Yuka Finance Guide — historical statistics and seasonal biases
Seasonality measures how an asset has historically behaved during a
given period of the year, across several decades. It is not a prediction, but a
descriptive statistic: "this month, over the last 30 years, this asset has gained
X% of the time."
Where these numbers come from
By looking at an asset's monthly returns over a long period (often 20 to 40 years
depending on data availability), you can calculate, for each calendar month, the
percentage of years in which the asset finished that month higher. A month in which the
asset was positive 27 years out of 33 shows a historical win rate of 82% for that specific
window.
Why some months repeat
Some seasonal patterns have plausible structural explanations: year-end flows into
equity indices, harvest cycles in agricultural commodities, institutional portfolio
rebalancing on fixed dates. Others have no clear explanation and could partly be the
product of statistical chance on a limited sample.
Important to understand: an 80% historical win rate for a given month
does not guarantee the asset will rise this year. It's a historical probability, not a
certainty — and 33 years of history remains a limited statistical sample.
How to use it reasonably
One ingredient among others — seasonality alone should never
justify a trading decision. It becomes meaningful when combined with other signals
(positioning, options structure, sentiment).
More useful as confirmation than as a trigger — if several
independent indicators point the same way as seasonality, the combined evidence is
stronger than any single signal on its own.
Be wary of short samples — seasonality over 5 years carries much
less statistical weight than over 30 years.
See seasonality live
Yuka Finance automatically calculates monthly seasonal statistics for major indices,
commodities and Bitcoin, built directly into the Score Yuka.