In the investment world, there’s no shortage of data. But how useful is it? To help get to an answer, let’s consider these four questions:
When the economy is strong, is that good for stocks?
The simple answer is yes. According to textbook finance, the value of any company should represent the sum total of its future profits. So when the economy is strong, and profits are higher, that should be good for stocks. Over time, in fact, the trajectory of the stock market has generally followed the trajectory of corporate profits.
But sometimes a strong economy can drive stocks lower. This happened in 2021. The economy was recovering from Covid, employment was improving, and corporate profits were rising. But that strength contributed to higher wages, and together with other factors, the result was that inflation rose. As a result—as we well know—the Federal Reserve had to step in, raising rates to put the brakes on inflation.
The Fed succeeded in bringing down inflation, but those rate hikes—seven increases in one year—also caused the stock market to drop. In 2022, stocks fell 18%. This, in short, is the nature of economic cycles. A strong economy and a strong stock market do tend to go together—but at a certain point, too much positive economic data can actually be bad for stocks.
The bottom line: Be cautious in drawing conclusions about where the stock market might be headed based on current economic conditions.
If the stock market’s price-to-earnings (P/E) ratio is high, does that mean stock prices are too high?
The simple answer is yes. While imperfect, the market’s price-to-earnings ratio can be a rough indicator of future market returns. In early 2000, for example, just before the market began to slide, the S&P 500’s P/E ratio stood at nearly 30. To put that in perspective, the market’s long-term average P/E has been about 17. So in that case, an elevated P/E was indeed an accurate indicator. The market was too high and ultimately fell nearly 50%.
But if we had revisited the P/E ratio in the midst of that downturn, it would have sent a confusing signal. At the end of 2001, by which time the market had already dropped 25%, the P/E had actually risen, to 46. Why, after a big market decline, would the P/E have risen? It seems like simple math that if prices had dropped, the market’s P/E should have dropped.
The answer lies on the other side of the ratio. When the economy goes into recession, as it did in 2001, Wall Street analysts’ earnings estimates drop as well. If those estimates drop proportionally more than prices, that can cause P/E ratios to rise, counterintuitively, during a market downturn. We saw the same thing in 2009. The key point: While P/E values have a bit of predictive power, they can be misleading.
If the Federal government is running enormous deficits, does that mean tax increases are a foregone conclusion?
The Federal budget deficit today is closing in on 100% of GDP, a level we haven’t seen since the 1940s. And even if Congress had the political will, cutting spending wouldn’t be easy. Social Security and Medicare account for 47% of the budget. Defense is another 14%, and because of the accumulated debt from prior years’ deficits, interest on the debt accounts for another 13% of spending.
That doesn’t leave a lot of room to maneuver, and as a result, many worry that taxes will need to rise, even above the increases already scheduled for 2026. It’s not an unreasonable fear—but things don’t necessarily have to go that way.
In the late-1980s, as we fought the last years of the Cold War, budget deficits rose to worrying levels. But that didn’t result in tax increases. Why? As the tech boom of the 1990s got going, government revenue swelled, and the debt load began to fall. At one point in the mid-90s, the government actually ran a budget surplus. To be sure, current trends aren’t reassuring, but trends can reverse.
If international stocks have lower P/E ratios than domestic stocks, does that make them more attractive?
On the surface, this sounds compelling. The P/E of the U.S. stock market today is just above 20, while in developed markets outside the U.S., the average P/E is just 14. To many, this means international stocks represent an attractive bargain. But that’s not the only explanation.
As we saw earlier, a lower P/E doesn’t guarantee higher investment returns. But that’s not the only reason P/E ratios can be misleading. Another reason is that stock markets differ from country to country.
That’s important because there’s an underlying connection between a company’s growth rate and its P/E ratio. Consider, for example, two companies: Microsoft and food manufacturer General Mills. Microsoft’s P/E today is 33, while General Mills’s is around 16. But that doesn’t mean General Mills is cheap, and Microsoft is expensive. Rather, it reflects the difference between a company growing at 15% to 20% per year (Microsoft) and one that is just barely growing (General Mills). In short, P/E ratios tend to reflect the growth rate of the business.
That helps explain why the average P/E in the U.S. is so much higher than in most of the rest of the world. International markets have far fewer fast-growing technology companies. In the U.S., seven of the top 10 companies are in technology. But in Europe, for example, just two of the top 10 are tech companies. The same is true in most of the rest of the world. In Europe, the biggest companies are mostly slow-growing banks, food and energy companies. That explains why international markets generally have lower P/E multiples than in the U.S. Through this lens, in other words, international markets aren’t necessarily a bargain; they’re just appropriately priced for what they are.
This past week, the investment world lost a giant: James Simons, the founder of Renaissance Technologies. According to Gregory Zuckerman’s The Man Who Solved the Market, Renaissance’s flagship Medallion Fund delivered average returns of 66% per year over a 31-year period—by far, the best investment returns achieved by any investor ever.
How did Simons do it? Renaissance was the first to sift through market data, looking for hidden patterns and correlations. But despite its astonishing returns, according to an employee quoted in Zuckerman’s book, Renaissance’s system was still only right 50.75% of the time. I think there’s an important lesson in this: If even the most successful data analysts in the world are still only right 50.75% of the time, it illustrates just how hard it is to draw conclusions from market data. That’s why the best approach, in my view, is to structure a reasonable portfolio and to stick with it, despite what the data says—or appears to be saying.
