stock market – Economist Writing Every Day

Is Every Stock a Tariff Stock?

April 23, 2025Jeremy HorpedahlLeave a comment

Not quite, at least not in the same way that every stock was a vaccine stock in 2020, as Alex Tabarrok put it.

Today the stock market does seem to move a lot on the news about Trump’s ever-evolving tariff policy. If you see the S&P 500 is up today, you can probably guess that Trump or his advisors slightly backed off some aspect of their previously announced tariff policy. And vice versa. That much is true.

But back in 2020, the implied correlation in the market was briefly over 80% in the spring of 2020, and was over 50% for almost all of the summer of 2020. Today, the correlation is closer to 40%. That’s a bit lower than 2020, but it is a significant jump from where it was 2-3 months ago.

Here is the Cboe’s implied 3-month correlation index:

In addition to the costs of tariffs themselves, investors should be worried about this correlation because “market returns are lower when correlations among assets are increasing.”

Why Low Returns Are Predicted for Stocks Over the Next Decade

February 11, 2025February 12, 2025Scott Buchanan2 Comments

I saw this scary-looking graphic of S&P 500 returns versus price/earnings (P/E) ratios a couple of days ago:

JPMorgan

The left-hand side shows that there is very little correlation between the current forward P/E ratio and the returns in the next year; as we have seen in the past few years, and canonically in say 1995-1999, market euphoria can commonly carry over from one year to the next. (See here for discussion of momentum effect in stock prices). So, on this basis, the current sky-high P/E should give us no concern about returns in the next year.

However, the right-hand side is sobering. It shows a very strong tendency for poor ten-year returns if the current P/E is high. In fact, this chart suggests a ten-year return of near zero, starting with the current market pricing. Various financial institutions are likewise forecasting a decade of muted returns [1].

The classic optimistic-but-naïve response to unwelcome facts like these is to argue, “But this time it’s different.” I am old enough to remember those claims circa 1999-2000 as P/E’s soared to ridiculous heights. Back then, it was “The internet will change EVERYTHING!”. By that, the optimists meant that within a very few years, tech companies would find ways to make huge and ever-growing profits from the internet. Although the internet steadily became a more important part of life, the rapid, huge monetization did not happen, and so the stock market crashed in 2000 and took around ten years to recover.

A big reason for the lack of early monetization was the lack of exclusive “moats” around the early internet businesses. Pets.com was doomed from the start, because anyone could also slap together a competing site to sell dog food over the internet. The companies that are now reaping huge profits from the internet are those like Google and Meta (Facebook) and Amazon that have established quasi-monopolies in their niches.

The current mantra is, “Artificial intelligence will change EVERYTHING!” It is interesting to note that the same challenge to monetization is evident. ChatGPT cannot make a profit because customers are not willing to pay big for its chatbot, when there are multiple competing chatbots giving away their services for practically free. Again, no moat, at least at this level of AI. (If Zuck succeeds in developing agentic AI that can displace expensive software engineers, companies may pay Meta bigly for the glorious ability to lay off their employees).

My reaction to this dire ten-year prognostication is two-fold. First, I have a relatively high fraction of my portfolio in securities which simply pump out cash. I have written about these here and here. With these investments, I don’t much care what stock prices do, since I am not relying on some greater fool to pay me a higher price for my shares than I paid. All I care is that those dividends keep rolling in.

My other reaction is…this time it may be different (!), for the following reason: a huge fraction of the S&P 500 valuation is now occupied by the big tech companies. Unlike in 2000, these companies are actually making money, gobs of money, and more money every year. It is common, and indeed rational, to value (on a P/E basis) firms with growing profits more highly than firms with stagnant earnings. Yes, Nvidia has a really high P/E of 43, but its price to earnings-growth (PEG) ratio is about 1.2, which is actually pretty low for a growth company.

So, with a reasonable chunk of my portfolio, I will continue to party like it’s 1999.

[1] Here is a blurb from the Llama 3.1 chatbot offered for free in my Brave browser, summarizing the muted market outlook:

Financial institutions are forecasting lower stock market returns over the next decade compared to recent historical performance. According to Schwab’s 2025 Long-Term Capital Market Expectations, U.S. large cap equities are expected to deliver annualized returns of 6% over the next decade, while international developed market equities are projected to slightly outperform at 7.1%.1 However, Goldman Sachs predicts a more modest outlook, with the S&P 500 expected to return around 3% annually over the next decade, within a range of –1% and 7%.42 Vanguard’s forecasts also indicate a decline in expected returns, with U.S. equities falling to a range of 2.8% to 4.8% annually. These forecasts suggest that investors may face a period of lower returns compared to the past decade’s 13% annualized total return.

Behind Last Week’s Stock Minicrash: Unwind of the Yen Carry Trade

August 13, 2024August 12, 2024Scott BuchananLeave a comment

Last Monday, August 5, the S&P 500 crashed by 3.5% from the previous close. That is a huge daily move, which seems to have been a surprise to most market watchers. The VIX index, a measure of the cost of options and widely seen as a measure of fear in the markets, went off the charts that day. What happened?

The previous week, there was an employment report that showed higher than expected jobless claims. Although that led to angst over a recession, a genuine serious dent in employment would bring the Fed roaring in with interest rate cuts, and the stock market loves rate cuts. In addition, as we have highlighted in recent posts (here and here), there is increasing skepticism that the monster spends on AI will produce the profits that Big Tech hopes. However, the AI skepticism and the employment worries seemed already baked into stock prices by the Friday close.

What apparently happened over the weekend was the unwinding of a big part of the yen carry trade.

What is that, you ask? To frame this, imagine you have $100 to invest in something very safe, like short term Treasury securities. In the simplest case, you go buy a 1-year T-bill which yields 4.5%. You will make $ 4.50 in a year, from this transaction. If you had $100 million to invest, you would make $ 4.5 million.

Now suppose that you could use that $100 as collateral to borrow $1000 at 0.05%. You then take that $1000 and buy $1000 worth of 4.5% T-bills. Voila, instead of making a measly $ 4.50, you can now make 1000*(4.5% – 0.05%) = $44.5. This is nearly ten times as much, a 44.5% return on your $100. Financial alchemy at its finest!

Now, if instead of investing in boring 4.5% T-bills, you had been buying Microsoft and Apple shares (up 25% and 21%, respectively, in the past twelve months), just imagine the profits from this 10X leveraged trade. Especially if you started with a $100 million hedge fund instead of $100.

Where, you may ask, could you borrow money at 0.05%? The answer is Japan. The central bank there has kept rates essentially zero for many years, for reasons we will not canvass here. This scheme of borrowing in yen, and investing (mainly in the US) in dollars is termed the yen carry trade. Besides this borrowing/investing, simply betting that the Japanese yen would decline against the dollar has been profitable for the past 18 months.

What could possibly go wrong with such a scheme? Well, you have to do this borrowing in Japanese yen. So, if you borrow in yen and then convert it to dollars and invest in the dollar world, you can be in a world of hurt if the value of yen in dollars goes up by the time you need to close out this whole trade (i.e. cash in your T-Bills into dollars, convert back to yen, and pay off your yen borrowings.

What happened on Wednesday, July 31 was the Bank of Japan unexpectedly raised its key interest rate target from 0-0.1% to around 0.25%, and announced they would scale back their QE bond-buying, in an effort to address inflation. As may be expected, that raised the value of the yen on Thursday and Friday, though not by much. But the yen made a surge up at the end of Friday’s trading.

Apparently, that caused enough angst in the carry trade community that participants in the carry trade started running for the exits, selling dollar-denominated assets (including stocks) and scrambling to buy yen. Naturally, that shot the price of yen up even more, so on Monday, Aug 5, we had a disorderly market rout.

Bad news sells, and so all the finance headlines on Monday were blaring about the stock price collapse and start of an awful bear market. However, nothing substantive had really changed. By Friday, the S&P 500 had recovered from this big head-fake.

As usual, investors sold stocks (at a low price) on Monday, and presumably bought them back at a higher price later in the week. This is why the average investor’s returns fall well below a simple buy and hold. But that is another subject for another time.

Though the Market Is a Winner, Most Stocks Are Losers

November 30, 2021Scott Buchanan4 Comments

The U.S. “stock market” is represented by various collections of stocks, such as the Dow Jones Industrial Average (30 stocks), the NASDAQ Composite (securities listed on the NASDAQ; weighted towards information technology), and the Standard and Poor’s 500 Index. The S&P 500 is an index of the largest 500 companies listed on the New York Stock Exchange and the NASDAQ, weighted by capitalization. The version of the S&P usually cited just takes into account stock prices. History shows that, over a reasonably long-time frame, the U.S. stock market rises. Here is a chart, using a logarithmic axis, of the S&P from January, 1950 to February, 2016. It shows a rise in value by a factor of about 65 between 1950 and 2016.

S&P 500 daily closing values from January 3, 1950 to February 19, 2016
Source: https://en.wikipedia.org/wiki/S%26P_500_Index

Below is a chart of S&P values from 1980 to 2021 on a linear scale, which compresses the earlier data and magnifies more recent variations. This shows the Covid-related dip in early 2020, which was followed by a meteoric rise as Fed and federal money flooded the financial system:

Source: Yahoo Finance

A lab technician I knew in my company in the 1990s took every bit of savings he had (about $50,000) and plowed it all into the stock of America Online (AOL). This was when the internet was just taking off, and AOL was a leading company in that field. My friend held on while his investment doubled, then had the conviction to hang on until it doubled again. He then cashed out with around $200,000, quit his job, got an MBA in finance, and ended up managing money on Wall Street.

With these sorts of success stories, and the (so far) reliable performance of the stock market, how hard can it be for the average small investor to pick a winning basket of stocks? Surprisingly hard, it turns out.

A study of the returns of U.S. stocks from 1926 to 2015 was published by Hendrik Bessembinder, a business professor at Arizona State University. A draft copy is here . He worked with total returns (stock price plus dividends). He found that the rise of the S&P is entirely due to huge gains by a tiny subset of stocks. The average stock actually loses money over both short and long time periods. In statistical terms, this is an extremely skewed data set; the mean return is greater than the median. There is a sort of Darwinian selection that occurs in a market index like the S&P 500. The companies that are doing well tend to get more represented in the index as their stock prices rises relative to other companies, while the relative weighting of losers automatically diminishes.

This asymmetry between winners and losers is partly a result of the following math: If you invest $1000 in a company that then tanks, the most you can lose is $1000. But if that company is one of the rare firms that really takes off, you could make many times your initial investment. If you had put $1000 into Microsoft (MSFT) in 1986, your shares would now be worth nearly five million dollars.

According to Bessembinder’s study, half of the U.S. stock market wealth creation had come from a mere 0.33% of the listed companies. The top five companies (ExxonMobil, Apple, GE, Microsoft, and IBM, at that point) accounted for a full 10% of the market gain. Each of these companies had created half a trillion dollars or more for their shareholders. ( A similar list of the top five or ten value-creating companies drawn up in 2021 would have a different set of names, obviously, but a similar principal has held in recent years – a huge portion of the rise in “stocks” in the past five years has been due to a handful of internet superstars, the FAANGM stocks).

Out of some 26,000 listed companies, 86 of them (0.33%) provided 50% of the aggregate wealth creation, and the top 983 companies (4%) accounted for the full 100%. That means the other 25,000 companies netted out to zero return. Some gave positive returns, while most were net losers.

The average stock which you might pick by throwing darts at the Wall Street Journal listings lost money 52% of the time in any given month, and 51% of the time over the life of the company. The lifetime of the average company was only seven years, with only 10% of companies lasting more than 27 years.

This helps explain why actively managed stock funds, where diligent experts analyze and select some subset of stocks in an attempt to beat the market, typically underperform the broad market indices. (The fees charged by these funds also drags down their performance relative to the market indices). This also explains why about half the small-cap stocks I have bought over the years in my little recreational brokerage account have lost money. I had thought I was particularly inept at stock-picking. Turns out I was just about average.

Why Short Selling Is a Good Thing for the Stock Market and Investors Large and Small

February 9, 2021February 9, 2021Scott Buchanan4 Comments

We noted earlier the hubbub over a hive of little investors on Reddit outfoxing some big Wall Street firms who had made massive short bets on the stock of GameStop. Some of the narrative around this event has painted short selling as a secret, evil practice only available for the big guys. But none of that is true.

Continue reading →

QE, Stock Prices, and TINA

January 12, 2021January 13, 2021Scott Buchanan2 Comments

The U.S. economy as quantified by GDP has been sputtering along in slow growth mode for a number of years. It took a huge hit in 2020 due to covid shutdowns and has not nearly recovered. But stock prices have been rocketing upwards, and this past year is no exception. Markets took a cliff-dive in March, but have since way overshot to the upside.

Here is a plot of the past five decades of U.S. GDP and of the Wilshire 5000 index, which approximates the total stock market capitalization in the U.S.:

Chart Source: St. Louis Fed, as plotted by Lyn Alden Schwartzer

These two curves have crisscrossed each other over the past five decades, but in recent years the stock market has roared to the upside. One of Warren Buffet’s favorite metrics as to whether stock are overvalued is to consider the ratio of these two quantities, i.e. the market-capitalization-to-GDP (Cap/GDP) ratio: