The Path of Least Stress

Published on 10/20/23 | Saurav Sen | 2,507 Words

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  • We send out The Buy Scan at least once a week.
  • We cover the most pertinent (and trending) topics in equity investing.
  • We rely heavily on our primary valuation tool - The Buycaster - to get actionable insights.
  • Everything we do here at The Buylyst is about making deep-dive equity analysis as simple as possible.

Step 1: Start with the Target Return

We must have a north star, otherwise we’re just drifting in the wind. For every stock or equity ETF or Mutual Fund you consider, I recommend that this target or required return be a long-term number – a guiding light through the cacophony of short-term noise.

I look 5 years ahead, always. What return do I expect in 5 years? Can this stock or ETF get me there? It’s less stressful this way. It’s a good way to remain a monk in a market full of myopic, emotionally volatile people.

But despite being a monk, don’t be shy! Demand a high return. I do! Especially, with the incredible yields of the US treasury Bonds – at 5% or more – don’t be shy about demanding more from your equity portfolio. A paltry 12% potential return to some random price target won’t do. We get to 12% in 18 months, and then what?

Of course, it must be within the realm of sanity. I can’t, for example, demand or expect a 5X return in 5 years. I’m not a Venture Capitalist. I’m guessing neither are you. This is where historical data is useful – it can right-size our expectations. Here’s a logical way to look at historical returns of equities (and not taking averages too seriously):

I’ll tell you exactly what I demand out of my equity portfolio: 80% cumulative return over 5 years or 12.5% CAGR. Like I said, don’t be shy.

Even though my portfolio has achieved that number over the past 5 years, I know it’s not going to be easy over the next 5. However, I’m not stressed or anxious about it – I’ve poured everything that I know into a Rationality System that allows me to be that monk in a crowd of fretful people. 

This article is not about my system, but about the principles behind the system – that you can use anywhere. 

Step 2: Narrow the scope of what you need to know.

"Risk comes from not knowing what you're doing" - Warren Buffett

But the first manifestation of Risk, which is the likelihood of losing money, is stress. Stress precedes any risk event.

So, first, stress comes from not knowing what you’re doing.

But that doesn’t mean we take on the herculean task of knowing everything about everything. Even the great Oracle of Omaha can’t do that. So, there is always an element of not knowing what you’re doing. There is always a little bit of stress. But it can be minimized to a negligible level.

The key to reduce stress, if not eliminate it, is to narrow the scope of what we need to know to make an investment decision – and to do that as fast as possible. 

Nobel Laureate Herb Simon coined the term Satisficing – a cheeky combination of satisfy and sufficing. The key to eliminating stress is to have a system for Satisficing.

All it requires is distilling about 2 decades of investing experience into a reliable number-crunching tool that can be used in any market condition. Don’t worry, I’ve done all this, so you don’t have to.

In this article, I won’t be digging into the specific Satisficing Tool that I use. However, I will list out the lessons that I’ve learned through my years on Wall Street – lessons that I had to learn myself through wins and some painful losses, because nobody told me about them. 

These are the underrated, under-discussed, and often unspoken rules of investing that form the bedrock of Satisficing.

The rest of this newsletter series will revolve around this list – I will elaborate on most of these in the coming days or weeks. In this article, however, I’ll keep it as simple as possible.

Step 2.1 Minimize Trading and Portfolio Churn.

Think about this: You get a “tactical trade” idea that promises you a nice big return in a few weeks. You make the trade. Then it works! Now what? Where will you put your money? You’ll want to find another trade idea. And do that at least 30-40 times over for your portfolio – over and over again. Sounds exhausting. 

The idea of trading incessantly stresses me out. Maybe that’s because I don’t invest for an adrenaline rush. I invest so I can retire as early as possible. It’s a long game for me. And so, a long-term return target is congruent with my style. I believe it’s less stressful to operate with an investor mindset rather than a trader mindset.

Charlie Munger was right:

"Be a business analyst, not a market, marcroeconomic, or security anlayst."

…which brings me to the 2nd stress reducer…

Step 2.2 Minimize degrees of separation from Cash.

You and I have 3 major liquid asset classes available to us:

  1. Bonds
  2. Equities
  3. Commodities (including currencies and cryptos) 

The difference between them – in terms of stress – is their proximity to cash. Most bonds (excl. junk and distressed bonds) pay a fixed cash coupon, with the principal being (at least theoretically) intact. High Yield and Distressed Bonds are another story. We like the stress-free nature of bonds. But they don’t usually meet our required return (even today).

In equities, there is one degree of separation from cash. We don’t get a cash coupon. But the underlying company does (should) generate cash. The company has the choice of paying out those cash profits as dividends or keep it within the company to (presumably) invest in projects that increase its value. Because the company generates cash profits (or is supposed to), they have an intrinsic value. Stocks trade on estimates of this intrinsic value AND based on demand for the security, which at some level is dependent on estimates of future cash flow in the underlying company.

 Commodities don’t generate any cash profits, so they trade purely on the supply/demand imbalances. There is no concept of “intrinsic value” because, unlike bonds and stocks, there is no cash flow stream to discount. So, this asset class is detached from cash. Commodities tend to trade primarily on the impulses of short-term traders who read the supply/demand tea leaves. But here’s the thing… 

At some level, even stocks trade on the impulses of traders even if there is some semblance of an intrinsic value of the underlying asset. Remember, there is one degree of separation from cash.

Step 2.3: Don’t obsess over Intrinsic Value

This is the most controversial point I’ll make: Intrinsic Value is unknowable. It’s like the Heisenberg Uncertainty Principle – once you spend the time and effort to pinpoint Intrinsic Value, it has already moved on.

When evaluating stocks, we can go about it in 2 ways:

  1. Calculate a specific intrinsic value. This is how most of Wall Street operates.
  2. Accept that intrinsic value is unknowable and therefore all investing involves some level of speculation. This is how the legends of investing operate.

It’s counterintuitive but I find the legend approach less stressful. That’s because the first approach involves a lot of (stressful) forecasting.

To calculate an intrinsic value, we must:

  1. Forecast cashflows.
  2. Forecast margins.
  3. Forecast discount rates.

I need a separate article to discuss the futility of forecasting each of these. For now, I’ll just leave you with this gem from Wall Street Journal veteran Jason Zweig:

FORECASTING, n. The attempt to predict the unknowable by measuring the irrelevant; a task that in one way or another, employs most people on Wall Street.

Step 2.4: Look for a mispriced gamble.

Let’s be clear: the price of a stock at any given point in time is based on what the market thinks of its intrinsic value. And these are all over the place because intrinsic value is unknowable.

I used to be one of those purists that thought that intrinsic value is knowable, and that I can time when a stock price would converge to the intrinsic value! But these two legends set me straight.

"In my investing career I operated on the assumption that all investment theses are flawed…The fact that a thesis is flawed does not mean that we should not invest in it as long as other people believe in it and there is a large group of people left to be convinced. The point was made by John Maynard Keynes when he compared the stock market to a beauty contest where the winner is not the most beautiful contestant but the one whom the greatest number of people consider beautiful." - George Soros

"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." - Charlie Munger

We can’t know or predict what the other judges or bettors will think in the future. But we can find mismatches in expectations of the other bettors – as quantified by the current stock price – and the probability that the horse (stock) will outperform those expectations.

Step 2.5: Remember the Buffett 4.

Speakin’ of probability, let’s bring it back to the Oracle himself. In Robert Hagstrom’s amazing book The Warren Buffett Way, Buffett succinctly defines the game we’re playing:

“Take the probability of loss times the amount of possible loss from the probability of gain times the amount of possible gain. That is what we’re trying to do,” says Buffett. “It’s imperfect but that’s what it is all about.”

So, what’s the best way to do this? Have fancy models to forecast each variable? No. that sounds too stressful – mainly because I don’t think it can be reliably done. Think back to Jason Zweig’s definition of Forecasting. Maybe Jim Simmons at Renaissance Technologies disagrees. But you and I don’t have racks of supercomputers to process zetabytes of data.

Whatever system you use – limit your guesstimation attempts to the Buffett 4. At least put them down on paper and think about them even if you cannot quantify them. 

The key message here is: Return outcomes cannot be known, and the distribution of those outcomes cannot be known either. So, just focus on the Buffett 4. There’s no need to pull out your Statistics book from college to think about the range of outcomes. 

So, how to guesstimate the Buffett 4? Charlie Munger gave us a hint.

Step 2.6: “Invert, always invert.”

I knew of this famous insight from Charlie Munger for years. But it wasn’t until I came across a little-known book called Expectations Investing by Michael Mauboussin, that I saw how valuable this “inversion” could be. It changed the game for me – it formed the central pillar of The Buylyst’s flagship stock rating tool: The Buycaster

Expectations Investing makes it much easier to estimate The Buffett 4. The basic idea of Expectations Investing is to invert – from the target return (see Step 1) to “what we need to believe about the underlying business to – rationally – expect the stock to get us that return".

That’s a mouthful! So, I call it The Buycast.

When we think about the Buffett 4, here’s how Expectations Investing maps on them:

  1. Gain: given – we choose this (see step 1)
  2. Probability of Gain – Expectations Investing gives us a numerical base upon which we can impose our subjective overlay.
  3. Loss – Calculate the potential loss that’s attributable to getting the thesis wrong (see next step).
  4. Probability of Loss – Again, Expectations Investing gives us a numerical base upon which we can impose our subjective overlay.

Step 2.7: Always think of Thesis Risk.

Once you shift from a trader-mindset to an investor-mindset, the definition of risk changes. It changes from the Volatility of Stock Prices to “Thesis Risk”.

In Expectations Investing, Mauboussin gives us guidelines on how to calculate a Buycast – “what do we need to believe about the business to – rationally – buy the stock.”

The risk is – if we believe the Buycast, buy the stock, and then realize that the Buycast won’t come to pass. What’s the damage then? What is the potential loss of capital. That’s thesis risk – because we got our thesis wrong.

 Choose stocks with the lowest Thesis Risk.

The key message here is: Thesis Risk is forward-looking – that’s how any measure of risk should be. Commonly used statistical measures of risk on Wall Street or at your favorite Asset Manager are backward looking and, sorry to say, useless.

I'll leave you with 2 charts (using Netflix as an example) from The Buycaster that depict everything we’ve been talking about.

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