Monthly US M2 money-stock intelligence panel, 1959-01 onward: M2 (billions of U.S. dollars, seasonally adjusted; FRED M2SL, Board of Governors of the Federal Reserve System, H.6 Money Stock Measures release, redistributed keyless via FRED fredgraph.csv). Carries 1-month and 12-month changes (levels and percents), the 3-month annualized percent change (the money-growth momentum read), and a contraction_flag marking months broad money is smaller than a year earlier. One row per month x USA; in-window nulls fail loudly, never imputed. Who joins this: treasury and funding desks join deposit and loan growth on year_month + country_code and use the momentum read and contraction_flag as money-creation regime features; macro and housing-demand models use m2_3m_ann_pct as the leading-liquidity gauge.

Source: US M2 Money-Stock Intelligence (FRED, keyless)
Rows: 812
Columns: 13
Source cadence: Monthly
Last refreshed: Sep 30, 2026
Theme: economy

Column	Type	Description
month_date	date	First day of the observation month (M2SL is monthly, month-start). (unit: date)
year_month	string	Calendar month as YYYY-MM (panel join key). (unit: string)
country	string	Country name (shared normalization layer). (unit: string)
country_code	string	ISO 3166-1 alpha-3 country code (USA). (unit: string)
m2_b	float	M2 money stock (FRED M2SL; Federal Reserve Board H.6 Money Stock Measures). (unit: billions of U.S. dollars, SA)
m2_t	float	Same M2 money stock in trillions of U.S. dollars (m2_b / 1000). (unit: trillions of U.S. dollars, SA)
m2_mom_b	float	1-month change in M2 (null for the first panel month). (unit: billions of U.S. dollars)
m2_mom_pct	float	1-month percent change in M2 (null for the first panel month). (unit: percent)
m2_yoy_b	float	12-month change in M2 (null for the first panel year). (unit: billions of U.S. dollars)
m2_yoy_pct	float	12-month percent change in M2 (null for the first panel year). (unit: percent)
m2_3m_ann_pct	float	3-month annualized percent change in M2 — the money-growth momentum read (null for the first 3 panel months). (unit: percent)
contraction_flag	integer	1 when 12-month M2 growth is negative (broad money smaller than a year earlier), else 0 (warm-up months carry 0: no YoY basis). (unit: flag)
row_hash	string	Deterministic 16-hex sha256 of year_month + the M2 level (idempotency key). (unit: string)

First 10 sample rows — a preview, not the complete dataset.

month_date	year_month	country	country_code	m2_b	m2_t	m2_mom_b	m2_mom_pct	m2_yoy_b	m2_yoy_pct	m2_3m_ann_pct	row_hash
1959-01-01	1959-01	United States	USA	286.6	0.287	—	—	—	—	—	0ccdc36aad3f7156
1959-02-01	1959-02	United States	USA	287.7	0.288	1.1	0.384	—	—	—	31d2e77b25b9221c
1959-03-01	1959-03	United States	USA	289.2	0.289	1.5	0.521	—	—	—	fa1692d9e55ea4fd
1959-04-01	1959-04	United States	USA	290.1	0.29	0.9	0.311	—	—	4.975	753be343059e9437
1959-05-01	1959-05	United States	USA	292.2	0.292	2.1	0.724	—	—	6.405	2e3e15b063bc58d7
1959-06-01	1959-06	United States	USA	294.1	0.294	1.9	0.65	—	—	6.952	94dfab5fcaf219d9
1959-07-01	1959-07	United States	USA	295.2	0.295	1.1	0.374	—	—	7.22	5eaca548f7568ad5
1959-08-01	1959-08	United States	USA	296.4	0.296	1.2	0.407	—	—	5.875	34d86c95ea580545
1959-09-01	1959-09	United States	USA	296.7	0.297	0.3	0.101	—	—	3.583	b4c26d70b238df66
1959-10-01	1959-10	United States	USA	296.5	0.297	-0.2	-0.067	—	—	1.773	bc43238a5ba377a1

Sep 30, 2026Current
20260930T143625Z-667e94044678 · sha256 667e94044678…
812 rows · first snapshot

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/fred_m2_intel/us_m2_money_stock_monthly" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/fred_m2_intel/us_m2_money_stock_monthly").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

API endpoint: https://datazimuts.com/v1/datasets/fred_m2_intel/us_m2_money_stock_monthly

Tip: fetch /llms.txt for the full machine-readable catalog.

Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.

Cite this snapshot

Pinned to snapshot 20260930T143625Z-667e94044678 and its content hash, so readers get exactly the data you used.

APA

US M2 Money-Stock Intelligence (FRED, keyless). (2026). US M2 money stock, monthly [Data set, snapshot 20260930T143625Z-667e94044678, sha256 667e94044678]. Datazimuts. Retrieved 2026-10-01, from https://datazimuts.com/en/datasets/fred_m2_intel/us_m2_money_stock_monthly?snapshot=20260930T143625Z-667e94044678

BibTeX

@misc{dz_fred_m2_intel_us_m2_money_stock_monthly_667e9404,
  title        = {{US M2 money stock, monthly}},
  author       = {{US M2 Money-Stock Intelligence (FRED, keyless)}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/fred_m2_intel/us_m2_money_stock_monthly?snapshot=20260930T143625Z-667e94044678}},
  note         = {Snapshot 20260930T143625Z-667e94044678, sha256 667e940446780c8b09057f07bfb7df02c2c30c73332389f40a1cd4a088a044cc; accessed 2026-10-01}
}

Embed a table or a chart

Paste this into any page. The embed is pinned to the same snapshot, follows the reader's light or dark setting, and always shows the source, license and a link back.

Type

X axis

Value

Aggregate

Theme

HTML

<iframe src="https://datazimuts.com/embed/chart?dataset=fred_m2_intel%2Fus_m2_money_stock_monthly&lang=en&theme=auto&snapshot=20260930T143625Z-667e94044678&x=month_date&y=m2_b&agg=avg" title="US M2 money stock, monthly" width="100%" height="380" style="border:0" loading="lazy"></iframe>

Sign in to comment

Ask about this dataset. Answers come only from its catalog record, measured profile and change history, and list the facts they used.

US M2 money stock, monthly

Follow this dataset

Cite this snapshot

Embed a table or a chart

Use your own AI key