Glossary term
Index Concentration
Index concentration is the rising share of a cap-weighted index's total weight held by its largest constituents. As those names outperform, cap-weighting mechanically feeds them more index weight, compounding the concentration further.
How Cap-Weighting Feeds Itself
A cap-weighted index assigns each constituent a weight proportional to its market value. When the largest names rise faster than the rest of the index, their weight rises automatically as a mechanical consequence — no rebalancing decision is required, the arithmetic simply does it on its own with every price update. Over a sustained run this produces a compounding loop: bigger names earn more of the index's weight, more index-tracking flow follows that weight passively, and the largest names keep growing their share further still. The result can be an index whose top handful of constituents drive a disproportionate share of its total return and, just as importantly, its total risk going forward.
What It Does to Diversification
A concentrated cap-weighted index offers less true diversification than its raw constituent count suggests on paper — owning five hundred names is not the same thing as owning five hundred independent bets if the top ten account for a large fraction of total weight and tend to move together on the same macro or sector driver during stress. It also skews factor exposure in ways that are easy to miss: an index nominally described as "broad market" can, in practice, behave like a concentrated bet on whichever single sector or theme its largest few names happen to belong to, regardless of what the label on the fund actually promises its holders.
The First-50 Effect
Closelook's read on this, in the First-50 Trap heresy, is that the top tier of a concentrated index behaves differently from the rest of it — the largest names can keep re-rating in ways that classical, mean-reversion-based valuation screens read as "expensive" at every single step of a much longer move, because those screens were built for the broad, mean-reverting middle of the distribution rather than for the top of a concentration curve that keeps compounding. Watching breadth alongside concentration — how many names are actually participating in a rally versus how much of the move sits inside a small handful of names — is one way to keep the two effects visibly separate rather than conflated.