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Is It a Bubble?

https://www.oaktreecapital.com/insights/memo/is-it...

Marks pulls (relevant) quotes from a number of recent thought pieces on AI and the valuation of the firms currently seen as leaders in the gold rush.
I know I don’t know enough to opine on AI. But I do know something about debt, and it’s this:
It’s okay to supply debt financing for a venture where the outcome is uncertain.
It’s not okay where the outcome is purely a matter of conjecture.
Those who understand the difference still have to make the distinction correctly.
(Bolding in the original)

His summation:

There’s a consistent history of transformational technologies generating excessive enthusiasm and investment, resulting in more infrastructure than is needed and asset prices that prove to have been too high. The excesses accelerate the adoption of the technology in a way that wouldn’t occur in their absence. The common word for these excesses is “bubbles.”
AI has the potential to be one of the greatest transformational technologies of all time.
As I wrote just above, AI is currently the subject of great enthusiasm. If that enthusiasm doesn’t produce a bubble conforming to the historical pattern, that will be a first.
Bubbles created in this process usually end in losses for those who fuel them.
The losses stem largely from the fact that the technology’s newness renders the extent and timing of its impact unpredictable. This in turn makes it easy to judge companies too positively amid all the enthusiasm and difficult to know which will emerge as winners when the dust settles.
There can be no way to participate fully in the potential benefits from the new technology without being exposed to the losses that will arise if the enthusiasm and thus investors’ behavior prove to have been excessive.
The use of debt in this process – which the high level of uncertainty usually precluded in past technological revolutions – has the potential to magnify all of the above this time.
Since no one can say definitively whether this is a bubble, I’d advise that no one should go all-in without acknowledging that they face the risk of ruin if things go badly. But by the same token, no one should stay all-out and risk missing out on one of the great technological steps forward. A moderate position, applied with selectivity and prudence, seems like the best approach.

(Ed: I sure hope he's sharing this perspective with his bosses at Brookfield. If I hear them repeat "backbone of the global economy: one more time with respect to data centers, I might take some painful capital gains).


Finally, it’s essential to bear in mind that there are no magic words in investing. These days, people promoting real estate funds say, “Office buildings are so yesterday, but we’re investing in the future through data centers,” whereupon everyone nods in agreement. But data centers can be in shortage or in oversupply, and rental rates can surprise to the upside or the downside. As a result, they can be profitable . . . or not. Intelligent investment in data centers, and thus in AI – like everything else – requires sober, insightful judgment and skillful implementation.

(Ed: Invest with skill, got it. Yogi Berra said it better (and shorter): predictions are hard, especially about the future. But Mark's postscript hits hard, because he starts thinking through the implications of "thinking" machines (or at least machines that can replace some amount of human activity) in a knowledge/skills based economy.

Joe Davis, Global Chief Economist and Global Head of the Investment Strategy Group at Vanguard, says, “for most jobs – likely four out of five – AI’s impact will result in a mixture of innovation and automation, and could save about 43% of the time people currently spend on their work tasks.” (Exponential View, September 3)
I find the resulting outlook for employment terrifying. I am enormously concerned about what will happen to the people whose jobs AI renders unnecessary, or who can’t find jobs because of it. The optimists argue that “new jobs have always materialized after past technological advances.” I hope that’ll hold true in the case of AI, but hope isn’t much to hang one’s hat on, and I have trouble figuring out where those jobs will come from.

TL,DR: May be

I hate to say this but Howard Marks memos have become boring (just my own opinion) with a lot of repetition and not a lot of wisdom lately.

AI has the potential to be one of the greatest transformational technologies of all time ... subject of great enthusiasm. If that enthusiasm doesn’t produce a bubble conforming to the historical pattern, that will be a first.
Bubbles created in this process usually end in losses for those who fuel them.

This motivated me to have a look at the hard numbers of another bubble that occured much more recently than the .com bubble, a bubble nobody talks about any more: SAAS stocks.

Overview for the uninitiated (hard numbers further below, after my preliminary blabla):
SAAS = Software as a Service = IT producing software which their customers don´t buy but rent, like Microsoft does with Office 365. Only that those companies do only that, relying on constantly renewed subscriptions to their software services, resulting in reliable(?) recurring revenue.

Surely you have personal experience with at least one of those companies, Cloudflare. Because near evewrybody sooner or later see a message "We need to make sure you are not a robot" on his screen and has to tick a box. This is one of the security features Cloudflare provides to it´s customers.

The SAAS bubble started around 2018. There were only a handful of pure SAAS companies around then, mainly Shopify. They had extreme growth rates. That draw the attention of some clever investors. Surely some here remember "Saul´s" (Rosenthal) board at The Motley Fool. Saul was/is a genius who very early spotted the advantages of the SAAS business model. He quickly had a huge number of followers. More SAAS businesses were founded. They made no profits, but their subscription numbers grew 50% or more each year (if I remember correctly +50%/year even was Saul´s criterion to put a company on his list). All was based on future hope that those extreme growth rates later could be converted into equally extreme profits. Their stock prices exploded. Many not just tripled or quadrupled within 2 years, but were 10x or more higher.

Very sophisticated and highly intelligent people on Saul´s board drilled deep down to make a well founded case for or against a SAAS company, looking deep into their numbers, at their competitors etc. Many of those early investors became Millionaires, Multi-Millionaires, maybe even more --- as always when a bubble forms and the clever ones get in early and leave before it bursts.

Bursting it did in 2022. The result for the SAAS stocks I followed during that time:

Name: Stock Price at height of Mania -> Current stock price
Amplitude: $83 -> $11
BILL: $334 -> $54
Cloudflare: $211 -> $208
CrowdStrike: $283 -> $517
Datadog: $192 -> $152
MongoDB: $500 -> $354
Sentinel One: $76 -> $14
Shopify: $169 -> $159
Snowflake: $392 -> $222 (a Berkshire investment)
Upstart: $390 -> 46
Zscaler: $368 -> $243

From those ones only the now undisputed leaders in Cybersecurity, Cloudflare and CrowdStrike, nowadays have a higher stock price than at the height of the mania. And even with those you probably would have lost nearly all your money if you had entered the "game" somewhere around the peak, as for the following years even those two winners traded far lower, Cloudflare even at around 1/3 of it´s peak price. Not to mention what happened to the other SAAS companies. Just have a look at Snowflake, a Berkshire investment: $387 at the peak of the mania, then for 3 years around $150, currently $222.

Summary: Manias are a great opportunity to make huge profits --- but only if your name is Saul (and not Said :)

Sorry for another post, but to be fair to the posters on Saul´s board I have to mention something very important I forgot: Saul was/is a trader, not a longterm investors. Somebody who spotted an opportunity, hopped on board --- and had no hesitation to sell the same stock a few weeks later when numbers came out which were not in line with his thesis (disappointing growth rates).

Therefore there was constantly A LOT of trading going on among his followers. And therefore the ones who did this right can only mildly smile about my comparison of "SAAS stock prices during the mania versus today" as it is not at all relevant for them. So it says more about Mania´s in general than about the results of the indivuals participating in them.

There’s a consistent history of transformational technologies generating excessive enthusiasm and investment, resulting in more infrastructure than is needed and asset prices that prove to have been too high. The excesses accelerate the adoption of the technology in a way that wouldn’t occur in their absence. The common word for these excesses is “bubbles.”
AI has the potential to be one of the greatest transformational technologies of all time.
As I wrote just above, AI is currently the subject of great enthusiasm. If that enthusiasm doesn’t produce a bubble conforming to the historical pattern, that will be a first.

Ok, I’m a just say it: it’s a bubble. When you can’t point to where the profits will come from and you’re still throwing endless gobs of money at it, that’s a bubble. That it might work out in the end - as the fiber laid in the dot com era or the houses which got absorbed (at distress prices) after 2008 didn’t go up in flames is irrelevant, the bubble is the definition of the investment dollars going up in flames.

A quick trip thru history tells me that the tulip mania lasted about 4 years. The Nifty Fifty era lasted over a decade, seemed a reasonable strategy for a while but only got crazy during the last 4-5 years and peaked just a year or two before the OPEC embargo, which crushed it. The real estate fiasco of the aughts went on for roughly 4-5 years.

The Railroad manias of the UK peaked from 1843-45 and crashed in 1847, while that in the US took a bit longer (and later) from 1866-73 ending in the (eponymous) Depression of 73. So again, half a decade, plus or minus. The Dot Com era began in 94, but the excesses became apparent in the late 90’s, say ‘97 or ‘98, and it was all over by 2001, if not sooner. So again: 4-6 years, depending on where you plant your “starting” and “ending” flags.

I’m thinking we’re about a year, maybe two into this “AI/data center era”. Suddenly everyone will wake up and say “Whew, what a hangover!”, and sanity will return. A few will do well rationalizing distressed properties, others probably not so much.

None of this means Google or Meta or whoever will go bankrupt, but there will be a reckoning of stock pricing which naturally drags everything else down, at least for a while. But the railroads continued. The internet continued. The telecommunications fiber is being used. The housing got soaked up, heck, we have a housing shortage just a few years later! (The tulip thing didn’t work out well for anyone, I guess.)

Anyway, the Goofy clock says Armageddon still could be a couple years away. Party on.

Anyway, the Goofy clock says Armageddon still could be a couple years away. Party on.


I think a major inflection point? milestone will be when Open AI goes public; which I think will happen next year.

tecmo
...

You definitely might be right. I've been thinking about DOW 50,000.

Just wondering about the paradox of bubbles.

On the one hand, Y'all talk about the dot com bubble as if everyone who ever invested in tech lost at least all their gains if not more. But me and (i'd estimate) a few thousand Qualcomm employees walked away with million(s) $ EACH, which to the best of my observation changed our circumstances permananently. (I became wealthier through the "bubble" and have never returned to the lower level). My uncle made millions, he bought MSFT and kept it. When I started working at Qualcomm he bought QCOM and kept it. Sure, his "winnings" peaked in early 2000 on the QCOM, but even at its maximum retrenchment, it was still many multiples of what it had been worth in 97, 98 or so.

Another guy worked for apple, kept his ESPP stock, and had millions of $s for tens of years. He eventually traded it mostly into Tesla and had millions from that, but that roller coaster certainly went in both directions while he was on it.

Obviously in a some very straightforward way, there are a BUNCH of stocks that seemed like the obvious choices in the 80s or 90s that if you just effing bought them and just effing kept them you have permanent wealth. My mistake wasn't buying AAPL before Jobs left and it almost went bankrupt, it was selling it. My mistake in TSLA wasn't buying it in the early 2020s, it was selling it. My lack of mistake in QCOM wasn't lovingly curating my options grants and ESPP stock, it was NOT selling them.

So what is the real story with these bubbles? Has somebody attempted to understand, how many people made money AND KEPT IT? And perhaps what they did that was different from the people who lost everything?

At the moment I find it doubtful you can lose money on the 10 year time scale by owning NVDA, OpenAI, Google, or likely even TSLA. Just like if you bought and the big techs in the 80s and 90s, AND YOU HELD ON TO THEM, you are still a lot better off.

I think losing money in tech booms is the subtext. I think making money in tech booms is much closer to most "reasonable" people's experience. Maybe I'm wrong, but I have lived a nice life for 1/4 century fundamentally rooted in my winnings from the .com "bubble". And I think I am on my way to doing even better with the AI bubble.

I just wanted to bring up this other thing which MIGHT be obvious, but nobody else is talking about.

R:)

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