Segments Across Regimes

How each of the 9 stock groups (and 19 subgroups) behaved in each of the 7 market regimes. Groups are equal-weighted baskets of their members; the benchmark is the equal-weighted average of all 2,000 stocks, so every number here is relative to the typical stock that day.

What stands out

One axis explains most of it

Pre-profit growth and cash burners at one end, low-beta value and yield & real assets at the other. The regimes decide which end wins, and the two ends almost always move in opposite directions.

Reflation is the sharpest rotation

When yields rise fast on a steep curve, pre-profit growth trails the typical stock by about 6% a month and cash burners by 5%, while low-beta value leads by 3.5% and yield stocks and banks by about 2%. It holds after removing beta (t ≈ 2 to 5).

Rebounds and AI melt-ups flip it

In growth-led rebounds pre-profit growth leads by about 5% a month; in the AI melt-up by 4.7%, with high-beta hypergrowth at +7.4%. Yield & real assets lag by about 3% in both. Beta explains part of it, not all.

Quality growth wins almost everywhere, with a catch

+0.8% a month over all days and positive in 5 of 7 regimes; it lags clearly only in reflation. Some of that is hindsight: groups are labelled on September 2026 fundamentals, so today's quality growers are partly yesterday's winners.

Calm, flat-curve markets favour defensives

Late-cycle calm is the quiet mirror of the melt-up: yield & real assets +1.7% a month and low-beta value +1.1%, while pre-profit and cash burners lag by about 3%.

The crash column is one event

Crash / panic is 45 days in two spells (COVID). Quality growth held up and banks fell hardest, but no significance test is possible and the returns are extreme. Treat it as a single episode.

Crosstab: stock groups × market regimes

Each cell is the group's average over the regime's days. Bold values with a dot are more than two standard errors from zero, with errors clustered by regime spell because days inside one spell are not independent.

Measure
Level
Timing

Same day: the return on the day carrying the regime label, which uses that day's close (descriptive). Next day: the return on the following day, when the regime is already known. Most large effects keep their sign in the next-day view because regimes persist, but they shrink.

Regime playbook

Groups ranked within each regime by excess over the typical stock, % per month.

Cumulative excess over time

Log excess return of a group over the equal-weight universe, summed day by day, with each day shaded by its regime. Rising stretches are where the group earned its lead.

Method and caveats