BTC vs M2

Two log-scaled series share the plot. The prominent line is Bitcoin’s USD price on the left axis. The second line is the M2 money supply on a second log axis on the right — the Global M2 basket today. Both axes are logarithmic: equal percent moves read as equal vertical distances, so the two series visually align when they are compounding at the same rate. The basket toggle at the top switches between the global aggregate (a USD-translated sum of major central-bank money supplies) and the US series (the Federal Reserve’s H.6 release).

Today’s reading on the Global M2 basket: M2 stock at $118324.79B, growing at +10.3% year-over-year (the 90-day trend in the growth rate is +1.1%). The trailing 180-day correlation with Bitcoin price is -0.86 — Negative correlation. The series carries 616 observations.

The chart pairs three derived values: the M2 supply level on the right axis, the year-over-year growth rate of that supply, and the 180-day rolling Pearson correlation between Bitcoin price and M2 supply.

M2 YoY is locally derived. Rather than trusting an upstream year-over-year field, we compute YoY from the supply level itself: for each observation, supply is divided by the closest available print to the same calendar day one year prior, minus one. That keeps both baskets on a single auditable definition and lines the US read up with the Federal Reserve’s H.6 series methodology — M1 consists of the most liquid forms of money, namely currency, demand deposits, and other liquid deposits… The non-M1 components of M2 are small-denomination time deposits and retail money market funds. ( federalreserve.gov ).

Global M2 is a provider construction. No central authority publishes “global M2.” The aggregate is a USD-translated sum of major central-bank money supplies — the choices are: which countries to include (eight major economies on common reference series, twenty-one on others); how to translate non-USD M2 into USD (spot daily FX, trailing average, PPP-adjusted); and how to handle definitional differences across jurisdictions (the European M3 ≠ the U.S. M2; the Japanese M2 excludes postal-savings deposits in some periods). Different providers get different numbers from the same underlying source data. The basket we ship is documented on the data sources page, with the caveat above flagged.

The correlation is Pearson. Standard Pearson on the daily-level (price, M2-supply) pairs, rolled forward to the latest observation across a window. The pipeline ships the 180-day rolling correlation; the page recomputes 90-day and 365-day correlations inline against the same series so all three windows refresh nightly. For the formula and window justifications, see the methodology page.

The 180-day rolling correlation is the chart’s primary regime classifier. In regimes where Bitcoin acts as a monetary hedge, the two lines compound together; correlation runs above +0.8 and price moves track M2 growth. In regimes where Bitcoin’s own demand curve dominates (post-ETF inflow phases, late-cycle altcoin seasons), the lines decouple and the correlation falls toward zero. Sharp negative correlations are rare and usually flag liquidation events where Bitcoin falls while M2 continues to grow on autopilot.

Reading the Global M2 M2 supply against canonical cycle anchors makes the monetary backdrop concrete. The 2017 cycle top printed against an M2 stock that has roughly doubled since; the COVID-flush window in March 2020 caught M2 at its pre-expansion baseline; the 2022 cycle low printed against M2 just past the post-COVID peak. The relationship the chart visualises is between the two paths — not between any single point on either.

The headline contribution of this chart over the rest of the Bitcoin-vs-M2 explainer family: rolling correlations at three windows simultaneously. Most published versions show one window — usually 90 days — and let the reader infer the rest. We compute all three nightly against the same daily series and present them inline, anchored at every cycle milestone. The pattern is consistent and worth pausing on: the 90-day correlation swings hard, the 365-day correlation smooths nearly all signal, and the 180-day window is the conventional middle ground for a reason.

The Bitcoin-as-liquidity-beta argument has a primary author. Lyn Alden’s September 2024 piece Bitcoin: A Global Liquidity Barometer, written by Sam Callahan, frames the case directly: During this period [May 2013–July 2024], Bitcoin’s price exhibited a correlation of 0.94 with global liquidity, reflecting a very strong positive correlation. On rolling windows the relationship softens but stays directional: Bitcoin moved in the same direction as global liquidity in 83% of 12-month periods and 74% of 6-month periods. Read in full at lynalden.com.

The counterpoint is worth carrying alongside, not buried. Joseph Wang — a former Federal Reserve open-market trader writing as Fed Guy — argues that M2 is the wrong measure of monetary conditions: QE essentially converts Treasury securities into bank deposits, which is basically one form of money to another. The conversion expands M2 mechanically, but the deposits do not necessarily flow into spending: Money that was saved in Treasuries was not money that was going to be spent on goods and services. It seems more likely to be moved into other financial assets, like corporate debt or equities. By Wang’s framing, the apparent Bitcoin-vs-M2 correlation in the post-2020 window is partly a relabelling of asset-rotation behaviour, not a deep monetary mechanism.

Both views can be true at the same time. Bitcoin can correlate with M2 as a matter of fact while M2 misrepresents the underlying drivers of asset prices. Treat the chart as descriptive evidence, not as a forecast or a thesis.

For a dollar-cost-averaging investor. Modest signal. The multi-year compounding pattern between Bitcoin and M2 is part of the long thesis for accumulating Bitcoin, but the chart is too coarse to time around. Read the 365-day correlation as the slow regime indicator; the 90-day window is too noisy to act on at this horizon.

For a cycle-timing trader. The 90-day correlation is where tactical regime shifts show up; the 180-day window confirms them; the 365-day window pins the structural backdrop. When all three move in the same direction, the underlying thesis (or its breakdown) is durable. When they disagree — 90-day positive while 365-day negative — the regime is in transition and the chart is telling you Bitcoin is decoupling from the slow trend on a faster timescale. Pair with cross-asset correlations to see whether Bitcoin is rotating toward equities, gold, or its own idiosyncratic regime.

For a researcher. The series, the locally-derived YoY values, and the three rolling correlations are the only inputs. The methodology page lists every choice — basket aggregation, FX translation, YoY derivation, Pearson windows. The two-basket toggle exists so you can sanity-check whether a given regime call is robust to the basket choice; when global and US disagree, the disagreement is the signal.

“Global M2” is a provider construction. No central authority publishes a single canonical global aggregate; every series is a sum-of-jurisdictions with provider-specific country lists, FX-translation methodologies, and definitional reconciliation. Two reputable global M2 series can disagree by trillions of dollars on the same day. The series we ship is one provider’s construction; cross-checking against another provider’s number is reasonable, splicing them is not.

The thesis is contested. Joseph Wang’s 2020 piece on QE and M2 argues that M2 doesn’t measure liquidity in the way the Bitcoin-as-liquidity-beta thesis assumes — Treasuries are money for the institutional cohort that drives Bitcoin’s marginal pricing, and a QE reshuffle from Treasuries to bank deposits expands M2 without changing “real” liquidity. The eurodollar critique — that the offshore dollar credit system is the actual driver and is invisible to the U.S. M2 release — is a parallel argument worth knowing about. Take the correlation reading as evidence; do not take it as a closed thesis.

Correlation is not causation, and the 180-day window is short. Two assets can correlate strongly for a quarter purely because they both respond to a third factor (risk-on beta, the dollar index, geopolitical risk). The 365-day correlation in the table above is the closer-to-structural read; the 90-day correlation is the closer-to-tactical read. A user who acts on a single 180-day reading misses the dispersion across windows that is the chart’s headline finding.

Reporting cadence introduces a known lag. M2 supply data lags real-time by several days for the U.S. series and up to a week for the global aggregate. The rightmost edge of the M2 line is systematically a few days behind the rightmost edge of the spot price line. That is a limitation of the release schedules, not the chart — no central bank publishes M2 in real time.

Canonical questions from Google’s “People also ask” block for bitcoin vs m2, answered against the data on this page.