Match the observation periods
Housing values and asset prices use the same calendar month, quarter or year before either series is compared.
Like-for-like datesNew York City. Compare the published home-value series with QQQ, SPY, GLD, Bitcoin and other assets.
Compare growth →US · United StatesSan Francisco city. Compare the published home-value series with QQQ, SPY, GLD, Bitcoin and other assets.
Compare growth →US · United StatesLos Angeles city. Compare the published home-value series with QQQ, SPY, GLD, Bitcoin and other assets.
Compare growth →US · United StatesMiami city. Compare the published home-value series with QQQ, SPY, GLD, Bitcoin and other assets.
Compare growth →UK · United KingdomGreater London. Compare the published home-value series with QQQ, SPY, GLD, Bitcoin and other assets.
Compare growth →EU · FranceParis municipality. Compare the published home-value series with QQQ, SPY, GLD, Bitcoin and other assets.
Compare growth →EU · GermanyFrankfurt am Main. Compare the published home-value series with QQQ, SPY, GLD, Bitcoin and other assets.
Compare growth →Housing values and asset prices use the same calendar month, quarter or year before either series is compared.
Like-for-like datesEach value is divided by its first shared observation in the selected range and multiplied by 100.
Relative growth, not price levelsIndexing both series to 100 at their first shared observation makes their percentage growth directly comparable even though their original price levels and currencies differ.
The gap is home growth minus asset growth over the selected range. A positive gap means the home-value series grew faster; a negative gap means the asset grew faster.
No. It compares changes in published home values with changes in the selected asset’s price. It excludes income, dividends, transaction costs, financing, maintenance, and taxes.
Only periods containing both a published housing value and a valid asset price are used. The two series are aligned by calendar period before either is indexed to 100.
It shows how two published price series changed over the same period. It does not establish that one caused the other, measure housing affordability, or forecast either series.
Yes. Housing data can be revised and recent periods can be provisional. The detail page reports the applicable source, data-through date, and revision policy.
Each range resets both series to 100 at its first shared observation. Changing that starting point changes the base period and can materially change the measured growth gap.
Housing measures are usually monthly or quarterly estimates built from transactions, valuations, or models. Market prices update more frequently and can react faster, even though this chart aligns both series to the housing frequency.
One tested idea, through the evidence stack. No migration of any kind.