For active managers, this question usually comes with a scorecard - measured in P&L, drawdowns, and risk metrics. Heading into 2026, the problem isn’t a lack of factor signals, but a shifting market structure. The assumptions that once kept factor behavior cleanly separated have weakened, and in some cases collapsed altogether.
Market leadership remains unusually narrow as a small set of companies continues to account for a large share of index performance, earnings growth, and capital spending. That concentration also affects factor behavior in practice.
Momentum becomes a function of crowding and liquidity rather than clean trend persistence. Growth increasingly expresses duration risk and dependence on sustained capital spending. Quality converges on the same large balance sheets, pricing power, and scale advantages.
The labels are still there, but in practice factor returns tend to move together rather than provide meaningful offsets. Surface-level diversification across sleeves is often just exposure to the same underlying drivers.
Many factor portfolios look well balanced on paper. In practice, they often converge more than managers expect.
Today’s growth exposure isn’t just about earnings acceleration anymore. It reflects long-duration cash flows, capital intensity, and reliance on the same narrow group of market leaders. Quality, typically framed around balance-sheet strength and stable margins, frequently points to the same companies, driven by scale, pricing power, and durable cash generation. Momentum follows where capital has already accumulated. In a concentrated market, that flow reinforces existing positions rather than diversifying them.
The result is that different factor tilts can end up expressing very similar risk, especially when markets start to de-risk.
Crowded exposures unwind quickly. When too many portfolios own the same trades, exits tend to be abrupt and correlated, even without a clear macro catalyst. That’s why factor drawdowns today can feel binary rather than gradual.
Traditional factor thinking assumes mean reversion - that value will eventually work, smaller names will catch up and leadership will broaden.
Over the last few years, those patterns have been unreliable. Rotations have been brief and broadening has stalled. Structural forces such as scale, capital intensity and capital flows have often overwhelmed cyclical dynamics. This leaves managers in an uncomfortable spot. Waiting for mean reversion can be costly, but abandoning it entirely risks missing the turn when it finally comes.
No factor wins or loses in isolation, at least not in markets like this one. Outcomes are shaped by how factor exposures align with the broader market structure and how deliberately the associated risks are managed.
What matters more than the label is:
- The exposures a factor actually introduces
- How dependent those exposures are on the same underlying drivers
- How they behave when liquidity tightens or positioning begins to unwind
The more useful questions tend to be about portfolio construction, not market calls:
- Where does factor overlap exist in the book? Is it by design or by accident?
- How dependent are returns on the same handful of stocks or themes?
- How liquid are factor positions if markets turn quickly?
- What macro assumptions are embedded in factor tilts, even if they’re not explicit?
None of this guarantees outperformance, but it does make risk clearer... and surprises less frequent.
