Seasonality spreads the asset’s month-by-month record out as a coloured grid, which brings any calendar habits into view, including months that have finished positive with suspicious regularity. Treat it as something to read alongside a decision, never as the decision.

The tendencies it shows are empirical patterns in a record, not properties of the calendar. Whether they will hold is a separate question the view does not answer.

What it actually measures

Every month gets a mark for each year on record and those marks are arranged in a grid, so the full spread behind a month is on show instead of one averaged figure. Where a month looks strong, the explanations usually reached for involve institutional money movements and tax deadlines.

Reading the distribution rather than the average is what the heat map is for. A month whose record is built from one spectacular year looks very different from one that has quietly closed positive again and again.

Each month has one observation per year, and no more

A decade of history gives ten observations for January. It is a small sample by any standard, and this is the whole evidence base behind any claim about that month.

It is also why a couple of extreme years can manufacture a month’s entire reputation. The heat map exists to make that visible: an outlier-driven month and a consistently strong one can show the same average and look nothing alike on the grid, and only one of them is telling you something.

That is also why the strongest-looking months deserve the most scrutiny. A month earns its reputation by having a large average, and a large average is exactly what one extraordinary year produces. The months worth trusting are the dull, consistent ones, which is the opposite of how the grid tends to be read.

What it does not tell you

It offers no mechanism. Explanations involving flows and tax years are plausible stories fitted after the fact, and a pattern with no cause behind it has nothing to stop it disappearing.

The record is also short and unusually eventful. Several of the years feeding each month contained conditions unlikely to be repeated, and the calendar had nothing to do with any of them.

How to read it

Favourable. Months that have finished up considerably more often than down. Institutional money movements and tax deadlines are the explanations usually reached for.

No Edge. Months that have finished either way about equally often, where the calendar contributes nothing at all.

Unfavourable. Months that have finished down more often than up. Worth having in mind, and not a reason to do anything by itself.

The Market Cycles dashboard tracks Seasonality beside Cycle Timeline, Days Since ATH and Halving Cycles.

Common questions

Can this be used to time the market?

It surfaces habits the record happens to contain, and nothing here is promised. Read it alongside a decision rather than treating it as one.

How much evidence is behind one month?

A single mark for each year on record, which is thin evidence by any standard worth respecting. That thinness is the main reason this is framed as background.

Why do certain months carry undeserved reputations?

Because two or three wild years can carry a thin record on their own. Laying the marks out in a grid is what exposes a month whose reputation rests on a couple of freak results.

Is there a reason behind the patterns?

Explanations are offered, and they are fitted after the fact. A pattern without a mechanism has nothing holding it in place.

What should I look at on the grid?

The spread within each month, not the average. Consistency and a single spectacular year produce the same mean and mean very different things.