Howard Marks is Dangerously Wrong – Mental Models Memo, October 2018

Here’s a spooky memo for Halloween: famous investor Howard Marks, of whom I’ve long been a big fan, is wrong.  Not just wrong, in fact: he’s dangerously wrong, and I believe his new book, Mastering the Market Cycle is likely to damage – rather than improve – readers’ decisions.

Before anyone jumps down my throat for having the impudence to criticize Howard Marks: I frequently cite The Most Important Thing (Illuminated) as the single most important book on shaping my investing philosophy, and I’ve long recommended it as a first read for aspiring value investors.  I don’t cover investing books on Poor Ash’s Almanack, but if I’d reviewed The Most Important Thing, it would get seven stars – my highest rating.

Nonetheless, even the best can get it wrong sometimes – – the behavioral literature strongly suggests Munger is wrong on 25/6, for example – and much as I respect Marks, I have to be blunt.  His new book will, to use a Mungerism, cabbage up your brain.

In his own words, here’s how Marks explains his misguided premise:

An investor has to learn to recognize cycles, assess them, look for the instructions they imply, and do what they tell him to do.

If an investor listens in this sense, he will be able to convert cycles from a wild, uncontrollable force that wreaks havoc, into a phenomenon that can be understood and taken advantage of: a vein that can be mined for significant outperformance.

It’s a seductive message, especially since Marks’s writing is as cogent, clear, and compelling as it usually is… but, as with most siren songs, succumbing to the temptation will most likely lead to us drowning.  Like Odysseus’s crew, we should put on our earplugs to avoid the danger.

The balance of this memo will explain why – using, of course, mental models drawn from the Poor Ash’s Almanack latticework.

Without Numeracy, We’re One-Legged Men In An Ass-Kicking Contest

Towards the end of this memo, I discuss some caveats – i.e. situations where Marks is right – which primarily include highly cyclical industries (like agriculture) and extremes in broader market sentiment at highs or lows (tech circa 1999, single-family homes circa 2006, stocks circa 2008-2009, Bitcoins circa 2018.)  

But most industries aren’t that cyclical, and most market environments aren’t so easily identifiable as bubbles or crashes.  So let’s talk about the basic mathematics of these middle situations in more depth..

Marks draws a number of graphs in Mastering the Market Cycle to demonstrate what cycles look like.  I’ve long had a similar approach; in fact, I’ve used similar graphs in previous posts and papers.  Here, from Wolfram Alpha, is my visualization of the equation x + 3*sin(x) – directionally, it sort of approximates how cycles look:

They’re dumb fake numbers, as Matt Levine might say, but they help illustrate a point.  Cycles are terrifying up close! Our results (whether sales, retirement portfolio balance, what have you) were all the way up at 5 just recently… and now they’re down to 2.  Eek.

The problem, however, is that we’re just standing too close to see what’s really important.  Richard Thaler has observed – in Nudge (Ndge review + notes), I believe – that the more frequently you check your investment portfolio, the worse you do, because (more or less) short-term volatility makes you forget about the long-term benefits of investing.  

When one zooms out, cycles become more or less irrelevant.  See? Here’s that same equation, from a distance.  

What Marks gets wrong throughout the book is, ultimately, this very basic math.  While my equation is fake and cycles are not that clean, predictable, and repetitive, the point remains valid: given any long-enough time horizon, the slope of the line (the secular trend) vastly outstrips the cyclical fluctuations.  

This secular-dominates-cyclical is true for many interesting phenomena, even outside of investing.  Examples:

Technology: while macroeconomic conditions might accelerate or slow down the pace of technology adoption, we’re not going back to flip-phones or MS-DOS anytime soon – everything of interest in technology is secular.  There will not be a cyclical revival in buggy whips. There is no cycle that takes us back to a world without search engines. (This is, incidentally, one of the reasons that the Shiller P/E is complete and utter nonsense… but I’ve ranted about that elsewhere.)

Globalization and American manufacturing: the financial crisis may have hammered in the final nail, but the coffin of the Janesville GM plant was built long ago.

There is, to my knowledge, no discovered fountain of youth to make aging a “cyclical” rather than secular process.

We’ll return to this in the investing context with some more specific examples (and math) momentarily.  Broadly, though, in modern American history, no downcycle other than the Great Depression and its aftermath has ever had impacts that amounted to extended catastrophe.  

Marks attempts to hand-wave this reality away with a weak and unconvincing argument:

I fear that people may look back at the decline of 2008 and the recovery that followed and conclude that declines can always be depended on to be recouped promptly and easily, and thus there’s nothing to worry about from down-cycles.

But I think those are the wrong lessons from the Crisis, since the outcome that actually occurred was so much better than some of the [other outcomes…] that could have occurred instead. And if those incorrect lessons are the ones that are learned, as I believe they may have been, then they’re likely to bring on behavior that increases the amplitude of another dramatic boom/bust cycle someday, maybe one with more serious and long-lasting ramifications for investors and for all of society.

This isn’t a particularly helpful viewpoint.  The 2008-2009 financial crisis is generally regarded as the worst in American history short of the Great Depression, and (as we’ll see in a moment), it had few lasting impacts for competent investors.  If you think the world is going to end, I think we have bigger problems than our investment portfolios.

Marks’s take here reminds me of a line to the opposite effect from Henry Petroski’s To Engineer is Human(TEIH review + notes):

“all bridges and buildings could be built ten times as strong as they presently are, but at a tremendous increase in cost […]

since so few bridges and buildings collapse now, surely ten times stronger would be structural overkill.”

Opportunity costs, in other words.  Spending our lives assuming the Great Depression (or worse) is around the corner is sort of like being so much of a germophobe that you never leave the house.  

It’s smart to, say, wash your hands before eating, and to wear sandals if you’re taking a shower at the gym – but washing your hands every five minutes, or doing your best Bubble Boy impression, is overkill to the point of being detrimental to quality of life.  Dose-dependency, again: some caution is good, too much defeats the purpose by resulting in net negative utility.

This, in fact, is a lesson that dates back to Benjamin Franklin.  Being a permabear (which is what anyone who attempts to “time the cycle” typically turns into) doesn’t pay. Here’s an amusing anecdote from Franklin’s autobiography (ABF review + notes):

“there are croakers in every country, always boding its ruin.  Such a one then lived in Philadelphia; a person of note, an elderly man, with a wise look.  This gentleman, a stranger to me, stopped one day at my door, and asked me if I was the young man who had lately opened a new printing house.  

Being answered in the affirmative, he said he was sorry for me, because it was an expensive undertaking, and the expense would be lost; for Philadelphia was a sinking place, the people already half bankrupt, or near being so; all appearances to the contrary, such as new buildings and the rise of rents, being to his certain knowledge fallacious; for they were, in fact, among the things that would soon ruin us.  

He gave me such a detail of misfortunes that he left me half melancholy. Had I known him before he engaged in this business, probably I never should have done it. This man continued to live in this decaying place, and to declaim in all the same strain, refusing for many years to buy a house there, because it was all going to destruction; and at last I had the pleasure of seeing him give five times as much for one as he might have bought it for when he first began his croaking.”

Let’s put some numbers (and real-world investment cases) around this.  Firstly, most investors and business managers regard double-digit returns as a floor for acceptable performance, whether they’re investing in lower-risk assets with an appropriate degree of leverage (like banks or credit funds), or higher-risk assets on an unlevered basis (equity managers like myself), or if they’re simply business operators that generate free cash flow and look to reinvest it accretively (say, well-run industrials companies like Honeywell or Danaher.)  

I use 10% as my standard equity cost of capital and target returns substantially higher (20% annualized); most banks and corporations also view 10% ROEs as a minimum acceptable level, and have substantially higher targets for actual results.

The problem, then, with attempting to time the market, is that you’d better be damn good at it – otherwise you’re leaving a lot of money on the table.  If you can consistently source and execute on investment opportunities with, say, a 12% return on equity, and reinvest proceeds at the same rate, you’ll have earned a tidy 40% in three years.

Using inversion, let’s look at this a little differently – in this scenario, you would need to sustain a 30% drawdown at some point during those three years for you to merely break even by sitting in cash and waiting to deploy until a drawdown.  (Roughly, 0.7 x 1.12^3 = ~1.)

30% drawdowns are fairly significant, and they certainly don’t happen every three years on average.  Conversely, if the manager (or business) has opportunities at higher hurdles, you need an even bigger drawdown – or for it to happen even more frequently – to justify market timing.  And all of this, of course, assumes you can time the market (a flawed assumption we’ll address in the next section.)

One basic problem here is heterogeneity.  What Marks fails to recognize and address is that the world has a massive positive carry – and, regardless of where the cycle might be, successful investing by business managers and investment managers is about identifying and deploying capital towards the highest-carry opportunities, which can often exist in interesting niches regardless of broader market conditions.  

Perhaps at Oaktree’s $100B+ AUM scale, securities are essentially homogeneous and they can’t really afford to pick and choose – but for the rest of us operating on a more pedestrian scale, this constraint doesn’t apply, and as such our focus should be on identifying the high-return investment opportunities, regardless of where we may be in the cycle.

My friend and fellow investment manager Travis Wiedower goes into more depth on the topic of holding cash or not in a blog post from earlier this year, and his post (among other discussions with thoughtful investors) actually led me to lower my targeted cash position for the Askeladden portfolio.

It’s worth noting that this logic applies no matter the investment style at hand.  I think that the division of investment styles into “growth” and “value” is overly simplistic and usually not helpful, but we’ll use it here for illustration (for the benefit of those readers who are not sophisticated value investors.)  

Two ways that an investor can earn superior returns over time are by purchasing assets that might have low to modest growth, but trade at very low multiples to their ongoing cash flow – classically referred to as “value” – or by purchasing assets that offer less of a current cash flow yield, but high future growth potential – classically referred to as “growth.”  

(It is worth noting that “value investors” such as myself don’t use such distinctions, and while some focus more on one end or the other of the spectrum, are generally attempting to buy companies that trade at or below their estimate of intrinsic value, of which the growth rate and cash flow yield are inputs.)

It’s easy to see how, from a value perspective, it makes sense (regardless of “where we are in the cycle”) to purchase high current cash flow yields with reasonable future growth prospects.  It’s somewhat less intuitive – but still quite stunning – how little of a blip the 2008-2009 global financial crisis (again, the worst since the Great Depression) had on the long-term revenue growth trajectory of companies like Costco, Ansys, Gartner, Cognex, and Tyler Technologies (a bucket of growth stocks with strong business cases).  Here is a chart from the beginning of 2017:

And here’s a chart of their stock prices since January 1, 2007:

This is not a celebration of growth investing, to be clear; all of these stocks have historically traded at valuations well higher than what I’d personally be comfortable paying.  Nor is this to suggest that all growth stocks performed like this (see sample size), nor is this to suggest that things couldn’t have turned out differently for these companies.  (See my comments in the Q3 2018 letter, as well as the process vs. outcome model.)

Still, it is clear that if you’d been able to identify a portfolio of 10 – 15 high-quality growth stories like the above, and purchased them all on January 1, 2007, notwithstanding the global financial crisis and even notwithstanding a huge correction that might happen tomorrow, you’d probably be pretty happy sitting here today.

A similar bucket of “value” stocks is harder to identify and track over time, as the opportunity set turns over somewhat more rapidly (i.e. what is cheap today might not be cheap tomorrow.)  But the same idea generally applies, and I believe similar results would have been achieved: regardless of the financial crisis, long-term investment CAGR since 1/1/2007 would have been more than acceptable for a competent and thoughtful investor, regardless of interim mark-to-market volatility.

And that brings us to the second set of problems with Marks’s advice.

There Ain’t No Such Thing As A Free Lunch

Okay,” I hear some of y’all saying.  “Maybe timing the cycle isn’t so important after all.  But why not try to juice our returns a little bit by doing so?”

Well, because.  There’s a lesson my dad taught me young: nothing’s really free.  

Everything comes with a cost, a tradeoff.  We’ve already talked about the tradeoff in a perfect world with perfect information (i.e. the opportunity cost of capital deployed), but Marks fails to account for the fact that you’re not always going to get it right with cycle timing.  Unless you’re investing in highly leveraged companies in heavily cyclical industries (which is a separate margin of safety issue), a downcycle is not going to kill you.

What will kill you, unfortunately, is missing out on an upcycle because you think you see a downcycle coming.  And I’m not talking about multiple expansion or contraction here: I’m talking about the strong positive carry available to investors who can identify reasonable double digit IRRs (to say nothing of teens-twenties IRRs).  There is a ton of execution risk here.  

Marks mentions, then proceeds to ignore, a giant hole in his theory: base rates.  I have not yet personally met a single investor who successfully used a cyclical, market-timing component to improve their returns through a full cycle; while there are many famous success stories of people shorting MBS into the financial crisis and so on, many of these investment managers – Kyle Bass, John Paulson, etc – have since seemed to be the broken clocks that were right once.

Marks sort of acknowledges as much at one point, talking about the general failures of “macro” investing… but that’s essentially exactly what he’s asking readers to do: add a “macro” top-down component to their bottom-up analysis.  He tries, and fails, to make a semantic differentiation where none actually exists.

Unfortunately, far too many otherwise smart people are seduced by something about macro.  I don’t know what it is. Grandeur? Ego? The feeling of knowing some big secret nobody else knows?  I’ve never understood it. But I have only ever seen macro “awareness” lead to bad results for most managers.

The extreme example here is someone like John Hussman, who was once a talented stock picker (by reputation, and per his historical returns), but went down the macro rabbit hole post-2008, and, well, this is what happened to his returns (blue line):

You will not often see a performance chart uglier than this one.  Hussman, sadly for Marks (and us), exemplifies the sort of approach that Marks is advocating.  

Marks states, in Mastering the Market Cycle, that investors should be aware that…

The odds change as our position in the cycles changes. If we don’t change our investment stance as these things change, we’re being passive regarding cycles; in other words, we’re ignoring the chance to tilt the odds in our favor.

But if we apply some insight regarding cycles, we can increase our bets and place them on more aggressive investments when the odds are in our favor, and we can take money off the table and increase our defensiveness when the odds are against us.

It doesn’t take much reading of Hussman’s materials to figure out that attempting to do what Marks recommends is precisely what wrecked his returns.  Hussman, from his 2018 Annual Report:

Specifically, the losses in the Fund in recent years can be largely traced to a single factor: our defensive response to extreme and persistent “overvalued, overbought, overbullish” features of market action.  These syndromes had reliably warned of impending market losses in prior market cycles across nearly a century of history, but were virtually useless in the face of yield-seeking speculation provoked by the Federal Reserve’s unprecedented experiment with zero interest rate policy.

Note that as of mid-2007, the green and blue lines in his chart (i.e. the actual hedged performance and hypothetical unhedged performance) were more or less overlapping – Hussman’s hypothetical $10K client, who would have had ~$20K or thereabouts at that time, would have $48.4K as of this summer if not for the attempts at market timing.  

That would have been a perfectly acceptable result since 2007 – not world-beating, but a high single digit CAGR compounded over ten years is nothing to sneeze at.  Instead, thanks to Hussman’s attempts to time the cycle, they now have $11.2K – and this is the dark side that Marks doesn’t discuss.

Again, Hussman is the extreme example of cycle-timing gone horribly wrong.  With the caveat that I’m not sure how Hussman’s portfolio would perform in such a scenario, assuming that it’s market-neutral and would stay flattish, the S&P 500 would have to fall by something like 70 – 80% for Hussman to merely break even on his disastrous attempt at timing the cycle.  

Clearly that is not going to happen; while opinions on current market valuations vary widely, I doubt anyone but true deep-end conspiracy theorists thinks it should trade at 20% of what it currently does.  There does not appear to be any plausible scenario where Hussman’s post-2008 attempts at cycle timing will ever end up being cumulatively additive to his investors’ returns.

But I’ve seen it in other fund managers’ returns, too, albeit to a far lesser degree.  Never once have I seen this sort of cyclical awareness successfully implemented over a full cycle – that is to say, some people sidestep danger because they’re congenitally cautious, while some people fully exploit boom times because they’re overly optimistic.

Marks draws charts of what this looks like in his book, then suggests you can combine the two to meaningfully outperform.  This is pure fantasy, as best i can tell. In fact, literally nobody I’ve ever met in the investment world has been able to, as Marks suggests, be aggressive at the right times and defensive at the right times as well.  This includes people who I highly respect for their stock-picking abilities… it just seems that stock picking abilities don’t translate to cycle-timing capabilities.

(In a business sense, by the way, I should note that most of the business managers I admire are also relatively agnostic as to the business cycle – they simply operate their businesses as well as they can and take advantage of the opportunities they see in front of them, in a thoughtful and disciplined way.  You underwrite good deals when you have them, with, of course, consideration of industry-specific factors that are relevant… but without consideration of largely unknowable future direction of the broader economy and market.)

Marks claims that he’s able to time cycles successfully and that it’s been a big contributor to Oaktree’s returns.  I am not going to dispute this claim because I’m sure he’s being honest in his assessment. But again, this may be an issue of trait adaptivity and selection bias.  

Howard Marks is obviously special.  Nobody is questioning that. He deserves respect for what he’s been able to do, and he has mine.  But that doesn’t mean the rest of us should try to adopt his investment style if we don’t have the tools to do so.  

It’s similar to the flaw of using elite athletes or Navy SEALs as role models for how we should go about our work and lives – there are plenty of fine heroes in our armed services who tried and failed to get into the SEALs and, undoubtedly, went on to have distinguished careers elsewhere.  

Hell Week selects for people who have the toughness to be SEALs; people who end up being SEALs most likely have many natural traits that are adaptive to success as a SEAL.  You can’t then turn around and apply their practices to normal civilians; most of us would probably quite literally die if we attempted to do what they did.

Howard Marks, similarly, has clearly been thoughtful enough to utilize an investment style which takes advantage of his gifts.  And he gets to write the book about it because, well, he’s Howard Marks. That’s what people who read his book will see – they won’t see the survivorship bias issue of all the managers who have tried and failed to do what Marks has done.

It’s like the story of Sanford Dvorin in Gregory Zuckerman’s The Frackers (frk review + notes) – who’s Sanford Dvorin, you ask?  

Well, as Zuckerman explains in a heartbreaking a/b story arc, Dvorin was almost a rich oil man like Aubrey McClendon or Harold Hamm.  But he wasn’t, because his money ran out just before he would’ve struck it big with extremely valuable acreage.  Today, he’s just another guy like you and me.

Similar stories play out with all the entrepreneurs who max out their (and their mom’s) credit cards starting their business… it’s only the ones who turn into billionaires who get to write books.  The ones who don’t? They only get to write bankruptcy paperwork.

To sum this section up, here is an excerpt from my Q3 2018 letter that I think represents the right way to do things (on the opposite end of the spectrum from the advice Marks provides):

Let’s translate this theory into practical investment ramifications: one of the most important lessons I’ve internalized as a professional investor is that my goal is not to maximize theoretically achievable returns – that is to say, returns that could ideally be achieved in some fantasy land.  Instead, my goal is to maximize practically achievable returns – what I can actually manage in the real world.

Our intentional avoidance of any sort of non-obvious macro view (i.e., something not based on very long-term, very obvious base rates) prevents our trained-intuition bottom-up underwriting of individual stocks from being confused by irrelevant exogenous noise.

Marks recommends what would be the right approach in an idealized world – but in the real world, investors should aim to be relatively macro-agnostic, focusing on underwriting compelling bottom-up opportunities (with, of course, basic sensibilities discussed in the “caveats” section.)

Complexity: The Final Nail in the Market Timing Coffin

I was fairly critical of Hussman in the previous section, so let’s throw him a bone.  The way Charlie Munger tells it, maybe at least some of what Hussman was barking at made some sense.

Such thoughts are way above my pay grade and not something I personally ever think about, but here is how Munger put it a few years back regarding ZIRP and QE:

“This has basically never happened before in my whole life. I can remember 1½ percent rates. It certainly surprised all the economists. It surprised the people who created the life insurance industry in Japan, who basically all went broke because they guaranteed to pay a 3% interest rate. I think everybody’s been surprised by it, including all the people who are in the economics profession who kind of pretend they knew it all along.

But I think practically everybody was flabbergasted. I was flabbergasted when they went low; when they went negative in Europe – I’m really flabbergasted. How many in this room would have predicted negative interest rates in Europe?

Raise your hands. [No hands go up]. That’s exactly the way I feel. How can I be an expert in something I never even thought about that seems so unlikely. It’s new territory….

“I think something so strange and so important is likely to have consequences. I think it’s highly likely that the people who confidently think they know the consequences – none of whom predicted this – now they know what’s going to happen next? Again, the witch doctors.

You ask me what’s going to happen? Hell, I don’t know what’s going to happen. I regard it all as very weird. If interest rates go to zero and all the governments in the world print money like crazy and prices go down – of course I’m confused.

Anybody who is intelligent who is not confused doesn’t understand the situation very well. If you find it puzzling, your brain is working correctly.”

What’s the answer to the confusion?  In a word, complexity.

No, I’m not just substituting one word with another.  “Complexity” is a mental model that I haven’t fully wrapped my head around yet (hence why there’s no writeup on Poor Ash’s Almanack about it.)  

However, it’s touched upon by many of the books covered on this site, including Geoffrey West’s Scale (SCALE review + notes), and more importantly, several books by John Lewis Gaddis, both The Landscape of History (LandH review + notes) and On Grand Strategy (OGS review + notes).  All three, by the way, are excellent books.

The basic idea is that there are many phenomena which are highly subject to feedback effects. Two real-life examples include turbulence and traffic jams: the same number of cars on the same freeway at the same time on any given day could have widely varying outcomes, from a crawl to a nice flow, depending on how each driver chooses to respond to the actions of drivers around them.  

This makes such phenomena hard to model mathematically, because there’s so much uncertainty in the way that components of the system will interact with each other, in the future, and how dramatic an impact that can have on our outcome.  

It also, per the sort of neuroscience discussed in books like Laurence Gonzales’s Deep Survival (DpSv review + notes), means that it is extraordinarily difficult to have cogent intuition about such things – our brains are not well-equipped to handle this sort of load cognitively, let alone intuitively.

The truth is that when it comes to the sort of macroeconomic cycles Marks is talking about, there are so many inputs – and so many outputs – that it seems unlikely that “in the middle” of the distribution, we’ll be able to accurately assess the probabilities often enough to do ourselves more good than harm.

Nor, even with perfect data, would the right answer be apparent.  Take a seemingly simple question: is a bank solvent? It’s not really a matter of simply running numbers on the balance sheet.  Practically any bank, even a strong one, could become insolvent if all of its depositors, en masse, suddenly decided for some reason that it was insolvent.  

Conversely, banks teetering on the edge of solvency could find a way to fix the situation if depositors are blase and choose to go with the equivalent of “pretend and extend” – i.e., not make a run on the bank trying to get their money back, even if the bank seems to be in trouble.

Throwing a further wrench into all of this is social proof – what one depositor does may well be highly influenced by what his depositor friend down the street does.

So, you could have funny situations where, based on the largely unknowable and unpredictable decisions of the individuals involved, a reasonably well-capitalized bank could go under, while a reasonably poorly-capitalized bank could be fine, under the exact same economic circumstances.

This is probably why Munger and Buffett have, as far as I’m aware, tended to take the approach of simply finding good swimmers, and letting the tide do what it may.

Two Tylenol: Dead Headache.  Twenty Tylenol: Dead Liver.

Before I wrap up, I think it’s important to point out some caveats in favor of Marks.  For example, there are path-dependency effects to starting your career in the middle of a downcycle, that can depress your long-term earnings.

Indeed, it’s not so much that I disagree with all of his points; in fact, I think many are cogent and correct, and he does a great job with some of the analysis.  Indeed, it would probably be a nudge in the right direction for the average retail investor who buys high and sells low.

But most of Marks’s readers are far more sophisticated than that, and they’re already trying to be fearful when others are greedy.  Such an approach is not new to his audience. So it’s more a problem of dose-dependency – an important mental model I discussed in my most recent investor letter.  Some is good; more is not always better.

At the extremes – say, the top and bottom deciles, that are easy to identify by simply looking around – it’s obviously prudent to buy low and sell high, and not terribly difficult to do so.  If U.S. market indexes are at multi-year lows and nobody wants to buy any stock at any price, it’s probably a good time to buy stocks.

Conversely, if everyone and their high school dropout neighbor are making tons of money with no real experience or skills – whether they’re buying some tech IPO circa 1998, flipping houses circa 2006, buying Bitcoins circa 2018, or blogging about 3D printing circa whenever that was – then it’s probably a good time to cash in your chips (in those asset classes).  That said, most of the time, it isn’t so cut and dried whether there’s excessive optimism or pessimism.

Continuing in favor of Marks, there are certain industries where there are, in fact, reasonably predictable cycles.  Failing to understand these cycles can spell near-certain doom for investors.

Here’s one tangible example.  Here and elsewhere, I’m violating the principle of “criticize generally, praise specifically,” but the firms I’m referencing are run by Big Famous Important People and I’m, well, me.  (Cue the classic line from How To Train Your Dragon.)

In October 2013, Kerrisdale Capital published an exhaustive research piece on publicly-traded Lindsay Corporation (LNN), one of the leading players in the oligopolistic market for “center-pivot irrigation” (used by farmers to increase yields).  It was an impressive piece of research – Kerrisdale interviewed dozens of dealers in geographies as far-flung as Brazil and Ukraine, clearly demonstrating some deep industry insights on Lindsay’s competitive position.

But the thesis didn’t work, and the research proved essentially irrelevant.  It suffered from some of the problems with primary research I’ve discussed previously.  I’ve often sent this LNN report to young aspiring value investors and asked them to see if they could find the flaw.  

Summarily, for those of you who aren’t interested in puzzle-solving: one of Kerrisdale’s core assumptions was:

Our… model… grows revenue by 15% a year until FY 2018, in-line with Lindsay’s historical rate.

This wasn’t a good assumption, nor did it turn out to be true.  Here’s LNN’s top line from 2009 – present:

I’m not entirely sure how Kerrisdale came up with this analysis, but Lindsay’s long-term historical growth rate was nowhere near 15% per year – it may have been that for a short period of time during an upcycle, but agriculture suffers from a boom/bust dynamic where farmers, flush with cash during good years, buy lots of equipment… then massively cut back on spending when the rain gods are unkind and leave the fields parched.  

Lindsay has been publicly traded for a long time, so it’s not difficult to look back historically and figure out what the real long-term growth trend was.  In an analysis I’d written in 2016, I noted:

Given that [center-pivot irrigation] penetration was sub-35% (of total irrigation) [in 1995], and is around 50% today, how can you project a higher growth rate for [North American] equipment now than then?

Notably, [per Lindsay’s annual report], irrigation sales in 1995 were $88.8 million (down from $94.3 million in 1994). Total irrigation sales in 2015 were $450 million. Admittedly, we’re at a trough and not a peak today, but that works out to about an 8% CAGR over 20 years by my math (including both U.S. and international).

Even if you take 2013 numbers of $626 million, and use 18 as your denominator, you only end up with an 11% CAGR – far below the teens growth expectations many bulls were using. Specific numbers will obviously bounce around depending on how you pick your start and end dates.

Still, I think this demonstrates that the long-term track record makes it very hard to project annualized teens growth going forward, unless [something] catalyzes more dramatic adoption.

So, to the point Marks makes, in a sector like ag, it’s important to have some awareness of where you are in the ag cycle – if you start at a trough, and draw a line up to boom times, you’re going to get bad numbers that don’t represent the long-term trend.

That said, Kerrisdale doesn’t deserve all of the criticism here – I deserve some too.  Note as well that despite my best efforts, I whiffed in calling 2015 a “trough” – 2018 Irrigation revenues for Lindsay are merely ~$440MM, up from ~$420MM in 2016 and 2017, down from ~$450MM in 2015 and ~$540MM in 2014.  

While I didn’t think LNN was a good value in 2016, I did think that their results in irrigation would probably improve over time from there.  And I was wrong.  This just goes to prove that even in an industry where the cycle is quite meaningful and relatively predictable, it’s still, to a great degree, a fool’s errand trying to time it.  (Hence why most smart investors I know tend to avoid heavily cyclical industries.)

Of course, agriculture is merely a limited case: at the other extreme, markets for goods like toothpaste and water are about completely acyclical.  While some industries, like construction and mining, can be highly cyclical, most industries are more in the middle – but far closer to “acyclical” than “highly cyclical,” directionally speaking.

So, as we discussed, the secular trend line (whether that’s company growth or total shareholder return from cash flow plus growth) vastly outweighs the impact of the cycle.

There are other good points Marks makes as well – he has one about homebuilders that touches on n-order impacts; I discuss a similar point (with the example of retailers and customer personalization technology) in the zero-sum games mental model.  

Ultimately, though, the broader message of the book is flawed, and leads readers down a dangerous path.


I’ve been fortunate to live in a place where – to use a bit of financial lingo – things have always “gone up and to the right” (i.e., gotten better and more prosperous over time).  Over the past few decades, Dallas Ft. Worth has been a very strong economy; even the 2008 financial crisis was far milder here than in many other parts of the country (and, contrary to popular opinion outside of Texas, it had very little to do with shale / fracking.)

On an even more micro level, I’ve spent more or less my whole life in one of the wealthiest suburbs of the Metroplex – which went from being a farm town with cornfields (when my dad moved in about four decades ago) to a town with one grocery store (when my mom moved here roughly three decades ago) to a town with (gasp) two grocery stores, to a desirable suburb, to an extraordinarily desirable suburb.

But the concept of things not always going up and to the right isn’t unfamiliar to me: my dad’s engineering career was, for most of my childhood, anything but up and to the right.  Long story short, a number of factors (including repeated offshoring of the facilities he worked in) put us in a financial hole from time to time.

Still, thanks to schema, I tended to view this as more of the exception to the general norm: my dad was the one exception among a sea of contradictory datapoints in my leafy suburb.  It wasn’t until this summer, when I – for the first time – visited the Rust Belt, that I started to think a little more deeply about how and why things don’t always go up and to the right.  There are parts of the world where my dad’s experience was not the exception, but the norm.  Where things went down and to the right, down and to the right, and then down and to the right some more.

A rusted railcar at the Soudan Underground Mine in Minnesota.  No cycle is bringing this back to life.
A rusted railcar at the Soudan Underground Mine in Minnesota. No cycle is bringing this back to life.

After coming home from my vacation, I read the book Janesville by Amy Goldstein, about the struggles of workers in one small Wisconsin town when the GM plant shuttered during the financial crisis – and, while that book wasn’t very good either, it did at least underscore some of the thoughts I presented here.  

Whether we’re talking about our careers, our investments, or our business decisions, the cycle is usually the least of our concerns – it’s the secular issues that get us.  We need to, in other words, position ourselves somewhere – anywhere – to take advantage of large positive carries that go “up and to the right.”

If we do that, the cycles, like the tides, will wash themselves out over time.  As long as we use a margin of safety in both our personal lives and business decisions – i.e., not, as Munger would put it, risking things we have and need for things we don’t have and don’t need – we’ll be just fine.

Trying to time the cycle: that’s one of those things we don’t have, and don’t need.  And we shouldn’t give up what we do have, and do need – i.e. the secular trend – in a fool’s errand to chase the cycle.

Last month’s memo: If I disappeared… would you notice I’m not here?

Askeladden Capital Q2 2018 Letter: Poor Ash’s Almanack – A Learning Journey

Here is the Q2 2018 letter, formally announcing the launch of Poor Ash’s Almanack – a website with ~half a million words of content that is the best free mental models resource on the internet by a wide margin.  I’ve been working on it in one manner or another since the launch of ACM, and work accelerated through Q1 and Q2.

The letter discusses the rationale behind taking the time to build such a resource; in short, I’m following the playbook that Charlie Munger – Warren Buffett’s billionaire business partner – has laid out for improving judgment and cognition.

If You See CA-PE/Shiller, Please Tell It To Go Away

Usually I’m not interested enough in “macro” topics to view them as worthy of much commentary; moreover, in most cases, I’m hardly qualified.  I also usually don’t get on a high horse… but I’ll break from tradition for once.

Here’s something I’m getting tired of seeing all over the place: if you are an investor, and you write things, and those things you write occasionally concern the valuation level of the overall market, please stop referencing the Shiller P/E (also known as the cyclically-adjusted price to earnings ratio, or, cutely, “CAPE.”)

A few reasons: first, it just doesn’t work.  As Blooomberg View writer Charles Lieberman put it in October 2017:

The only time the CAPE suggested stocks have not been overvalued in the last 25 years was in 2009, when it implied that stocks were fairly valued. Stocks have tripled since then.

Lieberman goes on to make the obvious conclusion (that something that’s been wrong for 25 years can’t be taken seriously as a useful indicator), and also makes the important observation that the CAPE:

“is inherently backward-looking, notably very far back, instead of forward-looking.”

Unfortunately, he doesn’t drill this point home.  It’s obvious but overlooked.  Plenty of investors lead with the CAPE, then proceed to hedge with statements that go, directionally “but interest rates” or “but tax cut” or something to that effect.

While these arguments all have their merits, they ignore the single biggest flaw with the CAPE that is extraordinarily rarely pointed out for reasons I can’t comprehend: it’s based on an incredibly flawed, cynical, and unrealistic premise, i.e. the idea that the way the world looked five or ten years ago should be the major driver of current valuation.

This makes any occasional successes of the Shiller P/E’s predictive value artifacts of luck rather than good methodology (similar to the famous “Super Bowl Indicator.”)  The CAPE essentially rests on the assumption that the world is cyclical; the problem is that outside of certain industries, secular factors matter far more than cyclical ones.

To start with, over the past 10 years, the U.S. population has probably grown (in round numbers) from ~300 million to ~325 million; meanwhile, China’s GDP has more than doubled from ~$4.5 trillion to over ~$11 trillion today.  Technology, meanwhile, has made everyone’s lives more efficient and productive, massively increasing wealth in real (lived) terms.  Obviously, factors like that means more business for everyone.

Perhaps more importantly, though, the way the world looked in 2008 (smartphones merely a novelty, Amazon not yet dominant, “the cloud” let alone “apps” not something that many people were thinking about) is completely different than the way the world looks today.  When you think about major index components like Google and Apple and look at a historical revenue chart, their revenues today are up 6-8x over 2008; in the case of Apple, EBITDA’s up over 12x.

On a bottom-up basis, using a “cyclically-adjusted” P/E to value these companies would make absolutely no sense – if you think that their go-forward earnings should somehow be modeled by an average of the past 10 years, you’re basically saying (in as many words) that we’re going to go back to a pre-mobile world and stay there, which I don’t think any reasonable analyst would view as a base case forecast.  Whether or not you’re an Alphabet bull (I have no horse in the race), is there anyone who credibly expects search volume to fall back to 2012-2013 levels?

Similar stories could be constructed about plenty of other companies – for example, let’s take Fogo de Chao (FOGO), a restaurant stock which I’ve owned twice now (including currently).  10 years ago, FOGO had ~10 restaurants in the U.S.; today, it operates 38 with another four or five in the works.   FOGO obviously isn’t in the S&P 500, but the CAPE should work as well in theory for other market valuation indicators, and similar stories could apply to many bigger restaurant stocks as well – are you telling me that FOGO or CMG or PNRA’s contribution to some market valuation should be “cyclically-adjusted” back to an average of 20 restaurants or something?

Obviously, there are puts and takes; I’m sure there are plenty of index components whose businesses today are structurally worse (bricks and mortar retail, newspapers?) than they were 10 years ago.  Unfortunately, the CAPE wouldn’t work well for them either on a bottom-up basis – I pity anyone who tries to value a generic mall-based retailer based on its metrics from 2007 or 2012.

Therefore, using the CAPE at a high level is basically hand-waving and hoping that progress in company A is fully offset by declines in company B… which isn’t generally the case: since the Industrial Revolution, at least from a purely economic point of view, the world has been in a steady up and to the right trend.

Being aware of potential cyclical impacts is certainly important (as energy and mining investors learned), but most industries aren’t that cyclical.  Perhaps fewer people would click on Google ads or buy Apple smartphones in a recession, but that number, and consequently the earnings of the respective company, is still going to be up a ton from 2008.

From a broader economic perspective, the long-term trend is something like X + some small sin(x)-looking component.  Here is a Wolfram Alpha chart to show what I mean:

As you can see, when you zoom out, cycles are the little sin(x) fluctuation on the broader trend, but progress marches on notwithstanding – and this is what CAPE fails to capture.  It, contrarily, assumes the world looks like this: 

Obviously, that isn’t true, and if you think it is, market valuation multiples are probably besides the point (because you’d never be able to invest in anything for the long-term).

One of the things I’ve tried to do over the years is become more open-minded and less intellectually prescriptive; i.e., just because I hold a certain view or do things a certain way, I don’t automatically assume that it’s the always-and-everywhere optimal approach for everyone.

Spending a lot of time thinking about macroeconomics never has been and never will be part of my process, other than the really obvious bits, but I’m willing to at least entertain the thought that perhaps there are others smarter and more ambitious than me who could have the kinds of usable, actionable insights that I don’t.

However, seeing the Shiller P/E referenced so widely by otherwise-thoughtful investors,  as if it’s some sort of useful or interesting data point, is annoying because it’s not only empirically indefensible, but conceptually worthless.

I certainly have no disagreement with the general conception that valuations are elevated based on my bottom-up view that attractive stocks are hard to find at scale and that, the way I value companies, far more companies are overvalued than undervalued, and those that are overvalued are typically overvalued by a much higher degree than those that are undervalued.  

So if you want to make that argument, I’m totally willing to get on board with it.  Just don’t use the Shiller P/E to do it, because while it may sound smart, it has no basis in or bearing on objective reality…

… thus ends my rare high-horse, soapbox-style rant.  We now return to normal, understated, less-headdesk programming.