Stats Best and worst days Best days in bear markets

Why the best days happen in bear markets

Best days/clustering · 1996 to 2025 · 3 sources · data as of 31 Jul 2026

You've almost certainly seen the line about missing the ten best days. Miss them and your thirty year return collapses. On its own that's just arithmetic, and it gets used as a conversation ender. The more interesting question is the one nobody asks next: when do those best days actually happen?

They happen while the market is falling apart. Of the fifty best trading days in a thirty year window, 48% landed inside a bear market and another 28% arrived in the opening two months of a new bull. That's 76% of the market's biggest single day gains occurring at moments when almost nobody wanted to own stocks. This page lays that out, explains why it happens rather than just asserting it, and puts a second study alongside it from a different firm, a different window and a different data provider, which finds the same shape from another angle: the best days and the worst days sit right next to each other in the calendar.

I put it together because the clustering is the part that actually makes the argument, and it's the part that usually gets left out. It also lets me be honest about what the statistic does not prove, which is a section I'd rather write myself than leave to someone selling something. Two studies, two windows, two data providers. Both are linked at the bottom with their dates attached, and I've kept them separate in the note rather than blending them into one tidy figure, because they aren't the same measurement.

TL;DR

76% of the stock market's best days occur either during a bear market or in the first two months of a new bull market. Of the fifty best days in a thirty year window, 48% happened during a bear market and a further 28% in the opening two months of the recovery. J.P. Morgan's separate finding is the same shape: six of the ten best days fell within two weeks of the ten worst, and five of those six came after the worst days, not before.

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