Our Investment Methodology

Published on 06/24/23 | The Buylyst Team | 6,837 Words

The BuyGist:

  • Objective: High Returns
  • Constraint 1: Sleep well at night.
  • Constraint 2: Intrinsic Value is a mirage.
  • Set the stage: Look for Positive Optionality.
  • Execute: Don’t forecast. Instead, back-cast.
  • Sleep well at night: Don't take the market seriously.

Objective: High Returns

We want what almost everyone wants: High Returns…with Low Stress. If only we had a magic wand…

But we do have the second-best thing – our suite of 3 world-class investment tools:

  1. The Buycaster
  2. The Buyscreener
  3. The Buychecker

Together, these tools help us execute our favorite style of investing: Sleep-well-at-night Investing. Even though we’re unwilling to compromise on good sleep, we want high returns. By “high returns”, we mean double digits. Anything above 10% (annualized) is good enough for us. Basically, we want to double our money every 10 years or so, post-tax. But this limits our investment universe to mostly Equities or Stocks.

Traditionally (over the past 25 years), American equites have generated about 9% annualized returns. Will it generate 9% annualized going forward? Most financial advisors – Human or Robo – believe it will. But that’s a statistical argument – that history will (probably) repeat itself. We believe this is a weak argument. That’s because stocks are not atoms or molecules, bound by immutable laws of nature. They are slices of living, breathing companies managed by living, breathing humans. History may rhyme, but it probably won’t repeat.

That human element is responsible for a stronger argument for that 9% long-term average. It comes down to incentives. That 9% number was for the S&P 500 Index – the most widely accepted barometer of equities in the western world. This index of 500 of the largest companies in the US is our proxy for equities in general. The important thing about the S&P 500 is that it is weighted by size (market capitalization). This has 2 big implications:

  1. There is an inherent momentum factor built into the Index. A stock’s weighting in the index increases as the stock price increases. The stock price increases when profits increase (at least over the long term). Profits increase when the company does the right things – when Management makes the right decisions to increase long-term cash profits. The transmission from profit growth to an upswing in stock price is never perfect, but it kinda sorta happens over the long-term (3-5 years).
  2. In today’s world technology is the name of the game, regardless of the industry. Technology – software or hardware – advantages widen the gap between the haves and have-nots of corporate America. This exacerbates the momentum factor. Companies that have momentum – in profits or stock prices – tend to keep having momentum. Success begets success. This makes the index an automatic “stock-picker”.

The point about Management making the right decision is important. Management teams in these large, publicly traded companies are incentivized (through their compensation systems) to make decisions with one objective above all: increase shareholder returns (measured by higher stock prices). Though some accounting shenanigans like dubious M&As or ill-timed share buybacks are occasionally employed to do this, the most sustainable way turns out to be to do the right thing – focus on increasing profit growth per share. That might involve making large, gutsy investments (in factories, or people or marketing etc.). These large investments are usually well-researched and well-enumerated. Finance and Operations teams run some very detailed scenario analyses on spreadsheets to estimate a reliable ROI number for each new investment. The threshold on these ROI numbers tends to be at least 8-10%. Management teams, who are tasked with increasing shareholder returns, will need to see a potential return of at least 8-10% (more in some industries) to commit shareholder capital. Over the long term, this ROI should trickle down to the stock price. That’s the theory, anyway. In practice, it’s not a one-to-one correlation, but it’s high enough.

“Over the long term, it’s hard for a stock to earn a much better return than the business which underlies it earns.”  - Charlie Munger from Poor Charlie’s Almanack

It’s logical to ask, “why would managers shoot for at least 8-10%? Why not 5-6%?” The main reason is Opportunity Cost. Over the long-term, investors can make 5-6% with “safer” securities such as bonds – sovereign or corporate. Bonds are considered safer than equities because they inherently promise to return the initial capital (principal) to the investor, along with regular payments of interest. That reduces risk because you’re getting a part of your money back in regular intervals. So, if investors can already make 5% or 6% or even 7% with bonds, why would they buy stocks which make no promises to return the initial investment and can, in fact, result in total capital wipeout? But they’ll consider it if they believe that stocks will yield a high enough return – say, 8-10% (annualized). Think of this number as the minimum “required return” of shareholders. So, the return-on-equity (ROE) threshold depends on that required return. Based on Munger’s observation, the long-term ROE of American companies (on average) is roughly 9%. But this number varies over time.

Let’s go back to the easier-to-digest, statistical argument for a minute. Even though the argument is a weak one, it’s good to know the historical numbers. In fact, here’s a good way to think about those numbers: “This is how all that financial gibberish about required returns and management incentives shakes out over the long term.’’ 

The chart above shows Minimum and Maximum Annualized Returns over every major time-window. If the future rhymes with the past, this chart gives us 2 important insights:

  1. As the time window expands, the range of returns shrinks. This means that our degree of confidence in any sort of average return number – to be used as a harbinger of things to come – increases.
  2. As the time window expands, the data suggests that the likelihood of losing money decreases significantly.

About averages, we’d like to reinforce a couple of important points on the chart: The average of the Min and Max shown in the chart above is not the same as the average annualized return over that full 30-year period. The Annualized Return over this particular 30-year window from June 1993 to May 2023 is about 7.9%. Over the past 25 years, it's about 9%.

If the assumption – that these numbers won’t change much in the next 15-20 years – holds up, shouldn’t we just buy a cheap S&P 500 Index ETF and sit on our a**? This is not a bad strategy. For folks who find investing intimidating, which is most folks, we think this “passive” style is the way to go. ETFs (Exchange Traded Funds) are cool because they package an index of, say, 500 stocks, into a single liquid security like a single stock. The most popular S&P 500 Index ETF is SPDR (affectionally called The Spider, ticker SPY). It’s reasonable to assume that The Spider will generate 8-10% over the long term.

But our peculiar problem at The Buylyst is that we want 10%, post tax, which means our “required return”, pre-tax, is at least 12.5% annualized. Many of our members share the same goal. Greed is good! We’re kidding. Financial Freedom is good. Let’s get there as fast as we can, without losing sleep over it.

To go from a passive 8-10% to an “active” 12.5% requires some work. Bonds won’t get us there unless we buy some High Yield or Distressed (corporate or government) bonds. But as mere mortals living outside the august halls of Wall Street Fund Managers or their overpriced beach homes in The Hamptons, we don’t have access to these high-return (and high risk) bonds - unless we buy some questionable Bond ETFs. It turns out that Bond ETFs are notoriously difficult to manage and therefore come with higher fees, lower liquidity, and unimpressive tracking errors (how it tracks the index it’s supposed to track).

That leaves Commodities or Currencies. Over the long-term most commodities don’t generate high returns. They go through short periods where they look invincible (like Gold during a pandemic or a financial crisis), but prices almost always retract when the macro environment changes. Remember, they are commodities – there is no pricing power in selling these products. There is no way for a producer or supplier of commodities to maintain profit margins by controlling price.

Currencies (and Cryptos) are outside our zone of competence. We tend to think of them as commodities – there may be short periods of blockbuster returns. But capturing those short burst requires constant vigilance and a penchant for playing with fire. It’s like the X-Games of investing. If you’re curious, we don’t have a high opinion of cryptos. We like to be as stress-free as possible. Long-term public equity investing has, for us, the best Return-to-Worry ratio. That brings us to our first constraint.

Constraint 1: Sleep well at night.

We like to sleep well at night. Apart from good diet, regular exercise, happy relationships, and daily meditation, it means taking care of 2 important aspects in our investment portfolio:

  1. Prioritize Loss Avoidance.
  2. Have the right temperament – never act on the short-term gyrations of the market.

There is only one real risk in investing: Permanent Loss of Capital. Let’s call it PLC. Wall Street and Academia have spent decades trying to quantify the probability and magnitude of PLC. Standard Deviation, Value-at-Risk, Conditional Value-at-Risk, Expected Shortfall, Expected Stupidity…the list goes on with fancy science-y sounding variables (maybe not the last one). We don’t subscribe to any of that for 2 reasons:

  1. Physics Envy: We’re convinced that most of these measures are attempts to make a science out of something that’s not a hard science.
  2. Myopia: Their measures tend to be short-term oriented – possibly useful to short-term traders. They’re not measures of PLC but of TLC (Temporary Loss of Capital).

Uncle Warren (Buffett) doesn’t subscribe to those dubious measures either. He cuts right to the heart of the problem: “Risk comes from not knowing what you’re doing.”

Risk and PLC are interchangeable. PLC comes from not knowing what you’re doing. You might get lucky occasionally, but deep down you know if you know what you’re doing. Eventually luck runs out and then you’re left holding the bag.

“Only when the tide goes out do you discover who’s been swimming naked.” – Warren Buffett

But it’s also true that it’s impossible to know everything. You cannot control all possible risks in investing (at least in public equity investing) because the latticework of factors that affect stock returns is too expansive for the human mind to process. And we believe it will also take some time before AI can reliably process all those factors. So, it’s important to accept these two facts of life:

  1. There will always be uncontrollable and/or unknowable factors that cause PLC. Occasionally, even the great Buffett misses something.
  2. So, all investing involves some degree of speculation, so the best we can do is to minimize the speculation component as much as possible.

The great economist Herb Simon invented the word “Satisificing” – a combination of “satisfying” and “suffice”. In investing, the best we can hope for is to go in with open eyes and clear minds if we’re “satisficed” with the information we have. And regarding the information we don’t have (there is always something), we try to analyze them enough to make sure they don’t kill us:

  1. Macroeconomic Risks
  2. Industry-level Risks
  3. Company-specific Risks
  4. Stock-level Risks

“All I want to know is where I’m going to die, so I’ll never go there.” – Charlie Munger

Let’s be frank: Macroeconomic Risks aren’t all that controllable. It is a bit of a crapshoot. But we can control some obvious things like: “don’t invest in a company with a high Debt/Earnings ratio in a rising-interest-rate environment”. And because of the unpredictability of Macro risks, we stay away from commodities (futures or stocks of companies that sell commodities). Take Oil, for example – its price trajectory is mostly driven by tiny changes in the supply-demand gap. This gap is usually manufactured. OPEC might suddenly decide to reduce supply to prop up prices or an autocrat might start a war, which almost always drives up prices. But tomorrow if the autocrat declares Cease Fire, or there’s another Shale Oil discovery somewhere, the price drops precipitously. It really is a crapshoot. So, reading Macro Tea Leaves is not a good use of our time.

We do spend a lot of time trying to gauge Industry-Level risks (and upside potential). We are big proponents of Thematic Investing, which means trying to understand and size up the most glaring inevitabilities, so that the grand forces of progress are not against our portfolio. Let’s put it this way: We don’t want to invest in the best buggy-whip factory when this new thing called a Motorcar is around the corner. Trying to dodge a falling knife is not worth it, and it’s incongruent with sleep-well-at-night investing. We do spend a lot of time researching themes such as Artificial Intelligence, Renewable Energy, and Healthcare to look for those inevitabilities that can not only provide us with some tailwind but also minimize our company-level risk if we’re wrong.

We try to not be horribly wrong when making company-level bets. Here’s how we try to minimize not knowing what we’re doing:

  1. Is the company operating in a stable or growing industry? Is this industry going to be thriving in 10 or 20 years? Here’s where that Thematic thinking helps.
  2. Does the company have a distinct competitive advantage in its industry? What is it?
  3. Is the competitive advantage durable? Do they have an Economic Moat?
  4. Does the management team look solid? Is their strategy going to fortify that competitive advantage?

There’s another important concept we picked up from the Mr. Buffett: Margin of Safety. This is about Stock Price Risk, which is related to Company Risk. The basic idea is that we should pay a significantly lower price than the Intrinsic Value of the stock. This is not just to maximize returns but also to minimize risk. It leaves room for error in estimating the intrinsic value of a company or its stock.

Margin of Safety is cool, but there’s a problem.

Constraint 2: Intrinsic Value is a mirage.

The idea of Margin of Safety is sound: pay much less than an asset’s Intrinsic Value, so if we’re wrong, we minimize the chances of losing money. The key phrase is: “what you think it’s worth”. Nobody can possibly estimate what the one true worth of a company is. There is no Intrinsic Value.

OK. It’s a bit theatrical to claim that “there is no Intrinsic Value”. Sure, there is. But there is no way of knowing a company’s one true Intrinsic Value. It lies in the eye of the beholder. So, value is, indeed, Extrinsic. And there’s another problem: Even if someone has special Godly powers to know a firm’s one, true Intrinsic Value, there is no reliable way of knowing WHEN a stock price will converge to it. This is a crapshoot.

This view is considered blasphemy in the halls of Academia or Wall Street ivory towers. But being against the crowd doesn’t bother us. We speak from our experience, from our wins and losses. And we’re not scared to go against the grain because the greatest investors are on our side (or we’re on theirs). Here’s how George Soros, one of the greatest investors of all time, has operated:

“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.”

That quote is taken from his first book, The Alchemy of Finance. The Keynes quote was probably from the 1940s, when such analogies were kosher. Now it looks outdated. The main point made though is that the winner cannot be the most beautiful contestant because beauty (or intrinsic value) is in the eye of the beholder.

Perhaps that young monk in the pathbreaking movie The Matrix had a better analogy than Soros and Keynes:

Young Monk: “Do not try and bend the spoon—that’s impossible. Instead, only try to realize the truth.”

Neo: “What truth?”

Young Monk: “There is no spoon.”

Neo:There is no spoon?”

Young Monk: “Then you'll see that it is not the spoon that bends, it is only yourself.”

Intrinsic Value is a mirage. Don’t waste time and effort trying to precisely calculate it. It is better to be approximately right than precisely wrong. All investment theses should be about being approximately right.

“Perfection in investing in generally unobtainable; the best we can hope for is to make a lot of good investments and exclude most of the bad ones.” Howard Marks

Set the stage: Look for Positive Optionality.

We want high returns…with low stress. But if there is no way know how mush something is truly worth, what do we do? The best we can do is prioritize not paying prices that are ludicrously high. This sounds like cop out. It isn’t. Let us explain.

The best thing in investing or any betting game is a “free option”. This is just the bee’s knees, but it’s as rare to spot one as the Loch Ness monster. The next best thing is an option that costs a small fee. A financial option allows you hedge your bets. A Call Option, for example, allows the buyer to have the right to buy a stock at a predetermined price (exercise price) at some point in the future – for a small fee. If the stock never reaches the exercise price, then the Option expires without the option-holder having to pay anything at that point. No harm. No foul. So, the option-holder’s risk is basically just the small fee. However, the upside is potentially unlimited. The payoff profile of an Option is what every investor wants: Low Risk, Hight Potential Return. And if the Option is free, it’s basically: No Risk, High Potential Return.

We don’t expect to find Free Options. But we can look for investment that have a Call Option like payoff profile. Now, we don’t normally trade Options directly for reasons that we won’t get into now. Let’s just say that pricing Options and trading them profusely doesn’t fall into our sleep-well-at-nigh paradigm. We mostly trade stocks and ETFs – ones that have Positive Optionality. That’s right in our wheelhouse. And the best we can do is to find stocks that are priced such that they have low downside and a potential upside that – realistically and rationally – matches our required return. That’s as good as it gets in equity investing. There is no spoon. There is no formula. There are just probabilities and educated bets. And the probabilities are all subjective.

The best explanation Positive Optionality that we’ve across is from Charlie Munger. He likened the stock market to a horse race. When were young analysts on Wall Street, we dismissed this notion. How dare he compare our prestigious careers to a horse race at Yonkers!? As we gained more experience and took our punches in the market, we realized he was right. There is nothing pure or sacred about textbook valuation models. There is no science to this. Here’s the whole game of equity investing according to one of the greatest minds in the game:

“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.”

Great. Now all we need is a system that quickly quantifies these mispriced gambles, so we can invest in the stocks that have a 1-in-2 chance of winning but pays us 3-to-1.

Execute: Don’t Forecast. Instead, Back-cast.

“Forecasting: The attempt to predict the unknowable by measuring the irrelevant; a task that, in one way or another, employs most of Wall Street.” - Jason Zweig from The Devil’s Financial Dictionary

Despite the best advice from legends of investing who’ve been successful for decades, Wall Street pros (we used to be one of them) love to precisely quantify Intrinsic Value. And they use 3 primary methods to do it:

  1. Discounted Cash Flow (DCF)
  2. Comparables (Comps)
  3. Triangulation (combination of DCF and Comps)

Until a couple of years ago, we used to prefer Triangulation. We never fully warmed up to DCF or Comps even when we were forced to use them as young analysts on the Street. We could never digest the myriad of (often questionable) assumptions that we had to make to forecast each cash flow item (for DCF) or to superimpose dodgy average or median Industry Valuation Multiples (Comps) on a specific company/stock. Triangulation, we had long hoped, would nullify the drawbacks of DCF and Comps. But that was just a leap of faith. Deep down, we suspected there must be a better way. And then we ran into Michael Mauboussin’s work.

Mauboussin’s concept of Expectations Investing changed our lives. It opened our eyes to a way of thinking that was dormant within us for years: It is futile to spend days building a multi-tabbed, multi-linked spreadsheet to precisely calculate an unknowable quantity like Intrinsic Value. Expectations Investing turns that whole approach on its head. And it turns out to be much more intuitive than DCF or Comps. Expectations Investing is based on 3 main pillars:

  1. Intrinsic Value is unknowable.
  2. Competitive Strategy and Valuation are joined at the hip.
  3. Avoid garbage-in-garbage-out forecasting models.

It’s not a coincidence that these foundational pillars point to the biggest criticisms of the beloved DCF approach. DCF 1) Rather arrogantly promises a precise estimate of Intrinsic Value 2) Competitive Strategy is an afterthought for investors and 3) It is entirely a garbage-in-garbage-out model. We’re sure that these factors bothered a practitioner like Mauboussin as well, which is why he set out to find a better way.

Then there’s a 4th criticism of the DCF model that always confounded us: the denominator. When we discount projections of cash flows, we need to discount them back to present value using a denominator called Cost of Equity or Weighted Average Cost of Capital (depending on which cash flow we’re discounting). Academics and Wall Street love to use these complicated denominators which is based on some, frankly, ridiculous assumptions, which are further based on debunked theories like the Modern Portfolio Theory. The main problem with this theory is its flawed foundational pillar: Volatility = Risk. For long-term investors, that’s just not true. Don’t take our word for it. Legends like Munger share our disdain for the foundations of academic cost-of-equity calculations.

“Beta and Modern Portfolio Theory and the like – none of it makes any sense to me…how can professors spread this? I’ve been waiting for this craziness to end for decades. It’s been dented and it’s still out there!” – Charlie Munger in Poor Charlie’s Almanack

So, now the question is: If we don’t use fancy theories to discount cash flows and precisely calculate an Intrinsic Value, then how do we know whether we’ve paid a good price or not? What does “good price” mean? It means that we’ve paid a price that’s much less than it is (or ought to be) worth. Obviously, we want that because it implies a positive return. But if we don’t know what something’s worth, then how do we know that return? Expectations Investing flips this puzzle on its head. We start with the desired return.

“Invert, always invert.” – Charlie Munger

Start with known quantities:

  1. We know a stock’s current stock price (CSP). Let’s say that’s $10.
  2. We will now boldly state the return we desire! Let’s say that’s 100%. Don’t be shy.
  3. Now we know the “desired stock price” (DSP). That’s $20.
  4. We also boldly state our time frame. Since we’re long-term investors, the minimum timeframe we consider is 5 years.

So, we know that to consider buying a stock, we need its price to go from $10 to $20 in 5 years. That’s the target. We now ask the most important question: What needs to happen in the underlying business to – rationally – expect the stock price to go from $10 to $20 within 5 years?

This is a back-solving process. We’re avoiding the futile task of calculating a specific Intrinsic Value, which involves forecasting cash flows. Instead, we’re back-casting from our DSP of $20 to what needs to happen in the business. At this stage we need to decide what variable we’re solving for – in the “what needs to happen” back-casting.

We’ve chosen Revenue Growth as our primary back-cast. We call it The Buycast. We solve for the “annualized revenue growth we need to believe” to consider buying the stock. During this Buycasting process, we need to make several assumptions about cash flow items as we move up the waterfall. The Buycaster dashboard has more details about how we do this, but here’s what a Buycast looks like:

This chart tells us that, as of writing this, to consider buying AAPL, we would need to believe that Apple’s revenue will grow at an average annual rate of 25.1%. Without any qualitative perspective on Apple’s business, we can safely say that, given Apple’s history, this Buycast seems hard to achieve. Apple will probably need to have more than one new blockbuster product to make this happen. So, buying AAPL looked like a risky bet. We suspect that, as of writing this, there are plenty of (safer) fish in the sea.

We selected Revenue Growth instead of Profit (Free Cash Flow) growth as a primary Buycast for 3 reasons:

  1. Revenue growth is easier to visualize and more comparable to past company performance, so it’s easier to benchmark.
  2. Profit growth could be influenced by changes in a company’s cost structure and/or margins.
  3. When we back-solve from Desired Stock Price (DSP), Revenue is the last numerical bus stop; it requires us to go through Profit (Free Cash Flow) and up the cash flow waterfall through Capital Costs and then Operating Costs. We cover the entire gamut of cash inflows and outflows.

This Buycast pierces through the noise and zooms into what really drives stock prices: expectations about future growth of the underlying business. The Buycast quantifies this – in a tangible, actionable way. Now, we must be clear: This is in no way a substitute for good old-fashioned subjective analysis of a company’s business prospects, but The Buycast and its related variables make that job a lot easier for us. Let us explain.

Once we have the Buycast, the next step is validating it. We know “what needs to happen” but the important question is “can it happen?” There’s a quantitative and subjective answer to this question. The quantitative answer – quantified in our Sanity Rating – involves comparing The Buycast (what needs to happen) to the company’s historical revenue growth (what has happened) and to what Research Analysts at major Wall Street banks expect. We take all that into consideration to estimate a “Downcast” – this is our best, realistic scenario of anemic growth. The gap between The Buycast and Downcast determines our Sanity Rating.

The Downcast also leads to our Safety Rating, which quantifies the potential permanent loss we’re likely to face if our investment thesis goes wrong – when we believe that the company can easily achieve The Buycast and actually end up buying the stock based on that belief. But that belief may not pan out. What’s the damage then? In AAPL’s case, as of writing this, this is our estimated potential loss if we end up buying the stock:

The combination of the Sanity Rating and the Safety Rating makes up our overall Buycaster Rating. That’s our quantitative answer to the question: “should we believe what we need to believe (The Buycast) to consider buying the stock?” In Apple’s case, The Buycaster Rating is not great:

This was just a short preview of the heavy lifting that that The Buycaster does. It provides nuanced insights on over 3,000 stocks in just seconds. It saves us hours, if not days, of Valuation work when we’re analyzing a potential investment. It frees up precious time for to analyze things like a company’s competitive advantage. Remember Munger’s description of the game of equity investing:

“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…”

The Buycaster helps us quantify whether a gamble is mispriced, and by how much. If we know the company’s story, The Buycaster gives us the numbers we need. When we combine the two, we “know enough to know whether the gamble is mispriced”.

Sleep well at night: Don’t take the market seriously.

Markets are neither omniscient nor emotionally stable. It’s high time Finance Academics & Intellectuals accept this reality and stop teaching us otherwise (Efficient Markets). The idea of “wisdom of the crowds” doesn’t port over particularly well in the stock market. There are 2 main reasons:

  1. Everyone has a different estimate of “Intrinsic Value” because everyone has a different valuation model and a different risk tolerance.
  2. The price of any specific stock is not a weighted average of a giant meta survey of Intrinsic Value estimates. It is the last traded price, often between two very frenetic parties. The idea that the last traded price represents the most rational valuation of the company is bogus.

“The Real Measure of Worth In that famous speech about Graham-and-Doddsville, Warren Buffett said many important things, none more profound than this: ‘When the price of a stock can be influenced by a ‘herd’ on Wall Street with prices set at the margin by the most emotional person, or the greediest person, or the most depressed person, it is hard to argue that the market always prices rationally. In fact, market prices are frequently nonsensical’.” – Robert Hagstrom from The Warren Buffett Way

Individual investors and the overall market go through long spans of time when they operate with elevated fear or greed. One of the best mental models we’ve come across is that of the Market Pendulum:

Picture a pendulum that swings from FEAR on one end to GREED on the other, occasionally passing through a “zone of rationality” – except that this pendulum is highly irregular and unpredictable. This emotional instability applies to both the level of price on a specific stock and to the average price level of the overall market (or index).

All this sounds a bit scary because it goads us to take the Nihilistic approach: “well, then, what’s the point of investing at all…?” But if you think about it a little more, you’ll realize that the market being an emotionally unstable toddler is why we can make money. Time and time again, Mr. Market offers us buy or sell prices that are ludicrously cheap or insanely rich. That’s the time to buy or sell. But that requires dispelling this notion that the market is always right. It’s a mindset shift that’s not easy for many pros on Wall Street.

If there is one immutable law in the world of investing, it is this: The market pendulum will swing back and forth between fear and greed, passing through the “zone of rationality” – this is guaranteed. But it’s impossible to predict the timing and the speed of these swings – don’t believe anyone who claims they can.

The way to sleep well at night then, is to…well, let the legends of investing have the final word on this topic:

Don’t take the market seriously: “Be fearful when others are greedy; be greedy when others are fearful.” – Warren Buffett

The market is emotionally unstable: “Of course, the best part of [Benjamin Graham's approach] was his concept of ‘Mr. Market’. Instead of thinking the market was efficient, Graham treated it as a manic-depressive who comes by every day. And some days "Mr. Market" says, "I'll sell you some of my interest for way less than you think is worth." And other days, he comes by and says ‘I'll buy your interest at a price that's way higher than what you think it's worth.’ And you get the option of deciding whether you want to buy more, sell part of what you already have, or do nothing at all. To Graham, it was a blessing to be in a business with a manic-depressive who gave you this series of options all the time. That was a very significant mental construct. And it's been very useful to Buffett, for instance, over his whole adult lifetime.” – Charlie Munger

Don’t try to time the market: “It would be wonderful to be able to successfully predict the swings of the pendulum and always move in the appropriate direction, but this is certainly an unrealistic expectation. I consider it far more reasonable to try to (a) stay alert for occasions when a market has reached an extreme, (b) adjust our behavior in response and, (c) most important, refuse to fall into line with the herd behavior that renders so many investors dead wrong at tops and bottoms.” – Howard Marks

Don’t just ride the wave; it never lasts: “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 clocks have no hands.

We wish you Many Happy Returns.

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