The Elephant's Hard Landing
The elephant in the room at the Fed is a Hard Landing.
2005, a full 10 YEARS into being an institutional investor, I was still naive.
At OppenheimerFunds, responsible for $6B in mid-large cap tech stocks, and naive.
I walk into my boss’ office:
“I’ve looked at it every which way, and Broadcom’s numbers have no upside from here.”
9 months before, I had argued that we become the largest single holder of Broadcom stock when it was out of favor and this new technology, bluetooth, was starting to get adopted.
Bluetooth demand grew like wildfire. People wanted their phones to easily connect with their cars, stereos, wearables, and more. Broadcom was one of two global suppliers selling bluetooth chips.
The percentage of cell phones that had bluetooth went from 0% to 20% to 80%.
Then the rate of growth slows, as those last phones may wait till the price comes down.
That’s where we were December 2005.
When I looked at my estimates for Broadcom, they were great estimates, but everyone else now believed the same estimates, so the potential for upside surprise was gone.
I still loved the company, but recommended we sell the stock.
Like a fine thoroughbred racehorse, we’d ridden the stock rally on rising estimates.
Makes sense, so why was I naive?
Apparently, I’d played the estimate game ALL WRONG!
I figured out BEFORE we bought the stock, what I thought would happen. Then I tracked if it was happening, and the stock grew into my estimates.
I only changed my estimates if data came in to significantly change my thesis.
In the case of Broadcom, I never changed my estimates.
And my boss’ response?
“Here’s what you do: just raise each quarter going forward by 1 cent and then your estimates will be higher and we can keep the stock.”
This guy was paid MILLIONS for that kind of thinking! (This is why in my book, $100M Careers, I say anyone can break into investing, as long as you want to, like it and know the rules of the game)
What did I do?
I went for a long gym workout, which I often needed after talking to him.
I kept my estimates the same. One smarter portfolio manager sold. My boss did not.
Broadcom went down with the rest of semiconductors by 40% over the following 6 months.
What did I learn and relearn in my career that you can apply today?
Estimates are not really estimates.
This is where I was green, naive, and slow to learn.
Now when I think of estimates I reflect:
Don’t be the messenger who gets killed
Don’t be the bearer of bad news
No one likes a whiner
…and I keep my negative estimates to myself!
Here’s how I thought it worked on Wall Street:
Come up with a thesis for a new tech or sector
Figure out who the winner might be and what share they could get
Map out how long it would take, what sales and profits they would earn
⇒ From this process, figure out what their numbers would be and valuation, and track both if my thesis is proving more or less right (and adjust the numbers), and watch the company come closer and closer to my numbers.
Here’s how it ACTUALLY works on Wall Street:
Come up with a thesis for a new tech or sector
Watch the winner emerge, and forecast their market share a bit higher than what they have.
Forecast their share price 20% higher than the current share price for stocks you want people to buy, and forecast revenues and earnings higher than what they are today, but lower than management guidance so you have room to move them up.
⇒ From this process, every time the stock gets within 5% of your target price, you have room to move up revenues, earnings and your target price. Then your new higher targets help the stock maintain positive momentum if you are an analyst for an investment bank.
This is true in bull and bear markets.
Analysts will keep estimates and target prices around where the stock is, then wait for management to miss or guide lower, then adjust. Thus, they avoid being the messenger that gets killed.
In 1996, the year I should have learned these lessons, (not 10 years later!), I discovered the fraud at Enron.
Enron’s cash flow didn’t reconcile. They have to for audited financials. But they didn’t.
“Love what is, not what should be.” - Byron Katie
The two sell-side (at investment banks) analysts that brought up this fraud in 1996 were fired.
Why?
Enron kept going up, for four more years. The average Wall Street analyst career is only 5 years. Clients made more money by owning a fraud for another 4 years than they would have avoiding it for 1996-2000 (as long as they could get out before the collapse - a big assumption).
Analysts were paid to make clients money, not to expose frauds.
Another wrinkle?
Analysts aren’t paid or appreciated for helping clients avoid losing money!
The system makes sense when you look at incentives.
People are paid to make money.
No analyst is paid to stick their neck out with a real forecast.
The system and narrative are nicely oiled when analysts keep raising estimates a bit ahead of where companies are reporting, so companies can keep beating those estimates.
Thus, “estimates” are more a directional call, a qualitative vote. They are not a true estimate.
How can you apply this today?
The Fed came out this week with their “estimates” for GDP growth next year at 0.5% (flat year over year). Naive me would say the Fed is calling for a soft landing. But I have learned!
The Fed doesn’t want to be the bearer of bad news, the nervous Nellie, the messenger that gets killed!
What’s their upside?
None!
So, the Fed estimates a soft landing while their own behavior locks us into a hard landing.
A hard landing is The Elephant In The Room because no one wants to say it.
We, as a population, don’t want the truth... at least, not all at once!
Remember that great speech “You Can’t Handle the Truth” from A Few Good Men?
Powell’s rapidly rising interest rates and the steadfastness with which he intends to continue gives us true insights into where the economy will go. Want the truth? Build your own estimates.
Watch what people DO, not what they SAY. This applies to the Fed.
What does the Fed say?
0.7% GDP growth 2023, 1.8% 2024
”The outlook for the U.S. economy looks weaker now than it did three months ago, according to 38 forecasters surveyed by the Federal Reserve Bank of Philadelphia. The forecasters predict the economy will expand at an annual rate of 1.0 percent this quarter, down from the prediction of 1.2 percent in the last survey. Over the next three quarters, the panelists also see slower output growth than they predicted three months ago. On an annual-average over annual-average basis, the forecasters expect real GDP to increase 0.7 percent in 2023 and 1.8 percent in 2024.”
These annual projections are lower than the estimates in the previous survey.
Recognize those smoothing of the message signs? Lowering since last time. Lowering next quarter. Lowering next year by a bit more than next quarter…
Yup, now you know the signs!
The Fed has never forecast a recession.
There’s no upside for them. And…the Fed has something even sell-side analysts don’t have… Seasonal adjustments!
The Fed can lie with statistics to keep us placated longer while they go about their work.
Their dual mandates are full employment and price stability (inflation 2%).
Sure, they got ahead of themselves with 2021’s crazy notions of driving inflation up to drive up demand (see my articles on Stagflation and Expected Inflation).
But once inflation burned hot like a wildfire, Powell firmly moved back to addressing inflation.
The Fed has a lot of latitude as to what they say, and how that narrative fits into what they want all of us to do and think. But, as to what the Fed will do?
Their dual mandates drive that.
What is the Fed doing?
Wrangling inflation all the way back down to 2%.
In 1976, the pre-Volker Fed took its foot off the gas on rate hikes too early, and inflation came back, but growth did not, causing the worst of both worlds: Stagflation.
Then Volker had to come in and raise rates to 20%+ and crush the economy in order to stomp out expected inflation.
Powell doesn’t want to repeat the mistakes of the 1972-1975 Fed.
Powell sees himself as Volker 2.0
And the early results of our current War on Inflation?
Fed watcher DiMartino Booth:
"We’ve seen a YOY negative print on biggest measure of money supply six weeks in a row, longest time in U.S. history. … pay attention because of effect it will have on the financial markets…"
Full video: https://www.youtube.com/watch?v=qRAu3ZMXBPA
DiMartino Booth’s emails have shown leading economic indicators like ABI (plans to build), and many others all hitting negative territory, along with early negatives in retail sales starting to rear their ugly head. Unemployment, which is supposed to be a lagging indicator, seems to be coming early this recession as the pace of layoffs has surprised most.
DiMartino Booth continues:
“While there was no wavering in the Chair’s channeling Paul Volcker, there was a glaring element of denial in the Fed’s economic projections. The inconsistency: The median unemployment rate is projected to rise 0.9 percentage points from 2022’s fourth quarter to 2023’s fourth quarter “achieving” a soft landing with back-to-back gains of 0.5% for GDP this year and next.
Okun’s law, the trade off between economic growth and unemployment, renders one of these projections incorrect. If it’s unemployment, the Fed gets its soft landing and joblessness does not rise as anticipated. But if it’s GDP, recession will be undeniable. There has never – NEVER – been a postwar recession without a nine-tenth deterioration in unemployment. Period. Full stop.”
My thoughts?
If I put my sell-side, weathered and learned hat on, I’d say we are going to keep seeing projections decline.
If I put my naive, true forecaster hat on, it’s looking like a deeper and longer recession, but we can keep taking in evidence as it comes to adjust that forecast.
That is very different than refusing to tell the truth of your forecast (aka Fed and sell-side analyst style). I wrote about how to navigate recessions here.
Next week, I’ll shift to writing about building your own leverage (health, career, network), and then as we head into the New Year I’ll write about tactics and thoughts of longer, deeper recessions.
Parting thoughts:
Christmas Carnivores?
If you are wanting a creative Christmas gift for a carnivore in your life, one of the ranchers who leases land from us took the huge financial risk of applying for a meat processing license. The big processors tried all kinds of financial and political blackmail to block his application, but he persisted.
Now, he and his family now have an end-to-end, personally-run farm where they raise the cattle and can ship out fantastic collections of beef, lamb, and more.
Tech not to be missed: ChatGPT
In 2020, I dove deep into GPT3. Now, it’s all the rage.
AI success is driven by two things:
The algorithm it uses, and
The data it learns from.
What’s different about GPT3’s algorithm?
Most algorithms are stale (math programs created decades ago). They ask the computer to minimize errors toward an objective. This doesn’t work for learning through trial and error.
Why?
Avoiding errors means less learning.
Enter Kenneth Stanley PhD who wrote the new algorithm called Novelty Search (in the Genetic Algorithm family). Novelty search asks the AI to try something it hasn’t tried before, with each step. You have to keep the search area limited so it doesn’t try infinite things, but Novelty Search can learn far faster and best mimics both evolution and innovation.
Dr. Stanley, the inventor of Novelty Search, is a friend of a friend. He invented Novelty Search at University of South Florida, was hired away to run Uber’s AI efforts, then left to lead OpenAI.
What’s different about GPT3s data.
GPT3 ingested 1,000 times more data than any AI had in the past. It read the internet. The WHOLE internet, or close to it at the time (in 2019).
Ask someone how to code and you are referred to the “documentation”.
GPT3 read that.
Blogs, code snippets, coding classes, social media.
GPT3 read it.
GPT3 combined a more modern open-minded algorithm that mimics evolution and innovation with 1,000X more data to train on.
The result?
AI that can write like a New York Times columnist, get Bs and some As on college exams, code and create art from written descriptions (Dale-E 2).
So now, OpenAi, the owner of GPT3 AI, released their first “product”: ChatGPT3.
In a matter of weeks, over 1 million users signed up. It can write articles, code, draw beautiful art, search for what you want like Google, and more. Ajay Agrawal, the co-author of “Power and Prediction: The Disruptive Economics of Artificial Intelligence,” and a professor at the University of Toronto, spoke to the NYT’s DealBook:
“Everyone should be thinking how this (ChatGPT) is going to change their jobs, and how their organizations should operate when people don’t have to do the writing.
Remember the first time you saw email?
People only thought about how it would impact postal carriers, but it actually changed the way we communicate as a species. In 50 years, looking back, this moment we’ve just witnessed, when a machine can write like a human, will mark a major shift.”
Of course, we have been saying some version of this about AI since the mid 1960s, but this looks like the real deal to me. Here’s where you can go to learn more and try out ChatGPT: https://openai.com/blog/chatgpt/