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Concentrating on Concentration

Authors: Victor Haghani; James White;

Concentrating on Concentration

Abstract

<span>The US stock market is heavily concentrated in a handful of technology companies, with the "Magnificent Seven" accounting for over 30% of total market capitalization. Many investors and commentators view this as a warning signal, arguing that concentration makes the market riskier and calls for defensive action. We argue that this concern is misplaced. Drawing on two recent papers — Kritzman and Turkington (2025) and Bye, Kvaerner, and Werker (2026) — as well as our own earlier research, we make three points. First, current concentration levels are well within historical and international norms; the US market was at least as concentrated in the 1930s through 1960s, and comparable concentration is observed across developed markets worldwide. Second, concentration has no meaningful empirical relationship with subsequent risk or return; dynamic strategies that reduce equity exposure when concentration rises have underperformed static allocations,&nbsp;not to mention allocations that are driven by estimates of stock market excess return and risk. Third, the observed degree of concentration is exactly what standard financial models predict from normal idiosyncratic volatility compounded over time — no bubble or market dysfunction is required. We conclude that investors who react to concentration by reducing equity exposure or shifting to equal-weighted strategies are likely to hurt their performance. Instead, we advocate dynamic asset allocation guided by direct estimates of the market's expected excess return and risk, an approach with both theoretical support and an attractive empirical track record.</span>

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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