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 is up roughly 1.6x 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.

Quote the Bitcoin-M2 correlation as a single number and you can defend almost any thesis — pick the window that flatters your view. The honest version is that the coefficient is a function of horizon, and the function is steep. The 90-day correlation swings hard, the 365-day correlation smooths nearly all the signal away, and the 180-day window is the conventional middle ground for a reason. The table below holds the basket fixed and reads all three windows at each cycle milestone, so the spread between them — not any one value — is the thing you take away.

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.

March 2020 — the lead that wasn’t. When the COVID flush hit on 12–23 March 2020, Bitcoin fell more than 50% in two days while the Fed had not yet expanded M2. The biggest monetary expansion in U.S. history then followed over the next two years, and Bitcoin ran with it — which is exactly the “Bitcoin lags M2 by 70–100 days” story analysts tell. But the lag is fitted after the fact: the same window also contained the first U.S. stimulus checks, a retail options mania, and the DeFi summer, any of which would have lifted a speculative asset with or without M2. A correlation that only resolves once you choose the lag in hindsight is not a leading indicator.

2022 — the cascade that inverted the sign. Through the Terra/Luna implosion in May 2022, the 3AC and Celsius failures over the summer, and the FTX collapse on 11 November 2022, Bitcoin fell roughly 75% from its cycle high. M2, meanwhile, barely contracted — nominal money supply almost never falls. The durable negative prints, though, arrived after the November-2022 low, not at it: as the 2022-low row of the table above shows, the longer windows were still positive at the anchor, and the falling-price-against- rising-denominator coefficient only turned decisively negative later — on the global basket through late 2022, and on the US basket not until 2023. When it did invert, the negative coefficient was not Bitcoin hedging against liquidity; it was idiosyncratic crypto-credit contagion overwhelming the monetary backdrop entirely.

The basket trap. “Global M2” is a provider construction — no central authority publishes a single canonical aggregate, and 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, and a strengthening dollar shrinks the USD-translated global number even when local-currency money supply is still expanding — an FX artefact, not a monetary contraction. Cross-checking the basket we ship against another provider’s number is reasonable; splicing them is not. When the global and US baskets disagree, the disagreement is itself the signal.

The eurodollar blind spot and the lag instability. The offshore dollar credit system — the eurodollar market that funds much of global trade — is invisible to the U.S. H.6 release, so the metric that Bitcoin’s marginal institutional buyers actually respond to may not be M2 at all. And the much-quoted 70-to-100-day lead time is unstable: across analyst writeups it has been reported anywhere from 56 to 107 days, which is wide enough that fitting it to the next move is curve-fitting, not forecasting. Read the correlation as evidence of a real long-run relationship; do not read it as a clock.

If you accumulate on a schedule, the signal here is modest and slow. The multi-year compounding pattern between Bitcoin and M2 is part of the long thesis for owning Bitcoin, but the chart is far too coarse to time around. Read the 365-day correlation as the structural regime indicator; the 90-day window is too noisy to act on at this horizon, and a negative 180-day print during a drawdown tells you about Bitcoin’s recent path, not about whether to keep buying.

If you are timing the cycle, the 90-day correlation is where tactical regime shifts show up, the 180-day window confirms them, and the 365-day window pins the structural backdrop. When all three move together, the underlying relationship (or its breakdown) is durable; when they disagree — 90-day positive while 365-day negative — Bitcoin is decoupling from the slow trend on a faster timescale. Pair the read with cross-asset correlations to check whether Bitcoin is rotating toward equities, gold, or its own idiosyncratic regime, and flip the basket toggle: when a regime call survives both the global and the US series, it is robust to the messiest input choice on the page.