SIP014: Tobias Carlisle on Deep Value and Special Situations - Sure Dividend Sure Dividend

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SIP014: Tobias Carlisle on Deep Value and Special Situations

Today’s conversation is with Tobias Carlisle, a professional investor and the author of The Acquirer’s Multiple, Deep Value, Concentrated Investing, and Quantitative Value – which happens to be one of my favorite books on investing. Tobias is a Co-Founder and Managing Partner at Carbon Beach Asset Management, a value investing firm that manages portfolios for high net-worth individuals, endowments, and institutions.

Our conversation is wide-ranging and discusses everything from special situations to portfolio construction and the Kelly criterion to an interesting concept called “The Broken Leg” phenomenon. Please enjoy this conversation with Tobias Carlisle.

Full Transcript Below

Nick: I just wanted to start by thank you for being on the show. I read some of your books and been following your work for a long time so I’m really excited to chat with you.

Tobias, you’ve done a lot you’ve wrote some books you have your own personal investor strategy you run that works on your books you’ve been an M&A lawyer. So I thought it’d be helpful for our listeners to start by just recapping where it all started and what originally made you become interested in investing?

Tobias: thanks very much for having me I first learned about value investing when I was at university in Australia. a friend of mine read Security Analysis and Warren Buffett’s letters and he said do you know Warren Buffett is basically the greatest investor alive and you can read all of his letters for free on the internet and also did you know that he runs an insurance company which I found that really odd at the time but I understand why he does now.

I read all these letters online tried to sort of summarize them down I got Lawrence Cunningham book which sort of gets all of his son letters and puts the themes into the same place so you can read the themes at the same time and I read the original version of Security Analysis the 1934 version which is really hard to read and it’s mostly about railroad bonds and they’re very hard going.

I graduated undergrad I went to law school and then I started working as an M&A attorney and a corporate advisory M&A; so it was when i first started i was expecting to do a lot of IPOs. But what happened was the 2000 stock market crash my first day was like April 2000.

Which was basically the very top of the dot-com boom and so then I just I spent most of my time doing M&A; because people just couldn’t raise money anymore and there was this curious kind of phenomenon occurring at the time didn’t really have a name for it. But there were these small investors who would buy shareholdings in these dotcoms that had been absolutely crushed and then they’d have like a 5% or 10% shareholding there’s a lobby to get on the board probably to have it wound up or they’d sort of try and get control and then they use that to buy another one of these companies.

And it was one of those things that I had kind of enough I’d read enough value investing stuff and I was aware that Warren Buffett was kind of a wonderful company at a fair price guy and it was just difficult to see what these guys saw in these dot-coms that were that they had no business.

Also the extent they had a business it was just burning cash but what they had identified of course was that they had raised lots of money and they were trading below their net cash value and so they’d get control and then either buy out all the other shareholders and then have a company that was had more cash in it than then it cost them to buy earn.

Or they’d use that companies are sort of daisy-chain others so I went back to that 1934 edition of Security Analysis and I found the chapter on liquidations and shareholder rights and then I realized what they were doing and so those all those guys who started doing that stuff they eventually became that that phenomenon became activism. and so I sort of started right at the very start of that and I worked with a lot of companies defending activists just because it was a bigger law firm and the companies tended to be bigger companies that an activist kind of grew up.

There was that berm from sort of 2000 of 2007-8 when activism sort of became they went from being kind of individual guys who had a little bit of money to kind of being a little bit more institutionalized and moving from pure balance sheet activism to operating activism and they were trying to get them to fix the business.

And so I was there as a lawyer and I watched it all happen I found it fascinating and I thought if I ever get the opportunity to find stocks like this again if the market ever crashes again in stocks trade by net current asset value, net cash value then I’ll do something about it.

So the next time the stock market crashed was 2007 to 2009. I

launched which was a little blog just looked at classic sort of Graham Nets-Nets where there was an activist involved who was trying to work the company out. And those stock picks hauled in really well over the few years that I ran the blog in 2009 at the very end of 2009 I had a very good year.

I went back to look at the cohort of companies that I could have invested in and I’d sort of gone through and don’t buy this one because it’s burning too much cash, don’t buy this one because it doesn’t have an activist involves, don’t buy this one for whatever other reason, and I looked at all the ones that I could have bought and didn’t buy and I found that they did about three times better than I did over the course of the year.

I sort of started down this process of becoming a little bit more systematic a little bit more quantitative and that’s the that’s the process that I’ve been following pretty consistently since of early 2010.

I call myself a deep value investor so I’m not looking for that wonderful companies at a fair price thing that Warren Buffett looks for I’m looking for fair companies at a wonderful price and I’m trying to do it in a pretty systematic way so to eliminate behavioral biases and things like that.

And that’s so I I run that strategy and managed accounts and a private fund and we will be launching a public fund in the not-too-distant future.

Nick: so this is interesting because you’ve done a lot you’ve blogged at greenbackd you’ve published a few books you’ve doing your stuff at Carbon Beach Asset Management and now the Acquirers Multiple.

So at what point did you decide that you wanted to take more of a long form approach and publish your findings and books instead of through your blog and Greenbackd?

Tobias: at the end of as I was sort of going through that process shifting from being a deep value net net type investor to being a little bit more systematic I was hunting for a book that sort of explained that process I’ve never really heard of quantitative value investing.

I now know that there is quite a lot of literature around and it has existed as an idea for a really long period of time but I just couldn’t find it at the time. the only book that I was aware of which is an excellent book by Jim O’Shaughnessy What Works on Wall Street.

But I had only ever used it as sort of an encyclopedia or to look up what which strategies do best and at the time the version of the What Works on Wall Street that I had hadn’t discussed enterprise value on EBIT dollar enterprise value on operating income. Which I was aware from the early 2000s when I looked at a lot of research that had come out about the activist as being a very powerful metric for finding stocks that were undervalued that we’re going to perform.

And it’s the metric that activists like to use because it’s because they imagine that they can go in and do something with the balance sheet so they’re looking at what kind of operating income are we going to get. And it’s also the metric that private equity firms like to use because they know they can take the company over it in its entirety and manipulate the balance sheet, put some more debt in there for the most part that’s what they’re seeking to do.

But I couldn’t find any book that discussed that metric and I couldn’t find anything that sort of discussed qualitative value more broadly so I had collected all of this research and I wrote on Greenbackd that I was thinking about writing a book with no real idea about how you get a book published or anything like that.

And I got contacted by Wes Gray who he was a PhD student at Booth and he said I have access to this back-testing database at Booth. I was thinking about doing something similar but I don’t want to write it side I wrote the book where as did the back-testing and the result was Quantitative Value and Wes also said I have a contact and we can get it published with Wiley which is sort of the biggest and the best in that in that published in that finance investing publishing area.

So that was sort of how it came about and the result was Quantitative Value which was which came out in late 2012. In the course of writing that Quantitative Value book, I was aware that Joel Greenblatt’s magic formula which everybody knows that’s the he where he takes the Buffett idea of wonderful companies at a fair price and he breaks that down into its constituent parts the way that Buffett describes that you should do that.

Which is to look for a very high return on invested capital as evidence of being a wonderful company and that’s how much money it makes for each dollar invested in it. and then on the other hand to look for a high earnings yield and the way he defines earnings yield is EBIT operating income which was the way Buffett does it on enterprise value which makes sense because you only really you get credit for the cash that the company has and you penalize it for debt that it carries.

And when he combined those two factors together he called it the Magic Formula or any back-tested and he found that it outperformed the market pretty significantly. So here that came out in 2006 we tested that idea Greenblatt had only had access to I can’t remember exactly now.

But a shorter period of data it had sort of only run from 1990 to sort of 2006 from off the top of my head from recollection and the database that wares had access to ran from 1963 to 2010 or 11 at the time that we were writing the book.

So we took that strategy and we subjected it to another liquidity and market capitalization constraint so is this just a phenomenon of small capitalization stocks or is this something that would work in big cap companies. And we found that even with those constraints on it that it had to invest in big companies it had to do it by market capitalization where it had liquidity constraints it’s still big the market which is kind of extraordinary.

In the process of doing that though we’d evolved the two factors to see which one was responsible for the returns or what each one contributed and we found that the return on invested capital actually reduced the returns and the value factor which was the operating income EBIT operating income on enterprise value was responsible for more performance was responsible for like a hundred and thirty percent of the performance of the magic formula.

Which is interesting because James Montier, a pretty well-known market strategist he was at Dresdner Kleinwort Wasserstein at the time he had written this little note he called it the Little Note that Beat the Market about the book where he had tested that idea in several different markets and he’d found that he found the same thing basically that the quality factor that return on invested capital factor reduced returns.

And it didn’t it didn’t help you in a risk-adjusted sense the only thing that could be said for it was that it helped you in a market that was sort of very bubbly like a late 1990s type market.

I thought that was kind of an interesting thing and that was the focus of my second book Deep Value that came out in 2014 and the idea was what is the reason for return on invested capital reducing return and how is it that these fair companies a wonderful process seem to do better than in a quantitative sense how is that they do better than wonderful companies at fair prices and so I found the reason was there’s a lot of mean reversion and return on invested capital.

It’s a very mean reverting series which means that when companies are doing very well other competitors come in from adjacent industries VC might come in and they tend to pull down the profitability of companies in those industries and the reverse happens as well if an industry is not doing very well.

So for example a recent example is when the oil price crashed oilfield services companies do really badly. All the capital sort of gets sucked out of the industry and only the ones that only a handful survives our competitors leave or they fold and the ones that survive. Then when the oil price picks up again they start doing very well because there’s not a competition they can charge premium prices.

And that goes on in lots of different industries so and that’s that mean reversion is the same thing that drives the returns to values or undervalued companies fundamental investors p/e private equity investors value investors come in and they find these undervalued companies and they push the price up until it gets to sort of the average valuation or beyond.

And it happens on the other side too and they get expensive fundamental investors tend to come in and they have a short or they don’t invest in them. So those two phenomena are going on in the market all the time.

Profitability is sort of mean reverting to the average and valuations are sort of mean reverting to the average and so if you’re buying the wonderful company at a fair price absent the sustainable competitive advantage then you find that you slightly underperform simply buying something that’s really undervalued.

So that was Deep Value.

And then I summarized them all in a more recent book called the Acquirers Multiple which came out in the last six months and it just sort of in very simple terms that phenomenon explains how to find stocks that sort of outperform in a quantitative sense and explains why it’s so difficult to find sustainable competitive advantages.

Nick: so that brings us to your last book which is I would say noticeably different than your others in the sense that is shorter and easier to read and more affordable.

So it’s centered on this concept of the acquirers multiple which is enterprise value on EBIT. Can you give some insight into why you made the change to a shorter and cheaper book and I guess what the acquirers multiple is and what the findings were with relation to that valuation metric?

Tobias: I the books that I had written for Wiley finance they tended to be sort of quasi academic lots of research and lots of charts and things like that that were a little bit hard to read. And Wiley Finance tends to set a very high price for point for them I think they sell for sort of $85 and so those two criticisms that I had had from people.

I thought the idea was simple and powerful but not a lot of people had read it for those two reasons it was just too hard to read it was too expensive to buy so I wrote a simpler cheaper book. So Acquirers Multiple it’s like $9.99 on Kindle in in Amazon and I also went through it and I wrote it I discovered this there’s a way of quantitatively examining how difficult your writing is to read and I applied that to the book so Deep Value was written at a grade fourteen level and so basically what it does is it equates your writing level to a grade in school and say grade fourteen is way too high that’s that sort of equivalent of like second year college second year undergrad.

And it means that it won’t be as read as widely as something that is written to a log right and if you look at the most successful books that are all written to about the fifth grade level that’s like an Ernest Hemingway, Harry Potter, Dan Brown because they’re easy to read.

I wrote the Acquirers Multiple purposefully to an eighth grade level it was extremely hard to write it to that level because my instinct is always to try and find an interesting word and if you put an interesting word they tend to have more syllables which is one of the one of the metrics. so this the book is written to a very simple 8th grade level so most people should be able to understand it and it sells a little more cheaply and the idea is so I can get this message out there.

Because Buffett has been in the value investing community Buffett’s been so successful that most people assume that the best way of value investing is to follow his example which is to buy that wonderful company at a fair price. But Buffett himself didn’t adopt that strategy until he was quite advanced in his career.

He was running the equivalent of sort of 200 million dollars before he started doing that and the reason that he changed was of course he had this interaction with Charlie Munger who had some bad experiences with businesses. He had a harvester dealership in Bakersfield where he had to buy the harvester which is an expensive piece of machinery and it sat on a lot sort of depreciating until somebody came along and bought that harvester.

And so he hated businesses that yeah and in order to grow they had to buy more harvesters so he hated these businesses where he had to put a lot of money into it upfront and then you would you’re relying on your ability to sort of turn the capital in order to make any money out of it.

He was thinking about what would be the reverse of that it would be a company that would grow really a business that would grow really easily without requiring a lot of investment that would be something that had a high return and invested capital which was away at a compound. But the other the wrinkle to that is the thing that I mentioned before the mean reversion so the way that you’ve the only way to protect that is to have some sort of sustainable competitive advantage.

So Buffett’s great skill has been identifying those businesses that do in fact have a sustainable competitive advantage which allows them to chair prices that give them more margin and more return on invested capital than that would otherwise be able to do.

Many people have sort of tried to scientifically analyze how you go about finding these sustainable competitive advantages and one is Michael Mauboussin, he has this ongoing research where he looks at in a universe of stocks say the largest 1,000 and then he divides them into these five buckets and in each bucket so that one bucket is the highest return on invested capital the second bucket is the second highest return on capital down to the bottom bucket which is the lowest return on invested capital which tends to be companies that lose money.

And then he follows those cohorts over ten years to see what happens and in each bucket they tend to regress towards the mean so the most the highest return on invested capital tends to trend towards the men and lowest return on invest capital also tends to trend towards the men so that means that the ones the losing money start making a little bit of money the ones that are making lots of money make less money hidden in that data though there are a small number of companies and I think it’s sort of about four percent that do four percent of a thousand so that’s about 40 companies that manage to resist mean reversion.

Mauboussin focuses on those and he says what other the characteristics of a company that can resist mean reversion he uses a DuPont analysis. basically that looks at the way that a company generates a profit and he says there are two possibilities for the way that a company can do that it can sell high margin goods at a lot of turnover sort of profit by turnover or it can sell lower margin goods at our very high turnover.

And he says that the ones that resist mean reversion tend to be higher margin and a lower turnover but when he dives into those companies he couldn’t really find any characteristic that will allow you to predict over the next 10 years which of them will be the ones that will sustain that all they could say for the cohort that I looked at in the book was that they tended to be biotechnology was one group and the other group slightly escapes me at the moment.

But he said basically it’s very difficult to predict its which of these companies will do that and so Buffett’s great skill has been to actually identify those companies in a pretty consistent manner and if you read his letters with that in mind you realized that he spends he devotes most of his time in his letters to identifying that moat.

I think for most investors that’s an incredibly difficult thing to do to identify the might and for most investors I’ll be able to get better returns kind of ignoring the quality of the business and just looking for deep undervaluation.

Nick: a large component of the research you’ve done so far is how to identify undervalued stocks. Another component of investing though is portfolio construction and portfolio management which was the topic of Concentrated Investing. So can you provide some insight as to what your findings were in that book and more generally how you think about portfolio construction today?

Tobias: yeah that’s a great question. So when you when you start managing your own portfolio you quickly realize that picking undervalued stocks is about half the battle and the other half of the battle is managing the portfolio you want you always want to have put more money in the ideas that worked and less money and the ideas that didn’t work.

Unfortunately you don’t get a retrospective scope to go back and do that but I was interested in in the different methods of constructing portfolios and what that meant for performance. With Michael Van de Beamer who runs a big fund of funds in New York and Allen is a value investor in san francisco they interviewed value investors who had a 25 plus year track record about performance and then looked at how they had generated that track record about performance and one of the things that united them was that they tended to run pretty concentrated portfolios.

In this context concentrated portfolio means about ten holdings there’s a great story about one of the investors in the book his new analyst was working for him and walked into his office and he said you know what’s the what’s the secret to this out performance and the guy said tennis shoes and he walked back outside and tennis shoes and he kept on thinking tennis shoes tennis shoes what does it mean.

And so I went and asked his head of research what does tennis shoes mean and the guy said ten issues ten stocks that’s that’s the secret I only followed ten stocks.

We looked at there are different ways of portfolio constructing this basically an academic method and that looks at volatility variance covariance of the portfolio basically what they’re trying to do is that the context of that research was how few stocks can we buy to get performance that looks like the market average if we just randomly select stocks out how few can we buy to get to minimize the nonsystematic risk which is the risk that you don’t track the market which if you’re an efficient market person then that’s that that’s the biggest risk there’s systematic risk which is that the market falls over.

But you can’t escape that the only thing that you can avoid is under nonsystematic risk which is not tracking the index so that was the focus of their research because they had their in a time when I was expensive to buy shares they didn’t want to have to go and buy 500 shares because that’s an expensive thing to do you need a really big portfolio.

How few shares could you buy and what they found was that at about 30 shares you’ve eliminated all the non-systematic risk at 25 you’re at about sort of 98% of non-systematic risk and then beyond that you’re buying additional shares and the cost of buying them starts outweighing the diminution in non-systematic risk.

For most investors that’s not a very helpful idea because that’s not what they’re trying to do what they’re trying to do is beat the market or be sufficiently diversified it’s off any single stock blows up goes to zero the portfolio is not hurt too badly.

So the way that value investors approach the problem is to say let’s define risk not as volatility which is which leads to variance-covariance efficient market hypothesis thinking let’s define it as the risk of permanent loss of capital. Which is if that capital is gone it can’t compound anymore and that the smartest thinker in the area is of course Warren Buffett and so he’s sort of popular as the idea of Kelly Investing.

So the Kelly criterion was developed at Bell Labs by John Kelly who was a mathematician. he was doing it in the context of they would they he was working for Claude Shannon who was an information theorist he identified the on off one zero binary that is sort of the basis for all computing.

And so he looked at he had this idea for if you have a noisy wire where you’re transmitting information down a noisy wire if you’re losing information on that wire and then you you’re trying to maximize your rate of return.

That’s a little bit confusing so he said if you if you’re aware of the outcome of a game of baseball before the game is finished and you can bet on the game of baseball how much would you bet knowing the knowing the result you 100% certain you probably bet your entire bankroll because you’re 100% certain that your outcome is going to be the one that comes up.

Now you have a noisy wire so you might be getting you might get the wrong message you might not get any message how much therefore should you bet and so he developed this this theory which is how much should you bet to maximize your rate of return over the over assuming that you can keep on playing this game over and over again until you quit.

He developed the Kelly criterion which is edge over odds so edges the correct odds of the outcome of this event and odds is the odds that the bookmaker or the MA or whoever else offers you and so if you have those two pieces of information you can figure out how much of your bankroll to bet with the idea that you’re going to maximize your long-run rate of return. and so the idea of the Kelly criterion it never risks blowing up so you never invests 100% of the bankroll or in most scenarios won’t allow you to invest that much.

If you’re offered a bet that’s a coin flip it won’t let you take a coin flip it wants you to have a positive expectation bet which is like 0.51 percent probability of winning and then if you put that into the so a point five one percent probability of 0.5 one probability of winning in an even game so you put up $100 you get $100 back it would tell you to invest two percent of your bankroll in something like that.

And so that’s basically dividing the point five one by 0.5 and you find as the odds improve or the payout improves then it’ll tell you a bit more and more.

Mohnish Pabrai wrote a book the Dhando Investor where he took Buffett’s idea and he actually explained how to do it using this assuming in a stock market context where he says assume 0.5% chance of doubling 0.3 percent chance of going up 10 times 0.2 percent chance of going to 0.

How do you then figure out how much to invest in this particular stock and he was talking about a funeral home Stewart Enterprises he said that he invested 10% in the stock but if he’d known about the Kelly criterion at the time he would have told him to invest 97.5 percent of the stock.

It became very fashionable to be a Kelly criterion investor in value investing circles and the gentleman who popularized the Kelly criterion outside of value investing is John Edwards thought I’m sorry Edwards Thorpe who was a professor of mathematics at University of California-Irvine still lives in Pasadena ran a series of hedge funds wrote will he be first used it to it as a blackjack player right beat the might beat the dealer then used it in as a stock market investor right beat the market and both books have been very successful in it both of his hedge funds have been very successful his son who lives in Pasadena went along to one of the value investing Congress that used to be held in Pasadena only heard that everybody was talking about the Kelly criterion and he went back to his dad and he said everybody’s using this idea that you kind of popularized in an investing context.

And Kelly sorry Thorpe who’s still a mathematician he wrote this mathematical proof where he took the Kelly criterion and he said while Mohnish Pabrai’s application of it is theoretically technically correct there are a variety of reasons why you wouldn’t want to put 97.5 percent of your portfolio into Stewart Enterprises and he went through those. And the first one was just it’s hard to get that kind of person it’s hard to get the precision that Kelly requires when you’re investing in stocks because it’s simply not that simple there’s always more considerations to make.

The other one that his second argument was that you it ignores the possibility of black swans which are high impact events that don’t sort of have sufficient probability for you to factor them into your calculation and he also said you should regard the Kelly criterion as the outer limit of how much you should invest in anything that is sort of a fraction of Kelly is a legitimate bet to be making so he often talks about he’s written a number of papers and you can find in those papers he’ll talk about going to the racetrack and making a fractional Kelley bet on some horses he calculates to have the right odds and that means that given the change in your pocket that doesn’t really mean anything.

But if you if you take that idea and see you take this sort of Kelly or half Kelly’s sort of a popular fractional Kelly that people apply so you calculate the Kelly bet for position you apply a half Kelly and then you make one final adjustment and that’s so it’s possible that when you’re running a portfolio you have two Kelly positions that are more than fifty percent or three that are more than thirty three percent for that are more than 0.25 percent.

Kelly itself would never risk ruin so Kelly would never tell you to bet your entire bankroll or more than your bankroll in stock so you need to scale those down and you need to consider other positive it if you start doing that you need to consider other positive expectation bits.

That could be a bank account that yields a return is a positive expectation that a bond that pays a coupon is a positive expectation that said Treasuries are a positive expectation. But you should be allocating some small portion to each of those things if you include all of those things that necessarily shrinks down your biggest bets.

After sort of going through all the mathematics of that I I realized a few things one of them is that if you apply the idea of trying to match and an index you come out with about 30 names that’s also something that if you if you look at what Klarman and Graham lots of other value investors they’ve fallen out at about 30 now and if you test that that kind of works pretty well.

So it’s one of those odd occasions where I think it’s just random chance it’s somewhere between 20 and 30 names the academics and the value investors agree equal weight at inception. if you want to be a little bit more adventurous you want to spend some more time researching the stocks and Kelly is a great way of doing that with the provider that you have to adjust Kelly for stock investing the way that I the way that I described.

And you have to be prepared to have some more volatility in the portfolio because that is the result of this sort of higher rate of return is a great deal of volatility.

I think when you when you in a practical rule of thumb sense that sort of means that you really shouldn’t ever sigh as a position much more than 10 percent 10 is about where Kelly falls out and then you you’re well advised to have some other positions that are that are smaller than that and he could have as many as 20 positions that included some sort of small 1% or 2% positions that might be a low chance of success but a very high payout if they work and a 10% chance 10% position might be a very high chance of success and a pretty good payoff so you’ve got both of those together.

That’s some that’s concentrated investing it describes the theory of it and then it takes you through I think eight or so investors who’ve some of whom thought that way others of whom have just applied that ten-by-ten idea which roughly not just Kelly to.

Nick: is the reason why you need to make the adjustment to the Kelly criterion does it have to do with the bets being in tandem or in parallel rather than it being in series like there would be when you’re betting?

Tobias: that’s exactly right so if you’re if you’re playing blackjack you get one hand at a time and you you’re able to adjust your bankroll for that hand. When you’re constructing a portfolio you’re doing it in parallel that all the bets are occurring at the same time and so you have to adjust each bit for the other bits.

Nick: that’s interesting now the topic of portfolio management is a nice segue into what I wanted to spend the second half of our conversation talking about which is your separate investment strategy that is a little bit more qualitative and focuses more on special situations and options trading.

So give us a little introduction to that and then we can dive into some more detailed questions.

Tobias: well there are two there’s we have we run a special situation strategy that is a traditional special situation strategy similar sort of approach to sort of a Buffett Partnership or Graham where we’re looking for true arbitrages.

So that can be we find them in a variety of different places but the classic is risk arbitrage which is the takeover you find a company taking over another when you look at in the traditional arbitrage you sell the acquirer and you buy the company being acquired you buy the target and there’s a little there’s a little arbitrage between the bid price and where the company tends to trade in the market because there’s always some risk that doesn’t go through there’s a time value of money question.

We don’t do the traditional kind where you’re that’s sort of more akin to picking up pennies in front of a steamroller although it has worked really well I think Buffett says he got about 20 percent compound out of a capital that he put into it or 20 percent each year that he did it.

I haven’t seen any further studies on it but I understand that he’s still returning something like that we don’t do that we look for busted arbitrage busted merges busted arbitrage. so there’s still a bid there you think the company’s really undervalued there’s some hiccup in the fortunes of or in the course of the merger so they the spread gets very wide so that’s got two good things about it if you think the company’s undervalued then as a value investor that’s a good position to be in and then you’ve also got the possibility that the arbitrage does in fact occur sorry the merger does in fact occur.

So that’s been it’s been a happy hunting ground for us over the last few years. We also look at companies that are just undervalued but then we might try and find a way to get a catalyst or get a return in them by using options and there are two simple options strategies.

One is selling a put which gives you a risk profile that has the downside of equity but you get and it has a capped upside but you get the premium up front and so you might look at a $10 stock you might be able to find a $2 premium option with it with a banner to put that you’re selling so you’re giving the other person the right to buy the stock at $8. so if it falls through $8 then you’re losing money on that portion of it but you still got the premium you received upfront so you can calculate basically the way that the calculation is done if that the strike is eight dollars you’re getting two dollars in premium then your implied buy price is six dollars and in a ten dollar stock that’s a lot of the stock has to fall a long way if you lose money in that transaction and your return is two dollars on six dollars so it’s about 33% and then you would analyze that return.

That’s put selling often people think that that’s a very dangerous thing to do but if you’re an equity investor and you used to equity downside risk then it’s just a matter of sizing it appropriately so much size it so that the notional matches whatever you would ordinarily put into a portfolio.

The other one is leap buying so it’s sort of an entirely different way or it’s the exact opposite of that transaction I just described it’s buying a call which gives you the right to buy the stock at some time in the future the thing that makes it a leap is you’re buying a very long dated call so it would be where in 2018 now it might be the strike in January 2020 which I think for most stocks is about as far out as you can go and in that instance you’re looking for not a lot of volatility in the stock so a cheap option relative to what you’re paying for what you’d have to pay for the underlying stock and the stock is undervalued at the same time and you find that if the if the underlying stock performs well over the next 18 months or 2 years the optional got multiple times.

But it’s a way of sort of cauterizing your downside risk – so a 10 dollar stock might have a $1 call that you can exercise out 18 months of 2 years the way that you would think about that is now you have to pay basically 11 dollars for this stock so if the stock goes above 11 dollars you’ll do very well and your $1 if the stock gets to $15 your 1 dollar premium option might be worth 4 or 5 dollars but it’s a good way of limiting your downside risk if that $10 stock goes to zero you’re only out the option premium that you paid.

We shape those ideas is depending on how we feel about the stock what the volatility and the options looks like and that’s just a way of sort of creating a catalyst where one might not otherwise exist so there’s an it there’s a there’s an end date for the option that means that you’re getting paid one way or not getting paid as the case might be.

We also do things like off the run security so a Bank of America top warrant was one that we bought in 2016 so basically when it looked like the world was ending in a financial sense in 2008/9 bust there were bail out securities issued and one of them were these top warrants and they’re very long dated a warrant is just an option convertible and into stock of the company rather than forcing another investors selling the stock the company must issue the stock.

These things sort of we thought that Bank of America was very cheap in the style of 2016 we thought the warrants were cheap

relative to the equity there wasn’t a lot of volatility in the stock and we bought them and they have an end date of about 2021 so you have a very long period of time to run limited downside very undervalued stock and the stock has performed pretty well since then and the options have performed really well since then.

So that’s sort of that’s the idea looking for off the run stuff looking for catalysts looking for unusual ways of generating returns from a by creating our own catalysts so that’s the special situations portfolio.

I also run a much simpler strategy which is just a sort of systematic deep value type strategy which is long short so it looks for what do I think what does this thing that I’ve created think are the 30 cheapest stocks in the US and what does it think are the 30 best short candidates.

That the long candidates are pretty simple that I use the acquirers multiple primarily which is operating income on enterprise value that’s the same way that as I said before activists and private equity firms used to value companies and I used some other metrics in there as well don’t want things that have got financial distress don’t want things that have got earnings manipulation which is often a gateway to fraud and so they look for fraud measures as well those are sort of statistical applications.

Altman or Piotrovsky which are just statistical ways of identifying financial strength and other things like that and then we look at the level of short interest in the stock. So heavily shorted stocks they might not be a great short because you have to pay a lot for the borrow but they’re often not a very good long so they’re good stocks to avoid.

It’s one of those things that people often think that are heavily sure that stock is a potential squeeze candidate so if they buy them they’ll be this pop at some stage in the future when the shorts have to cover. But the research seems to say that they’re just not good candidates to buy long because the shorts are often very well informed in a short money tends to be smart money.

So we just avoid them and we look across every industry every sector and we find that that we do a few other things in there as well but basically that deep value portfolio which doesn’t look at return on invested capital the way the magic formula does it just sort of looks at it approaches these stocks the way a private equity firm or an act of a smart approaching that does pretty well.

You can get sort of an interesting return profile if you then look for some shorts in there as well so shorting is kind of a dark art. It’s not the opposite you don’t you don’t reverse the process for buying something long to find something short something that is something that is really overvalued and fundamentally weak might still be a really bad short if it’s got lots of momentum in it.

You can find lots of these stocks they’re sort of they’re the story stocks they’re the ones that everybody knows about Tesla Netflix possibly Amazon other companies like that if Amazon is an exception to this because Amazon is it does have some incredible financial strength but Tesla in particular is a fundamentally weak business and the reason I say it’s fundamentally weak is if you look at they’ve been burning more and more cash each quarter in order to build these cars.

The problem though for short investors who’ve been trying to short Tesla is that it has had this enormous momentum in it so if you’ve been short it’s been an incredibly painful ride so you can’t just apply the you can’t reverse the process that you would use as a long investor to find shorts you need to find some other things in there as well. And the other thing that that he is naturally it’s just what I’ve just described is momentum you want to find stocks that don’t have any momentum.

Momentum as its defined academically and by industry participants is stock price performance total stock price performance it’s an factor that has worked very well for a very long period of time it’s it has better return characteristics than value.

Basically the idea is that you look at the companies that have gone up the most over a given period of time 3 months 6 months 12 months and the ones that have gone up in lots of the least volatile fashion so they’ve just sort of smoothly roll up over that period of time they tend to be the stocks that do the best over the next twelve months or six months or three months or whatever them the case may be.

You can use that as an idea when you’re trying to find shorts so you don’t want to find companies that have a lot of this momentum because even though they’re fundamentally weak and they’re very overvalued they’re still going up and they tend to still keep going up so you look for companies that have no price momentum or negative price momentum and also weak financials very overvalued lots of debt deteriorating financials in some financial distress all of those things together tend to be very good short candidates.

So that the portfolio holds Long’s that are basically acquire multiple long’s and shorts that are that are the reverse but with the additional lack of momentum in them.

Nick: okay so I have about a dozen questions to follow up from that but we’ll start by just digging into this idea of merger ARB and busted mergers. so would you say that for example AT&T; Time Warner is that an example of this strategy at the moment.

Tobias: I haven’t followed that one as close. The best example I can give is the Aetna Humana transaction that started in 2016 and that’s one that we were invested in I followed it very closely and we did a lot of things in there that sort of illustrate the way that we would go about doing that.

So you might remember in 2000 at the beginning of 2016 the Department of Treasury moisture was Barack Obama’s admin the Department of Treasury wanted to stop the reverse mergers that were being undertaken for the purpose of getting the head office outside the US as a tax minimization strategy.

So they blocked the name of the transaction is this case me right now but they blocked the I think it was all again I can’t remember now but they blocked out again and spreads in every single merger our blue out in sympathy and that might have been because the merger arb’s had to unwind that particular transaction and so they had to get cash from other places or it might just be that the fear that the Treasury might block other transactions sort of became real.

We went through all of these busted arms the spreads got very wide on an annualized basis some of the returns were very high and we found the ones that didn’t weren’t merging for the purpose of moving the head office overseas and the most obvious one was Humana and Aetna so Aetna the health insurers and the state’s fitness buying Humana we looked at the gap between the purchase the offer and where it was trading in the market it was about 30 percent with the transaction set to close about nine months later which analyzes that to more than 40 percent could have I think I can’t remember now that 40 to 45 percent annualized return which is very good.

And in addition to that we thought the Humana was very undervalued so Humana had been one of my lungs in my in my systematic value strategy for a very long period of time for six or seven years and I had held it all the way up to the bid which occurred in July 2000 June July 2015 sold out at that time and then ignored it for the next nine months until it sort of popped up in the merger arb screen as being very undervalued so he put that position on the market sort of quickly recovered from that shock of the Department of Treasury blocking that transaction and within sort of three months the gap had closed sort of 5% and at that stage it was sort of now you’re in a risky merger that might not go ahead the upside is less so we took a lot of the position off but we left a little bit the position on because it was still a positive expectation for still pretty good returns.

The DOJ which is a different not the Department of Treasury Department of Justice came in and they bought the transaction on the basis of antitrust so Aetna and Humana combined we’re going to be about the second or third biggest health insurer in the state’s. United would be the biggest and there were two others that were merging at the same time and they would have been the second biggest if that transaction doesn’t go through then Aetna Humana becomes the second biggest.

We thought being second or third biggest behind United probably means that this is still likely to go through but the spread widened up a great deal so we put the position on it and we came up biggest position again there was some question about whether the DOJ would actually file or what they would do. As it happens they ended up they ended up filing and blocking the merger.

Funny thing on the day that they block the merger the stock jumped 50 Humana jumps 15 percent which is probably just one of those things that the thing that the market was most scared about was uncertainty and the very worst outcome possible actually made the stock rally so just knowing that the worst outcome possible cause the stock market about the stock to rally which is one of the crazy things about the market.

Humana came out immediately and said we’re going to sue or Aetna and Humana came out jointly and said we’re going to sue for this merger to go through. the court date was set for December and in about August or September we knew that they were then going to be several months before anything happened but there was a great deal of volatility in the stock.

So he took that opportunity to sell puts which is gives you the downside risk of equity but you get all the premium up front knowing that most likely all of his puts were going to expire before they even got to court and if they settled before they got to court than they’d likely be a pop or something in the stock.

We thought that was a pretty good risk reward returns so we got some option premium in for going about continuing to hold the stock they went to court they were ultimately defeated and the merger didn’t go through so over the course of that 18 months to 20 months that Humana and Aetna had been trying to merge. United which is another company in the in the sector had gone up a great deal and United and Humana had sort of been stuck where the bid price was and probably on a on a peer comp basis it was undervalued relative to United.

When it was actually defeated the stock rallied and the stock is up a great deal since then so it’s an unusual situation because it got bought once and rallied and when the when that was finally when they lost the court case it continued to rally. so it was one of those things that it was just so undervalued that the undervaluation provided a great deal of protection so that’s the best example of the way that we approach we’re looking for undervaluation primarily hoping for some sort of catalyst that may or may not occur and then looking for other ways to sell options to sort of improve the return as you go along.

Sell options where there’s very long so puts with this very little chance of them being struck.

Nick: now I work in a very different field of the financial industry but III know maybe five or ten mergers off the top ahead right now so that makes me wonder and think about how do you find opportunities to implement mergers. Is they’re a publication that you read to find mergers that are going through or what’s your research process look like?

Tobias: we have a we have a list of all the arbs of all the mergers that are going on and they’re just ranked on their ranked on two things they’re ranked on the size of the absolute profit in it can you make 10 percent 15 percent. The other possibility is the annualized profit and then we go through them all and we look at are they undervalued as a first sort of cut is this likely to go through are there other interesting ways of playing it in a in an option sense.

I have to say we don’t have a lot on at the moment because they all tend to be pretty tight and just there are no outstanding ideas right now.

Nick: and does it become a lot harder to quantitatively assess these opportunities if the acquire is paying for the new company in stock?

Tobias: no you just you just work out the ratio how many shares are being offered for how many shares are being acquired and you just I have a spread I have a Google spreadsheet that tracks them all so you can look at the updated price on a sort of tick by tick basis. That’s how we that’s how he looked at Aetna was offering I can’t remember now the exact ratio but it was a point there was some fraction it ‘nor sell for a Humana share.

Nick: would it be possible to short out the exposure to the Aetna shares if you’re buying Humana?

Tobias: yes and we did that and that was probably a bad thing to do because the everything in that sector rallied so we would have been better just being just being naked long but if the market had gone the other way it would have had a different outcome.

Nick: that’s fascinating. Let’s pivot and talk about your long short quant equity strategy. So where are you seeing opportunities today?

Tobias: well let me pull it up so I have a website the Acquirer’s Multiple that shows all of these opportunities in at any given time if. I go through the top 30 so that this seems to be there’s a lot of semiconductor equipment electronic equipment there’s a biotechnology company in there let me just say Airlines there are four Airlines in the top thirty two auto components tw automobile companies two biotech four metals and mining three oil and gas a little bit of specialty retail footlocker is one of the specialty retail that’s free on the acquirers multiple website you can go through and just see the sort of names that it pulls up.

There’s some interesting stuff in there so United therapeutics is an interesting company it’s a yeah biotechnology company but its net cash it’s throwing off pretty good operating earnings pretty good free cash flow yield it’s an interesting stock that I’ve been looking at its currently the second in the in the in the screen.

I think it’s worth sort of between where it’s trading in a heart and a hundred dollars so it’s trading at one hundred and nine dollars today it’s between so roughly 110 and two hundred dollars it’s a very wide range for evaluation but I think the downside is very limited and something like that.

Nick: and when you’re doing the security selection for this portfolio management do you employ solely quantitative analysis or is there you use the quant screen and then follow up with qualitative analysis to either juice returns or reduced risk?

Tobias: yes but the qualitative analysis is done in a quantitative fashion so what we’re looking for is things that are in the notes that should be on the balance sheets some of these things going to be fixed in the next round of changes to the accounting standards but operating leases is an obvious one. where it’s just a you have a choice whether you buy an asset out right and then borrow against the asset if you do that then the asset sits on the balance sheet and the debt sits on the balance sheet if you listen then because the ownership never transfers to you the lease obligation doesn’t ever sit the liability that police obligation implies doesn’t sit on the balance sheet.

Accounting standards going to change that now so that loose obligation will be brought on but previously that’s something that had to be done by hand and there are a variety of other things like that underfunded pensions various things that need to be manually brought onto the balance sheet and then you also want to look at the so I’m not just looking at operating income I want to make sure that thee the cash flows match the operating income earner different ways of doing that.

One is to look at the changes in the accruals on a year-to-year basis and then to actually look at the cash flow so you want cash flow to at least match or roughly coincide with operating income over a period of time because if it’s not often that’s a sign that there’s some fraud going on there reporting better and better earnings but it’s not really actually being reflected in the business.

So what at the point of the additional stuff that is done by hand is to make sure that the accounting the financial statements match the economic reality of the company and at the moment there’s no way to do that computer natural language computer analysis algorithms don’t do it the way a human does it say.

Ideally I’d do it for every single company in the entire universe and rank them all at the moment I don’t have the capability to do that so what we do is we take the names as they appear and we perform that analysis very rarely do we find something that doesn’t pass that analysis. but it is it is it’s always a concern if you’re a quantitative investor that you’ve identified a company that’s quantitatively cheap based on the financial statements but the financial statements don’t match the economic reality of the business so that’s what we’re that’s sort of that that’s the thrust of the additional work.

Nick: this idea of making adjustments to quantitative models to improve outcomes is really fascinating to me and you’ve written about it in your books with respect to the broken leg phenomenon so can you talk a bit about that and how it relates to what you do in your long short strategy?

Tobias: all right so the broken leg I dear is that it’s an example of Johnny goes to the cinema on a Friday night that you might construct an algorithm that predicts whether he goes or not and the algorithm might include information like is it showing an action movie which he likes is it a romance which he doesn’t like is it raining which means he’s less likely to go is it a dry night he is likely to go so you might have a few of these important factors that dictate whether he goes or not.

You learn one night that he has a broken leg and that information is not in the algorithm it has never considered that possibility before the argument is that you should therefore be able to override the algorithm and the argument against that is that the reason that you don’t override the algorithm is that when humans exercise their discretion they tend to do so.

Too frequently everything looks like a broken leg and it’s particularly apt in deep fine deep value investing because these are companies that are already not great companies this sort of they all look like they have broken legs so if you go through the list you desperately want to override the decision in every single one of them and you wouldn’t end up with much in your portfolio at all.

The way that I have avoided that is like there are things that I know that aren’t really important and those are business quality what do I think about the business what do I think about the prospects of what this business can do. but the things that are important that I have found when we go back so we can go back and look at every single name the portfolio would have bought all the way back to 1963 and you find that there are some sort of clusters of problems and those problems tend to cluster around the problem that I’m trying to eliminate which is that the financial statements don’t match the accounting or the economic reality.

Nick: have you read or seen about Joel Greenblatt’s research with factor based investing and human interference?

Tobias: with that strategy so he’s talking is this the he wrote a he wrote an article for Morningstar in 2011 or 12 where he said your two cents may cost you I think that’s the name of the article something like that and the idea it was that he looked at his original sort of investment firm that had offered magic formula style investing was called formula investing and that were going to allow people to take the magic formula names and buy a portfolio of those names but they could cherry-pick they could put whatever names they wanted into the portfolio.

At the very last moment they offered this sort of automated feature which just said buy them all and in rebalance do all this stuff for me and he found that the people who did the discretionary investing underperformed the automated system and the problem for the discretionary investors was that they exercised their discretion to pull out all the big winners. so they as a group that I think the market did something like over the two years the market did something like sixty percent the magic formula did something like eighty percent the discretionary investors did fifty percent so they took what was a winning strategy and underperform not only the strategy but the market.

When he looked at the portfolio’s that the discretionary portfolio for Halle us that had done quite well he found something odd in there too and that was that the discretionary portfolios that outperformed had bought a portfolio that basically looked like the automated portfolio and then they’d never trade it again they just sort of forgotten that they had these stocks there and that had tended to outperform too. So his conclusion was that exercising your discretion leads to under performance.

Nick: and it sounds like just based on the anecdote that you shared earlier that you’ve experienced this firsthand with your investing around the financial crisis you said your portfolio of net nets performed really well but when you just looked at the cohort analysis of the companies you excluded they did about three times as well so that’s another than another example of the phenomena.

Tobias: that’s right and that’s one of the reasons that I had I had gone through and excluded these companies that were losing money but when you look at the research internet net investing it’s an unusual thing in net nets the companies that lose money do the best and so I had gone through and picked out all the ones that did the best thinking that I was sort of enhancing the risk limiting the risk in the portfolio but it just limited the returns.

Nick: and then just to back out and speak more broadly what’s an example of an individual investment opportunity that you’re very excited about right now I tend to not like discussing individual investment opportunities because I invest at a portfolio level and I’m always concerned that if I give one name then people go and buy that one name and I could roll out of that at the end of the next quarter I could be selling that and I don’t really want to update people about that.

I think that the best way to approach the market is to have some sort of good process for identifying undervalued stocks that you can stick with through thick and thin and that’s that that’s the way to go about doing it so I like to use the acquirers multiple I use that to pick long’s and I use I use that define shorts as well with the additional proviso that I just discussed earlier that have no momentum.

So if people are interested in finding stock picks then the acquirers multiple has a free screener on them.

Nick: one of the things that I wanted to ask you just to wrap up our conversation is about all the work you’ve done at Greenbackd through your books through Carbon Beach and more recently the Acquirers Multiple. Looking back at all of this writing and research what do you feel has been the most rewarding or insightful for you personally?

Tobias: I mean Greenbackd was a great has been great for me because it introduced me to Wes which then led to the first publication first book led to other books and that was a free blog that I was sort of doing in my free time while I was working in a fund in Australia.

So it was looked at US stocks because I knew that that fund would never buy US stocks but I had worked in the States as an attorney and my girlfriend then who’s now my wife who we have we have three kids together. I knew that we’d be coming back to the States eventually so Greenbackd has been great from that perspective it led to all of the other opportunities and right now I’d say it’s probably the Acquirers Multiple.

I was sitting in the finance library at my university reading through these dusty old finance periodicals from the 1980s talking about and they were talking about private equity and leveraged buyouts and I thought if I sound is really interesting I think this is a really interesting way of analyzing the public stock market companies in one of those articles the guy described the enterprise multiple which is enterprise value on EBITDA or operating income he described it as the acquirers multiple as a what I’ve sort of describing it and that’s where I got the name from that’s why I called the site the acquirers multiple that’s what I call the little algorithm the acquirers multiple and I can’t for the life of me find that periodical I’ve got no idea where it is I’ve gotten back to that University and now there’s thousands of books on shelves and shelves books that I think I read through in the time that I was there I wish I could find it if I could ever find that it probably try and buy that periodical because then that little algorithm has been very good to me.

Nick: awesome and then just as a last question Tobias if people want to learn more about you and what you’re doing where can they find you?

Tobias: I’m on Twitter I’m sort of addicted to Twitter so I’m on Twitter and the handle is @Greenbackd it’s a funny spelling it’s GREENBACKD like the old Ashton Kutcher Punk’d there’s no ed. I also have a website Acquirers Multiple and all of my books are on Amazon if you go to Acquirers Multiple you can see it has links to all the books has the free screener has the blog has all the research. So that’s sort of that’s the place that I spend most of my time these days.

Nick: thanks so much for taking some time to talk with us today Tobias it’s been a pleasure.

Tobias: thanks Nick it’s been so much fun. Great chat.