Tag: musing

Foreword

There are some who think that stocks are gambling, that trading stocks is, essentially, a zero sum game. In some sense, they are right, but the truth is more nuanced than that.

How do we reconcile the idea that trading stocks are a zero sum game, with the very real fact that a non-trivial number of financial fiduciaries encourage their clients to invest in stocks?

Can you even “invest” in something that is a zero sum game?

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Flip flopping

Let’s say we have 2 buddies, Alex and Blair. They each have $1,000 as they begin their journey:

	Total Cash (dollars)	Total Assets (units)	Asset value (dollars)	Debt (dollars)	Net Worth (dollars)
Alex	$1,000	0	$0	$0	$1,000
Blair	$1,000	0	$0	$0	$1,000

Now, let’s say they have a brilliant idea(1) — they’ll create a brand new asset, let’s call it Kelpie, and they have a brilliant, fool-proof way to get rich, together. First, Alex starts with 100 Kelpies, conjured out of thin air, and they will value it at $1 each.

	Total Cash (dollars)	Total Assets (units)	Asset value (dollars)	Debt (dollars)	Net Worth (dollars)
Alex	$1,000	100	$100	$0	$1,100
Blair	$1,000	0	$0	$0	$1,000

Voila, our two friends, combined, are now $100 richer. But they have grander plans than that! Alex next sells 50 Kelpies to Blair at $1.10 each. The “market value” of each Kelpie is now $1.10.

	Total Cash (dollars)	Total Assets (units)	Asset value (dollars)	Debt (dollars)	Net Worth (dollars)
Alex	$1,055	50	$55	$0	$1,110
Blair	$945	50	$55	$0	$1,000

Now, our two friends are, combined, $10 richer — Blair is still worth $1,000, but Alex made another $10. Well, this is a mutually beneficial relationship, and so far, only Alex is making hay. To make it up to Blair, Blair now sells 10 Kelpies to Alex, at the princely price of $2 each.

	Total Cash (dollars)	Total Assets (units)	Asset value (dollars)	Debt (dollars)	Net Worth (dollars)
Alex	$1,035	60	$120	$0	$1,155
Blair	$965	40	$80	$0	$1,045

Notice how both Blair and Alex are now worth more than their initial $1,000. More interestingly, even though Alex bought Kelpies from Blair at a much higher price than when they sold it to Blair, Alex actually “made” $45! I think we have a winner here!

Alex and Blair continue trading between themselves, with Kelpies trading at higher and higher prices. Eventually, we hit this state, where Kelpies are $100 each:

	Total Cash (dollars)	Total Assets (units)	Asset value (dollars)	Debt (dollars)	Net Worth (dollars)
Alex	$2,000	20	$2,000	$0	$4,000
Blair	$0	80	$8,000	$0	$8,000

Now, we have a problem. Blair is supposed to buy Kelpies from Alex this round, but they are out of cash! That’s fine, Blair takes out a loan of $1,000 against their “assets” of $8,000 — that’s only a 12.5% loan-to-value (LTV), which is generally considered “safe” by most banks. Blair then use the newly acquired cash to buy more Kelpies from Alex at $200 each.

	Total Cash (dollars)	Total Assets (units)	Asset value (dollars)	Debt (dollars)	Net Worth (dollars)
Alex	$3,000	15	$3,000	$0	$6,000
Blair	$0	85	$17,000	$1,000	$16,000

Notice how Blair’s net worth doubled, despite taking out a loan, and spending cash to buy Kelpies.

Our two friends continues trading Kelpies between themselves, taking out loans if needed if one of them runs out of cash when it’s their turn to buy. By trading Kelpies back and forth, both of them managed to greatly improve upon their net worth. Their last trade has Kelpies valued at $1,000 each. Houston, we have liftoff!

	Total Cash (dollars)	Total Assets (units)	Asset value	Debt (dollars)	Net Worth (dollars)
Alex	$10,000	40	$40,000	$5,000	$45,000
Blair	$2,000	60	$60,000	$5,000	$57,000

Car shopping

At some point, Blair decides they want to buy a new car. And since they are rich now, only a fancy car will do — a fancy car that costs $50,000. It’s going to hit their net worth hard, but what the hell, you only live once! Besides, Blair has found the secret infinite money cheat to life!

Unfortunately, the car dealership won’t take Kelpies (they simply do not see the transformative nature of Kelpies), and they want cash instead. So Blair went to Alex, and asks (nicely) if Alex would buy some Kelpies from Blair at, say, $1,100 each, so that Blair can raise $50,000 for the new car. However, Alex does not have the cash, and is unwilling to take out such a huge loan.

That’s OK — they have on their hands a transformative asset, that is rising in price faster than inflation. Everybody trading this asset has agreed that it can only go higher, and will never sell at a lower price. So it seems only natural that they should spread this gospel to the world, and lift millions out of poverty!

Alex and Blair approach Cameron, their mutual friend, and fortunately, someone already rather wealthy. They persuaded Cameron to buy some Kelpies from Blair, at $1,500 each:

	Total Cash (dollars)	Total Assets (units)	Asset value	Debt (dollars)	Net Worth (dollars)
Alex	$10,000	40	$60,000	$5,000	$65,000
Blair	$54,500	25	$37,500	$5,000	$87,000
Cameron	$0	35	$52,500	$0	$52,500

Blair then takes $50,000 and buys the new car.

	Total Cash (dollars)	Total Assets (units)	Asset value	Debt (dollars)	Net Worth (dollars)
Alex	$10,000	40	$60,000	$5,000	$65,000
Blair	$4,500	25	$37,500	$5,000	$37,000
Cameron	$0	35	$52,500	$0	$52,500

Reality bites

To celebrate their new found wealth, the 3 friends decide to take a road trip in Blair’s fancy new car. Unfortunately, they got into an accident, and were all seriously injured. The medical bill came out to $12,000 for each of the friends.

No problem, they thought — all 3 friends are much richer than that, and can easily afford it.

The friends offered Kelpies to the hospital for their bills, but the hospital politely declined. As with the car dealership, the hospital simply did not have the foresight to see the transformative nature of Kelpies, and instead, demanded cash. Well, now we have a problem — our friends are asset rich, but cash poor.

Alex quickly realized that they really only need another $2,000 to cover the bills. So with deep regret, Alex offers to sell 2 of their Kelpies at the previous price of $1,500 to Blair. Alex was previously planning to sell only when Kelpies hit $3,000, so Blair is really getting a good deal here!

Blair looked at their holdings, and at the medical bill, and came up with another idea. How about, Blair sells Alex 8 of their Kelpies, at the unbelievably great deal of $1,200? This will give Blair enough cash to pay their bills, and still have $2,100 left over. And Alex got to buy Kelpies at the fantastic price of $1,200!

Cameron, too, looked at their holdings, and at the medical bill and came up with another even better idea. How about Cameron sells Alex 8 Kelpies for only $1,000 each ($200 cheaper than Blair!), and then another 4 Kelpies to Blair at the same price? That’ll give Cameron enough cash to pay the bill, and both Alex and Blair will get a GREAT DEAL!

This goes on for a while, until eventually, the friends realize, that between the 3 of them, there really is only enough cash to cover one person’s medical bills, and no amount of trading or discounting will change that fact. Also, collectively, they are now $10,000 in debt.

Stock vs flow

As alluded to in Investing vs Speculating, purely trading/speculating is a zero sum game. In our little story, the entire “market” only ever had the actual value that the friends themselves put in. Before Cameron joined the game, there was only ever $2,000 (net of debt), which was why despite their lofty “net worth”, Blair was not able to buy the car without the cash infusion from Cameron.

There never was the grandiose “value” that our friends made up in their minds, it was only ever “paper gains”, and our friends committed the sin of confusing stock with flow.

Flow – The transactions at the margin of the market

Stock – The totality of all assets in the market

Our friends thought that just because there was flow, and that the flow was consistently valuing Kelpies at a higher price, that, therefore, their stock of existing Kelpie was worth as much. This quickly breaks down, when the liquidity needs of the market participants exceeds the available flow in the market. And when that need for liquidity emerges, the phrase “prices are set at the margins” quickly became apparent.

Zero sum game?

Kelpie was just a analog for a stock, right? So, are stocks a zero sum game?

No, and no.

Kelpie is an analog for any asset that can be traded, not just stocks. This means, stocks, gold, bonds, houses, cars, bread, art, etc. Everything that can be traded. But no, that does not mean stocks (or any of the other assets listed) are zero sum games.

Remember that stocks represent fractional ownership of actual businesses. Assuming the business is performing well, it will generate profits. Even if the profits are not distributed to the shareholders, the profits exist somewhere. Unless there is fraud, that somewhere is generally “the books of the company”. This means that if Kelpie was a business, then the 3 friends could have just found another entity to buy the business from them. If the business is run well, and is profitable, it shouldn’t be hard to find some entity willing to pay for the business, although possibly at a discount — the 3 friends are desperately in need of liquidity, and thus have less leverage in making the deal with the buying entity.

In effect, a productive asset, like a stock (or bond) periodically injects the value of their production into the system, which means the entire system is a positive sum game.

For other assets, like cars and bread, which have intrinsic values (people want the car/bread, because both have attributes that are desirable), there is a natural floor to how low the prices of the assets will go. Yes, in a firesale, where the seller is desperate for liquidity, they may sell the asset for less than intrinsic value. But if the seller has enough time to shop around for buyers, they will likely be able to get fairly close to intrinsic value at least. This also means that if someone bought an asset with intrinsic value at a price higher than its intrinsic value, they stand a higher chance of losing money — unless they can find a greater fool to pay an even higher price, they will be forced to sell at intrinsic value, at a loss.

In effect, for non-productive assets, trading is basically a zero sum game — without the constant injection of value from production, the net of all trading will be $0. That said, assets with intrinsic value at least have a price floor. Assets with no intrinsic value, like our original Kelpie, will likely go to nothing eventually (technically, they revert to their intrinsic value of $0).

Productive assets at any price?

Let’s consider a stock that represents fractional ownership of a business.

At an instance in time, where the business already has some amount of assets on its books, and also has the potential to generate future profits, we are able to value the assets currently on its books, and as well as to provide an approximate value for the future profits (see the How To Value A Company series for discussions on how to value a company).

In some sense, at a specific moment in time, we can say that a business has a fixed intrinsic value, and we can treat the business as essentially non-productive, at that instance in time.

Which means that yes, like with regular non-productive assets, it is possible to overpay for a business (i.e.: stock).

To paraphrase Investing vs Speculating —

The net amount of gains and losses, from all investors of [a business], across all time, based only on [the business], will be exactly equal in dollar value to the sum of all earnings of [the business].

So, you can consider trading stocks as both investing and speculating. Part of the profits from trading stocks will come from the productive part of the business (i.e.: investing), and part of the profits will come from just selling to a greater fool (i.e.: speculating).

Now, consider the P/E ratio of a company — it is the price of the company, divided by its earnings (i.e.: profits (2)). In effect, the P/E ratio is how much you pay for each dollar of profits from that company.

Remember how profits are injected into the system for productive assets, leading to positive sum games?

Let’s say we have a company with a P/E ratio of 1, i.e.: investors pay $1 for each $1 of earnings.

Every year, an equal amount of value is injected into the system as the value of the stocks. In this extreme case, the productive nature of the asset is very significant to the trading — it represents 100% of the stock value of the asset every year! In effect, if we have $1m of stock value, then every year another $1m of productive value is injected by the business, pushing our zero sum game to a sum of +100% per year.

Now, let’s consider a company with a P/E ratio of 1,000, i.e.: investors pay $1,000 for each $1 of earnings.

Every year, only 0.1% (1/1000) of stock value is injected into the system by the production of the business. In this extreme case, the productive nature of the asset is almost a rounding error — it pushes the trading from zero sum to sum of +0.1% every year.

So, the larger the P/E ratio(3), the most speculative, and more “zero sum game”y the asset.

Final words

As with our 3 friends, in the heat of the moment, when our paper net worth is rising quickly for what seems like doing nothing, it is easy to convince ourselves that we are geniuses, that we have discovered “the secret to wealth”, or that the asset(s) we are investing in has intrinsic value — who wouldn’t want to own an asset whose price is going to the moon?

But remember that unless the asset has productive value, in an emergency, when you desperately need liquidity, it may be hard to sell the asset for anything more than intrinsic value. And intrinsic value may be a lot lower than whatever price you personally paid.

It may help to think of “the asset” as “a $1 bill”. Yes, if you have a $1 bill that, for whatever reason, is desirable (maybe it was handled by some famous celebrity), you may be able to sell it to a speculator for more than $1. But the universe of people who are wiling to pay more than $1 for a $1 bill is relatively small — not everyone cares about the provenance of their cash. So the latest owner of that $1 bill, may find that in an emergency, they can really only use that $1 bill as… a $1 bill — even if they paid $100 for its provenance. In effect, that $100 “intrinsic value” applies only to a niche market, and the broader market simply does not care, and unless you can find someone else from that niche market, you are stuck with the broader market’s intrinsic value of $1.

Footnotes

1. For the purposes of this illustration, we are going to ignore the legality of the things discussed. Some of the things discussed here are in the legal gray area (some may be outright illegal!), so please, do not try this at home.
2. Earnings/profits mean something very specific in finance/accounting. Technically, the usage here is not quite correct, but it’s close enough. See How to value a company – income statement for details.
3. This is an oversimplified explanation. In reality, businesses grow — just because a business generates $100 in profits this year, doesn’t mean it’ll only generate $100 in profits the next year. A company with growing profits and static stock price, will naturally see a P/E ratio that shrinks with time. In effect, P/E ratio is a static, snapshot in time, valuation metric, that does not capture the dynamic nature of businesses over time.

Foreword

I recently chanced upon some benchmark numbers of the new(ish) Apple M1 chip, and the results were rather surprising. Like all good little engineers, I started digging deeper, and frankly, what I found WILL BLOW YOUR MIND! (1)

Note that this post is mostly a nerd-out. But there is a finance bit to it. If you are only interested in the finance bit, skip to the Wild guess section below.

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Disclaimer

Before we begin, I want to note that I am not an Apple fan. At least, not a traditional one. I do have iPads (multiple over the years), iPods (multiple over the years, and technically, my wife’s), and various other Apple services/products.

But for computers, I’ve always been a DOS/Windows/Linux kind of guy. I’ve never owned a Mac of any form (except assigned by work), and I’ve never owned an iPhone.

An impressive little package

I stumbled across a bunch of blog posts and videos and whatnot’s, and it’s probably not very useful to link all of them here. So I’ll just link this one video (2), start at the linked timestamp (around 8m30s). There are a lot of issues with the methodology (3), but it presents a fairly accurate picture based on my understanding of the other blog posts/videos.

In short — the new M1 chip from Apple seems to be outperforming both Intel and AMD chips by a fairly large margin. This particular video is against mobile chips from Intel and AMD, though other sources suggest that general trend carries across to desktop chips. This out performance is also generally true for both CPU and GPU intensive benchmarks. Most importantly, the Intel and AMD chips, are sometimes packaged in machines multiple times more expensive.

The only times the M1 has conclusively lost are generally in one of these categories:

• Benchmarks where more than 4 CPU cores are involved — the M1 only has 4 “performance” cores, so loses out in these benchmarks.
• Benchmarks where an external GPU is used — M1 machines don’t seem to work with eGPUs (at least, none of the comparisons I’ve seen included M1 machine+eGPU).
  • In GPU-intensive benchmarks, and depending on the eGPU, the M1 generally loses by a fair margin.

You do not make potato chips with apples

Apple is not a traditional manufacturer of chips. Yes, they’ve dabbled more and more in recent years, mostly for their iPhones/iPads, but most people think of Apple as more of a purveyor of “final packaged products”, instead of a player in the chips space, like Intel or AMD, both of whom have decades more experience.

There have been many, many other players who have tried to take on the chips space. For the most part, they are either gone or have gone niche — Intel, AMD, nVidia (for GPUs) remain the undisputed heavyweights in this space.

So what is Apple doing, challenging the champions… and seemingly winning?

Golden Apple

On a different note, Apple has also been, traditionally, a manufacturer of higher end products (“lifestyle” products), and the prices they charge tend to reflect that. While they have made forays into the lower end of the consumer market in recent years, people still generally associate Apple with “expensive but good”.

And then the M1 comes along, plonked into relatively affordable machines like the Mac mini, new iPads, MacBook Air, etc., many of which start below the psychological $1,000 barrier. For reference, my first ever computer (in the 80’s) was a $2,000 beast (in size) that probably has less firepower than the modern day handheld calculator.

So it is doubly confounding, that these relatively cheap Apple machines are beating the traditional champions housed in machines that are much more expensive.

Wild guess

A long time ago, chip manufacturing was tightly coupled with chip design — Intel (or AMD, etc.) designs a new chip, and then manufactures that chip in their own foundries. So a large part of a chip manufacturer’s ability to deliver superior products, was based on their ability to research and come up with better chip manufacturing (as opposed to design) techniques (4).

In more modern times, this has changed somewhat. Actual chip manufacturing tends to be outsourced to 3rd party manufacturer like TSMC, Samsung, Qualcomm, etc. The traditional manufacturers also do some manufacturing of their own, but my understanding is that the 3rd parties generally have better technology that can produce better chips (4).

As a somewhat simplistic mental model — Intel/AMD/Apple draws on a piece of paper what they want built (i.e: the chip design), flies it by carrier pigeon to TSMC/Samsung, and it is TSMC/Samsung that does the actual manufacturing.

In this new paradigm of chip manufacturing, it becomes easier to see how it is that a relative upstart (admittedly a very well funded one) is able to produce the M1, and apparently, at a lower price point.

So what?

The traditional strength of the OG chip manufacturers used to come, largely, from their ability to manufacture better chips. That strength apparently has been eroded by this new “Manufacturing Chips as a Service” (MCaaS?). This seems to be best shown by the M1 chip — the first, in a very long time, (that I know of) chip from a non-OG manufacturer that unambiguously beats out chips from the OG group, at least in the mobile space.

Intel recently made announcements that it’s planning on building a bunch of new factories. Part of that seems to be motivated by national security concerns (the new factories are entirely in the US), part of it seems to be motivated by the recent chips shortage. But I can’t help but wonder, if part of it is also they recognize that their traditional strength and thus competitiveness has been eroding for years?

Roger that – short Intel, AMD, nVidia!

No. That’s not what I’m saying at all (though I am seriously rethinking my model of AAPL valuation).

No doubt Intel, AMD, nVidia have leadership that aren’t idiots, and will likely try to turn their ships around. AMD and nVidia, in particular, are also doing pretty well financially (in part due to Intel’s recent stumbles).

Also, remember that hardware is not like software. The additional complexity required to add 1 more bit of data is not always linear — in some cases, adding 1 additional bit of data doubles the complexity of the circuit. So the fact that M1 only has 4 performance cores, while top end OG chips have as high as 64 (hyper threaded) cores suggest that at least at the very high end of performance, the OGs still have a trick or two up their sleeves.

The OGs can also learn from the M1. Traditionally, they’ve made chips with scaling power/performance tradeoffs. Maybe the better way is to just build chips with a fixed number of “performance” cores, and a fixed number of “efficiency” cores. My very naive (and likely outdated) thinking suggests this would make the circuitry quite a bit simpler to design.

It’s still not a foregone conclusion that the M1 heralds a new age of Apple chips everywhere, but it is, at least, a fairly resounding shot across the bow. And maybe, the OGs will take notice and up their game.

Footnotes

1. I’ve also recently read about click baits and the tricks they use. Did it work? 😉
2. I am not endorsing the author of the video — I’ve seen his videos before, but I don’t subscribe to them, I chanced upon this one. That said, his videos are of reasonable quality, though with some caveats (see below).
3. Benchmarks are not very scientific — manufacturers have been known to game them with specialized hardware/code that makes their products seem better than they really are. Also, the benchmarks necessarily must run atop software (the OS, various drivers, etc.), as well as other non-chip hardware (motherboard, RAM, the various buses, etc.). The fan-speed/noise complaints and the thermal imaging bits are also rather iffy — that’s very heavily dependent on the material of the casing, layout of the board, etc.
4. Technically, I’m formally trained to design my own chips. Practically, I go to NewEgg/BestBuy just like everyone else (not endorsement). Which is to say, if I’m misusing some terms, I apologize, please let me know and I’ll correct.

Foreword

I first made a version of this post over a year ago in the early days of 2020 BC (Before Covid19). Back then the markets were roaring, despite news of some virus in some province of China. I mean, who cares, right?

Just before news of the virus, we just sort of started a trade truce, for a trade war with China, that wasn’t really a war, officially called a trade dispute. And that itself was just a few short weeks after one of the most tense nuclear standoffs between the US and North Korea in recent memory. Oh, and 2020 was an election year. I mean, clearly, markets should be ROARING! What could go wrong? Amirite?

As usual, a reminder that I am not a financial professional by training — I am a software engineer by training, and by trade. The following is based on my personal understanding, which is gained through self-study and working in finance for a few years.

If you find anything that you feel is incorrect, please feel free to leave a comment, and discuss your thoughts.

Death of price discovery?

Something that has been catching the headlines lately, and was actually talked about in certain circles for a few years now, is the “death of value”.  I want to broaden the scope a bit, and make the claim that (not that I believe it, but rather, just as a motion to debate) “price discovery is dead”.  Not “dead” as in completely irrelevant, but “dead enough” that maybe it does not (and maybe should not!) factor into most people’s investment decisions, and certainly means valuation metrics like P/E, P/EG, P/S, P/FCF, etc. ratios are mostly meaningless nowadays.  Whether it eventually resurrects, is, also, an interesting side topic to explore.

Let’s go back a few decades, to pre-1990.  Especially in the 80’s, large financial entities that engaged in essentially “price discovery” were common.  Large hedge fund do fundamental research (Berkshire Hathaway is a well known example) and buy/sold based on that research.

In the 90’s and beyond, new financial innovations and research popularized “passive investing”, where essentially, the individual benefits from the work of the “price discoverers” via buying a basket of names.  With this as the basis, further research mostly tended to focus on allocation across asset classes, with an almost religious belief that prices properly reflected fundamentals (or at least, close enough to not matter).

Having worked in a (relatively successful) quantitative hedge fund for a few years, it surprised me greatly to find that many there probably cannot make sense of a balance sheet, income or cashflow statement — even people working on the research side of the business don’t always focus on fundamentals.

Also, when talking/listening to people from other hedge funds (some of which are not quantitative) and banks, it does seem like focus on fundamental value is not highly prized.  Most people seem to care more about quantitative issues like “relative value”, “momentum” or “reversion”, technical issues like “crowding” or “short squeezes”, and behavior issues like “story stocks” (aka meme stocks), etc.  In the past decade or so, almost nobody has talked to me discussing a trade where the subject was a buy or sell because of its fundamentals, with an argument that wasn’t easily dismissed as naïve or wrong.

Final note to illustrate this point: I attended a course, over ~6months of roughly fortnightly classes, where a lecturer (former head researcher of a major bank) was invited by a major bank to teach the basics of finance to their new hires, and new hires of clients (i.e: the hedge fund I worked for).  Throughout this course, we learned about how to value derivatives and bonds, how to trade swaps, FX, etc.  Yet, we spent a grand total of 0 minutes on how to value a stock.  Yes, we literally learned how to derive and compute various higher order derivatives of a stock, but never bothered to even discuss how to estimate the price of the underlying.  Imagine if your physics/calculus teacher taught you how to derive dy/dx, d^2y/dx^2, etc., but did not teach you how to solve for y = ax^2 + bx + c.

Quant hedge funds make money by being more efficient, or taking advantage of small arbitrage opportunities of some form (time arb, info arb, statistical based on behavior/technical, etc.), banks profit off spreads based on arbitraging their superior market knowledge or customer relationships.  What about fundamental hedge funds?

Let’s say you have the magic formula, and you can determine the exact correct price for a stock at any point in time (to the 10th decimal, etc.).  What then?  You cannot profit by simply buying/shorting the stock.  For that to work, it’s not enough that you “see the truth“.  Others must see the truth too, and they must see it after you.  This is why many fundamental hedge funds (Muddy Waters is really the only one that comes to mind right now) go public so often with their research. But convincing a large majority of people to see your point of view isn’t easy, and even if you are right, if someone with enough wealth decides you’re wrong, you may still lose financially (see Ackman vs Icahn, re: Herbalife).

So, most non-quant hedge funds nowadays mostly just work off a few related concepts:

• Relative value (1)
• CAPM (1)
• MPT (2)
• Technicals (e.g: selling covered calls to generate additional income, many/most long-short strategies, etc.)

Very few of them actually find stocks that are undervalued/overvalued and then buy/short them.  Underlying all the points above, is the argument that everyone essentially believes that the price of stocks are “correct” (or at least, “correct enough”).

What about the average person?  Here, I have no anecdotal evidence, but general sweeping statements (which I hope most people will agree with):

• The average person knows even less about valuations than the average financial company employee.
• The average person either buys passive instruments and forgets about their investments, OR
• are mostly buying “randomly”, OR
• are mostly buying things they understand (i.e: brands they like).

So, given that very few people are actually trying to value stocks on a fundamental basis, are prices still correct?  But more importantly, do they still matter?

And here, I’m going to make a wild claim (again, not that I fully believe it): Prices no longer matter (much)… for a company that is stable.

Let’s say you have a company, we’ll call it Tongass.  Tongass is not a particularly profitable company, but it is profitable.  It IPO’d a long time ago.  So, how much would you pay for 1 share of Tongass?

If Tongass went bankrupt, then $0 (or more accurately, (total assets – total liabilities) / share count). But since Tongass is profitable, and seems likely to remain that way, bankruptcy is not an issue.

So now what? $1? $2,000? $10^6?

At some extremes ($1 or $10^6), the stock price would matter, since Tongass no doubt rewards some number of employees with equity, and that affects their motivations, etc.  But for the vast range of “in the middle” (say $1,000-$3,000), it probably won’t matter too much.  Yes, some employees will be able to afford nicer houses/cars, but most of them will still need to work, and most of them will still be motivated to remain with Tongass. (3)

So, for a large range of the stock price, the operating metrics of Tongass will not be affected much, if at all.

And if the stock price doesn’t really matter to Tongass, and nobody seems to really care about the absolute value of the stock/company, then, does it really matter?

Footnotes

1. I don’t consider CAPM as fundamental valuation, but rather, a form of “relative value”.  If you look at the formulation, you can see that everything in CAPM deals only in quantitative space, there’s zero mentions of whether the company is even profitable.
2. Similarly, MPT is mostly about trying to manage risk and configuring your portfolio for optimal expected returns based on accepted risk parameters. There are no mentions of fundamentals at all in MPT.
3. Just to note, that if you were actually considering between $1, $1,000, $3,000, or whatever for each share of Tongass, you would have already fell into the trap — I did not mention at any point the metrics of the company, nor how many shares it has outstanding. So how can you even begin to value a single share of an unknown quantity of shares, for an unknown quantity of sales, profits, expenses, etc.?