Introduction

Patrick: [00:01:24] It's been a while since we discussed private equity on the show, so I was excited about this week's conversation. My guest is Dan Rasmussen, the founder of Verdad Advisers. Dan worked in private equity but has also spent years studying the entire field. Dan identified several key drivers of private equities, outsized returns, size, value, and leverage. His firm uses these factors as a starting point to build a portfolio of public equities that behave like their private brethren. We cover a ton of ground discussing the perspective returns for all equities, forecasting, and tons of different investment strategies. Please enjoy this wide-ranging conversation with Dan Rasmussen.

Private Equity Investing and Its Myths

Dan: [00:02:03] Private equity is a really fascinating world. I think it's an asset class that very few people understand. From 1980 till 2010, it was probably the best place you could possibly invest, returns, net of fees for about 6% in excess of the public market. Private equity, this is all the more remarkable because we know so much about how difficult active management is and how high fees can drag on returns. Here you had a very complex, clearly very active, they're taking control of every company and very high fee asset class dramatically outperforming. The question is, why was that? Why did it work? Then even more interesting, perhaps, is that it hasn't worked since 2010.

If you look at the Cambridge Associates benchmarks, private equity has actually underperformed since 2010. The key question is, what's changed? I think that if you look at what's changed, probably the biggest thing is that, and you see this all the time in investing where something that really works well, and is a very good idea gets adopted by everybody. Money pours in and the returns go down. That's what you see happening now in private equity, where every institutional allocator believes that the ongoing forward returns of private equity are going to look like that 1980s, '90s, 2000s history. They're saying, "Well, we should have a 20% allocation to private equity and we only have 12% today, so let's deploy a ton of capital into this asset class." As that money is rushed in, private equity firms have sprouted up, they've raised huge amounts of money and they're all competing for the same limited set of opportunities.

The number of businesses going up for auction has not changed. What has changed is the number of competitors in the auction. If you think about that from public an equity market perspective, these are tiny, little businesses, 15, 20, 30, 100 million of EBITDA and they're selling for absolutely insane prices. 11, 12 times EBITDA, six to seven times net debt to EBITDA. You have debt financing, and it's just a crazily competitive market. It's almost to some extent like a gold rush Patrick.

Patrick: [00:04:10] Can you talk about the three levers which you explore in the piece describing how private equity firms profess to have earned such impressive results and why maybe those things aren't necessarily even true? Or at the very least, maybe very different looking forward?

Dan: [00:04:24] Yeah. I think the three persistent myths of private equity are first, that private equity makes money through operational improvements. This is actually the whole rebranding. It used to be the leveraged buyout industry. Now it's the private equity industry, and they're even trying to rebrand it as growth equity now, which is, I find amusing. But the first myth of private equity is that private equity creates value through operational change, that you have these brilliant managers that went to Harvard Business School that can come in and turn around a business.

The second myth is that private equity is lower risk and less volatile than the public markets. That's a myth because private equity firms mark their portfolios quarterly. They're private companies and so they decide every quarter, what is this worth? Generally, they look at it and they say, "Well, EBITDA is up a percent or they down a percent." We'll say that it's flat, we'll mark it at one. Now, Patrick, if you and I could do that with our public market portfolio, we'd say, "Well, nothing's changed about this business. There's no new information since we bought it." But there's no new catalyst so it's flat. But of course, that's not how markets work. Markets are dramatically volatile, they go up and they go down for sometimes for a reason and sometimes for like they did in early February for seemingly no reason at all. The private markets don't experience that because it's just based on the judgment of an accountant or the private equity firm itself. As a result, private equity looks less volatile. But in reality, what they're doing, which is buying small companies, using a ton of debt is actually, if it were a public market equivalent would be much more volatile than the public markets. There's this aspect of misunderstanding the risk.

Then third, and finally, I think that although every disclaimer in every fund presentation says past returns are not a predictor of future returns, everybody looks at private equity and says, in this case, past returns are a predictor of future returns. Because they don't necessarily have another way of thinking through, what are the factors that drive returns that would change the expected return and because they think that the source of return is operational change, then all they need to do is find a great operational change agent and they should get the same returns. Because factors, in their minds, purchase price or leverage levels are not the core driver of the outcomes. Just because those things change, doesn't to them, signal a change in the asset classes potential for outperformance. Those are, I think, the three myths of private equity. I'm happy to dive into each of them individually or whichever one you'd want to start with.

Patrick: [00:06:51] Well, let's start with the operating one, because you did some good empirical work, which obviously is in the spirit of how we try to look at things as well, not just to theorize about what might be or could be, but what actually has been in the actual data. Talk about the data that you collected at your firm to assess whether or not this operational improvement narrative was in fact true?

Dan: [00:07:12] Yeah, and before we get into this, specifically, I think there's this analogy, which I keep coming back to, which is that, in private equity, they keep saying, we make operational improvements or, and we do X, Y or Z. We do deep diligence, etc. But they say that but they never offer any evidence. They never offer any proof. Making money in the market is so hard, five to 10% of managers are creating really significant alpha and everybody else is losing to the index. In some sense, it's almost like someone came to me and said, "Well, I can run an Olympic level 100 meter sprint." You say, "Really well, that's impressive, what was your last time?" And they say, "Well, I don't keep track of time but I guarantee that I can run it." The fact that they never offer any evidence for their operational improvements other than anecdotes, that they never ever any evidence that their diligence results in superior forecasts. It's as equally as absurd that someone who does not keep track of their operational improvements or does not keep track of the accuracy of their forecasts could be doing the equivalent of an Olympic level sprinter is absurd. But let's dive into the operational improvements. I'm going to speak in aggregates and averages. This is not to say that no private equity firms add value, they're certainly ones that can and do. But again, those are the top five or 10% of firms. For the bulk of firms, it's not the case. To test this, what we did is we said, "Let's look at every private equity deal that issued public debt as part of their financing."

The reason that we wanted to look at that was because if they issued public debt, that meant that they had to give gap financials prior to the acquisition, usually two or three years prior to the acquisition, which is what they used for the financing. Then also to report afterwards, how the financials of the business did. We looked back, we found out 390 private equity deals that issued public debt. What we looked at is, let's look at the three years pre-acquisition and three years post-acquisition. What changes about the financials and what's statistically is significant about that? What we observed is that revenue growth and EBITDA, growth slowed. If you think about why that would be the case, every private equity firm in their underwriting is selecting for high growth firms that they can then input into their models having high growth into the future.

Of course, if you read what works on Wall Street, for example, you'll quickly see that things like growth rates are mean-reverting, and so it should be no surprise that private equity firms choose things that have grown in the past and that the growth rates mean revert a post-acquisition. Second, private equity talks a lot about cost-cutting, efficiency, margin improvements, we found almost no improvement in margins, at least nothing particularly noticeable, maybe a few basis points. Now, what did change? In 70% of cases, a massive increase in debt. Typically, from about two times debt to EBITDA to four or even five times debt to EBITDA. As a result of that, obviously, massive increase in interest payments, and then what we also observe is a decrease in capital expenditures, which makes sense. If you just took out a lot of debt, you're probably not going to want to invest in capital expenditures, what instead you're going to do is shift that money to interest, debt service, and debt repayment. I think if you back up and say, "Okay, what does that tell us about the asset class?" Is that in the vast majority of cases, private equity firms are buying the whole company, they're taking control in order to, and affect a change in capital structure. That is the goal of the private equity transaction, is to lever the firm up and through that leverage, enhance equity returns. Everything afterwards about operational improvements is to some extent, window dressing. It's like, "Well, if you own the firm, surely you're going to want to talk about the things that you did when you served on the board or the wise counsel you gave to the CEO."

Private equity talks a lot about cost-cutting, efficiency, margin improvements, we found almost no improvement in margins, at least nothing particularly noticeable, maybe a few basis points. Now, what did change? In 70% of cases, a massive increase in debt. Typically, from about two times debt to EBITDA to four or even five times debt to EBITDA.

But the idea that having a private equity manager on the board or even having the advantage of their considered judgment would somehow dramatically improve every operational metric for a company, it's just not the case, at least in aggregate. What you see in aggregate makes a lot more sense, which is they just buy things that are growing fast, that those growth rates slow down, they lever them up a lot and they take all the cash and use it to pay down debt and service interest.

Valuations and Delivering on Returns

Patrick: [00:11:25] I'd love to explore the price component in all of this, there's a great chart in the piece that you wrote, which compares the median to EBITDA multiples for both the private equity pool and the S&P 500. You see going back to the late '90s, this massive discount that was available in private markets paying, eight times EBITDA versus 14 or 15, for public markets and then really into the financial crisis and then since, those two lines have converged and they basically look exactly the same. You would think that you would get some discount for the illiquidity that you're taking on as a private investor. But that doesn't really look like the case. I think your research suggests that probably the most predictive variable, and certainly we'll talk about this and public markets too, a future performance is a price paid at the beginning when you're talking about averages. Of course, there are always outliers that you buy it at an expensive price, and it was still a great buy. But on average, price matters. Maybe talk about how you think about private market valuations, what's driving them, and how important they are on the outcomes for investors?

Dan: [00:12:23] Yeah, and this is probably one of those things that are most misunderstood about private equity from the outside and the most clearly well understood by people that actually do the transactions. That's the importance of valuation. I would say that private equity valuations are even more important than public equity valuations. The reason for that is that every private equity transaction or at least the vast majority are in aggregate, are debt-financed usually about 65% net debt to enterprise value. As you increase the purchase price, you're increasing debt levels and you're increasing interest payments. That has an effect, if you think of free cash flow yield, as being at least theoretically, should be the driver of equity returns.

If you increase the purchase price, you're not only decreasing the size of the denominator in that free cash flow equation, because you're increasing the amount you pay, you're increasing the market cap or the equity value. But you're also decreasing the numerator because you're adding interest costs. Any increase in valuation actually has almost an exponentially negative effect on free cash flow yield. Conversely, as you get cheap, the cheap levered equity is, the 1980s, 1990s LBOs, done at seven times EBITDA. In those cases, you had the increase in leverage far outweighing the increase in interest payments. But there's essentially this exponential curve as you increase valuation. That's what makes private equity much more price-sensitive, is that the expensive companies are at a higher risk for bankruptcy, their interest payments are substantial relative to their free cash flow. That means that you have a lot more downside in those expensive LBOs than you might in an expensive public equity that's not levered.

Patrick: [00:14:03] How do you think about, as a quick aside, thinking about some of the famous private equity firms, you mentioned a few of them in the piece, one that comes up all the time is 3G. Less because of their results, which have been impressive, but more because of this philosophy behind the operational improvement behind, zero cost budgeting and these really interesting theoretical ways of potentially improving a business. I'd be curious what your take is on a company like that in particular and whether you think it's possible to identify a subset of private equity firms that looking forward because obviously, that's all that really matters for people making decisions today. That looking forward might have some higher chance or higher average percentage chance of delivering on this excess return over public markets through unique operating means?

Dan: [00:14:48] Patrick, I think I'm an empiricist. I think that, let's just take the data and look. Take every LBO that the firm has done, look at the financials, three years pre-acquisition and three years post-acquisition, and if something jumps out at you. You say, "Oh, gee, in every single case, EBITDA margins double," then probably that firm is good at cost-cutting. If revenue growth is 8% for everything historically and 16% afterward, and they say they're a growth equity firm. Then I'd say, "Well, gee." You see them over dozens of examples to actually achieved what you're selling me on. I think that's a good way to test it and it's simple. If you look at 3G, for example, and there are other examples of this, Vista Equity, for example, in San Francisco. Cost-cutting is something that works.

Every business has fat to cut and especially a lot of these software businesses and consumer packaged goods, software companies where the product is selling itself. You don't need to service it necessarily. Those firms, if you look at pre and post-acquisition for 3G's buyouts, EBITDA margins often double after their acquisition. I think it's pretty clear that 3G has a real skill at cross-cutting that I think investors could underwrite. Now, perhaps unsurprisingly, 3G uses their own money to do the deal, so you can't necessarily access those returns because they're not taking outside capital. But I think the point holds that there are firms that can operationally change businesses and I think it's easy to just ask for proof.

That's not an anecdote, like when was the last time you improved a company, but rather, systematic across the portfolio level data. I think for those that look at that data, what they'd see is the vast majority, again, don't do anything. They just lever the firm's up, and where firms are successful, and so far, as I've seen it, the most successful strategy tends to be cost-cutting. It's very hard to systematically improve growth rates. But cutting costs is I think, a doable and achievable systematic thing, something where you can develop real expertise.

Patrick: [00:16:38] We're going to talk a lot about a new method for forecasting that you're a subscriber to and just forecasting in general, and it's how difficult it is and how it can be useful, how it's misused in finance. I'm not going to ask you to make a forecast about the future of private equity. But instead, just to ask if there are any other observations of the landscape. As you look at it today, you mentioned this massive amount, I think it was $700 billion, or something of committed capital, meaning investors have committed capital to private equity firms that have yet to be deployed. You've got this interesting recent rise in rates, so you need to think about the cost of debt financing. As you look at the landscape today, is there anything that jumps out at you, that could be interesting to investors considering the asset class?

Dan: [00:17:22] Yeah, I think the biggest developments, I think you're going to see these large institutional investors, the Dubai Pension Funds, the Abu Dhabi Investment corps of the world increasing their allocations to private equity. I think that you're going to see massively increased flows into the asset class for years to come. That's going to continue to drive purchase prices higher. I think any firm where you're seeing the aggregate or average buy out multiple for their deals north of 10 times EBITDA, you shouldn't expect those funds to return higher than the public equity markets. It's just not likely, at least in aggregate. Now, because these portfolios are so small, if they do 10, or 15 deals per fund, they could just have one or obviously, everything's probability distribution.

Some of the funds that do really expensive deals are going to work. But I think in aggregate, they're not going to and a lot of those deals are going to end in bankruptcy or restructuring, or they'll just hold them for seven or eight years or nine years before you ever get your money back. I think the biggest advice to investors, I think, is to say, be really, really careful, because it's unlikely that those expensive investments are going to perform to the extent that you think that they are. It's shocking to me, but the consensus among institutional investors about private equity outperformance is so firmly held. I think it's something like 50% of institutional investors believe private equity will outperform the market by 4% per year. I think there's maybe less than 10% who think it'll even be even.

I'm just saying, I'm not a radical or an extremist. I'm just saying, "Look, over 10 times EBITDA, even Cambridge Associates data suggests this underperforms the public equity market." My view is if they're doing deals of 11, 12 times EBITDA, which is where prices are this year, it's just not going to work. It's going to lag the public market, it's a huge fee load, you're locking up your capital for seven or eight years, maybe more, be careful. If you are going to allocate to private equity, allocate to the firms that are buying companies cheaply, those still exist, and allocate to firms that can actually prove to you that they can create value across their portfolio in an aggregate rather than just being seduced by anecdotes.

Patrick: [00:19:34] One of my favorite parts of all the various stuff you sent me to read ahead of this conversation, which was great fun, everyone should definitely subscribe to the thing you send out every week. There's some really, really great stuff in there, was this idea that many of the most successful investors in history, the Mount Rushmore type names, the names that we revere and hold that as examples all the time, maybe successful largely because of the reference class or area that they chose to invest in. You mentioned, Mitt Romney, his success was likely not because he was some amazing equivalent of a stock picker in the private markets. But just that he was operating in a very cheap, levered, small-cap, private business space. Maybe talk a little bit about that idea of where you choose to hunt and that will be a good transition into how you've decided to invest your own money and choosing a reference class like that accordingly?

Dan: [00:20:21] So I went back and read all Mitt Romney's early letters when he was investing. I found one from, about 10 years into his career. He said, "Prices this year are getting more expensive. We used to buy things at four to six times EBIT, but we're having trouble finding things at those valuations, which worries us about our ability to generate alpha at higher valuations. We're seeing some of our competitors get involved in auctions, which just seems crazy to us." I'm paraphrasing, but you look back and say, four to six times EBIT, or you're buying things at four to six times EBIT, of course, that worked. I think that your idea of reference classes is exactly right. Did Buffett succeed because he was a genius or because he realized the value of using insurance float as a form of permanent capital?

Did Mitt Romney and Kravis and Roberts and all these guys, did they succeed because they were the best stock pickers in the world, or because they found a corner of the market that was deeply undervalued? I think that when you then think about these reference classes of these great investors, they were finding places that were undervalued, where other people weren't doing this, "Uh, I don't know, it seems crazy to go out of the public equity market and buy small private companies with debt. I don't know, it sounds really risky to me," or "Gee, putting insurance money into common equity. I don't know. That sounds really, really risky."

I think it's Peter Thiel, who says that good ideas are the intersection of something that could be a good idea, but sounds like a bad idea so it scares enough other people away. I think anything, where there's consensus, is unlikely to provide a good investment opportunity. Investment opportunities are almost always found in non-consensus contrarian places.

Patrick: [00:22:03] If reference classes is critically important. Talk about what then you've done with the lessons that you've learned from your experience, personally in private equity, studying the business, how does that then translate into what you do on the investment side?

Dan: [00:22:15] Yeah. I think ultimately, investing is about making good forecasts. I think too many investors subscribe to this clinical or expert based judgment that, if I know a lot about something, I should be able to make good forecasts. There's a huge amount of academic literature, which well, that really started with Paul Miele and Daniel Kahneman and Philip Tetlock at Wharton has really run with this. But figuring out, and Tetlock does this amazing study where he surveys thousands of experts for I think a 10 year period. They do some 30,000 forecasts and he finds that expertise in a given field does not improve forecast accuracy. All it does is increase your confidence in the accuracy of your forecasts. If you think about investing, there's nothing more dangerous than increasing your confidence without increasing your accuracy.

That's a massive calibration error. The fact that the vast majority of fundamental investors are using discounted cash flow models, and they're trying to understand these asset classes, start to understand these individual investment opportunities by studying them in great depth. It's just not going to work. It's not the right way to make forecasts. What Tetlock and Kahneman found is you have to use base rates. A base rate is saying, a classic example they use is, Jenny has studied English literature at Amherst, and she wears glasses and she loves to read Trollop's novels. Is it more likely that Jenny is a nurse or a librarian? Most of the expert, clinical, everything is telling you, well, she must be a librarian, because they're all these signals that she likes reading, she wears glasses, she must be a librarian, but actually, nurses are, I think they're 999 nurses for every one librarian.

Of course, the answer should be nurse. She's much more likely to be a nurse and that's a base rate. You just say, "What is the probability distribution of outcomes given a certain of historical probabilities essentially?" If you wanted to say, "Well, how are these buyouts going to perform?" You'd say, "Well, what are the statistically significant predictors of a buyouts performance?" You might say, okay, size, value leverage, maybe what industry it's in, who knows? I think probably the first three would be the ones that I would pick size, value, and leverage. Then you might say, "Okay, well, how did comparable private equity deals done at a similar size, similar values, similar level of leverage perform?" I think if you look, you'd say, "Well, the deals done at less than seven times EBITDA do really, really well."

You look at the vintage years that were done at those valuations, they dramatically outperformed the public equity market, and they were small, cheap, highly levered rate that worked. But if you look at the vintage years or the individual deals done, greater than 10 times EBITDA, they don't appear to beat the market. You should use that reference class judgment rather than saying, "Well, Seth has been doing private equity for 30 years, and look at his track record. Seth thinks this company is a really good investment today. He wants me to give him money to do the deal." That's a way of thinking. It's just not a way of thinking that's going to lead to accurate forecasts.

Applying Purely Technical, Systematic Thinking into Public Market Investing

Patrick: [00:25:22] I always love that Bezos idea of Amazon betting on things that won't change, meaning they're not trying to forecast technological change, all they know is that the customer is going to want certain things in 10 years, just the same as they do today. I always try to think about that in terms of investing, like, what am I pretty confident will not change? Everything you just said, really makes me think of a couple of things. One is this, we just so crave a narrative agency, the fact that there are people that are more or less skilled than others and somehow we can find them. It just feels to me like that is something that is never going to change and therefore might represent a persistent advantage for us quantitative more systematic base rate-driven forecasters, I guess you could say. I'm curious then how you take that philosophy, assuming you agree and translate it into a live investment strategy in public markets?

Dan: [00:26:12] Probably one of my most formative experiences was, I spent a summer at Bridgewater Associates and you don't need to spend long at Bridgewater to get infected with their way of thinking and Ray Dalio's influence. It really shaped a lot of how I approach investing today. Ray's approach to investing is, so first come up with a logical principle. Something that makes sense, it is simple. Second, since most good ideas don't work, test that logical, simple principle across as many market cycles, as many regions or geographies as long as the time period is possible, and see whether your logical intuition matches the empirical evidence. Then third, if both of those two things work, try it out in live trading and see if it works out of sample, the great out of sample market which is the future. I think that's how I approach investing. I think my logic is very simple, which is that private equity dramatically outperformed the market from 1980 to 2010.

The way they did that, if you look quantitatively, what they did is they bought companies at less than seven times EBITDA, they levered them up 65% and they generally bought small companies, about 200 million a market cap. My logic was simple, is that buying small, cheap, highly levered companies should be a good investment strategy based on the historical evidence from private equity. I think if you think logically, again, what small cheap, really what cheap and levered together do is jack up free cash flow yields. If you're buying something at six, seven times EBITDA, about 50, 60%, leverage, your free cash flow yield should be around 20%. It should be unsurprising to you if you buy things at the 20% yield that they return 20%. That's the logic.

I think the empirical evidence is to go and test that, broadly does buying small, cheap, highly levered things work across markets, across geographies across market cycles? To which the answer is broad, yes. Then finally, third is to do it in live testing. Put your money where your mouth is, to bet on the results being right, which would I do on a day to day basis. I think the biggest lesson I've had since starting my fund, and since doing this in live trading, is to almost think like Blue Team, Red team. If blue team is, buy cheap, highly levered things with really big free cash flow yields, your red team is, "But gee, these things are levered, and they might be cheap for a reason." You've got to do everything you can to ensure that you're not buying things that are going to go bankrupt.

You're not buying that sub-segment of firms that are cheap, because they're really having deteriorating operating performance. I think of my process as basically a balance between the red team and the blue team. I think the red team is relatively simple, small, cheap, highly levered thing. On the blue team side, I think there are some key quantitative rules that you can use to help fully eliminate bankruptcy risk or not eliminate but reduce. You can eliminate all firms that have a C credit rating, you can eliminate all firms that have a really high short interest. You can eliminate firms that score low on the relevant Piotroski F-score factors. You can use all of the literature from, the quality literature that you've put out, that Piotroski has put out, that Cliff Asness has put out. Take all those quality factors. Those are going to be doubly important to some extent, in levered equities because bankruptcy is always a possibility if you have debt.

Patrick: [00:29:23] The small and the value pieces of the three-part beginning point that you've laid out here are obviously very familiar to quantitative investors around the globe. That many of whom have found, we would question maybe the small one a little bit, but certainly the value one is pretty impossible to argue with. What really stands out and is unique is this notion of higher leverage. I'd love to dive into the thinking there. How you have found in the empirical evidence, the difference between let's just say the reference class of all cheap small stocks versus small, cheap, and levered stocks? What are the differences in returns or risk-adjusted returns you observe there? Then talk about how you then dive into these companies, as you mentioned, to alleviate concerns around bankruptcy risk and the like?

Dan: [00:30:08] If you compare small, cheap levered firms to small cheap firms that are unlevered, if you look on an EV-to-EBITDA basis, the levered ones will outperform, though with higher volatility. But if you look on a free cash flow yield basis, roughly, they're going to have a similar profile. What leverage does, is it just Jacks up free cash flow yields. If you buy something for 10 times cash flow, if you're unlevered, you have a 10% cash flow yield. Well, if you lever that thing up, 50%, now you have something that has 20% minus whatever the interest costs are, but let's say roughly 20% free cash flow yield. A 20% free cash flow yield firm is comparable to another 20% free cash flow yield firm. But leverage is just one way to increase the free cash flow yield to equity. I think broadly, that's how I would say they compare, is that by using leverage, you can create a broader sample of high free cash flow yield opportunities.

I think, secondarily, I think in a time, I think there are so many people chasing small value. That at least over the past few years, small value hasn't seemed to work as much. But I think the advantage of investing in levered firms is that, which has worked over the past few years is that leverage creates its own catalyst, because as you repay the debt, the firm gets less levered. That's more attractive to a broader selection of investors who like cheap firms, but not cheap levered firms. I think, if you think about most value, investors say, never touch a levered firm, don't invest in levered firms, and write fortress balance sheet, etc. There is an opportunity in the levered universe to go to a place where other people dismiss the entire cross-section of equities and without seeing that, for some portion of those equities, the returns are actually extremely attractive. The returns are going to come from the deleveraging process.

There is an opportunity in the levered universe to go to a place where other people dismiss the entire cross-section of equities and without seeing that, for some portion of those equities, the returns are actually extremely attractive. The returns are going to come from the deleveraging process.

Patrick: [00:32:06] One of the things that we found in the empirical work that we've done is that it's not just the level of the leverage, but the direction as well. That if anything, maybe a Goldilocks scenario would be something that is, a company that is relative to its say, industry or sector peers, paying down debt to get closer to like the midpoint of the distribution of capital structures within that space. How do you think about the direction versus just the raw level of debt?

Dan: [00:32:33] That's exactly right, Patrick. It's the most important thing you have to know about investing in levered equities, is that it's the direction of leverage. You've got to be delivering and that's also free cash flow yield. That's how I calculate the free cash flow yield. How much debt did they pay off in the last year? Let's divide that by a market cap. What I'm looking at, you can call it almost de leveraging yield. If you buy these high deleveraging, yield companies, you get a bonus, because you don't just get the yield, like you would with a dividend. But as they pay off that debt, and they get closer to the median leverage for that industry, or for that subset of companies, you get multiple expansions, because a lot more people grow comfortable with the firm. Understanding the dynamics of debt pay down, and what causes a company to pay down debt, why do some companies pay down debt and others don't? That is, to some extent, the key I think, to unlocking value among leveraged companies.

Patrick: [00:33:23] Is that something that you actively tried to predict? One way to do it is just to look at the recent past and say, firm XYZ has had a recent trend of consistently paying down debt and so we think that's going to be a predictor of propensity to continue to pay down debt. Or is it more complicated and nuanced than that?

Dan: [00:33:38] To go back to forecasting, I think that investors have to multiply importance by knowability. Something like, how fast is the company going to grow over the next five years? Very important to your outcome. How knowable is it? According to most academic literature, not knowable at all. A company that has grown above the median for the past three years has about a 50% chance of growing above the median next year. It's just pure chance. Now deleveraging is not only very important, because if you can pay down debt, obviously that's going to accrue to equity, but it's also knowable. If you just said, "Let's look at all firms that paid down debt last year, what percent of them will pay down debt next year?" The answer is 60%. That's a lot better than 50%.

That's a great number. It is a very persistent phenomenon. Just looking at firms that have paid down debt in the past, gets you a long way towards predicting next year. Now, we actually use just a simple Bayesian boosted tree algorithm, where we took all the US data back to '64 and said, all the statistically significant factors that you would look at or I would look at, asset turnover and net debt to enterprise value, market cap, price, momentum, etc. Plugged that into a machine learning algorithm and said, "Hey, show us whether you can improve on that 60% accuracy rate?" We see in our tests and we've done this out of sample, and we've also done it in live trading, we can hit probably about 70% accuracy by going more complex than just looking at historical debt pay down. There are other predictors that help shade that. How much absolute debt, for example, firms that have had sharp drops in share price tend to be more likely to repay debt, etc.

Predicting a Firms Ability to Deleverage

Patrick: [00:35:21] I think about the process that you've laid out very transparently in the work that you've put out there, as a couple of simple stages. One of them is just the ... Obviously, you needed to arrive at these variables that you felt were important, we've talked about those. You use those variables to get to a small subset of global equities that seem to exhibit these characteristics that mimic what used to make private equity so successful. But then from that point, you're winnowing the portfolio down more and one of the things that I thought was most interesting was this grid that you showed, basically explaining how often you had and your team has added value on top of just the purely quantitative screen. Talk a little bit more about how you do that, how you're diving into these companies, how you think about forecasting within there, and whether or not you've added any value through that additional layer?

Dan: [00:36:08] This is something we track really closely because after we do all of our processes, our quantitative process, we don't just take the top 40 ranked things from our quantitative work and invest in them equal-weighted. We actually go and say, "Okay, let's go, I know that all the quantitative work we've done says this is a good opportunity. Let's just go read the financial statements, let's check it over, let's make sure we understand it, let's read some of the earnings call transcripts, and see if there are any red flags that would really change our perspectives on this business, in a big way, relative to what we know about the company from our quantitative work." Then second, I think, in addition, we're also saying, we don't necessarily want to equal weight everything, because, in deep value, I think that you really want to average in and average out. You want to move slowly because oftentimes big price movements, which drive valuations are also signals of future fundamentals. If you see a stock that's dropped 50%, most likely the next quarter's earnings are not going to be too hot. You really want to wait a quarter or two quarters or even three quarters to get a full position and to make sure that you're not buying on a bad signal, which is, LTM financials relative to market cap today. I think between those two things, we then track, if we just had bought the top 40 equal-weighted, would we have done better? Our hypothesis is, we're going to try to do better than the top 40 equal-weighted through those two methodologies.

But I think a lot of evidence from Paul Miele, from others suggests that it's really hard to add value relative to a simple algorithm. Are we able to do that or not? We've been tracking it for the past three years and we found that about 70% of the time, we're right. We can add value relative to our simple screen. I think part of that is the weighting and timing and how we buy and sell things. I think another component is just, I think pairing a fundamental logic. We know what we're looking for, we're looking for small, cheap, highly levered firms that are going to pay down debt, and that are not falling off a cliff or are going to go bankrupt next quarter. Actually, when you look at some of the things that score most highly, the smallest, cheapest, most highly levered businesses, if you looked at our global screen today, the number one thing would be a small-cap Canadian mining company that trades at 1.2 times EBITDA. It does not take long to dig into that thing to find out that you do not want to touch it with a 10-foot pole for about half a dozen reasons. I largely think of what we're doing as sanity checking the quantitative work. It's more algorithmic in some sense than it is. We're certainly not doing DCF models or other crazy stuff like that, or saying, "Well, we met with the management team and we looked in his eyes and we saw a hunger for making money that we just knew we had to back him." Or some of the other stuff that seems insane but a large number of fundamental investors actually think works for some reason.

We know what we're looking for, we're looking for small, cheap, highly levered firms that are going to pay down debt, and that are not falling off a cliff or are going to go bankrupt next quarter.

Patrick: [00:38:59] With respect to the Canadian mining example, I think it's funny and interesting that you have been able to add value, I used to go through this exercise where for new names that would come into our screens, I'd go read, as much time as I could allocate, which often probably wasn't enough for this to be a super-serious exercise. But I would read the historical 10-K's for companies and try to just give like a for fun subjective guess as to whether or not this company was going to be one of our better performers. I was virtually always wrong.

I think it says something about the, that was largely based on my read of the 10-K and the language etc. That this value factor is so often predicated on the pessimistic outlook being wrong or the overly pessimistic outlook being wrong and it makes me even wonder about the Canadian mining stock, like yeah, it seems like a disaster but when we look back every year or every quarter at our attribution, oftentimes it's the stocks that seemed like the greatest disasters that deliver the most incredible results. I just think that's such an interesting exercise to go through.

Dan: [00:39:59] Yeah. I think In our case, another way we looked at it, is we looked back at every quarter for the past three years, what we've done is we've forced ranked our portfolio. What do we think subjectively was the most attractive opportunity? What do we think was the worst? We found actually very little ability to distinguish between say, number one and number 30. But at the bottom end, the stuff that we really didn't like, actually did slightly underperform the rest of the portfolio. I think, really, what we're doing is we're saying, "Hey, I don't think what we're doing is trying to say, Oh, I know people are really pessimistic about this company because they think that pulp prices are declining and capacity is coming on in China or some really complex thing."

We're just trying to say, Hey, is there anything… You read the 10-K and you say, "Oh, I didn't realize they'd already breached their covenants," or "Oh, Holy smokes, all their maturities are due in a year and anyone who could have refinanced would have." Or "Gee, I didn't see that they actually lost their biggest customer and that's a 20% hit to EBITDA, so it's actually not as cheap on a prospective basis as it is on an LTM basis." It's much more simple things like that, rather than I think, if you train your mind I think to say, we are fully in line with what the screen is looking for. We have a clear view that we want to buy things that are not going to go bankrupt and if we can identify those things that are going to go bankrupt through whatever means necessary, we're going to do it. We think there's some ability of humans to look at a company and say, "Gee, that thing is on a path to bankruptcy."

The Global vs US opportunity set

Patrick: [00:41:29] I think one of the most interesting questions prospectively for investors is geography. I'm talking, specifically about public markets. But I suppose a lot of this logic could be applied to private markets as well, which is looking forward, how would expanding our universe to a global or international opportunity set versus the US opportunity set where I think we have our home bias, where the returns have been best since the financial crisis with the S&P crushing everything. How do you think about the global versus domestic opportunity set? What things do you think are good about it? What risks concern you? I'm fascinated by this question as we think about returns going forward.

Dan: [00:42:06] Yeah. I run a global fund and a Japan fund. I don't run a purely domestic US strategy. I think, to me, it always seemed, if you could look at 15,000, equities and you can buy them on your brokerage account, why would you limit yourself to the 3000 that happened to be in your country that you happened to invest in. Unless there's a very solid reason why a company being headquartered in the US should be predictive of future returns. I didn't really see a reason why there should be. I figured let's just go wherever the opportunities are global. I think broadly today, today personally, our global fund's about 40% in the US. We still see a lot of opportunities in the US and about 35% in Japan, which is a really interesting market for what we do. Then the remainder in emerging markets in Europe.

I think Europe is a little bit of a harder place today, for us to find opportunities both because of the absolute number of companies in Europe. The opportunity set is more limited and few of them are levered and high yield spreads in Europe are so tight that, it's just hard to find great value opportunities in mainland Europe. There are a bunch of good ones in the UK, but in France, Germany we almost have no exposure to. Then I think in terms of which geographies really do generate, maybe surprising results or where the country of geography actually does predict outcomes. One of the most interesting things we've found is that if you look at Japan, and specifically to the Japanese Keiretsu system, the bank, government, company, cabal, whatever you want to call it.

The way that their financial system works, essentially, they will not let public companies go bankrupt. For a strategy like ours of buying small, cheap, highly levered things, and then trying to avoid the ones that do go bankrupt, we can basically buy anything in Japan, because nothing is going to go bankrupt, except for maybe one out of 3500 companies a year or something. For us, we love Japan because it's a much lower risk way to execute our strategy. It's a place where valuations are still very low and there's a large, large opportunity set. There are 3500 publicly listed companies in Japan, so you have almost as many companies to choose from in Japan as you do in the US, which is just great from a quantitative perspective in terms of being able to find the things that meet for us a very specific set of criteria.

Patrick: [00:44:22] Seems like one of the most interesting markets in the world, not only in terms of maybe the opportunity set today for the reasons you just laid out, but also for its history. It's just such a difference, you mentioned Keiretsu and I think Zaibatsu is the other term, where you've got this interesting emphasis on market share versus profitability and the interrelated nature of the businesses, the conglomerates. What was it that originally drew you to Japan as an interesting source that led you to launch a standalone strategy there?

Dan: [00:44:50] Initially, Patrick, and the way my mind works is I just saw a bunch of cheap stuff there. As a legit, there are so many cheap companies in Japan, it seems like a place I should look into and so when we'd done our US backtests of our strategy so, "Gee, I'm curious as to whether this works in Japan. Man, there're so many cheap opportunities there, why don't we test it?" Ran the whole backtest and I got the results back and I actually sent it to a friend I worked with at Bridgewater and he wrote back and said, "Dan look, great, you've replicated this other sample, but you messed it up. The data is totally BS." I said, "Well how did I mess it up? I can't see any problems." He's like, "Well, I don't know but look at 08, the volatility on this thing is like half that of the Nikkei and that's just impossible. How could, leveraged small value be less volatile than the broader large-cap index? It just doesn't make any sense."

How could the volatility be, 17% standard deviation, which I think what we found. As we dug in, what we realized is, it was all about these bankruptcy dynamics. Without bankruptcy, why would a small levered company be riskier than a large public company, when you have explicit support from the banks and the government to promote stability and to promote small business, you essentially have this backstop which the large exporters don't necessarily have. They have big capital inflows in, big capital outflows out. They're heavily dependent on external business cycles. They're way too big for a small Japanese bank to buy a few shares to prop up the stock price. But, you go into small-cap land, and you go into the firm's that are levered, it's a really different world over in Japan.

For us, we also thought, I think the problem, that there are problems with investing in leveraged in small value generally is that it's really volatile. If you look at, your philosophy and mine is that in order, you help people really understand what they're doing and really understand how that volatility works in order for them to make money in a strategy that exploits small value or exploits leveraged small value in particular. In the US, you're just going to see a huge amount of volatility and that's just not right for everybody. I think being able to say, "Well, if you like small value, you like levered small value, but you don't like drawdowns and you don't like volatility, do it in Japan, where you'll have a much more cushioned experience on the downside."

Patrick: [00:47:04] You mentioned earlier this interesting observation that it was very hard for you to force rank numbers one through 30 out of 40. But you could maybe find some information in the absolute worst 10, we found something similar in the, just purely quantitative way that we do things that, everyone talks about quality, it's such a nice word. We're going to get to Porter's five forces here in a minute, which is going to be a fun conversation, that's a little bit different. But the general consensus seems to be that quality is a good thing. You want to own better businesses, for the long term. What we found is that nah, like it's maybe a little bit true. Like not really, what you really want to do is avoid the absolute worst quality stuff. That there is some really useful information in that left part of the distribution.

But they're like really high-quality stuff doesn't matter all that much. But one of the interesting things that we found in this recent period, is if we could go back in a time machine and take off some of the factors that we used to strip out or we view as like super irresponsibly levered companies. This would include companies that have a lot of leverage, but that are in the process of adding a lot more. That if we could just turn that off for this cycle, we actually would have done a lot better. That companies that have judiciously used debt and levered up, have done really, really well.

I'm curious how you think about that in the context of the future specifically with interest rates. Most of the period that all of us quants used to study equities is a secular declining interest rate environment. There are of course, pockets of rising rates. There's the '70s, it's not just one direction. But I'm curious how you think about prevailing interest rates, whether it's something you use as an input or something that concerns you looking out for the next 10 years let's say of your strategy?

Dan: [00:48:41] Yeah, so we went back, and we looked back to 1964. We did a few different things, we looked at the correlation between, one-year returns and every different interest rate, Fed funds rate, one year Treasury yield, five year Treasury yield, 10 year Treasury yield. We also looked at, not sure the exact number I'd have to look, but maybe a dozen or 18 or so periods, where interest rates rise over 1% over a year or two. If you look at both of those types of environments, and you say, "Okay, well, how did that correlate with equity returns? How did that correlate with a small value premium? How did that affect levered small value in particular?" What we saw is that there's no correlation really, between interest rates and equity returns.

Actually, small value appears to do quite well in rising rate environments and leveraged small value does not appear to be penalized in rising rate environments. I think that's just the interest rates as they rise or fall, they often rise or fall, they rise in correlation with good things happening, like rising growth or for equities, rising inflation, and they fall obviously when things get bad. If you layer those two things together, it's really hard to find any useful signal from interest rates. I think that said, what we find is that obviously the borrow cost and the refinancing risk of companies is cyclical, and it's cyclical and the much more volatile time series other than interest rates is actually high yield rates and the spread between high yield and the prevailing interest rates.

What we find is that anytime that high yield risk spikes when you go from historical average of, 3 or 4%, high yield premium, and all of a sudden in a year rates go from, the high yield spread goes from 3% to 9%. That's going to be a really bad time, a really painful time for levered public equities. For us, we are just cognizant that anytime that the high yield market panics, levered equities are going to panic even more. We just have to design our strategy in the US and Europe to be full cycle to make sure that investors are not going to sell at that one year out of five when the high yield market panics and that they live, because the rebounds from that are very quick. It's just a liquidity-driven thing.

These are liquidity-driven panics where people say, "Oh, my gosh, nobody's going to lend to a company ever again," and of course, 12 months later, they're lending to companies again. These things are always short-lived. But dealing with that volatility is one of our core business issues. Then I think if you go over to a place like Japan, where there is no high yield cycle, and interest rates have been, zero for 30 years, you don't see that risk or that volatility. But in the US and Europe, you really do.

Long Duration Capital

Patrick: [00:51:19] How do you manage that on the business side? Do you lock people up?

Dan: [00:51:22] Yeah. We only accept locked up capital, it forces a very productive discussion. If people are willing to lock up their capital for three years, we generally think they're aligned with us on understanding that this is a long term thing, and it's going to be volatile. If they say, "How, gee, well why do you have that lock up?" But aren't these underlying firms quite liquid? I'm going to say, well it's not that the firms aren't liquid, it's that, we want to make sure we're aligned behaviorally, to make sure that we can make money across a full cycle.

I think that the Hippocratic Oath of investing to some extent is don't lose people money. The easiest way to help people not lose money in equity markets is to extend their timeframe. If you just run bootstrap simulations on US equities or small value equities or levered small value equities, doesn't take that many years to dramatically improve the probability distribution of outcomes. But people think, in such short term, they think in quarters or years. If you think that way, it's going to be really hard to make money in some of these more factor-based strategies.

Patrick: [00:52:25] It's remarkable how uncreative the industry has been with fees. How we've learned certainly in the behavior gaps that exist in public markets, where just every single study you look at shows, people just make dumb timing decisions that hurt their returns. Selling out at the worst time and buying when stuff's expensive. I wonder why that's not a more common thing. It sounds like when you were describing Buffett's strategy of, "Investing in common equities with insurance flow, that sure sounds risky." It seems like maybe we might look back in 20 years and say, how dumb was it that we didn't force some investors to lock up their capital, especially those that can afford to do so with perpetual time horizons? It seems like a really interesting way of aligning incentives, I love it.

Dan: [00:53:06] Yeah, and I think it's also funny, just to get back to the beginning where this discussion started which was private equity. If you talk to institutional allocators, they say, "Well, what do you like about private equity?" And say, "Well it's just that they're really long term thinkers, it's long term holds, our money's locked up for 10 years and it's just great. We think it's worth paying two and 20 for the privilege of having our money locked up for 10 years. They say, "Well, what about locking your money up in a really smart, factor-based, small value strategy, would you ever do that?" And says, "Oh, no, no, no we would never do that. Why would we want to lock up our money? We hate lockups." You say, "But I just thought you said you wanted to pay higher fees for the privilege of locking up your capital in private markets. Walk me through why you wouldn't want to do that in public markets?"

I say, "Well, public markets are so short term oriented and the private guys are long term orientated." I say, "Well you give them 10-year capital. Of course, this upsets their long term oriented, and I think it's funny, you just think of the incentive effects and how that changes. Private equity in some sense has the perfect wrapper for an equity product. That wrapper is a 10-year lockup with quarterly valuations that are subjective and based on the manager's opinion of where the portfolio has worked. That's just perfectly designed to behaviorally adjust for the problems that most investors face which is buying and selling the bad things, buying the things that have gone up, switching your money around too much, etc.

That in some sense, the straitjacket of private equity is very good for these institutions, and the lack of transparency on interim valuations is also historically been very good. But I think where that becomes worrisome is if they start to do bad things, the results of those bad things won't be seen for five or 10 years. Investors can fly blind into a very risky environment where they're not getting the constant feedback that you'd get in public equity markets.

Patrick: [00:55:04] One of the things that I'm sure you've thought a lot about, and certainly we do here as business owners and managers, is the idea of competitive advantage. Something that we can do uniquely well relative to the peer set and sustain that through time to have a real successful business, which brings us to Porter and what you call the modern parable of five forces. You wrote a long piece in Institutional Investor talking about the lack, this has been the theme of our conversation, the lack of empirical evidence for the five forces framework and some of its predecessors. Maybe you could start by giving an overview of your view on this widely accepted paradigm for thinking about industries and businesses and competitive advantage. Then we can talk about maybe some alternatives.

Dan: [00:55:49] Yeah, so it's interesting, the story of how Porter's five forces came about, was that in the '60s and '70s, there's a prevailing school, it's called industrial organization. It was a subfield that looked at how does the structure of different industries affect the performance of firms. Broadly, the theory was that the industry really mattered. Different industries had these structures, and the structures of those industries affected how firms performed, and within that, essentially, the higher the market share of a firm within its industry, that the higher their profit margins would be. The more market power they would have in that industry to dictate prices, to do bad things like keep competitors out, etc. That was called the structure conduct performance theory.

It was actually the basis for most of the antitrust legislation in the '50s and '60s, which said, "Gee, we got to stop monopolies because gee, if a company gets a, if they take a 30%, market share company, they buy another 30%, market share company they'll have 60% market share. They'll use that market power to screw over customers or suppliers or whatever it might be." That was really the fear. Porter emerged from that world and he studied under a few of the foremost thinkers in that structure, conduct performance field. He comes to Harvard Business School at a time when Harvard Business School's strategy curriculum, was SWOT analysis, Strengths Weaknesses Opportunities Threats.

You draw these four squares, and you'd say, "Oh, well, this company has strength in this and a weakness in that." That was how they defined strategy. Porter looked at this and said, "Well gee, that doesn't sound very rigorous." It sounds a little bit silly. How can you possibly get any useful insight from doing a SWOT analysis? He said, "Well, why don't we take structure, conduct performance and have students study industry structure, and study how industry structure and how market power can shape a company's profitability. That's much more rigorous." He came up with this theory of the five forces, which was really saying the power a company has over suppliers, over customers, of competitors, barriers to entry, etc. In each one of those cases, the power you have over a supplier, in essence, is your market share.

How much market share you have is going to dictate how much power you have over your supplier and in the same verse your customers. In effect, it's just a reframing of the simple idea that higher market share is going to lead to market power, which is going to allow firms to bully suppliers or customers or competitors and thus earn higher profit margins. I think all this sounds really plausible. I think we all intuitively, would agree with that. If you control the market for x, you should be able to drive prices higher or something. Certainly, a company that's the only company that can produce something should earn some higher-margin or something. It makes perfect sense.

But what happened is basically a bunch of the Chicago School economists, some of these really famous guys, Bork and Posner, and others started saying, "Well, is this really true? Does industry structure actually dictate performance? Does higher market share actually translate to higher profitability? Are any of these nice stories actually empirically true? They started running all these industry concentration profit margin studies and they found that it's not true, it's not true at all. There's no relationship and industry as a factor does not predict almost anything about a company. A company's market share and its industry doesn't predict almost anything. There's just no correlation.

Starting in the '70s, basically the antitrust court started to say, "Well gee, we can't use this. We can't just say because a company has a high market share, it's going to be bad because there's actually no evidence for that. We're going to have to start using a different methodology, which is to actually look at the impact on customers." Actually, the field of industrial organization too said, "Well, gee, based on the studies, it's clear that industry does not dictate structure. Industry structure does not dictate conduct or performance of firms. We're going to actually stop doing these industry studies." All of that was happening, basically a huge intellectual demolition of this whole bad theory was happening at the Same time Porter was making this the heart of the Harvard business school curriculum in the early '80s. What's shocking is that for 30 years, maybe longer, this is the centerpiece of the strategy curriculum.

People are learning market shares, market power drives conduct, drives margins and it's just been wrong. It's been empirically wrong since the '70s. I think for investors, it's even more worrisome because I think, as we talked about earlier, anything that increases your confidence without increasing your accuracy is the most dangerous thing in investing. A theory like Porter's five forces, which says, "Buy the winners, buy the companies that are really great businesses, and you're going to do well because they have power. It's going to lead you to come up with elaborate intellectual justifications for buying large-cap glamor stocks." By and large, that is not a strategy that works.

Dan's Thinking on Competitive Advantages

Patrick: [01:00:51] It's so funny when you look at things like net margin, it's just simple factors, which again, I think you said earlier, there's a lot of things that seem logical and very few of them actually mean anything. Net margin is one of my favorite examples, something we get asked a lot about as like a quality factor or something else. Sure enough, you look at the data and it's almost irrelevant. It doesn't seem useful in virtually any way at all. But it's something that people talk and think a lot about. It's remarkable how long some of these things can last. I wonder if you think if there's anything redeeming about the five forces framework, maybe not for investors but for managers.

Do you think that the framework is a smarter, interesting way, like let's say you, for your business? Are these things that you are thinking about, that your behavior might be different because you're thinking about them? Or do you think about competitive advantage in a totally different way? If so, well how do you think about it?

Dan: [01:01:41] Yeah, well, I think it comes back to this idea of forecasting, which is that I think that predicting the future is really, really difficult. I think most efforts to plan things are bad because those are not going to come true, other things are going to happen. So the more time you invest in planning, and saying, "Well, gee, let's use this strategic model to dictate what we do," it's just a really bad way to make decisions. I think there are much better ways to make decisions. I have a very simple idea, which if I can produce, beautiful, excellent strategies that beat the market, I'm going to have a great business.

By the way, it's a heck of a lot of fun to go look into the market and try to figure out, how do you build these strategies to design them to do the research, to prove that they work, to tell people about them. It's a huge amount of fun, and I love doing it. I think that when you love what you do, and you do it really well, maybe you make beautiful chairs. What you derive meaning from in life is that you make the most beautiful chairs and people love the chairs, and they buy them and maybe there's no great strategic plan. There are a ton of other companies that make chairs and so you might not have a high market share or high competitive advantage or anything like that.

But if you love what you do, and you do it well, and you make your customers happy, I think that's much more satisfying than these elaborate plans as though you're sitting in a war room in World War Two. Plotting out tank movements two years in advance, I just don't think it's the right way to act or to make decisions. I think from some of the critiques of Porter's Five Forces and these strategic planning curriculums, I think are so good. It's just that, there's the rise of the managerial thinking that so distanced from the actual thing or art or profession or method. The actual thing that you're supposed to be loving, doing and doing well and doing for the customer.

But if you love what you do, and you do it well, and you make your customers happy, I think that's much more satisfying than these elaborate plans as though you're sitting in a war room in World War Two.

Instead, you're doing it because of your PowerPoint presentation, Beynon & Company came in and gave you a 50, PowerPoint slide presentation about how you need to segment your market differently and act to increase your score on one part of your Gantt chart or something. Who wants to live their lives that way or run their businesses that way? It just sounds so dull and unsatisfying.

Patrick: [01:03:50] My guess is that you're not a fan of the interview question, where do you see yourself in five years?

Dan: [01:03:54] No. It's funny because I'm going back to lecture at Stanford to Charles Lee's class and talk to the students there and point out the craziness of the things like the DCF model. You've just built this model, which forecasts cash balances, income, profit for five years in the future. Does any single one of you want to offer a two decimal point figure for how much in revenue they're going to make in 2023, what their net income on their tax return is going to be in 2023, and how much money they're going to have in their bank account in 2023? Even what industry they're going to be working in in 2023? You are the world's leading expert in you and if you can't forecast that, what in heaven's name makes you think that you can forecast that for like a complex business like Microsoft? It's just the height of idiocy and hubris.

Patrick: [01:04:41] I always thought that the far more interesting and eye-opening interview question would be to ask people, what are the things that they do every day or every week? Another way of asking, what is your personal process? I'm curious what yours is. What are some of the things that in pursuit of interesting investment strategies and sort of the analysis that you clearly love to do, what are the things that you do either daily or weekly?

Dan: [01:05:04] Yeah, I think the first and foremost thing I do is just read a lot. I think we are so blessed with things like Google Scholar, and Amazon. I have all these books on my shelf. I can reference, I've got what works on Wall Street. I've got Wesley Gray's book, Quantitative Value. I've got Tobias Carlisle's books. I have all these books that I can read and learn what the great minds of investing are thinking, what all this empirical research is showing? Then you can come up with questions as a result and you can think, "Well, gee, I really wonder, does market share drive profits?" You go to Google Scholar and you say, market share profits, relationship, Enter. Or Meta-analysis, profitability returns and Enter. The whole world of knowledge is open to you. I think if you just bother to spend time reading these things, and studying what other people are putting out, you can accelerate your personal learning so dramatically.

I just think that ultimately, if you read even 50 pages a week, over a year and then over 10 years, the exponential amount you'll have learned relative to what people who don't read or don't bother to study stuff is just massive. I think not just reading within investing, I think there's obviously a lot of great stuff in investing. But I think a huge amount of interesting research is being done in behavioral psychology in the Kahneman, Tetlock world. All that research is fascinating. I think, reading stuff also, I've been reading a lot in evolutionary biology recently. Steven Pinker, E.O. Wilson, some of these guys have just incredible data-driven insights that I think are so valuable. I think reading a lot, and then I spend a lot of time just walking and thinking and I think being a more quantitative person.

It frees you up because you're not doing all these things that waste most people's time, like creating PowerPoint decks about competitive advantage. You have time and I think, taking a nice walk and just thinking about things, and are there any ideas that I might have as I reflect on the stuff I've read. I think that largely, it's nice because those two things are also pleasant to do. I enjoy reading, and I enjoy going for walks, and I enjoy making bats at our company. I enjoy doing a lot of empirical research so it's an ideal life from my perspective.

Patrick: [01:07:11] One of the mantras we have around here is to never confuse activity with effectiveness. We couldn't agree more on reading and walking, I think they're probably, that combination is an incredibly potent and powerful thing that seems to people like you might not be working as hard. But in fact is a far smarter way to work. I'm curious looking at, when you look at the markets, we've talked a ton about private equity, its prospects, leveraged small value public equities. Are there other areas, whether it be asset classes, corners of these two markets we've talked about, that have piqued your interest recently. I'm curious as you look out and are thinking about the world and where opportunities maybe, back to that picking the right reference class. If there are other areas of deep interest for you right now?

Dan: [01:07:51] It's funny, I've almost thought about writing an article that said, why most good ideas don't work or something. I feel like I've spent a lot of time diving into things mostly just to reject them or say, "Well, I don't know." One that's caught my eye recently is if you look in the public equity markets, and I think because I'm thinking a lot about a lot of the companies in my portfolio that think we do, do a good job of picking the ones that are, or eliminating the ones that have low expected returns and that aren't, are sort of false positives. I spent some time looking at companies, I'm just running screens of companies that look like to me, they're going to go bankrupt, and then from there went down the pathway of looking at stocks that seem likely to be fraudulent.

If you look at today's market, there's so much fraud and especially in some of the US small-cap, biotech, and tech in particular. There are a lot of things that look like frauds, and they've got these huge market caps and no revenue, no profits, and they're promising to use a spray gun to cure cancer with gene editing or something. You're just like, "This is nuts. How does this have an $800 million market cap?" But what's interesting is, even though I've made those observations, that I can run a lot of these screens and see things that obviously don't look attractive. Anytime I run a quantitative screen on this or a backtest on any of the rules I've come up with, even though it generates alpha relative to a negative market index, they all lose money, which I think is interesting because I like making money.

So losing less money than other hypothetical alternatives is not overly attractive to me. But it's been fun looking into it. But even though I probably I'm not going to do anything with this information, it has been fascinating to look out there at all the things that predict bad outcomes. Yet, even with all the things that can predict bad outcomes, it's still really hard to make money shorting things for any number of reasons.

Patrick: [01:09:39] I forgot to ask earlier, when we were talking about the key variables, about small-cap in particular, one of the things that we always think about is capacity of strategies and having this philosophy that we should always forsake higher capacity for the sake of higher alpha. We just always want alpha instead of assets. I'm curious how you think about that because my guess would be that the test of an unconstrained version of this that's not just small-cap, but would be allowed to go up into medium and large-cap stocks would also do extremely well. I'm curious about the strength of your conviction in that part of the three-part stool, I think value and levered, we've talked a lot about those. But what about that idea of small and why not go upmarket?

Dan: [01:10:16] Yeah, I'm with you, Patrick. I think size, at least in our research, especially in Japan and outside the US, and more recently in the US does not seem to be overly predictive. We don't weigh it very much. But we do say we do leverage small value because most of the levered value opportunities are small so it's a good descriptor of what we do, even though it's not a driver of our decision making. We don't necessarily think a 200 million market cap company is automatically going to outperform an $800 million market cap company.

I think when you go up, I love running, these beautiful, niche capacity constrained, tiny little strategies because I know that there's a huge amount of alpha to be made in them. I think my view is that, hey, once we fill up the capacity of these strategies, we can run levered small value. Would there be an opportunity to run levered mid-cap value? I think, there might be in the future. But I think we have a while to go before we do that.

Patrick: [01:11:11] What have been some of the most, you mentioned this idea of Google Scholar and reading. I'm curious if there was a person or a source that you've learned the most from that might be surprising to people recently?

Dan: [01:11:20] The single most influential thinker to me is Philip Tetlock. I think his book, Expert Political Judgment and then more recently, Super Forecasting and he's one of Daniel Kahneman's students. I think that investors, we are forecasters. That is our job and we have to be reading the forecasting literature. Tetlock in particular has done so much good work on how to make better forecasts, what bad forecasts look like, about how to make good decisions about the future. Even he does things like, what's the duration of a forecast? Like how accurate, how far into the future can our forecast see?

I think I have just learned so much from studying his stuff, and then comparing it to every part of my own process and saying, "Well, gee, if Tetlock says it's nearly impossible to predict outside of a one-year horizon, certainly we should be only thinking, and why would we ever think in two or three years or gee," just focusing on the use of base rates. Even Tetlock says, interestingly enough, in his Super Forecasters study, he actually does not just stop, his super forecasters don't tend to just stop at the base rates, they actually do make individual more qualitative adjustments at the end after they've finished doing a base rate assessment.

He's found that that does work. I think, that is probably the field that I've learned the most from and I think it's the most contrarian too. I think so few people are familiar with the forecasting literature and so much of our industry is tied up in forecasting, sometimes unwittingly that it's probably the single most impactful thing I think any investor can read.

Patrick: [01:12:55] What was it like writing your book? This is something that's totally outside of the field of investing, maybe describe what the book was, what got you started and whether or not you enjoyed that process?

Dan: [01:13:04] Yeah. I wrote a book as my senior thesis, I studied history and literature of the 19th century American South with a focus on slavery in college. I wrote my senior thesis about a slave revolt in New Orleans that was actually the largest slave revolt in American history. I think what interested me about it was this sort of, I think when you look at American history, first and foremost, America is an absolutely amazing country. One of the most amazing enlightenment, reason, the rise of capitalism, free market, democracy, those forces have driven such a huge amount of human progress. These are some of the best ideas humans have ever had. I think it's very easy to look at American history therefore and write this narrative of tremendous progress and to do so accurately.

But I think some of the most interesting literature, the most interesting things from a moral or philosophical perspective are to look at those places wherein the service of that progress, moral compromises, or great sins were made. I think if you look at the American South in particular, you see that in the greatest relief, where tremendous economic progress is coming at the cost of literal enslavement of people, of a lot of brutalities. Then to see those enslaved people rising up and trying to overthrow that system. But doing so in a way that was obviously incredibly violent, that's the only way to do it, but destructive.

To think about those tensions between good and evil, economic progress and slavery, between a violent destructive uprising, but then also the concomitant brutal violence of slavery. I think it's just such a fascinating place to study the human condition and what drives people and the trade-offs that this country has made and that we all make. I forget who said it, but that the line between good and evil passes through every human heart. I think there's no better way to look at that than in some of these more graphic and interesting episodes and I think the slave revolt in New Orleans was one such.

Patrick: [01:15:09] I'm curious what details looking back on that research, most standout?

Dan: [01:15:13] Yeah, so it's funny. I approached the study in a very similar way to the way I invest. If you look at the history of the slave revolt, what's interesting is that there's no, none of the slaves that have written down anything that they did. There are no letters, no diaries, they were illiterate so we actually have no way to know what they were thinking or doing. So constructing the narrative of what happened in the revolt was actually quite difficult because most of the records we had were actually wills and testaments, the land records that said, "Well, I had 80 slaves five years ago. Now I have 20." Court cases, which were basically these lists where they said Kook was a 23-year-old slave, purchased for $800, who used a machete in the cane fields and he was executed on x date for insurrection.

What I did to decipher this is, took all of this data, put it into Excel, into this big database, where I had aligned for each of the individual participants in the revolt, where they came from, what we knew about them, where they came from, from those property records and legal records. Then took those and then I got old land maps, and then from the time and I shaded in if there were 10 slaves or more red, five to 10 orange, less than five, etc. So you could actually see visually mapped where they came from, and then marked each event where we knew, where it had happened on the old land maps. Then used Google Maps to say, "Okay, well how long would it have taken to walk from point A to point B?" Etc. So we know that if this happened at 10:00 a.m., this other event which we know from the legal records happened here must have happened at 5:00 a.m.

It was this huge process of detective work and using, empirical tools or quantitative tools, in some sense to unpack history. Then once I had the bones of the story, the architecture of it done, to then go back and say, "What would it have looked like, felt like, smelled like, how would they have felt? What their emotions had been?" And to paint that by using other contemporary sources. Really the process was, although, writing about history, probably a process or a thought process that is not dissimilar from the way I approach investing.

Patrick: [01:17:20] If you were forced to write, that's a fascinating process, first of all, what a neat story. If you were forced to write another book today, what would you write about?

Dan: [01:17:27] I've been thinking about it, is there a theme to the pieces I've been writing about Porter's Five Forces or Modern Finance Theory? I'm working on a few others but I think if there's one theme to them, it's, I think, are two themes. One is that, most good ideas don't work. I think the second would be that experts who are often purveyors of good ideas that don't work are often no better or worse because they're more confident than laymen armed with common sense and logic. I think it would be fun to write a book, maybe, maybe not to bonfire the vanities but bonfire the bad ideas or something and just talk about, because I think there's a great study.

I forget if you posted it on Twitter or someone did that, basically, they looked at financial advisors, and many financial advisors make horrible decisions. But they then looked at what the financial advisors do with their own portfolios, and they actually made the same bad decisions that they made for their clients. It wasn't that the financial advisors were out screw their clients, far from it, they were doing the things they thought were best, they were just making bad decisions. They had bad ideas. I think that's a better picture of a lot of the parts of Wall Street. It's not these people are bad people, they're trying to screw people, it's just that they are operating from frameworks that don't work, informed by ideas that don't work, believing theories and philosophies that don't work.

I think it would be fun to continue to expose some of them and then to offer alternatives that are based on reason and logic and empiricism and the scientific method, which are things that anyone can access. Anyone can say, "Hey, what's the evidence for that? Let me weigh that evidence and see whether it makes sense?" It doesn't require you to spend 400 hours studying the vacuum cleaner industry.

Patrick: [01:19:08] Well, my closing question for everybody which you probably know ahead of time is to ask for the kindest thing that anyone's ever done for you?

Dan: [01:19:14] It's such a wonderful question. I think for me, my mother from the age, probably when I was little, barely able to talk until I could read on my own, would probably spend an hour or two a day reading to me. I think that instilled a lifelong love of learning in me and I'm sure it was boring for my mother to read book after book after book. But her self sacrifice and time she spent reading to me, I think, really inspired in me a love for reading, which has shaped my entire life and career. I think that, that was probably the greatest kindness and it was done, I think surely out of love and self sacrifice.

Patrick: [01:19:53] It's a wonderful, wonderful answer. One that's unique. I haven't heard that, I've heard obviously a lot of parents over the 75 answers I've gotten, but I love that answer and that I can so attest to it as a parent myself where it's so easy to turn on a TV or a device of some sort occupy your kid. It definitely is boring at times to read to them, but it's so clearly impactful. What an awesome answer and great place to end. This has been a really fun conversation as I knew it would be, thank you so much for your time.

Dan: [01:20:23] Thank you, Patrick.

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