Storytime

GLENGARRY GLEN ROSS, Al Pacino, Jonathan Pryce, 1992, (c) New Line/courtesy Everett Collection

Ricky Roma: I’m going to tell you something. Your life is your own. You have a contract with your wife? You have certain things you do jointly? Bond there. And there are other things, and those things are yours. And you needn’t feel ashamed, you needn’t feel that you’re being untrue. Or that *she* would abandon you if she knew. This is *your* life.

Glengarry Glen Ross

Ricky Roma is the best salesman in the office. He’s at the top of the Cadillac board. And that’s no accident. Ricky Roma is a masterful storyteller. He knows all about needful things.

Ricky Roma’s stories appeal to us on an emotional level. But there are other, equally effective storytellers out there appealing to us on an intellectual level.

Much of what we think of as “financial analysis” is this second type of storytelling. Finance people tend to look down on writers and artists, but I can assure you there’s no less creativity involved in financial analysis. If you’ve ever built a discounted cash flow model, or an LBO model, you’re well aware of the enormous number of assumptions embedded in the things. Choosing a discount rate isn’t so different from a painter mixing colors on her palette.

Granted, that’s a fairly subtle example. Storytelling masquerading as analysis is much more obvious (not to mention silly) in the context of “portfolio update” and “strategy” meetings.

These are the meetings where a PM or strategist sits down with a slide deck and tells you about the state of a portfolio or the world. Make no mistake. There’s nothing analytical or scientific about this process. It’s theatre. The slide deck and the charts are just props to be used in the performance.

If the PM or strategist is a value guy, the story will be about mean reversion.

If the PM or strategist is a trend guy, the story will be about momentum.

The odds you’ll derive any decision-useful information from a performance like this are slim. To the extent there’s decision-useful information embedded in the performance, it’s in the metatext—the story of the story.

For example, there isn’t decision-useful insight embedded in a CE webinar about how floating rate securities have performed historically in rising rate environments. This is what I’d call a bagholder webinar. Same with sell-side research.

You don’t derive decision-useful insight from naively sitting through bagholder webinars and naively reading bagholder-oriented research. Do you honestly believe these firms produce research out of a deep, unwavering commitment to the Search For Truth?

No. Research groups are cost centers. They produce reports and exhibits in support of their salespeople. So always ask yourself: “why am I seeing this NOW?”

The first-order answer is usually that someone’s trying to sell you something. That firm hosting the CE webinar knows you know we’re in a rising rate environment. They know you’re worried about what it means for fixed income portfolios. Oh, look, they just happen to run a floating rate fund.

This may be a useful insight. But it’s also a trivial insight. Just because someone’s selling you something doesn’t mean it’s a bad deal.

More valuable insight comes from understanding the issuers of floating rate paper (via the sell-side) also know the firm running the floating rate strategy knows you’re worried about what rising rates mean for fixed income portfolios.

Put another way, what you need to address in your analysis isn’t how the asset class has performed historically. You need to address how the asset class might perform based on how deals are priced, structured and sold today.

Deal pricing is predominantly influenced by buy-side appetite for various types of securities. From there, it’s a matter of supply and demand.

The stories told by PMs and strategists and the sell-side and everyone else in the market ecosystem are told to influence our appetites for different cash flow profiles.

It’s storytelling that drives demand.

It’s storytelling that closes deals.

Remember this next time you’re parsing pro forma financial statements; or some chart illustrating the value/growth performance divergence; or a scatter plot showing how some asset class (*ahem* private equity) dominates everything else on a risk-adjusted basis.

It’s storytime.

The Best Risk Questionnaire (Bonus: It’s Free!)

Answer the following questions with complete honesty:

  • Did I buy equities in October and/or November of 2018?
  • If so, what did I buy?
  •  Why?

This exercise will give you a pretty good idea of how you handle market volatility. Not in a theoretical, highly-abstracted, mean-variance optimized way but in the visceral OH-MY-F*ING-GOD-this-stock-I-own-just-fell-40%-WTF-do-I-do-now?!?!? kind of way.

In other words, this exercise gets you thinking about risk in the only terms that matter.

Many people have told me, “oh when the market goes down stocks are on sale so I buy. Buffett says to be greedy when others are fearful.”

Most of them are liars.

People overstate their risk tolerance in bull markets. Ask the crypto people how much time they spent thinking about risk last December. Ask the FANG cheerleading section how much time it spent thinking about risk in 1Q18. I bet if you’d given these investors risk questionnaires they would’ve come back showing an extreme willingness to take financial risk. Everyone feels like Warren Buffett when the tape is printing big, fat green numbers day after day.

In the financial advice business we like to pretend we can put neat little numbers around people’s risk tolerance. We give them risk questionnaires or gussied-up, Millennial-friendly versions of risk questionnaires to match them with a model portfolio that ultimately ends up being the usual 80/20 or 60/40 or 70/30 mix you’d give someone just from eyeballing her age. Maybe we go 50/50 if she seems particularly elderly and infirm.

All of this is nonsense. It is scientism.

The way you measure someone’s true risk tolerance is to look at how they’ve allocated real dollars of their hard-earned cash. If a prospect shows up in your office with $500,000 in a bank savings account and no equity investments whatsoever, you’re dealing with someone who doesn’t like taking risk. If someone shows up with $1,000,000 of a $2,000,000 portfolio in small cap biotech stocks and another $500,000 in rental properties with a bunch of debt on them you know you’ve got a gunslinger on your hands.

Simple. Easy. Robust.

Yes, guy in the back, I can hear you muttering something under your breath about “investor education.” “Some of those people with $500k sitting at the bank just don’t understand investing and that’s why they sit in cash.” So what? Their willful ignorance further underscores their risk aversion.

People who are extremely tolerant of financial risk seek out risk on their own initiative. In business we call these people “entrepreneurs.” They may sometimes take risk in stupid ways, by reading scammy stock newsletters or buying a bunch of Litecoin or whatever, but their propensity for risk taking clearly manifests itself in their portfolios.

To steal blatantly from Taleb, this is a “skin in the game” thing.

Ignore what people say.

Pay close attention to what they do.

Time to go long Bitcoin?

It’s fashionable these days to dunk on Bitcoin and cryptocurrency more generally. Charts like the one below lend themselves to dunking. And I must confess some schadenfreude as certain crypto shills and charlatans get some well-deserved comeuppance.

181130_BTC_1YR_Chart
Source: WorldCoinIndex.com

I’ve written about crypto on several occasions on this blog. While I’ve enjoyed following the space from a distance, I’ve never put real dollars on the line. As I wrote last year in my Bubble Logic post, I just can’t get my head around how to judge when the stuff is cheap or expensive.

Are cryptocurrencies actually worth anything? If so, what are they worth?

I took a stab at this myself not too long ago. It was a useful exercise although it did not exactly end with concrete results. So despite having learned even more about blockchain and cryptocurrencies in the meantime, I remain stuck.

How am I supposed to invest in something that I cannot value?

Now, there is a pragmatic solution I have not really discussed (also mentioned by one of Patrick’s interviewees). That is, you can simply look at cryptocurrencies as call options (or, if you prefer less financial jargon, as lottery tickets). Viewed through the lens of portfolio construction this is far and away the best way of approaching the problem given the dramatic skew in the distribution of potential returns. Max downside is 100% of the original investment. And max upside is what? A 1000x gain? More? That is a pretty attractive option.

Yet it still doesn’t sit right with me. It feels too much like gambling. Which isn’t the worst thing in the world. I enjoy the occasional trip to the casino. However, conflating investing and gambling does not seem like a real answer. In fact it seems like bubble logic: gamble a little so you won’t miss out and regret it.

I wrestle with the same dilemma today.

On the one hand, the narrative around crypto has definitely shifted. It’s gotten extremely negative. I’d say it’s bordering on capitulation. If valuing this stuff were as straightforward as valuing stocks, it would be time to go bargain hunting.

Unfortunately, valuing crypto is not as straightforward as valuing stocks. You don’t have cash flows to look at. You don’t have hard assets to look at. All you’ve got is supply and demand.

For what it’s worth, I don’t believe Bitcoin is a zero. Bitcoin is ultimately a faith-based asset. It has value to the extent other people believe it has value. There’s probably always going to be at least some subset of the population that believes Bitcoin has value. But as a potential investor, I have to suss out whether the size and enthusiasm of that faith community translate to a price of $0.001, $1,000,0000, or something else entirely. Then I have to assign probabilities to those outcomes. That’s simply not something I’m able to do with any real confidence.

That said, I’m not ready to write all crypto off as an investment fad or fraud.

I’m interested in applications for distributed ledgers that aren’t built on a narrative of “get rich or die tryin’.”

I’m interested in crypto (and Bitcoin specifically) as a potential financial hedge against kleptocracy and economic mismanagement (China, Zimbabwe, Venezuela).

I’m interested in crypto’s potential to democratize and decentralize the issuance and trading of securities that can be valued using traditional means.

I do think crypto is here to stay, in some form or fashion. But I’m still not prepared to make financial bets on those outcomes.

Needful Things

Satanic_Leland_Gaunt

Mr. Gaunt steepled his fingers under his chin. “Perhaps it isn’t even a book at all. Perhaps all the really special things I sell aren’t what they appear to be. Perhaps they are actually gray things with only one remarkable property—the ability to take shapes of those things which haunt the dreams of men and women.” He paused, then added thoughtfully: “Perhaps they are dreams themselves.”

–Stephen King, Needful Things

If your job is to sell people stuff, the path of least resistance goes something like this:

1)      Sell cheeseburgers to fat people

2)      Sell advice on giving up cheeseburgers to fat people

The point here isn’t to poke fun at fat people. The point is that “fat person” is an identity with a lot connotations attached to it. One might go so far as to call those connotations “baggage.”

Other identities with a lot of connotations attached to them include: “retiree,” “former executive,” “doctor,” and “little old lady who wants a good rate on her CDs.”

We’ve all got identities. We’ve all got baggage. We’ve all got cravings.

Salespeople know this.

I opened this with a quote from Stephen King’s novel. Needful Things. In the novel, Leland Gaunt sells trinkets. The trinkets take the form of something that matters to you. Whatever triggers your deepest desires and fears. And, of course, Leland Gaunt’s willing to give you a deal on that particular item. All he asks in return is a little favor…

You go into Leland Gaunt’s shop thinking you’ll shell out some cash for a trinket. A rare baseball card. A lampshade. A religious relic. But the true cost is your soul.

Investment products, too, are things that matter. They trigger powerful emotions. You come to associate them with your aspirations, hopes and dreams.

People who sell financial products know this. People who sell deals know this.

“Oh, so you’re a Little Old Lady Worried About The Market? We’ve got an equity indexed annuity for you.”

“Sophisticated allocator? I see private equity co-invests have caught your eye.”

“Tech entrepreneur? Have you ever looked at crossover biotech funds?”

The Leland Gaunts of the investment world traffic in symbols and memes:

Yield!

Diversification!

Innovation!

Security!

Sophistication!

Tax Breaks!

Deals!

I hate to break it to you purists, but most investments aren’t sold on the basis of future expected cash flows. Most deals are sold as little gray things that will satisfy whatever cravings you’ve got as a retiree or endowment CIO or little old lady looking for the best rate on a CD. Whatever matters to you, there’s a broker out there who will sell it to you.

And you’ll probably get a deal.

Caveat emptor.

 

(major h/t to Epsilon Theory for inspiring this post)

A Man’s Got To Know His Limitations

Lieutenant Briggs: You just killed three police officers, Harry. And the only reason why I’m not gonna kill you, is because I’m gonna prosecute you–with your own system. It’ll be my word against yours. Who’s gonna believe you? You’re a killer, Harry. A maniac.

[Briggs starts to drive away when the car blows up]

Harry Callahan: A man’s got to know his limitations.

That’s the end of the 1973 movie Magnum Force. Briggs, a vigilante cop, has an opportunity to shoot Harry Callahan dead. But Briggs is an egomaniac convinced of his own moral superiority. He opts for a clever revenge scheme instead. He flees in a car, which, unbeknowst to him, has a live bomb in the backseat.

A man’s got to know his limitations.

I was moved to reflect on this after a recent due diligence trip. In investing, outcomes are inherently uncertain. We never have perfect information when making investment decisions. We’re lucky to have “good” information in most cases. Even then, unexpected events have a nasty habit of blowing up our plans.

Investing is an exercise in probabilistic thinking. Outcomes do not necessarily reflect the quality of decisions (good investment decisions often result in bad outcomes and vice versa).

When investing, you’ve got to know your limitations.

If you’re a typical outside minority passive investor, you have minimal control over investment outcomes. Basically, the only variable you can control is your own behavior.

You need to be realistic about what you can and can’t know, and the kinds of things you should and shouldn’t expect to get right. The more you can expect to get a decision right, the more time you should spend on that area. Don’t waste time on things that aren’t knowable, or things subject to lots of random noise.

 

Things I Will Never Get Right

Forecasts for prices and other variables. (This would seem obvious but it never ceases to amaze me how much time and energy is wasted here)

Timing, in the sense of trying to buy the bottom tick or sell the top tick.

Macroeconomics.

Intrinsic value. (It’s not observable)

 

Things I Should Get Right More Than Half The Time

The general quality of a given management team.

The general quality of a given business.

Industry dynamics, competitive forces and secular trends.

The potential range of outcomes for a given investment.

 

Things I Should Get Right Most Of The Time

The handful of key variables that will make or break an investment.

How I’ll know if I’m wrong about any of the key variables that will make or break an investment.

Assessing the major “go-to-zero” risks: leverage, liquidity, concentration, technological obsolescence and fraud.

When to average down, when to hold and when to sell out of an investment, not based on price action but on the key drivers and risks.

Mental Model: Value vs. Momentum

We’ve discussed at length how asset prices are driven by changes in investor preferences for different cash flow profiles. I’ve explored this both here and here. In this post, I suggest those preferences are grounded in two psychological profiles: mean reversion (value) and trend (momentum).

The psychology of mean reversion assumes all things revert toward long-run averages over time. Today’s winners will win a little less. Today’s losers will win a little more.

The psychology of trend assumes winners keep on winning, and losers keep on losing.

The more time I spend with investors and savers of varying sophistication levels, the more I believe people are hardwired for one or the other.

Personally, I’m hardwired for mean reversion. It’s extremely difficult for me to extrapolate strong growth, earnings, or profitability into the future. It’s painful–almost physically painful–for me to own popular stuff that’s consistently making new highs. If I happen to be winning in the markets, it invariably feels too good to be true.

A trend guy is just the opposite. Why own stuff that sucks? he asks. Stick with what’s working. It’ll probably get better over time. If anything, you should be shorting the losers.

A popular misconception about value and momentum guys is that value guys buy “cheap” stuff and momentum guys buy “expensive” stuff. I used to think this way. And I was wrong. For a long time I fixated on the headline valuation multiples of the stuff each personality owned, totally ignorant of what was going on under the hood.

The value guy says:

This security is pricing such-and-such a set of expectations, which reflect the naïve extrapolation of present conditions. This, too, shall pass. When expectations re-rate to properly reflect the characteristics of the underlying cash flow stream, I will exit at a profit.

The momentum guy says:

This security is pricing such-and-such a set of expectations, but those expectations aren’t high/low enough. When expectations re-rate to properly reflect the characteristics of the underlying cash flow stream, I will exit at a profit.

Of course, there’s another guy relevant to this discussion. That’s quant guy. Quant guy steps back and thinks, “gee, maybe all these mean reversion guys’ and trend guys’ psychological dispositions impact security prices in relatively predictable ways.” Quant guy decomposes the mechanics of value and momentum and builds systems for trading them. Quant guy catches a lot of flak at times, but I’ll say this for him: he tends to have a pretty clear-eyed view of how and why a given strategy works.

In closing, I want to suggest all fundamentally-oriented investment strategies, whether systematic or discretionary, are rooted in the psychology of value and momentum. Both have been shown to work over long periods of time. However, they don’t always (often?) work at the same time. Arguably, this inconsistency is directly responsible for their persistence.

Put another way: value and momentum tend to operate in regimes.

And regimes deserve a post all their own.

Mental Model: Investment Return Expectations

(This post assumes you’re familiar with the concepts outlined in the preceding mental model post on how to make money investing)

There are no shortage of people in this world selling promises. Financial advisors sell you promises. Banks sell you promises. If you’re an allocator, asset managers, consultants, third party marketers and cap intro groups all line up to sell you promises, too. Such-and-such returns over such-and-such a time period with such-and-such volatility.

Only rarely are these promises derived through anything resembling deductive logic. They’re almost always based on storytelling and data-mining.

When your financial advisor tells you she can get you 8% (god forbid, 10%) annualized on your US-biased public equity portfolio, what is that number based on? It’s almost always just a historical average. Same with your Fancy Consultant pitching private equity or middle market lending or crypto-cannabis venture capital or whatever other magical strategy happens to be selling well at the moment.

He who builds on historical averages, builds on sand.

There’s no natural law requiring US equities to return somewhere between 8% and 10% on average over 20-year rolling periods. Same with your private equity and middle market lending and crypto-cannabis venture funds. As with everything, you should build up your return expectations from first principles.

For bonds, your expected nominal return* over the bond’s tenor is equal to the starting yield.**

For stocks, your expected nominal return is equal to the starting dividend yield, plus expected growth in earnings, plus any change in valuation (price).

For the remainder of this post, we’ll focus on stock returns.

Remember the two ways to make money investing? You’ve got cash distributions and changes in investor preferences. Dividend yields and expected growth in earnings are the fundamentals of your cash distributions. Multiple expansion, as we’ve noted before, is always and everywhere a function of changes in investor preferences for different cash flow profiles.

Where people get themselves into trouble investing is extrapolating too much multiple expansion too far into the future. When you do this, you’re implicitly assuming people will pay more and more and more for a given cash flow stream over time. This kind of naive extrapolation is the foundation of all investment bubbles and manias.

If you want to be as conservative as possible when underwriting an investment strategy, you should exclude multiple expansion from the calculation all together. This is prudent but a bit draconian, even for a curmudgeon like me. I prefer a mean reversion methodology. If assets are especially cheap relative to historical averages, we can move them back up toward the average over a period of, say, 10 years. If assets are especially expensive relative to historical averages, we can do the reverse.***

Below are a couple of stylized examples to illustrate just how impactful changes in valuation can be for realized returns. Each assumes an investment is purchased for an initial price of $500, with starting cash flow of $25, equivalent to a 5% annual yield. Cash flows are assumed to grow at 5% per year, and the investment is assumed sold at the end of Year 5. Only the multiple received at exit changes.

In the Base Case, you simply get your money back at exit.

In the Upside Case, you get 2x your money back at exit.

In the Downside Case, you only get 0.25x your money back at exit.

Despite the exact same cash flow profile, your compound annual return ranges from -12% to 17.9%. I hope this conveys how important your entry price is when you invest. Because price matters. It matters a lot. At the extremes, it’s all that matters.

BASE
Base Case: Constant Multiple
UPSIDE
Upside Case: 2x Exit Multiple
DOWNSIDE
Downside Case: 0.25x Exit Multiple

If you’d like to get more into the weeds on this, Research Affiliates has a fantastic primer on forecasting expected returns. Research Affiliates also offers a free, professional grade interactive asset allocation tool. It covers a wide range of asset classes in both public and private markets.

In the meantime, what I hope you take away from this post is that there are straightforward models you can use to evaluate any investment story you’re being told from a first-principles perspective. Often, you’ll find you’re being sold a bill of goods built on little more than fuzzy logic and a slick looking slide deck.

 

Notes

*Real returns for bonds can vary significantly depending on inflation rates. This is a significant concern for fixed income investors with long investment horizons, but lies beyond the scope of this post. Really, it’s something that needs to be addressed at the level of strategic asset allocation.

**Technically, we need to adjust this with an expected loss rate to account for defaults and recoveries. This doesn’t matter so much for government bonds and investment grade corporate issues, but it’s absolutely critical for high yield investments.

***Why is it okay to use historical averages for valuation multiples while the use of historical averages for return assumptions deserves withering snark? The former is entirely backward looking. The latter at least aspires to be forward looking.

Also, if you can establish return hurdles based on your investment objectives, you can back into the multiple you can afford to pay for a given cash flow stream. That’s a more objective point of comparison. Incidentally, the inputs for that calculation underscore the fact that valuation multiples are behaviorally driven. Mathematically, they’re inversely related to an investor’s return hurdle or assumed discount rate.