Month: February 2024

A Tale of Two Consumers (KKR)

Home ownership has been a significant factor in consumer resilience in a turbulent economy. In the United States, fixed-rate mortgages protected existing homeowners when interest rates started to rise. More than 95% of U.S. mortgages have fixed interest rates, and the average existing mortgage rate is at a 45-year low. Many focus on rates of 30-year U.S. mortgages, which sat above 7% for much of the second half of 2023 and now sit at 6.63%.

However, the average effective rate for existing homeowners is about 3.5%, about 50 basis points lower than the pandemic. In fact, some 80% of U.S. mortgages have an interest rate under 5%, while some 40% of American homeowners own their homes outright.

Debt Service Costs as % of Disposable Income

Data as of March 31, 2023. Source: Federal Reserve Board

A rally in asset prices has disproportionately benefited higher-income consumers. The wealthiest 10% of Americans owned 89% of equity and mutual fund shares at the end of the second quarter of 2023. (…)

Younger consumers and those with lower incomes, however, spend a far greater share of their incomes on essentials, making it more difficult to cut expenses meaningfully when inflation hits. Lower-income borrowers are also more likely to be renters at a time when rents have risen dramatically. Rents were some 7.2% higher as of October 2023 than they were a year ago. Our macro team also points out that low-wage employment grew more rapidly than employment in higher wage categories after the pandemic but is now tapering off.

Pandemic stimulus funds temporarily boosted the credit scores of many younger and lower-income borrowers, but some recent data shows that lending to this group may have increased more than warranted. Credit card balances among lower-income consumers have risen sharply. Younger consumers stepped up their borrowing the most during the pandemic and are now driving a recent uptick in credit card and auto defaults. Indeed, defaults for subprime credit card and auto borrowers are already above pre-pandemic levels, though unemployment has yet to meaningfully increase.

Percent 30+ DQ

Source: Dv01 Consumer Unsecured Benchmark as of October 31, 2023

The upshot of these trends is that consumer defaults are ticking higher and are likely to continue doing so as economic growth slows. Our Global Macro & Asset Allocation team, however, expects that subprime borrowers will make up a disproportionate number of defaults.

EARNINGS WATCH

From LSEG/IBES:

448 companies in the S&P 500 Index have reported earnings for Q4 2023. Of these companies, 77.5% reported earnings above analyst expectations and 17.9% reported earnings below analyst expectations. In a typical quarter (since 1994), 67% of companies beat estimates and 20% miss estimates. Over the past four quarters, 76% of companies beat the estimates and 19% missed estimates.

In aggregate, companies are reporting earnings that are 6.8% above estimates, which compares to a long-term (since 1994) average surprise factor of 4.2% and the average surprise factor over the prior four quarters of 5.7%.

Of these companies, 63.8% reported revenue above analyst expectations and 36.2% reported revenue below analyst expectations. In a typical quarter (since 2002), 62% of companies beat estimates and 38% miss estimates. Over the past four quarters, 66% of companies beat the estimates and 34% missed estimates.

In aggregate, companies are reporting revenues that are 1.1% above estimates, which compares to a long-term (since 2002) average surprise factor of 1.3% and the average surprise factor over the prior four quarters of 1.6%.

The estimated earnings growth rate for the S&P 500 for 23Q4 is 10.0%. If the energy sector is excluded, the growth rate improves to 13.7%.

The estimated revenue growth rate for the S&P 500 for 23Q4 is 3.4%. If the energy sector is excluded, the growth rate improves to 4.8%.

The estimated earnings growth rate for the S&P 500 for 24Q1 is 5.4%. If the energy sector is excluded, the growth rate improves to 8.4%.

Corporate guidance is weak however with a negative/positive ratio of 3.7 vs 3.0 one week ago and 2.1 one quarter ago. Of the 27 pre-announcements of the last 2 weeks, 22 were negative.

But analysts (and investors) don’t care, or don’t believe. Q1’24 earnings are seen up 5.4%, from +5.2% one week ago.

Positive revisions are concentrated in only 3 sectors: tech, health care and Utes.

Trailing EPS are now $22.92, up 36% from their pre-pandemic level. The S&P 500 is up 50% from its pre-pandemic high (Feb. 2020: 3391).

If you wonder, Fed funds rates were 1.5% in February 2020 and 10Y Ts were 1.8%. Core inflation was 2.3%.

The Rule of 20 P/E has been in the red zone (above 22) for 43 months. The record is 65 months (1997-2002) but the S&P 500 peaked at the 41st month when the R20 P/E reached 29.9 and the conventional P/E 27.3 (now 26.7 and 22.8 respectively).

Interestingly, the relationship between the stock/bond ratio and the labor market also diverged in the late 1990s as Callum Thomas shows: “the stock/bond ratio is acting as if the unemployment rate is going to 1%!” yet, the Fed keeps telling us it wants north of 4%.

Source:  Stock/Bond Ratio vs Unemployment Rate

Large cap equity prices are also diverging from labor data …

… but so are earnings:

This is really a margins story:

While revenues positively surprised by 1 pp, better-than-feared margins have been the primary driver of the EPS beats. S&P 500 margins expanded by 27 bp year/year, well above the 14 bp of contraction consensus expected at the start of the reporting period. (Goldman Sachs)

But wait! This is a very narrow margins story as GS explains:

During the past 3 months, Magnificent 7 earnings estimates have been revised upwards by 7% and margins have been revised upwards by 86 bp. This compares with a 3% downward revision to earnings and 30 bp downward revision to margins for the remaining 493 stocks.

Ed Yardeni illustrates how his Mega-Cap-8 margins have exploded in the past 12 months while the remaining 492 companies experienced lower profitability.

Remarkably, all MegaCap-8 except TSLA boosted their margins in 2023, some spectacularly (AMZN, META, NFLX), but none like NVDA which boosted its net margins from 35% to 56% per Yardeni Research data.

Question: are 56% margins sustainable? The market obviously doubts it, hence the 32x P/E (28 for the 8 of them).

SENTIMENT WATCH

• Investor Euphoria: The Euphoriameter is something I put together about a decade ago, designed to capture market sentiment from multiple sources (forward PE — higher valuations imply higher confidence, VIX — lower volatility is seen at times of maximum complacency, and surveyed bullishness — people feel bullish when prices go up). But you probably didn’t even need to see this chart to know that Euphoria is the dominant market mood right now! (Callum Thomas)

Source:  The Euphoriameter Topdown Charts

• Hedge Fund Euphoria: Hedge fund traders have one job: generate a positive monthly PnL. There’s no room for academic big-brain discussions about valuations and long-term expected returns. Just make money. And so, as a group, they’re all-aboard the growth/momentum train (“just buy Mag7”). That’s what works right now, it’s obvious. And if it’s obviously right…

Source:  @modestproposal1

• Foreigner US Asset Allocation:  Foreign holdings of US financial assets are heavily concentrated in equities. Brings to mind the Swiss National Bank, which invests a heavy component of its USD reserves in tech stocks. But also — compare and contrast the heights of 2000 vs the depths of 2009 — what do you think this indicator is telling us?

Source:  Topdown Charts Topdown Charts Professional

• China Tryna:  Chinese stocks are trying to put in a base here… while others are chasing trends and piling into momentum, mean reversion likers will be paying close attention to this. Chinese stocks are cheap, have promising technicals, monetary easing (see below), and extreme pessimism (no one wants to buy China) — seems like this is one of those situations where you have to choose between politics/perception and pragmatism.

Source:  @AlfCharts

AI WATCH

Signs of the time, a new “Watch” topic.

Ed Yardeni: “Artificial Intelligence Isn’t Intelligent”

(…) AI is artificial but hardly intelligent. It is basically a statistical probability model that can digest huge amounts of information from the Internet but lacks the ability to recognize and correct its own mistakes, which is a key attribute of intelligence. (…)

Gary N. Smith is the Fletcher Jones Professor of Economics at Pomona College. His research on financial markets, statistical reasoning, and artificial intelligence has been cited often. He has focused on stock market anomalies, statistical fallacies, and the misuse of data. He is the author of dozens of research articles and 16 books.

Gary was an assistant professor and one of my teachers in Yale University’s PhD program in economics. He has recently influenced my thinking about AI. See for example his January 15, 2024 article titled “Internet Pollution—If You Tell A Lie Long Enough…”

He argues that:

(1) “ChatGPT, Bing, Bard, and other large language models (LLMs) are undeniably astonishing. Initially intended to be a new-and-improved autocomplete tool, they can generate persuasive answers to queries, engage in human-like conversations, and write grammatically correct essays. So far, however, their main successes have been in providing entertainment for LLM addicts, raising money for fake-it-till-you-make-it schemes, and generating disinformation efficiently.”

(2) “It is said that if a lie is told long enough, people will come to believe it. In our internet age, a lie repeated in a large number of places on the Internet will eventually be accepted as truth by LLMs—particularly because they are not designed to know what words mean and consequently have no practical way of assessing the truth or falsity of the text they input and output.”

(3) “This self-propelled cycle of falsehoods is likely to get worse, much worse. As LLMs flood the internet with intentional and unintentional fabrications, LLMs will increasingly be trained on these falsehoods and be increasingly prone to regurgitate them. It won’t just be amusing garbage about Russian bears in space. It will be vicious lies about people, businesses, and governments—all spouted confidently and authoritatively—and many people will be conditioned to believe the LLMs’ rubbish.”

Gary Smith about his queries of “How many bears have Russians sent into space?”

LLMs are just clueless text generators.

In other exchanges that I had with ChatGPT, it reported that Russia had sent 5, 52, or other numbers of bears into space, again providing made-up bear names and references. I was not alone in noting this hallucination, which is now reported in several places on the Internet.

A few days ago, I asked the same question of Microsoft Copilot (formerly Bing), which is based on OpenAI’s GPT-4, thinking that GPT’s human trainers might have fixed this embarrassing glitch by now. They hadn’t—and Copilot’s answer to my query was revealing:

Human:  How many bears have Russians sent into space?

Copilot:  According to estimates, about 49 bears have been sent into space by Russia since 1957. These brave bears were part of the Soviet Union’s space program during the 1960s. Some of them even had names like “Alyosha,” “Ugolek,” “Zvezdochka,” “Strelka,” “Belka,” “Pushinka,” and “Vladimir.”

Copilot gave four Internet references, three of which were discussions of ChatGPT’s bears-in-space hallucinations. The fourth reference was about the history of Russian space dogs. Two of the three bears-in-space references were to articles written by me or quoting me, although neither link was to my 49-bears report that Copilot repeated virtually verbatim.

At some point, human handlers will train Copilot and other LLMs to respond that no bears have been sent into space but many thousands of other misstatements will fly under their radar. LLMs can generate falsehoods faster than humans can correct them.

I asked the same question to Perplexity.ai (with Copilot)

Answer:

The claim that Russia or the Soviet Union sent bears into space is not supported by credible historical records or scientific documentation. The information suggesting that bears were sent into space, including specific missions involving bears named Marfusha, Mishka, and Masha, appears to be a fabrication or a misunderstanding.

The confusion may stem from a mix-up with actual space missions involving other animals, notably dogs, which the Soviet Union famously used in its space program. For example, the Soviet space program did launch missions with animals, including the notable flights of dogs like Laika, Belka, and Strelka. These missions were part of a series of biological experiments to study the effects of space travel on living organisms.

Additionally, there has been a documented instance of a plush toy, Smokey the Bear, traveling to the International Space Station aboard a Soyuz spacecraft in 2012, but this obviously does not equate to sending actual bears into space.

The mention of “water bears,” or tardigrades, surviving exposure to space refers to microscopic organisms known for their extreme resilience. Tardigrades were part of scientific experiments to study the survival capabilities of certain organisms in the harsh conditions of space, but they are not related to actual bears.

In summary, there is no credible evidence to support the claim that the Soviet Union or Russia sent bears into space as part of their space exploration efforts. The stories of spacefaring bears named Marfusha, Mishka, and Masha, as well as the claim of 49 bears being sent into space, are not based on factual events.

The answer came with 8 references, including one to a Gary Smith’s February 2023 piece discussing that very fallacy and one from Hacker News (Nov. 2022) asserting that “The Soviet Union was the first country to put a bear into space.”

Artificial Intelligence Investing (KKR)

The AI investment opportunity set is massive (some estimates suggest Generative AI revenues may exceed USD one trillion per annum within a decade), but we and many of the CIOs with whom we spoke favor a more nuanced approach to start.

Specifically, while direct plays on AI tech development are quite compelling, they are also quite expensive. By contrast, we think a number of non-direct plays, including data center capex, semiconductor manufacturing, power transmission and distribution, will likely also undergo massive investment cycles stemming from the need to develop the underlying infrastructure and energy consumption.

Consider that the proliferation of AI work streams also comes at a time when hyperscale operators, which represent roughly half of data center capex, are already dealing with significant backlogs, rising lead times, and higher construction costs. In other words, we believe it will be difficult to quickly scale data center infrastructure to meet the rising demand for computing capacity.

The additional power demand created by AI is related to the fact that AI workstreams are more computationally intensive. It is estimated that the energy density per server rack is ten to thirty times higher for AI servers than for general-purpose cloud computing, meaning each square foot of data center space will require much more power than it did previously.

This higher power consumption will further accelerate the transition from air cooling to liquid cooling in data centers, as well, we believe.

U.S. Flash PMI: Cost pressures dissipate further in February, but growth momentum in service sector softens

At 51.4, the headline S&P Global Flash US PMI Composite Output Index fell from 52.0 in January and signalled a marginal expansion in business activity midway through the first quarter of 2024. Nonetheless, the pace of expansion was the second-fastest since July 2023 as manufacturers and service providers recorded growth in output.

Although service sector output rose for a thirteenth straight month, the sector lost growth momentum. Manufacturing firms meanwhile registered a renewed rise in production. Factory output increased for the first time in three months, and at the fastest pace since April 2023.

Goods producers signalled the steepest rise in new orders since May 2022, as customer demand improved for a second month running. Some businesses attributed this to clients having worked through their excess inventories.

Meanwhile, service providers continued to see an increase in new business, albeit the slowest in three months and only marginal overall.

At the same time, stronger demand conditions in manufacturing drove a return to growth in new export orders. The latest rise ended a two-month sequence of contraction. External demand was subdued at service sector firms, however. (…)

Job creation was broad based during February, as manufacturers and service providers alike reported a rise in workforce numbers. The overall pace of employment growth eased to the slowest in three months, however, amid a less marked rise in services staffing numbers. Buoyed by stronger demand conditions, goods producers recorded the fastest uptick in employment since September 2023. Services firms highlighted caution with regards to hiring due to cost concerns and softer new order growth. (…)

Cost pressures eased again in February, as input prices rose at the weakest pace since October 2020. The rate of cost inflation slowed at both manufacturers and service providers, as firms noted lower raw material costs and competitive pricing at suppliers. The overall rate of increase in input prices was softer than the series average.

In contrast, the pace of charge inflation picked up midway through the first quarter. The rate of increase quickened from January due to a faster uptick in service sector selling prices. Manufacturers saw an unchanged pace of inflation from January’s nine-month high. Nonetheless, the overall rise in output charges was historically muted, and the second-slowest since June 2020, as firms sought to drive new sales with concessions and discounts as requested by customers.

At 51.5, the S&P Global Flash US Manufacturing PMI was up from 50.7 in January and signalled the sharpest upturn in the health of the goods-producing sector since September 2022. Although only modest, the expansion was supported by a return to output growth and quicker increases in new orders and employment.

The early PMI data for February indicate that the US economy continued to expand midway through the first quarter, pointing to annualized GDP growth in the region of 2%.

Bloomberg has this chart showing new orders finally outpacing output confirming the end of the inventory down cycle (“clients having worked through their excess inventories”).

• The labor market remains strong as evidenced by today’s initial unemployment claims report showing a drop of 12,000 to 201,000 for the February 17 week. This suggests that the unemployment rate remained below 4.0% during February for the 25th consecutive month. (Ed Yardeni)

But the 4-week m.a. has flattened and continued claims keeps rising, suggesting that laid off workers cannot find a new job rapidly.

Indeed job postings have declined since mid-January. Nothing dramatic however.

Home Sales Rebounded in January After Last Year’s Sharp Decline Drop in mortgage rates since October has made home purchasing slightly more affordable

Home sales increased 3.1% in January from the prior month to a seasonally adjusted annual rate of 4 million, the highest level since August, the National Association of Realtors said Thursday.

January existing-home sales, which make up most of the housing market, fell 1.7% from a year earlier. (…)

The national median existing-home price rose 5.1% in January from a year earlier to $379,100, NAR said. (…)

Nationally, there were 1.01 million homes for sale or under contract at the end of January, up 2% from December and up 3.1% from January 2023, NAR said. (…)

The share of first-time buyers in the market was 28% in January, down from 31% a year earlier. About 32% of January existing-home sales were purchased in cash, up from 29% in the same month a year ago, NAR said. (…)

Comments this week from Fed officials and the minutes to the January FOMC meeting suggest that the first rate cut is unlikely to come as early as our previous forecast of the May meeting. We have therefore dropped our forecast of a May cut and now expect 4 cuts total in 2024 (vs. 5 previously) in June, July, September, and December, followed by 4 more cuts in 2025 (vs. 3 cuts previously), to the same terminal rate of 3.25-3.5%.

Yesterday, Fed Vice Chair Philip Jefferson confirmed that the FOMC is done raising the FFR because it seems to be restrictive enough to bring inflation down to the Fed’s 2.0% target. However, reviewing the past six easing cycles, he showed that “most easing cycles start because of concern about slowing economic growth.”

That has not happened yet.

Plus the January inflation scare:

Underlying inflation momentum is rising again. (The Daily Shot)

Source: TS Lombard

KKR’s CRE Deal Pipeline Heats Up Amid ‘Year of Transactions’

The decline in commercial real estate values has eased enough that private investors are starting to fill in a financing void left by the pullback of regional banks and other traditional lenders to the industry, according to buyout giant KKR & Co.

Issuance of commercial mortgage-backed securities will pick up by nearly a third this year compared to last, and private equity funds that have spent the last 18 months in wait-and-see mode are “awash in dry powder,” KKR’s head of real estate credit Matt Salem wrote in a note to clients. KKR’s own real estate credit pipeline has now swelled to $15 billion, up from an average $10-12 billion in 2023, he said.

“We are bringing multiple deals to our equity investment committee each week,” Salem wrote.

Fear of widening losses in the commercial real estate market has been a top concern with investors, according to Bank of America Corp.’s latest Global Fund Manager survey. In that heightened risk, though, a growing number of investors are looking to deploy capital. Property giant Brookfield, for example, is seeking to raise $15 billion for a new real estate fund to capitalize on an expected wave of value deals.

Despite the influx of private capital, it probably won’t be enough to completely fill the gap left behind by regional banks, Salem said.

Banks hold around 50% of outstanding commercial real estate debt, but they now face heightened regulatory scrutiny and have pulled back, according to the note. And there simply isn’t enough private capital available to step up. If bank lending recedes to 40% of the roughly $5.8 trillion commercial real estate debt market, then that would leave a “gap” of over $500 billion in need of financing, Salem said. (…)

Office CRE remains a problem but it is less than 20% of the total CRE market.

Private capital seems ready to tackle the non-office market credit risk.

Canada Retail Sales Rise 0.9% in December But Fall in January

An advance estimate of retail sales receipts indicates sales fell 0.4% last month, Statistics Canada said Thursday.

That comes after sales in December climbed 0.9% to a seasonally adjusted 67.30 billion Canadian dollars, the equivalent of about $49.84 billion, the data agency said.

The early indication for January, based on responses of just under 53% of retailers surveyed, marks the biggest decline in nine months. (…)

December’s sales increase was the strongest advance since last April and was slightly stronger than 0.8% increase forecast by Statistics Canada and penciled in by economists. It comes after sales in November were revised upward to unchanged from an earlier estimate of a 0.2% fall.

In volume terms, total retail sales lifted 0.8%.

New car sales led the increase for the vehicle and parts segment, which has seen trade rise four consecutive months.

Core retail sales, which exclude gas stations and car and auto-parts dealers, showed a more modest increase, rising 0.5% from November. The increase was led by sales at general merchandise retailers and at supermarkets and other grocery retailers, and was partially countered by a drop in sales of furniture, home furnishings, electronics and appliances.

For the final quarter of 2023, headline retail sales rose 1.0%, a second quarterly rise in a row. Sales in volume terms were up 1.3% for the quarter, building on increases in wholesale trade in December and for the final quarter. Official GDP data is due out at the end of this month, though Statistics Canada’s early estimate points to industry-level growth of 1.2% annualized for the fourth quarter following a slight contraction the quarter before. (…)

Canadian retailers finished last year with about C$794.4 billion in sales, an increase of 2.2% over 2022.

U.S. retail sales rose 3.4% in 2023.

China’s Real-Estate Crisis Just Got Worse A prolonged fall in home prices shows the huge task facing policymakers, who have so far proved unable to turn the market around.

New home prices fell 1.24% from a year earlier, accelerating from December’s 0.89% decline, according to calculations by The Wall Street Journal based on data released Friday by China’s National Bureau of Statistics.

Secondhand home prices did even worse, falling by 4.4% in January compared with a year earlier. It was the steepest such decline in almost nine years. (…)

The latest data showed that new home prices in China’s first-tier cities—Beijing, Shanghai, Guangzhou and Shenzhen, the hottest housing markets in the country—dropped 0.5% in January from a year ago. (…)

But beneath the surface, there were signs of diverging fortunes among those cities. New home prices in Beijing and Shanghai rose 1.3% and 4.2%, respectively, in January on a year-over-year basis. That was offset by drops in Guangzhou and Shenzhen, two southern cities, where prices fell 3.6% and 4.1%, respectively.

Secondhand home prices fell in all four major cities by between 3.7% and 6.1%.

Private surveys show China’s 100 largest developers recorded a deep slump in new-home sales in January. They sold homes valued at $32.8 billion, down 34% from a year earlier, marking the worst month of sales since at least July 2020, according to data provider China Real Estate Information. (…)

Bloomberg has a different vision of things:

China Home Prices Fall at Slower Pace as Support Mounts

China’s home prices declined at a slower pace for both new and existing-units in January, the first signs of improvement in 10 months.

New-home prices in 70 cities, excluding state-subsidized housing, dropped 0.37% last month from December, when they retreated 0.45%, National Bureau of Statistics figures showed Friday. The second-hand market also improved, with price declines narrowing to 0.68%.

Existing property values edged up in two cities featuring holiday homes, Sanya and Kunming. New-home prices gained in 11 cities, mostly tier-two regional centers.

In both markets, the number of cities with rising home values picked up, the first time in 10 months.

“The slide in home prices may have passed its worst period,” said Yan Yuejin, research director at E-house China Research and Development Institute. (…)

Goldman Sachs data show that new house prices have actually not dropped much…

… and that secondary market prices have only started to fall below pre-pandemic levels.

From the 2006 peak to the 2012 low, U.S. house prices collapsed nearly 40%. The Chinese government is trying hard to avoid a similar pattern.

China Car Sales Slump on Holiday Lull, Drivers Awaiting Rebates February shipments down 15.7%, according to preliminary data

BYD Co. earlier this month slashed the price of its popular Qin Plus sedan by 10,000 yuan ($1,390), sparking similar cuts by at least half a dozen manufacturers. But the price war may have the unintended consequence of dampening demand as customers adopt a wait-and-see approach, hoping for even better discounts, PCA said. (…)

EV sales in February are expected to slump 43% from January, PCA said. (…)

John Authers: Partying Like 1999? An NBubble Isn’t Here

(…) Nvidia has sold much more stuff for a far bigger profit in the last 12 months. It also has a clearly defined idea that’s easy to grasp, in artificial intelligence.

This is nothing at all like the absurdity 25 years ago, when companies came to market before they’d even made any revenues, let alone profits. This time, there is a “there” there. The problem is that the presence of something this exciting adds to the risk that a bubble will form. (…)

A bubble’s final stage is almost entirely about judging human behavior; buy an asset because it’s rising, and sell before it crashes. You can identify this in one way by looking at technical patterns, of how swiftly share prices are advancing. On that basis, we can say this is at best a very pale imitation of 1999. The following chart compares the Nasdaq 100’s performance over two periods — starting in October 1998 when the dot-com melt-up began, and from the start of the current upswing in December 2022 (apologies for the limitations of our graphical software). So far, this rally is far behind the dot-com schedule. (…)

Higgins makes the following case:

Unlike most bubbles, this one hasn’t been accompanied, at least so far, by obvious signs of high and rising leverage… Margin debt has actually been falling recently. And the ratio of margin debt to the size of the stock market has been doing likewise.

(…) Yes, the US market is really bad value. (Plenty of others look much cheaper.) US tech stocks look almost as expensive relative to the rest of the world as in 2000. This chart is from Dhaval Joshi of BCA Research:

Again, we are not yet at extremes, and in any case valuation is terrible for timing. Keynes was right to say that a market can stay irrational longer than most people can stay solvent. But it’s important to note that stocks definitely look expensive relative to bonds. (…)

Will Denyer of Gavekal suggests that a continued rally “likely depends on one or both of the following: (i) earnings continue to exceed expectations; (ii) the Federal Reserve cuts rates and real bond yields fall—with no recession.” Either could happen, and neither is a given. (…)

This is from Deutsche Bank’s Jim Reid, and measures the weight of the top 10% of stocks in the S&P 500:

(…) The tech sector is further ahead of the market than even at the top in 2000:

Does It Matter That Companies Are So Big?

This is critical. Big companies got bid up to silly valuations in 1999, but smaller ones went ballistic. Nothing like that is afoot today in small caps. The issue, I think, is a genuinely new one. Companies just haven’t been this big ever before, relative to everyone else. I certainly can’t remember any one set of corporate results mattering as much to the entire financial world as Nvidia this week. But it makes sense because, as shown in this great chart from Reid, the Magnificent Seven stocks are now bigger than your average country. The companies between them make more money than any countries bar the US, China and Japan (which is only just ahead):

Does It Make Sense?

Are the assumptions about what’s going to happen in the real world consistent with what we can truly expect? In the case of the mega caps, can they possibly stay this dominant? Joshi suggests not. Tech companies’ profits are growing far faster than everyone else’s. That implies, presumably, that their money is being made at the cost of others, which is perfectly legitimate if true but suggests problems for the overall market.

(…) capitalism might do the job by prompting innovations that allow new firms and technologies to compete. Plenty of companies in the past had apparently impregnable positions and were ranked among the five largest in the US, only to fade. Examples include Sears Roebuck, General Electric Co., AT&T, Eastman Kodak Co., and Intel Corp.

In the case of Intel, the decline is phenomenal. The world’s former dominant chipmaker is worth $300 billion less than in 2000. At one point, Intel’s market cap was $497.6 billion bigger than Nvidia’s; now it’s $1.78 trillion behind. Dominance isn’t necessarily forever, but now that the Magnificents are deemed to have macro importance, a Kodak-like decline would hurt for the world at large. (…)

The problem is that even when a technology fulfills all the greatest hopes in it, as when everyone got a phone for their pocket, the companies that seem like a direct stake won’t necessarily profit. Reid’s chart compares the growth in mobile phones with the performance of telecommunications stocks

If you bought in 2000, you were dead right about the future growth of mobile telephony. And you lost a hideous amount of money. (…)

Wednesday, I posted American Exceptionalism: Don’t Extrapolate. Yesterday, Richard Bernstein Advisors published:

How to avoid another lost decade in equities

The current speculative environment seems to increasingly resemble the Technology Bubble of 1999/2000. Leadership is narrow, valuation dispersions are massive, relative strength and momentum are the primary drivers of performance, and investors are shunning diversification to take impulsive near-record portfolio risk.

All bubbles eventually burst, and the bursting of the Tech Bubble led to the so-called lost decade in equities during which the S&P 500® provided negative returns for a decade. When today’s speculative burst ends, the equity markets’ extreme concentration again makes it likely an extended period of subpar performance for equities will occur.

Today’s consensus remains focused on the Magnificent 7¹ stocks, but no sound financial theory counsels that seven stocks constitute a well-diversified portfolio as a core for building wealth. The possibility of another lost decade in equities and the broad range of investment opportunities outside the Magnificent 7 leads us to position our portfolios with significant diversification. (…)

There was very narrow leadership during the Tech Bubble as only a few sectors were considered part of the “new economy” (stocks related to the potential growth of the internet). Traditional businesses, termed “old economy” stocks, significantly underperformed. (…)

Once the Tech Bubble deflated, the equity market began an extended period of underperformance which came to be known as “the lost decade in equities.” From December 31, 1999 to December 31, 2009, the S&P 500® returned -1%/year, whereas NASDAQ returned -5%/year [or -6%/year for the NASDAQ 100]. In fact, if one had bought NASDAQ at the peak of the Tech Bubble in March 2000, it would’ve taken nearly 14 years to simply break even!

However, certain segments within the global equity markets performed extremely well during the lost decade. Chart 4 shows NASDAQ’s extended underperformance (white line) versus the significant outperformance of the energy sector, small caps, and emerging markets.

There seems a common misperception that the current speculative period of narrow outperformance is vastly different from that during the Tech Bubble because the Magnificent 7 companies are “real companies” and not the worthless IPOs issued during the Tech Bubble. Few seem to realize the Tech Bubble was indeed led by real companies.

Chart 5 recaps what happened to the 6 largest Technology companies (as of December 1999) after the Tech Bubble burst. These were real companies with strong balance sheets and cash flow. The quickest stock to post positive returns still took roughly 7 years to recover. The longest recovery among these real companies was more than 20 years, i.e., much longer than the period shown in the chart. (Note: RBA may own the companies mentioned in various portfolios.)

The bubble today isn’t being inflated by stories of the internet, but by a similar story about the exciting future of artificial intelligence (AI). The combination the AI hype and immense pandemic-related liquidity that has not been fully absorbed into the real economy has inflated equity valuations and created highly speculative and narrow leadership.

US M2 growth peaked at 27% which is the highest in modern US history. That huge money growth, like the money growth that fueled the Tech Bubble, could not be fully absorbed into the real economy, and has fueled another financial bubble.

The extreme amounts of excess liquidity have also fueled a bubble in cryptocurrencies. (…) As there is no tangible legitimate economic use for Bitcoin, this relationship demonstrates well that excess liquidity and easier financial conditions are prime determinants of Bitcoin’s value.

Investors should seriously question the narrow leadership and valuations of the so-called Magnificent 7 stocks. Whereas some of today’s Magnificent 7 do have strong fundamental growth, that growth isn’t uniform within the seven stocks nor is it unique relative to many non-Magnificent 7 companies’ growth prospects. Chart 7 shows there are currently about 140 stocks within the G-7 equity markets (US, Canada, Germany, Japan, France, the UK, and Italy) projected to grow earnings 25% or more over the next year. Most importantly, only 3 of the Magnificent 7 pass the screen and the fastest growing of the Magnificent 7 ranks only 25th.

The relative performance between the NASDAQ 100 and the Russell 2000 is as extreme as it was during the Tech Bubble. Chart 8 shows the relative total return between the two indices. History seems to be repeating: new technology hype, significant liquidity, bubble outperformance, investors’ enthusiasm and risk-taking. Will another lost decade in equities be next?

Investors should consider what they are missing with their Magnificent 7 myopia. Shunning diversification has never been prudent, and that’s certainly true during bubble environments. The key to future returns may be simple, basic diversification.

As we emphasized in the first chart, the range of underappreciated investment opportunities seems historically broad and historically attractive. Given the last time similar opportunities arose was after the Tech Bubble, which was 24 years ago, we don’t think we are exaggerating when we describe this as a once-in-a-generation opportunity.