10 Hard-Earned Lessons in Investing

Published on 10/18/21 | Saurav Sen | 3,720 Words

The BuyGist:

  • Here are 10 lessons in investing that we've internalized...in our bones. 
  • We've learned these lessons in the trenches - not in school or on the job - but by making mistakes with our hard-earned savings.
  • Some of these may be familiar to you in theory, but in practice they're hard to implement.
  • We hope that this list (and discussion) steers you away from some common assumptions and pitfalls in investing.

#1: Equity Markets are NOT Efficient.

Don’t believe what academics tell you. In theory, equity markets (especially in developed markets) are Efficient – meaning that stock prices already incorporate all the information that’s out there before you can, and so it’s all priced into the stock, which means you pay a fair price, thereby implying that you can’t make much money or beat the market. This is the “strong form” of the Efficient Market Theory (EMT). But…

In theory, there is no difference between theory and practice. In practice, there is.” – Yogi Berra

In our experience, the EMT is hogwash. Yes, and new information is swiftly incorporated into stock prices. But whether that swift incorporation was correct or not is a different debate. In our experience, new information often leads to overreactions. Overreactions = Opportunity to buy at low prices. The crux of the issue is that different people (market participants, if you want to sound academic) have different time horizons. Some want to make money in days. Some (like us) are prepared to wait for years. This leads to, as academics like to call it, different “risk preferences”. This leads to a lot of buying and selling, as it should. That’s how markets function properly.

In our view, based on years of jubilations and tribulations in the equity markets, the markets are kinda, sorta efficient in the long-term (more than 3 years). In the short term, the emotional pendulum of the market swings wildly from pessimism to exuberance and back.

“When I speak of [the efficient market] theory, I also use the word "efficient" but I mean it in the sense of speedy, quick to incorporate information, not "right". I agree that because investors work hard to evaluate every new piece of information, asset prices immediately reflect the consensus view of the information's significance. I do not, however, believe the consensus view is necessarily correct.” – Howard Marks

#2: Temperament is the main competitive advantage.

The main source of opportunities, in our experience, has been patience. Most investors, traders or speculators are too short-term oriented. There’s too much focus on next quarter’s earnings or sales. Wall Street (well, any street for that matter) has a habit of extrapolating known data points into the unknown future. “Well, if things remain like this…”, the thinking goes. But they rarely do.

We’ve found that our long-termism, which requires a steady temperament, is a huge advantage. In fact, we’re surprised that even in the arena of well-known, large, mega cap stocks, there is a lot of short-termism, which means there is enough inefficiency that one can use to their advantage. Thank you very much.

“One of the key elements to successful investing is having the right temperament – most people are too fretful; they worry too much. Success means being very patient, but aggressive when it’s time.” – Charlie Munger

Call it "Time Arbitrage", if you're fancy. Long-termism can be your superpower.

#3: Economies of Scale and Scope are the bee’s knees!

Mr. Market is not particularly good at forecasting Economies of Scale and Economies of Scope in companies. Forecasting (or as we should correctly say: Guesstimating) these dynamics is important because it informs how guesstimates of profit growth can be derived from guesstimates of sales growth. Mr. Market, one can argue, is quite adept at guesstimating sales growth. But, rather surprisingly, he’s not so good at guesstimating changes in a company’s cost structure (therefore profit margins) or guesstimating what new business lines a firm might launch to boost revenue and profits.

Economies of Scale accelerates when a firm can produce an extra unit of product for just a fraction of the increase in costs. This happens when most of the firm’s operational costs are “fixed” – think software firms whose main expense is people (software programmers). Once the software is developed, it doesn’t take more people to multiply sales (downloads or Cloud subscriptions). Such a firm’s profit margins grow much faster than revenue. Mr. Market constantly underestimates this, especially over the long-term.

Economies of Scope is the real doozy. A firm’s core expertise in one type of product can be ported over to a totally new type of product. Mr. Market generally misses this. The greatest example is Amazon. Until 2007, they were decidedly an e-commerce company. But over the last 5 years or so, their main profit engine is their Cloud Computing business - AWS. Nobody could have guessed the effect of this business on Amazon’s valuation back in 2007.

The irony is that a lot of tech stocks get obscene valuations because of top-line growth and implicit Economies of Scale expectations; but many of these rosy valuations are ascribed to businesses with high variable costs – this means that even if revenue grows by leaps and bounds, profit growth won’t really outflank revenue growth. You know the old Wall Street joke..."They sell each unit at a loss, but they'll make it up on volume!"

The opportunity for long-term investors is in businesses where the market doesn’t expect profit growth outflanking revenue growth, but their cost structure inherently sets these companies up for precisely that. Money is made when a company keeps surprising Mr. Market with higher-than-expected profit growth. These tend to be companies with low variable costs and high fixed costs. At The Buylyst, we spend a significant amount of time trying to find such companies.

#4: Accept that all investment theses are wrong.

You might know there’s a high chance of Economies of Scale & Scope, but you can never be sure. The hard truth about investing is that it’s ALL guesstimation. Some guesses are more “educated” than others, but it is ultimately just guessing the future. Not many professional investors and finance professors want to admit this. They’ll give you reams of treatises on the craft of investing, and they'll sound impressively scientific in doing so.

However, if you invest, you do need a thesis. But be real about it – ALL theses are wrong. They are just scenarios or combinations of scenarios that may or may not happen. The probabilities attached to those scenarios are subjective, even if they’re informed by fancy statistical models that have a whiff of “physics envy” about them. In fact, the more “scientific” a model gets, the stronger the illusion of surety is. That’s a dangerous sort of hubris to have in the game of investing.

“It’s not what you don’t know that kills you but what you know that isn’t so.” – Mark Twain

#5: Accept that Intrinsic Value is unknowable.

Here’s another doozy that fund managers and professors don’t talk about – Intrinsic Value is a mirage. You (or I or Warren Buffett) simply cannot know for sure what a company or its stock is worth. Again, we can have all sorts of fancy valuation models to precisely calculate an Intrinsic Value but we must accept that they are wrong.

The best we can do it to guesstimate a “reasonable price” and buy something if it’s much below that reasonable price…you know…have some margin of safety for being (almost always) wrong.

#6: Back-Cast, don’t Forecast

Here’s the thing: In theory, the valuation of any asset is as good as the laundry list of assumptions that you put into your valuation model; in practice, the valuation of any asset is how much the market is willing to pay for it. So, is it worth spending all that mental horsepower to precisely forecast what something “should” sell for?

Here’s a better way: Take the price as it is. That is the valuation at this moment whether we like it or not. Then work backwards. Try to estimate what expectations are built into this price. And then gauge whether those expectations are reasonable. This – the gauging of built-in expectations – requires man-hours and mental horsepower. This gauging process also requires the exercise – the theoretical exercise – of Valuation. If the built-in expectations are too high, we either avoid or sell. If the built-in expectations are too low, we think about buying. This reverse-engineered process of valuation is called Expectations Investing. The method was popularized by Michael Mauboussin, and now forms the basis of our investment process at The Buylyst.

Don’t forecast, because by definition it is:

“The attempt to predict the unknowable by measuring the irrelevant; a task that, in one way or another, employs most people on Wall Street" – Jason Zweig, The Devil’s Financial Dictionary

Instead, back-cast to “what needs to happen” or “what we need to believe” for the current market price to make sense. Then choose to either ignore the market quote or act on it. We never know what something is truly worth. But with some work we can know whether the price quoted by Mr. Market is reasonable or completely bonkers.

#7: Don’t keep dancin’ in the dark.

You might ask, “so, why do any valuation anyway…?” Good question. Well, here’s another thing they don’t teach you in school or on the job: Valuation is essentially about Reducing Risk.

It’s emotionally hard to:

  1. Accept that all investment theses are wrong, and
  2. Accept that Intrinsic Value is unknowable, and yet
  3. Make an investment decision.

So, we can operate in two ways:

  1. Buy or sell with NO idea of whether the price is reasonable or not…
  2. Buy or sell with SOME idea of whether the price is reasonable or not…

Option 1 is called Gambling. Option 2 is called Investing. Option 2 is less risky because over the long-term, the probability of getting something totally wrong is much lower. Unless we have some idea of a reasonable price, we’re flying completely blind. By back-casting, we can gauge whether something is reasonably priced or not – subjectively. Then we fly less blind.

The difference between Option 1 (Gambling or Speculation) and Option 2 (Investing) is about degrees of blindness. With Investing, all that hard work is to shine some light (even a glimmer) on that elusive concept of Intrinsic Value. Uncle Warren has a better analogy…

“The line separating investment and speculation, which is never bright and clear, becomes blurred still further when most market participants have recently enjoyed triumphs. Nothing sedates rationality like large doses of effortless money. After a heady experience of that kind, normally sensible people drift into behavior akin to that of Cinderella at the ball. They know that overstaying the festivities that is, continuing to speculate in companies that have gigantic valuations relative to the cash they are likely to generate in the future will eventually bring on pumpkins and mice. But they nevertheless hate to miss a single minute of what is one helluva party. Therefore, the giddy participants all plan to leave just seconds before midnight. There’s a problem, though: They are dancing in a room in which the clocks have no hands.”

– Warren Buffett

Don’t dance in a room in which the clock has no hands.

#8: Forget about measuring Risk.

Academics and Wall Street strategists have all sorts of fancy definitions of Risk – Volatility, VaR, CVaR, Downside Deviation and so on. There is no limit to their creativity. But in practice, the only risk that matters is this: permanent loss of capital. The equation that every academic and portfolio manager should perfect is this: Probability of Permanent Loss of Capital X Magnitude of Permanent Loss of Capital. But you guessed it – it’s impossible to measure this accurately before the fact even with all the computing power we have these days.

It’s best to forget about measuring Risk. We should focus our energy on managing it instead.

  1. Accept that our thesis is wrong
  2. Accept that we don’t/can’t really know the true value of anything
  3. Accept that, at best, we can know if something is reasonably priced or not
  4. Accept that we can’t measure Risk with any meaningful degree of accuracy BEFORE sh** hits the fan.

Wow, this just keeps getting better, right?

We made the point earlier that the point of doing any sort of Valuation is to manage Risk. It’s simple: Pay much less than the guesstimate of “reasonable price”. If the current price has baked into it some unreasonably high expectations, we skip it and move on. If the current price has baked into it some very timid growth expectations, then we consider buying because “current price is probably much lower than that elusive intrinsic value”. “Probably” here is subjective.

Managing Risk is about paying less, with a healthy margin of safety.

“The greatest risk doesn’t come from low quality or high volatility. It comes from paying prices that are too high. This isn’t a theoretical risk; it’s very real.” - Howard Marks

#9: BUT, Business > Price.

Paying less is all good, but it’s a mistake to focus mostly on price. Here’s something I knew in theory many years ago, but it wasn’t until I played the game of investing with most of my hard-earned savings that I learned – viscerally – this hard-earned lesson:

“If the choice is between a questionable business at a comfortable price or a comfortable business at a questionable price, we much prefer the latter.” – Warren Buffett

This is totally consistent with everything laid out earlier: Accurately measuring a “comfortable price” is impossible. However, it is a lot easier to spot a “comfortable business”. Given a choice, it’s better to focus on the business than that unobtainable thing called Intrinsic Value.

In my journey as an investor, the biggest mistakes I’ve made – taking permanent (fortunately small) losses on investments – have been because I’ve gone for the “it’s too darn cheap!” thesis. I learned the hard way that I should obsess over the business prospects of a company and not on the valuation of its stock because “intrinsic value” is a mirage anyway.

This shift in focus from “comfortable price” to “comfortable business” – not just in theory but in practice – has been the most transformative lesson at The Buylyst. We now operate with the notion that the best we can do in investing is to reduce our probability of permanent loss of capital. And doing that involves spending most of our time forming a cogent opinion on these business attributes:

  1. Does the business play the right sport? This is why we’re big proponents of Thematic Investing.
  2. Does the business have a clear Competitive Advantage?
  3. Does the business have a clear Economic Moat – a way to protect that Competitive Advantage?
  4. Does the Management Team have a clear Growth Strategy?

And then we spend maybe 20-25% of our allotted research time on the issue of “comfortable price”.

#10: Think of everything as Options.

Here’s another thing they didn’t teach in school or on The Street: Think of investing in equities as a series of Options. Option Theory can get complicated but here’s the gist of it:

Use fancy statistical models to calculate the price of a contract that gives you the right (not the obligation) to buy a stock at a specified price on a specified date in the future. This option of buying something for a specified price at a specified data is a hedged bet on the stock price appreciating – hedged because we pay a small price for this right instead of paying the full stock price. If it all works out, at that specified date in the future, we exercise the Option and buy at our (lower) Exercise Price and sell that position in the open market for a profit. This type of Option is a Call Option. Pricing a Call Option is a highly quantitative process. But the objective of the fancy statistical models is to quantify:

  1. Probability of potential gain
  2. Magnitude of potential gain

While Option Pricing is deterministic, it is inherently probabilistic. And that’s the lesson to be learned from Options Theory – always think probabilistically. And we should think probabilistically because we don’t/can’t know anything about the future for sure.

A Call Option basically allows us to manage Risk – it caps the downside and leaves open the possibility of an infinite upside. In our simple, plain-vanilla stock and ETF positions, this is the sort of payoff profile we want – low downside, high upside. The best kind of Option is a Free Option – one that doesn’t cost anything but also gives us the chance to win big. A Free Option is almost impossible to find. A cheap Option is what we’re looking for.

In stocks, we can find cheap options by:

  1. Finding companies in the right megatrend, with a clear competitive advantage, moat, and growth strategy.
  2. Paying a cheap price (much below our guesstimate of a reasonable price).

We don’t ever know the upside. But we want in on that action with a low-priced admission ticket. The lower we pay for the stock, the lower the chances of losing money. The payoff profile then looks more like that of a Call Option.

If all this talk of statistical mumbo-jumbo isn’t your jam, Charlie Munger explains this concept more eloquently than we ever could:

“To us investing is the equivalent of going out and betting against the pari-mutuel system. We look for a horse with one chance in two of winning and which pays you three to one. You’re looking for a mispriced gamble. That’s what investing is. And you have to know enough to know whether the gamble is mispriced. That’s value investing.”

The choice of the word “gambling” is interesting. We simply must accept that Investing and Gambling are part of the same Speculation spectrum. But in investing, you put in the work to “know whether the gamble is mispriced”. In gambling, you don’t.

#Bonus: Don’t fret over Macroeconomics; focus on dominant Themes.

Macroeconomics means dealing in generalities or aggregates or averages. While macroeconomic indicators are informative (but often lagging) barometers of the real economy on the ground, we find them only mildly useful when we make investment decisions. The Fed’s meeting transcripts, or GDP forecasts or the Yield Curve or [insert your favorite macro indicator here] is something we like to track but we never act upon.

Instead, we spend our mental energy on exploring themes or megatrends that represent real progress in our civilization – making lives easier or better for people. But we don’t look at themes as tailwinds that will carry us to that promised land of financial freedom. The time and effort we spend on exploring these themes/megatrends – like Renewable Energy or AI & Big Data – is about Risk Management. We don’t/can’t quantify the magnitude of the upside, but we try to gauge the probability of massive upside. High probability of upside = low probability of downside.

Charlie Munger (again) captured this notion of lowering the probability of the downside in simple and clear terms:

“The great lesson in Microeconomics is to discriminate between when technology is going to help you and when it's going to kill you….When technology moves as fast as it does in a civilization like ours, you get a phenomenon that I call competitive destruction. You know, you have the finest buggy whip factory, and, all of a sudden, in comes this little horseless carriage. And before too many years go by, your buggy whip business is dead. You either get into a different business or you're dead - you're destroyed. It happens again and again and again.”

We work hard to avoid the best buggy-whip businesses, even if they're highly profitable at the moment.

Many Happy Returns!

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