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This conversation is part of our Wisdom in Books podcast. Every week we inspire your reading with an exclusive author interview or my takeaways from a consequential book on investing, business, or life. Stay tuned for a new release every Wednesday at 3:30pm ET.
I had the pleasure of speaking with Tobias Carlisle about his book, The Acquirer’s Multiple: How the Billionaire Contrarians of Deep Value Beat the Market. Tobias is a well-known investor and author of several books, including Quantitative Value, Deep Value, Concentrated Investing, and The Acquirer’s Multiple. Tobias is also the founder of Acquirers Funds.
The Acquirer’s Multiple is an easy-to-read insider’s account of deep value investing. It shows how Warren Buffett, Carl Icahn, David Einhorn, and Dan Loeb got started in investing and how they go about their craft.
The following transcript has been edited for space and clarity. (MOI Global members, access all features, including ways to follow up with Tobias.)
Tobias Carlisle: The Acquirer’s Multiple came out in late 2017. I wrote it because I wanted a much shorter, easier-to-read, and more inexpensive version of the other three books I had written. To describe this one, I need to go quickly through the evolution of the other books.
I wrote Quantitative Value with Wes Gray, who was a PhD student at Booth. This book came out in 2012. We took every bit of industry and academic research we could find on fundamental and value investment and tested it in an environment we built to see which of those bits of research continued to work and which things had been datamined and stopped working. We looked at things like how we detect financial distress, find earnings manipulation, uncover fraud, spot good businesses, and identify undervaluation. Then, combining all of those things together, we tried to determine how that model would behave. We found that it did quite well.
In the process, I noticed there was this unusual phenomenon that kept coming up over and over again, namely that companies which looked ugliest on a fundamental basis often turned around and started to outperform and did better than companies which looked more attractive on a fundamental basis. I became very interested in why that might be the case. This led to Deep Value, which was essentially an explanation of the mechanics of mean reversion. Why do companies turn around and start doing a little better when they look to be at their worst? Why do companies that are the very top of their business cycle seem to come back to Earth? How can an investor take advantage of those things? In brief, the answer was activists, private equity, and just mean reversion in the underlying businesses. When businesses are at a nadir, other competitors leave the industry, the returns improve a bit, and the world looks a little better for those businesses. At the top of the cycle, the story is similar. If they’re earning very high returns, it’s very profitable to be in the industry, which attracts competitors from adjacent industries. Substitutes come in, so a lot of that profitability is competed away.
With Concentrated Investing, it occurred to me that choosing stocks is about 50% of the battle of investing, and the other 50% is portfolio management. You can compare two investors, both of them great stock pickers, but one does very well and the other not as much, the reason often being that portfolios are created in different ways. The better investors seem to make more money when they’re right and don’t lose as much money when they’re wrong. We interviewed value investors who had 25-year track records of outperformance, and that’s a tiny group. We interviewed Charlie Munger, Glenn Greenberg from Brave Warrior, and Kristian Siem, a Nordic value investor focused on oil and gas.
All these books, which came out under Wiley, were expensive, quasi-academic, and difficult to read. I wanted something that could summarize the findings of those books in an easy-to-read format, and that was The Acquirer’s Multiple. It was written at a fifth-grade reading level, which was really difficult to do. There are no big words, and the sentences are quite short. It’s told with a lot of stories and charts, distilled down so that you can read it in about two hours. You should be able to give it to somebody quite young who’s interested in the stock market, and it will give them a very traditional view of investment. I hew more closely to Graham and Buffett, and the best example of why is because I wrote it as something that might be comparable to The Little Book That Beats the Market, Joel Greenblatt’s wonderful book published in 2006. I really love it. I thought it was a great explanation of what Buffett does in an easily readable format that you could give to a kid. I wanted something comparable. This isn’t for a young kid, but it’s probably for someone who might be at college or in high school and has an interest in investing.
I used Greenblatt’s book as a way to make a clear differentiation between a deep value investor, which is what I do, and perhaps a Buffett-style franchise investor. Greenblatt does a great job of describing quantitatively what Buffett does. Everybody knows that Buffett buys wonderful companies at fair prices, and Greenblatt looks at what that means in a quantitative sense. What it means, of course, is very high return on invested capital. Then he says a high EBIT on enterprise value, which Greenblatt describes as an earnings yield, and I call the acquirer’s multiple. The question is whether a naive computer simulation of some of what Buffett does can lead to a market-beating performance, and it turns out it does.
We tested it in 2011 in Quantitative Value, and we threw everything we could think of to make that strategy underperform. We valuate (which is market capitalization-weighted) the holdings in the portfolio because one of the early criticisms of the magic formula was that it was a micro-cap strategy. We looked at it in an extensive universe. We used the NYSE 40th percentile cutoff, which today equates to about the top 1,500 stocks listed across the various exchanges with a market capitalization cutoff of around $2 billion. These are large, highly liquid companies. Even throwing all of those things at these companies, we also lag the data. It means we took the K data, or the end-of-year data available sometime in the first quarter, and then we said you’re not allowed to trade until June. We’re already using a point in time database, but we’re assuming that all of the information has been disseminated to the market, so it’s not a timing issue. We’re not taking advantage of the January effect or something like that. The magic formula does outperform.
In the book though, we talk about how we devolved the returns. What are the contributors to the returns to the magic formula? The two parts of it are return on invested capital and the acquirer’s multiple. The way we tested, it was about 16.2% compound over the full dataset (1972 to 2017). This compares to an S&P 500 equal weight total return of about 10.5% – 6.2% compounder over a long period of time is an enormous outperformance. The interesting thing though is that if you only looked at a return on invested capital portfolio, so you screen only for return on invested capital and don’t care about valuation, you do about 13.7% compound, which is still a great return. It does outperform the S&P 500, but it is materially less than the combined together. The reason is that the EBIT/EV, the earnings yield, or what I like to call the acquirer’s multiple, generates 17.9% compound of the return, and the return on invested capital detracts from the returns to the pure value, which is why I’m a deep value investor.
The criticism is always that Buffett doesn’t merely buy undervalued stocks with his very high return on invested capital but looks for sustainable high return on invested capital. If you read his letters, you’ll notice that most of time he’s talking about the sources of competitive advantage, the sources of business franchises, and the reason why something is able to keep these high margins and high profitability. Michael Mauboussin has done some great work, which we cover in the book. He can take the top 1,000 companies and rank them all on return on invested capital. Then he puts them into five buckets, and the highest return on invested capital is one group. The lowest return on invested capital is the other group. If we then run that portfolio forward over 10 years, what we see is that the highest return on invested capital companies tend to mean revert down to about the average profitability. What happens is that when you’re buying those stocks, mean reversion is leading the profitability of those companies to fall. Another way of saying it is we’re buying them close to the top of their business cycle and then falling over the following decade. For the quintile with the lowest return on invested capital, the profitability gets better and better over the ensuing 10 years.
You’re buying these companies where, fast forward over the next period of time, they do a bit better. If you combine those together, what you see then is a description of why the value stocks tend to outperform the value plus growth or value plus quality, which is a little counterintuitive. It doesn’t make sense. As value investors, we often think we’re looking for diamonds in the rough, for that really high-quality good business that is trading too cheaply. I think the returns, statistically and quantitatively, are better if you look for companies which are not just undervalued but also closer to the bottom of their earnings cycle.
That’s the book in a nutshell. We go through the mechanics of why that is the case and what Michael Mauboussin has done to identify scientifically the indicia of companies able to sustain high returns on invested capital. About 4% of companies seem to have this high sustainable return on invested capital year-on-year. To give you the punchline, he hasn’t been able to find prospectively how we can identify companies which will have that very high sustained return on invested capital over the following decades. Sometimes I think it’s easier to say, “Let’s just ignore that and try to buy things that are extremely cheap.”
John Mihaljevic: Thank you for that introduction and overview. To be clear on the term acquirer’s multiple, is it just EBIT to enterprise value?
Tobias: What I use is operating income. It’s an almost immaterial difference, but the point of it is that it’s constructed from the top of the income statement down. EBIT is a non-GAAP measure constructed from the bottom up. Buffett says in his letters he tracks the EBIT operating income of the companies in Berkshire Hathaway’s portfolio, so I think it’s a good metric. EBIT is earnings before interest and taxes, so it makes it agnostic to capital structure, taxation payments, and so on. It’s a very good metric from that perspective, but it’s also close enough to the top of the income statement not to be too muddied by all the add-backs and various things that happen as you get closer to the bottom line.
John: Do you call it acquirer’s multiple because it ignores the capital structure?
Tobias: Right. It’s the acquirer’s multiple because that’s the way a private equity firm or an activist might think about it. They can look at that stream of income and say, “We could lever up this company, pay down some debt, or buy back some stock.” They think about how they can change the capital structure, and you want to look at the income streams to do that. It’s the way an acquirer would think about the business.
John: As you said, it is a bit counterintuitive that this single metric would outperform the two-metric approach, where you take into account quality as well. Can you talk about how the data is done or the performance measured? In other words, how often is the rebalancing done of this kind of portfolio? Do you think that if the rebalancing period was longer, the two-factor approach may outperform the single factor?
Tobias: That’s a great question. It’s something we spend a lot of time perturbating, as the academics in the quants like to say, which simply means testing different variations of different lengths of holding periods. The answer is it doesn’t seem to be impacted by the holding period, but that seems to be the natural question. If you were to hold these for longer, does the return on invested capital become more important? The answer appears to be no. Whether you’re buying on a pure value basis or on this combined metric, you get the same rough outcome, which is outperformance for a value pick, on average, over the full dataset after five years. It means that if you form a portfolio today and it’s cheap, you would expect it to still be outperforming after five years, but the bulk of the outperformance comes in the first year. It’s asymptotic. You can imagine the line just gets closer and closer to the market return as you go on until it gets about five years, at which point there’s no difference between the two. It doesn’t seem to matter whether you do that on a value basis or on a value plus profitability basis.
