out of sample estimates of intrinsic value. And I think one of the one of the interesting things about our data set and what we used to prepare this paper called Valuation Beta, is that a lot of finances, well, let's go back to nineteen sixty three, and someone will say no, let's go back to nineteen thirty and someone will say no, I have a data series going back to the seventeen hundreds. Well, at some point this data is really irrelevant because the world has changed so much. Maybe there are these quote fundamental truths, but if you look at the factor work. Oftentimes these factors are discovered in a back test setting and then when they go live they don't work. And certainly that's been an important part of the experience with Book to Price since it's had prior to ninety two. From six to ninety one, it was basically a money making machine. The return attributes of that variable or extraordinary. Since ninety two it's had a much more spotty record, and the same as as if we dig down a little deeper on some of these other factor metrics, such as the profitability factor, the investment factor. Since they were really Eastern publicly, they've had a spotty or record as well. So I think it's important, as you said, to differentiate between back testing, which is when you're kind of formulating your your ideas, versus evidence, which happens after you've released your ideas and you you let the let the world run. As Mike Tyson likes to say, everyone has a plan to you're punched in the face, and for Book to Price and value investing, that punch in the face has happened over the last decade when it basically hasn't worked. H So you make this distinction between value valuation versus cheapness, and as you characterize that measures of price to book or really any other sort of ratio based valuation, it's not to measure of value per se, it's just a measure of cheapness. So can you explain a little bit further, like what the differences between what your measure of valuation and cheapness and why it is in your view that some of these traditional metrics measures of cheapness that at one point did produce returns have failed to do. So let me focus first on explaining our worldview and kind of how we get we get to an answer. And there's there's probably lots of reasons to speculate about why something doesn't work, but I'll offer our view of it as well. So, first, as opposed to beginning with some metric of cheapness, what we begin our discussion with is an estimate of intrinsic value. So how do we go from accounting data to an estimate of affirms intrinsic values. So we begin we process the data, and there's a lot of around the world, there's a lot of accounting issues that we've dealt with and tried to incorporate so dramatically in our analysis, but I'll just talk about a few that I think make for for a quick, interesting discussion. Since since the beginning of our of our company, we've viewed research and development as an investment rather than an expense. So since we've capitalized R and D, and our view is this is a piece of operations based cash flow the company is generating currently. Another item is the use of operating leases. You know, the accountants historically have treated that as an expense rather than anything having to do with the balance sheet. Systematically, in the last couple of years, fast he has kind of come around to our view of thinking and as required companies to start capitalizing operating leases. We want to view companies on a on a capital structure free basis. So we're going to add back interest expense on an after tax basis, We're going to make adjustments to the balance sheet for inflation. It sounds a little silly now, and certainly is silly for technology companies that have very little physical plant, but for industrial firms that have assets on their books that they acquired in the seventies, inflation is a big deal because it's easy to have inflated return on investments because the balance sheets reflecting historic cost the income is respecting is displaying current values, current dollars values. So there's a litany of adjustments we go through. We do all that, and one last thing that we we account for is how long the company's assets last on average to get an asset life. So then we can configure a firm as a project and we can calculate what we call an economic margin. We don't have to get into all the geek speak on that, but essentially, at the end of the day, what we end up with is a corrected return on investment on an inflation adjusted asset based minus acost of capital. That spread or economic margin, starts to tell us a lot of things about the company. First of all, if you have an economic margin that's negative, it tells you the firm is investing in projects below its cost of capital. So the last thing we'd want to see a firm like that do is grow its business. That's what we call wealth destroyers, and it's it's a very key piece of how we think about analyzing companies and what they're doing. If you have a negative spread to your cost of capital. You should be shrinking your business or rationalizing what you have to figure out how to at least get to a zero spread. Companies that have a positive spread, and again this is after accounting for things such as investments in R and D off, balance sheet releases, on and so on. Companies that have a positive spread should grow. And I think Joe in one of your tweets a while back that that initiated our discussions, you asked a question about Monster, and you said, can anyone explain Monster to us? The Monster story is pretty simple. This is a firm that some people know. This is the the energy drink maker with lots of caffeine, that's the best performing stock. Go on, I just wanted to, uh, just for people who are great, great, it's been an incredible wealth compounding company through the years. It's not a it's not a recent thing. You know. This is a firm that's earning ten to fift percent returns above its cost of capital and has been growing its capital based at double digits. So you have This is a classic example of what we call a wealth creator, a compound wealth creator generally reinvesting in high rates of return, creating more and more wealth for the existing shareholders, and the company continues growing into its valuation. I think we sent you a chart that traces out our estimate of Monsters intrinsic value through time, and again these are basically live estimates going back. This is in this case going back to ten years at least, but it traced out our intrinsic value for Monster relative to its traded price. And what's interesting is this thought consistently was trading at or below its intrinsic value, and even recently with the big runs it has, it's not grotesquely overvalued from our perspective, which is what what leads to the tension between the way we view the world from an intrinsic value perspective. Intrinsic values of function of this level of economic profitability how much you're able to reinvest in the business to create more economic profits. Then we discount that back to reflect the firm's risk based on its size and its leverage characteristics. And then lastly we incorporate an overlay. And this is where we diverge quite a bit from traditional DCF methods that say, okay, we're gonna go out five, six, seven years, and then put a terminal value or used to Gordon growth model to assume that the rest of the world is kind of static. We're going to capitalize everything back via perpetuity. We think that's kind of a crazy assumption, and you can just talk to kmart about how valid the world being constant is. And we apply what we call an economic profit horizon, which, again based on the research we did, we assign every firm a factor based on fundamental characteristics that say, how long will this economic profit persist? How long can we expect this firm to have an economic margin greater than zero. Because once the margin, once your returnees, the cost of capital just present value. Math says from that point forward growth is irrelevant because the net present value of future growth of zero. So all of that a lot of different complicated concepts going on at once behind each level, but at its most basic, we're basically we're saying, let's figure out what the true economic return of a firm is. Let's get a handle on how much it's reinvesting in itself. Let's let's get some idea on how risky these cash flows are, so that from a from an a risk adjusted basis, we can compare companies on an apples to Apple's perspective. And then let's say companies are not going to earn economic profits forever because of competition, so we combine those to get an estimate for intrinsic value for twenty companies around the world every week. That becomes the basis for us looking at the world and then sorting out portfolios of companies and Dubai's into cells or creating, you know, slicing and dicing that to create subsets of products for our clients. What do the tech stocks look like under that framework? You know, things like an Apple or Facebook or a Netflix. I think it's always useful when we're talking about differences in how we're measuring intrinsic value to actually speak about concrete examples. And the Monster one was a great example just then. But I'm thinking something like Apple, you have a lot of profits, a lot of investment of very low cost of capital. Does it look good in your method of intrinsic value? Let me go back a little bit in time as well. Uh, and again not in the context of a back test or observation, but in context of kind of our our main strategy portfolio. If we go back to eleven, and this is this is an example that week. We presented to some clients the other day because they're kind of asking the same type of question. In eleven, we purchased three. This is a very low turnover portfolio averages less than ten percent turnover a year. But in twenty eleven we made three purchases in the tech space, Alphabet and Vidia and master Card. Okay, at the time, they were trading on a multiple basis well above the market median, and from a multiple perspective, those multiples only grew more and more expensive relative to the market through time. I think we added Apple to the portfolio. Uh five years ago. I think we added Facebook to the portfolio. So we own all of those stocks and they've all been attractive to us from an intrinsic value perspective. In Video, we bought in twenty eleven and thirteen dollars a share I think in eighteen or at the end of the year crashed from three hundred to one fifty. People thought we were nuts to have owned it at three hundred. I remember having a conversation with a with a really prominent journalist and he's like, you guys are crazy. How can you call that a stock that's undervalued at one fifty after the crash, We're like, we believe it's undervalue, We're gonna own it, and then we just sold that this past August at We continue to own Google, Apple, Facebook, MasterCard, um at the same time, we own what you consider to be some classic value stocks. We own Intel, we own Hewlett Packard, We own Financials, which is a big chunk of the of the value universe, so its valuation. This whole dichotomy of value versus growth is really a false way to think about firms, because every firm is growing, whether it's positive or negative. There's growth taking place for every firm. And you know Warren Buffett obviously super successful, wise guy. Everything is a function of what you're paying for in the market. Please, you can have all the stocks that represent an incredible investment opportunity just as easily as you can have a stock like Monster represent an incredible investment opportunity. It really is a function value. Ultimately, true value becomes the intersection of economic profitability, growth, competition, and risk. The attractiveness of that is a function of what the market's paying for or how psychotic the market is at a point in time for any of these stocks. Does that make sense? Yeah, I mean talk to us further like expanded, pick a pick a name, like okay, in video, you tell the story you got it super cheap, it's soared. It had that brief crash, I remember that, but then it climbed back up in an extraordinary like walk is through like what did you see? What year did you say you first bought it? Okay, So now everyone knows the narrative around and video and video games and AI and automotive chips and stuff like that, Like what was it at that you saw and were able to identify as a you know, it's so great perspective. So in video was basically a graphics chip producer, right, And this is an interesting view of how the world is continually changing around companies and around data. A graphics chip producer that we thought was very attractively priced relative to its underlying fundamentals. And then over time it started to evolve and the at that early in the early stages that we owned it, it was it continued to be a graphics chip producer designer, if you will, because a lot of a lot of these chip makers are fabulous now they don't produce but a graphics chip designer, and that continued to grow and evolve, and then all of a sudden, we started to get little indicators of AI and technology continued blossoming in the story. AI story became sting for us. The reason we were able to stay with it is because as much as it was increasing in value because of AI, the company was continually delivering on its investments. And even without our analysts modeling the company, the company continued to look attractive with our systematic valuations that we do for every stock, so just on pure as reported data converted into our economic margin framework and then an intrinsic value, the company was very attractive for years and years and years and years. And it wasn't until that these stocks exploded so much after that march to client that we painful. We had to part ways. You know, we prefer to never sell a company a lot of our turnovers because these companies get acquired, which is which is kind of like a happy and sorrowful moment for us, because we own them. For a reason, we only owned fifty stocks in this portfolio, and we own across all the sectors, and we're jealous when someone buy the stock out below our estimate of it's an intrinsic value. It's nice to get the immediate buzz for performance, but it really is is kind of annoying that that someone's getting such a good deal on our back on that note, I'm trying to think how to phrase this question. But I guess if you identify a stock that you think is undervalued in some way, does that signal something about the company, something sort of fundamental to the company, that it will perform well in the future, or is your measure of intrinsic value maybe correlated with something else going on in the market, like a much larger factor. I guess I'm trying to get to the flows argument um that we briefly talked about in the intro. Does any of that make sense? It does? And let me take your correlated comment and if I may, let me go off on a tangent just for a moment, and then we can circle back if if, if, if, the conversation returns there, and I'm sure it will. But I think the question you're getting at is fundamentally, is intrinsic value a causal variable or is it a correlated variable with a much larger set of phenomenon. Right, Yes, thank you. You put it much better than I did. No, not at all, Not at all. The only reason I framed it so so quickly is because we think about that all the time, and I think it's particularly relevant with respect to the cheapness literature. And if if you were to think about taking book to price portfolios and intrinsic value portfolios, right, and if you were to form groupings of them, say the top thirty most undervalued companies, the bottom most overvalued companies, and do the same thing with a book to price portfolio, and then you have the middle, the middle forty, which is some mix of fairly valued, somewhat overvalued, somewhat undervalued. We can kind of test to see what is driving what by decomposing and deconstructing these returns. And if you take that approach and you look at book to price, we only are looking at data that's live for us. We're not looking at at any simulated data or data that we were creating to kind of calibrate our estimates of risk or estimates of of economic profit horizon, only looking at data that we've produced live consistently on a monthly basis. So going back to if you look at book to price based stocks and intrinsic value based stocks, I would argue that book to price is not on a one three five tenure losing street. Book to price since has added zero to the investing world. And I say that because if you take a look at those attractive book to price stocks and you separate out the ones that are supported by intrinsic value. In other words, those are also attractive intrinsic value stocks, the resulting set of book to price stocks generate negative alpha. And that's not again, that's not a one three five year window, that's a twenty two year window. Book to price, if it's not supported by intrinsic value, generates new alpha. So then the flip question becomes, okay, well intrinsic value then, and a lot of people will say, well, no one can trade short against us. No one's going to short the high multiple stocks against a value strategy, And that's not really true. If you look at high multiple book to value stocks that are undervalued, they generate significant positive alpha. And so to me, the birth of book to price is the result of confusing correlation and causality. Book to price has done extraordinarily well. When when that section of stocks correlated with intrinsic value do really well and outperform the market and carry everyone else along, but by itself unsupported. If you strip out the support of intrinsic value, the meaning subset of attractive book to price stocks generate negative alpha, and the absolute flip happens on the unattractive book to price stocks. The only ones with negative alpha are those that are really overvalued. The fairly or undervalued high multiple stocks generate positive alpha. So this notion of correlation and causality is really near and dear to our heart because we see an entire industry that was birthed by confusing correlation and causality. And that's, you know, one of the messages that that we're getting out and we've just started. We've just started this message in in earnest recently because we just felt we didn't have enough data to construct serious arguments. We've been accumulating this data out of sample for twenty two years, and then a year and a half ago we started to accelerate our efforts to begin organizing it to do research the way kind of in the FAMA French tradition just so that we have more of a of an Apples to Apple comparison, so people don't have to unscramble how we're organizing things. And then with with the COVID crisis, that gave us a lot of time to focus on that, and that's we completed this work back in in September and release the paper in October. But I think the correlation causality argument is really interesting. I think also the quantitative investing world is starting to come to grips with some notion of valuation. If you look at how that work was extended by former French and they motivated their research upfront with a dividend discount model, and from that they derived a profitability factor saying all all else equel af firms increase their profits, they increase their value. And then they have a second factor that they added, the investment factor, which I think really missed the mark. But I think it's interesting virtually everybody in the quantitative value space, any firm that seems to be anybody, incorporates this investment factor into their work. And what that missed the picture on and it says, okay, firms that are investing in their business are expect to generate negative future returns. And what that missed from evaluation context is you can't separate investment without the return on that incremental investment. And so of course, if you only make an investment in the firm and it generates no future returns, absolutely companies should never invest. But if you had the brightest quantitative value investing minds in the world. Back in talking to Jeff Bezos and he asked them, you know, I'm thinking about these different extensions of my business. If they're looking at the profitability factor, they'd say, all that's great. But if you're looking at the investment factor, they'd say, don't reinvest, don't expand beyond books, because they're going to generate negative future returns. And to me, that's a worldview that's just missing the wealth creation element that comes from a complete valuation framework. Literally, you're biased against the greatest in estments of the last sixty years. Not tech companies necessarily, of course those are some, but you're missing the McDonald's, the Walmarts that the targets, the fisers until as a as a manufacturing slash tech company, Apple, Google, Facebook, all of these firms have to make huge investments in their business. And if you have a worldview that says investing is bad, you automatically have at least one aspect of your investing world view that's counter to the best returning companies in the world. And I think that's just a fundamental flaw on that approach. Why don't you know when you say that, when you describe it, it sounds so obvious that it's kind of weird to penalize these companies that are investing in building future technologies and future things. We can't conceive of what is their intuition in your view, like because it doesn't intuitively, it doesn't seem to make any sense at all. But I'm trying understand like accounter argument. So the first argument is the data overwhelmingly says it's true companies that invest underperformance. That that's an absolute fact that I wouldn't argue that with anybody, But I would say that's a very naive slice of the data that's not accounting for economic profitability and cost of capital. So yes, on aggregate, over these big periods of time, say sixty three, if you looked at all firms that were reinvesting on aggregate, the investment factor turned out to be negative. But I don't think that's a really that's a complete view of the world because I think it it naively misses the key component evaluation, which is that investment gets reinvested to generate future returns. So if you then segment companies based on their economic margin, positive economic margin firms that are growing versus negative economic margin firms that are growing, you end up with distinctly different return profiles. We captured this. We've been doing this notion of wealth creation and destruction through what we call a management quality score for fifteen plus years out of sample. Also, when we first created this metric back somewhere in the two thousand's, we converted this into a financing yield, with the story being, look, there's a stewardship aspect to this, and when we look at what companies are doing and able to finance their business on their own versus having to turn to external capital, that captures companies that are growing like an apple, but also returning money back to shareholders, and that changes the underlying characteristic of just saying growth is bad. Growth is bad, but it has to be tempered by what's the underlying wealth creation aspect of the company or wealth creation prospects of the company to really sign whether growth is a positive or negative. The overwhelming data shows the returns are negative. And in a fact world agreed, you have a factor that's negative, but I think it's a factor motivated by really poor theory, which is problematic in my mind. I wanted to ask you about that. So we've been focused on investment as one path towards growth. We haven't talked as much about the capital side, the cost of capital and capital funding decisions going into a company, whether to buy back shares or whether to borrow from the market and add on leverage. How much has that impacted or how much has trends in the capital markets impacted the performance of traditional value investing in recent years. So that's a great question, and it's something we've we've started tackling more recently. And that's I think this notion of value and growth getting at the heart of this question is really more of a duration argument and a duration problem. You have from the nineteen sixties to the eighties sort of a period of increasing interest rates. Since the late eighties to today, we've basically seen decreasing interest rates. I think it's just present value math when we when we build out economic profit profiles for companies, the higher growth companies ultimately end up with much higher durations and a much greater sensitivity to what's happening to discount rates than what's traditionally viewed as value companies or low duration companies that all their assets, all their cash flows are basically coming from what they already had in place, and there's not much on the on the horizon. So we've had a great we've had a great environment for for kind of traditionally defined growth stocks since the nineties. Obviously we've had periods of increasing and decreasing rates, or many cycles within the larger trend of decreasing rates. We're at zero now. You know, it wouldn't surprise us to see these value, low duration type stocks have their day in the sun again for an extended period of time. If we end up with some thematic increase in discount rates and cost of capital over time, because those further out cash flow has become much less valuable to us, doesn't mean that they'll be undervalued per se. That we have to see how the market, how fast, and how the market digests that and prices that if indeed rising interest rates is even what happened, I have my my ability you I would probably have to pay someone to listen to my thoughts on future interest rate increases. So I won't speculate, but I can just say from an economic valuation perspective, those are the factors that will be at work driving you know, longer versus shorter duration investments. So what happened going back? You know, since you sort of identify this moment in which your sort of intrinsic value framework seems to diverge from the cheapness models, is it just about the sort of rise of these more intangible based business models what we call a tech or software things like that, or what sort what explains this diever this period? Since then? So I wouldn't say we recognize that our model diverges from cheapness? Are we have a very different worldview than than what I'd say a typical quantitative value investor is a quantitative value investor is generally going to have completely signed off on an efficient market hypothesis, because by definition, what they're saying is we're not here to create outfit. We're just trying to get you a really fair market return for all the risk factors you're you're taking on any given portfolio. Our view has always been was sismatically believe some companies are overvalued, others are undervalued, and probably the majority in the middle. There's not enough of the difference to really worry about. So it's kind of the the plus on each side that really are important to construct a portfolio, and with the rest of the stocks it's okay, which leads to certain exploiting of specific behavior. If you look at passive investing, you know our view is their systematically over investing in the overvalued stock systematically under investing in the undervalued stocks. So we're we're super happy with the rise of passive investing because it's a natural segment for us to trade against. Same with growth investors and value investors that we believe their views on the world systematically lend them themselves to being exploited. The rise of intangibles and intangibles are a really interesting topic because now you have a lot of people that are that are trying to grapple with that and rescue the price if you will. I think that a recent paper by Campbell, Harvey and Rob ar No saying let's capitalize R and D, and let's take of intangibles and of s G and a expense and call it intangibles and added to book value. And indeed, when they do that, what they see is that book value performs a little bit better. Going back to that deconstruction of value that I mentioned on on as reported book to price, well, i'll call I think they called the variable i h mL intangible based high minus low book to value book to price. It does absolutely nothing relative to intrinsic value. All the alpha in that approach is also supported only when stocks are undervalued, are overvalued in terms of the long short portfolios, and when you capitalize the intangibles. If you if you looked at the return profiles they published, that was for all the stocks, yes, but if you look at the large caps, the large caps really didn't do materially better than an unadjusted book to price, and certainly on a on an intrinsic value adjusted basis to perform poorly. And I think the reason is all of these approaches to intangibles are completely missing the picture on how to deal with them. They're immediately treating intangibles as a valuation issue, and they're saying Google spending a billion on intangibles adds to its book value, but so does Macy's. And I would tell you the properties of return for Google investing a billion dollars versus Macy's and advertising are wildly different. And to treat intangibles immediately as a valuation concept, I think is completely wrong. What you need to do is you first need to treat it as a corporate performance concept. You need to answer the question how well is the firm performing the reason you're struggling with intangibles as you disagree with the accounting convention of conservatism that writes it off immediately, and that's fine, Then treat it as an investment and figure out what the real rates of return the companies generating on investments, just the way you would have the factory, assign a life to it, put it on the books, and generate and calculating r o I. Companies that consistently are generating significantly positive returns on that investment will start to see their r o I s increase as they continue spending. Companies that don't won't. So Macy's can spend a lot on intangibles and R and D whatever, R and D would be for them, and it's not going to move the needle on their valuation much so to just say they're cheaper because they've spent this money on advertising, I think it's just it's a super naive view of understanding what valuation is all about. It's a convenient view because it lends itself to a lot of you know, in the classic mean variance factor world, that's a convenient view, but I don't think it's anywhere near the appropriate view. And the other the other aspect of a lot of these studies is going back to this notion of back tests. I don't believe you can. You can start to look at it a variable and go back time and look at it, and even if you don't have any mal intent, it's really hard to not know. Over the last ten fifteen years technology firms, which are the ones spending the most on R and D. I've been the ones that have exploded in stock price. You don't have to have mal intent, but everybody knows that unless you've lived in a shell. So it's hard to be an objective researcher and say, well, the solution is, let's add back R and D and we get a better metric. Any of these finance studies that are looking backward in time and consistently drawing back test results and claiming they're real. I think you need to put in the hard work and effort. Every time you changed your model, your track record stops and you need to start tracking what's the efficacy of the model going forward. You can't say I launched this model ten years ago, I've improved it now because of this additional variable that I've backed tested and added to the model. I don't think so the models reset when you added this new variable to it. Buddy, That's just the way it is. We waited twenty two years to kind of make this explicitly public because we wanted to make sure there was enough data and the data is growing to really do the study properly. And I think that's a standard everybody needs to do it here to. You can't. You can't create a valuation model looking at historic data when you know how you're estimating these parameters to assign risk and it fits for that period and say you have a great model. Yeah. It's great to observe, and observations are an important part of science. You have to observe, you formulate your theory, you formulate your model, then you have to start calculating the data, and you have to let the data theri and age live out of sample. It's it's it's painful and it's costly, but it's really the gold standard. And Harvard Campbell even wrote a paper describing how big of a problem this potential for forward bias, you know, foresight bias and inadvertent data snooping is in financial research, and he said, clearly the gold standard is live out of sample data. But it's just very difficult to obtain. And that's one of the things that I think really sets us apart from any other firms. We've made the investment in time, because you can't short change the time. We've made the investment in time to get that data and to offer our results relative to other data that's been developed through backward looking approaches, and we still came out on top. If you look at in this valuation data research paper we rereleased in October, we systematically reconstructed an asset pricing framework looking at all the popular value quantitative value factors, profitability, book to price, the investment factor, momentum, low volatility. They all basically are subsumed by these concepts of intrinsic value, wealth creation or stewardship, and leverage. And what is quantitative value investing When you start adding factors such as momentum and volatility there, what's the identity of that field? What's the theory that links price, momentum and volatility to thetrinsic value of the stock? I think it started as a as a very clearly defined having a very clearly defined identity, i e. This book to price is a factor that either represents a behavioral problem that people are missing this information, or it's some sort of embedded risk factor. But then over time is that factor hasn't worked and they've continually added on. I think quantitative value investing the value component has lost a lot of its identity. What is it exactly? It's okay to have to be a quantitative investor, but I'm not sure. Again, getting back to our initial discussion at the top of the show, value doesn't belong in there. That needs to be reclaimed in a more appropriate manner. I think. So I'm going to try to squeeze in too hopefully interrelated questions here, But how dynamic are your own models? Then? I know, you just very much criticize people that are constantly changing their models in order to fit new data coming in. And secondly, what did you learn from how did your funds actually perform and did you make any changes off the back of that. How dynamic are models? We pretty much locked in our models in Nothing has changed structurally to what we do, the way we estimate uh the persistence of economic profit, the way we calculate cost of capital risk adjust cost of capital for a company. There have been along the way what we considered to be minor accounting changes. For instance, recently Accountant started capitalizing lease's last year and putting them on the balance sheet. We have to undo those because we think they actually did it incorrectly for a number of reasons that are way way more geeky than probably the show needs to get into at the moment. But there's always little adjustments like that. But the fundamental thrust of the model has not changed, since it's a very dynamic model because market prices are always changing and the performance and strategy of firms are always changing, so that's constantly at work. So the answers, we haven't really changed the model. I feel comfortable with my criticism because we haven't done that. There's been lots of time where our performance hasn't been what we wanted it to be. The going back to the first part of you know, the value guys weren't in this boat alone. We we performed poorly relative to the S and P I. We we were benchmarked in the value category. Our mutual fund in that space significantly outperformed the value indexes last year. Since we started today, we've outperformed the S and P with this with kind of our core strategy, the valuation fifty strategy. What we learned in twenty is that it's it's really two interesting points from one. What we learned is the same lesson we've learned over and over. It's very difficult to be true to your process. Sometimes it's it's extraordinarily painful when you when you see the world is trading against you every day and you're underperforming. Yet you need to hold on because if these are central truths you believe in, this is what your investment clients purchased from you, and this is what they expect they're getting, and that's what we delivered. So in I think we had two trades to the portfolio. One was selling in video UH at five plus in August after it just run well above finally exceeded our estimate of its intrinsic value, and we we had to sell as we were crying pushing the button. It had become kind of an old friend of our since and a great performer. The other interesting thing of in our history of twenty five years of firm, we've issued four market calls. Basically, one was in two thousand when we thought the market was overvalued along with everybody else. We don't. We don't think our insight was necessarily unique, although the a we went about it I think was kind of fun. With Cisco, we showed kind of what the expectations built into Cisco's price were in two thousand of the process we called we created back in ninety eight called value Expectations, where we take our model and we reversed out the performance implications of a of a stock price and we showed Cisco basically had to grow it plus sales for the next five years. In twenty the end of two thousand and eight, two thousand of nine, we came out with another market call that we said the market was just extraordinarily undervalued. That that was fun because I happened to be on CNBC mentioning that at the time, and they thought I was nuts. And then this year, with all the volatility, we made to market, called one in March saying the market's really undervalued. It reminded us of two thousand and eight, and then to us finally the market became overvalued in August of this year. Now, obviously we've been way wrong. We didn't in August. We didn't say, uh, this is an absolute time to get out, but we did say statistically, we think the market is expensive. We'd be very cautious here. You know, who knows whether it'll be right or not with that, But you know, that's just what our models indicated to us. So that's that's the way we're approaching the world. I think it's important to stick to your discipline, and that's what stick to your discipline. The market isn't always efficient, but it sure is generally rational through time. And like I said, a lot of stocks that that it underperformed continued to do really well after March, and if we looked at our returns last year, we underperformed the SMP year to date this year, that fund is outperformed the SMP by more so from the start of we're up this process. We launched this strategy in two thousand and four. It's significantly up on the SMP since inception over the last ten years. As I mentioned, over the last year plus, I think over three years. It's probably down over five years. It's probab we are I don't really I don't really track all the return profiles because we don't. You know, the turnover on this portfolio is about ten percent a year for to five stocks a year, unless we have companies that are acquired. So what do you do? I mean you you said you sold in video. You said in August you identified, uh, the S and P or the market overall is being overpriced. What do you do from a portfolio perspective? What kind of shifts do you make or what are what are the implications for you when you make an overall market valuation call. In this particular portfolio, it's a long only fund, so we aren't going to do anything and the charter is to be fully invested. So we sold in video, we replaced it um and again this is this kind of speaks to why valuation is a little quirky. Let me just give you a little a little background prior to this. The direct answer to a video we the direct answer to the video, we sold the video. We bought k l A, the semi conductor equipment maker. But the background of that that makes that particular purchase interesting. And if you go back to the composition of this portfolio is approximately twenty five stocks that would be classified as sort of value or core, twenty five stocks that would be classified as sort of core or growth. Over time, as the market has kind of pushed up the valuations of growth stocks, the portfolio is naturally then shifting its marginal trades away from shading growth, getting more and more into value. By August of this year, the composition of the portfolio was approximately seventy seventy of the portfolio was in value core stocks. In core value stocks. KLA Corp. Happens to be at growth stock. So it's it's it's hard to just pigeonhole what we're what valuation says, because it doesn't necessarily just have to put you in a in a quote non growth value stock or or a high flying growth stock. It really is constantly shifting between what the market is giving us, and so would we When we pulled the trigger on video, we bought kl A Corps and immediately KLO Court dropped ten percent, which is always the case when we big a trade, which is really annoying. But since then it's it's done. A really nice job. Routy that Ruffael, that was. That was a great conversation. Any other sort of last thoughts or key things that you think we should, uh our listeners should think about. No, that was. That was a lot of fun. I hope we can do again sometimes. That was a lot of fun. Well, yeah, let's definitely do it again sometime. And I really appreciate you joining it. Thank you both, Thanks so much so Trazy, I thought that was that was super interesting. I mean, obviously we've talked about a lot of these themes before, resuscitating value, reviving value, intrinsic trying to come up with some new concept of intrinsic worth based on intangible assets, and I like that. It feels like their work tries to just go about the problem differently, rather than starting from this premise that there are ratios or book that book value is a useful idea sort of defined value, but not within not within the old constraints, right, although it does get me thinking if whether you know, one of the enduring mysteries of our investment age is why value investing hasn't performed better, it makes me wonder whether or not like it all just comes down to the definition and semantics. And you know, I guess we kind of touched on this in the intro, but if you have a completely different definition of value investing, then hey, it actually works. I guess maybe we the way, and I'm sure this won't be our last conversation on the topic, But I wonder if the better question is why don't cheap stocks do better? Because I sort of like, I mean, ultimately, or why don't or why don't the sort of the traditional value factors do better? Because it seems like um Raphael's criticism isn't that what the concept of value value investing per se obviously because he is sort of in that category, but just in this idea that the sort of like the traditional like farmer French factors that one at one point seemed to point to outside returns no longer do well, is you gonna say? Then we can at least sort of define what we're talking about better? Because you know, again, if anyone can sort of redefine value, then you can never really prove that it's working or not working. But if we could start our convert station with why don't these traditional ratios work the way they used to? Why does it price to book, why does it price to earnings work the way we used to, then at least we can define the debate. Yeah. I think that's a good point. Um. I also liked how strongly he feels about back testing, uh and sort of like fitting your thesis to the data. And also this idea of if you're making substantial, substantial changes to your model every month or every year or whatever, you're basically starting from scratch. I don't think you hear that very often among a systematic investors. So that was fun. He also had some like pretty like strong negative words towards you know, what we called quant investing, and so you you know, the idea that you could have one person who's a sort of quant investor who looks at things like price to book, another person who's a quant that looks like at momentum factors, they're not out really can as he put it, you know, maybe some people argue they would they're not. Really, They're not intuitively connected. It's not obvious why they should be under the same family of thought about investing or about stock picking. Sort of ratio based investing is obviously intuitive to the company. Momentum factors are intuitive to the price of the stock itself or related to the price of the stock itself. It's pretty different stuff that ends up getting lumped into one broader category that we call quant Yeah. I think that's a good point. Should we leave it there? Yeah, let's leave it there. Okay. This has been another episode of the All Thoughts Podcast. I'm Tracy Alloway. You can follow me on Twitter at Tracy Alloway and I'm Joe Why Isn't Though? You can follow me on Twitter at the Stalwart. Follow our guests on Twitter. Raphael Ascendez He's at our Ascendas and check out check out their paper that he co off Third Valuation Beta, addressing inadequacy inadequacies of book to price with intrinsic value, stewardship and leverage that's available for download online. Follow our producer Laura Carlson, She's at Laura M. Carlson. Followed the Bloomberg head of podcast, Francesca Levie, at Francesca Today and check out all of our podcasts under the handle at podcasts. Thanks for listening.