Q3 2026 looked uneventful from 30,000 feet and strange from everywhere closer. In How to Win in a Weird Market1, Courtney Doyle lays out why Algorithmic Investment Models (AIM) calls this a "scattered" market, and why that word matters more than it sounds.
The Quarter That Wasn't What It Looked Like
Global equities rose roughly 1.1%. Fixed income fell about 3.5%. On the surface, a calm, modestly positive quarter. Underneath, almost nothing behaved the way a normal market behaves. Most sub-sectors declined even as the index climbed, carried by a narrow slice of mega-cap names. Cap-weighted benchmarks beat equal-weighted ones by a wide margin. Oddest of all, the riskiest stocks slightly outperformed the safest ones, even though both groups lost ground. Doyle's team notes that a historically large number of S&P 500 constituents were negatively correlated with the index itself.
That is the scattered market. As Doyle puts it, "We currently sit in one of the most concentrated equity markets in history." Few things beat the tape, and the few winners share no common thread.
Two Problems, One Cause
AIM frames 2026 around two standing challenges: generating returns without leaning on AI exposure, and cutting risk without leaning on bonds. Both trace back to the same culprit, real interest rates sitting at their highest level in more than two decades. Rate-sensitive sectors like housing stalled. Low-volatility, bond-proxy equities lost their appeal once bonds themselves offered competitive real yields. Meanwhile the largest technology names, insulated by the AI growth narrative rather than financing costs, became the default refuge, concentrating the index further.
A secondary current reinforced the first. Public sentiment toward AI soured over the quarter, including researcher warnings about long-term risk, and AI-linked equities, which trade more on story than on quarterly earnings, swung harder between headlines. Energy held up as one of the year's best performers despite that backdrop, while biotech, sold near its high in August, and clean energy, exited in June, both continued to slide. A semiconductor drawdown of roughly 29 to 30 percent between late June and late July validated a volatility call AIM had flagged before the selloff. A Q3 re-entry into solar, by contrast, was poorly timed and dented the Moderate strategy, a misstep the team owns plainly rather than smooths over.
Capitalizing on the Divide
Doyle's team sorts the opportunity set into two buckets: an "AI bucket" that is large, volatile, and now drives most market risk, and an "other" bucket that has been overlooked yet quietly resilient. The practical consequence is a reframing of diversification itself. With fixed income now more correlated to the S&P 500 than the average stock is to its own index, and with roughly 240 ETFs screened for market-beating returns or low correlation, risk reduction increasingly means buying different equities rather than bonds. The hard part, as always, is selection and timing, which is precisely what AIM's models are built to do.
The firm also reports process upgrades: beta-targeted models and machine-learning "conditional" variables that let the same price pattern read differently depending on whether markets are calm or turbulent. Nine months of live results show these outranking their predecessors, with incorporation into live portfolios contingent on that pattern holding.
The Concentration Question
Doyle draws the inevitable comparison to the dot-com era, carefully, noting its limits even while making it. Extreme concentration has preceded every major index peak, and eventual broadening, when it comes, should hand active, selective strategies a real advantage over passive exposure. Whether that broadening arrives on a gradual glide path or a disorderly one, particularly if Energy's tailwinds reverse quickly rather than fade, remains, in Doyle's own framing, genuinely unresolved.
Five Takeaways for Advisors and Investors
- Index-level calm can mask sub-sector chaos; headline returns are no longer a reliable read on market breadth.
- Real interest rates, not AI sentiment alone, are the primary driver reshaping sector leadership this cycle.
- Fixed income's diversification value has eroded as its correlation to equities rises; equity-to-equity diversification is filling the gap.
- Historic concentration has always preceded broadening, and broadening favors selective, active positioning over passive exposure.
- Process discipline, acting on volatility signals before the selloff, mattered more this quarter than any single sector call.
Footnote:
1 Doyle, Courtney. "How to Win in a Weird Market." AlgoModels, algomodels.com/how-to-win-in-a-weird-market/. Accessed 5 Nov. 2026.
