Judging by the highly valued US stock market (the second-highest in 150 years via the Shiller PE Ratio), the outlook for risk assets is bright or treacherous, depending on your bias.
Animating the optimists is an assumption that the economic and business eco-system of artificial intelligence will drive investment, revenue and earnings far into the future and thereby keep the bulls humming. The alternative view: The market’s in a bubble and the usual outcome will be inescapable… eventually.
Which narrative appeals to your editor? Neither. Yes, we have a view, just like everyone else, but our main focus is on the more-practical goal of deciphering Mr. Market’s outlook. That’s always a tricky affair, but we remain persuaded that a robust estimate of the primary trend is a useful first step.
On that score, not a lot has changed lately. Our usual set of global asset allocation ETFs posted a mixed trading week through Friday’s close. For all the breathless headlines last week, our trend indicators for the funds remains pinned at flat-out bullish readings.
As a check on how each the four ETFs stack up, we always estimate the overall primary trend via the lens of the Global Trend Indicator (GTI), and the result continues to affirm that the upside bias remains strong. As a reminder to new readers, GTI summarizes the technical profiles of the global asset allocation ETFs in the table above. As of Friday’s close, the indicator is trading at/near the upper band for the trailing 1-year range, a strong bullish sign.
Nonetheless, GTI looks vulnerable to a pullback, according to our Overbought-Oversold Indicator. If and when a correction arrives, the drop may trigger a longer-term warning, or merely reflect the normal give and take that unfolds when markets run too hot too fast. Deciding which outlook is more compelling will depend on how the numbers shake out during such an event. Meantime, this is a risk factor we’re watching.
What would a meaningful correction look like? The first profile we’ll consult in search of an answer is the short-term risk signal for the aggressive asset allocation strategy (AOA). The indicator is relatively vulnerable when the appetite for risk starts to retreat. As such, the chart below is one of our early warning metrics. For now, a solid upside bias endures.
There are isolated pockets of short-term weakness in a closer breakdown of global markets, but I’m comfortable looking through this until more red pops up on the table below.
Market sentiment, in short, is telling us to sit back and continue to enjoy the ride. On that basis, the core assumption is that the AI effect will keep the party going. This is more than wishful thinking, at least for now.
Ed Yardeni, president of Yardeni Research, reports:
S&P 500 earnings per share continue to beat expectations. Q3 earnings per share are on track to rise to a new record high. They are driving the S&P 500 stock price index to new record highs. The Magnificent-7 are leading the way higher on both fronts.
Sparkline Capital notes that the AI-driven surge in capital expenditures has become the elephant in the room, which is raising concerns:
The AI revolution has reached a key inflection point, with the largest U.S. tech firms embarking on a massive AI infrastructure buildout. While the market has rewarded this spending so far, we find that historical capital expenditure booms have typically resulted in overinvestment, excess competition, and poor stock returns – both at the macro and individual firm level…
So far, investors have looked upon these capital investments favorably. The so-called Magnificent 7, who are driving much of the buildout, have continued to outperform; Oracle’s stock surged 36% after announcing a deal to build OpenAI’s data centers; and CoreWeave, an upstart AI cloud provider, has seen its stock triple since its March listing. The valuations of AI stocks reflect considerable optimism…
However, it remains far from clear if these investments will ultimately deliver adequate financial returns. Bain estimates that, to justify their cost, these data centers will need to generate $2 trillion in annual revenue by 2030. Yet, three years after ChatGPT’s launch, AI revenues remain modest. At an estimated $20 billion, they would have to grow 100-fold to justify the expected buildout. Enterprises have struggled to implement AI, and even ChatGPT, by far the most popular AI consumer application, has yet to fully monetize its users…
Big Tech’s huge AI gambit has put investors in a precarious position. The stock market is increasingly driven by a single theme: AI.
Coatue Management Partners suggests that the AI leadership is evolving, noting that the “Mag 7 is no longer outperforming” and “the market is welcoming new AI leadership,” such as companies poised to profit from rising AI-related demand for elecgtricity, cloud storage and semiconductors.
Perhaps, but there’s no law that says that even healthy shifts in market leadership must be orderly and smooth. Consider this chart from Goldman Sachs (published Oct. 8), which reminds just how far the current AI-infused leaders have run:
Is this a sign of a bubble? One reason to keep an open mind, the investment bank advises: “While stock prices have appreciated strongly, up until now, these have been reflected by powerful and sustained profit growth rather than excessive speculation about the future.”
Even if we’re in a bubble, trying to time by shifting to an extreme defensive position is ill-advised (assuming you have an investment time horizon that’s at least 5 years). Recall that Fed Chairman Greenspan at the end of 1996 made his famous “irrational exuberance” speech that raised doubts about the high-flying stock market at the time. Although he made a persausive case, the market never got the memo and the S&P 500 Index proceeded to more than double from that point until it peaked in early 2000 before the bear market started.
The lesson, of course, is that accurately identifying a bubble in real time (no mean feat) is only half the battle. You also need to get the timing right, a far more challenging task.
My view: Don’t even try. Instead, watch the trend across a range of markets and act accordingly, based on the data in hand. Granted, that’s no guarantee of success vs. buy and hold over the long term. But to the extent that you’re inclined to engage in opportunistic rebalancing and/or tactical asset allocation, the case for using trend analytics looks more encouraging vs. most of the other choices, including relying on forecasts and news headlines to inform your portfolio decisions. ■
The Sparkline observation about needing $2 trillion in annual revenue by 2030 to justify current data center buildouts against $20B current AI revenues crystallizes the key tension in your trend analysis approach. What's compelling about your framework is recognizing that Greenspan's irrational exuberance speech preceded a 100% S&P 500 gain before the eventual peak, which means identifying a bubble correctly but acting defensively too early destroys returns worse than staying exposed and managing the exit via trend signals. The shift from Mag 7 to electricity, cloud storage, and semiconductor leadership that Coatue identifies isn't just sector rotation, its the infrastructure layer monetizing before the application layer, which historically happens in technology cycles but often marks the late innings when capital expenditures peak before revenue catches up. Your overbought oversold indicator showing GTI vulnerability while maintaining bullish primary trend captures exactly why mechanical trend following beats narrative driven timing, because it forces you to stay positioned until the data actually breaks rather than preemptively rotating based on valuation fears that could take years to materialize.
Valuations are not a market timing device, they are more along the lines of a market awareness tool. Historically it has been the case that so long as the economy is expanding the direct of stock prices is higher. But, when high valuations meet an economic downturn then the decline in stock prices is significant. Given the elevated level of valuations, it is likely prudent to alter the asset allocation profile even though as of right now an economic downturn is not on the horizon.
The Sparkline observation about needing $2 trillion in annual revenue by 2030 to justify current data center buildouts against $20B current AI revenues crystallizes the key tension in your trend analysis approach. What's compelling about your framework is recognizing that Greenspan's irrational exuberance speech preceded a 100% S&P 500 gain before the eventual peak, which means identifying a bubble correctly but acting defensively too early destroys returns worse than staying exposed and managing the exit via trend signals. The shift from Mag 7 to electricity, cloud storage, and semiconductor leadership that Coatue identifies isn't just sector rotation, its the infrastructure layer monetizing before the application layer, which historically happens in technology cycles but often marks the late innings when capital expenditures peak before revenue catches up. Your overbought oversold indicator showing GTI vulnerability while maintaining bullish primary trend captures exactly why mechanical trend following beats narrative driven timing, because it forces you to stay positioned until the data actually breaks rather than preemptively rotating based on valuation fears that could take years to materialize.
Valuations are not a market timing device, they are more along the lines of a market awareness tool. Historically it has been the case that so long as the economy is expanding the direct of stock prices is higher. But, when high valuations meet an economic downturn then the decline in stock prices is significant. Given the elevated level of valuations, it is likely prudent to alter the asset allocation profile even though as of right now an economic downturn is not on the horizon.