US Treasury par yield-curve intelligence, daily

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Le jeu complet n’est pas encore publié — revenez après la prochaine actualisation.Télécharger l'exemple CSV Télécharger l'exemple JSONLignes d’exemple seulement (jusqu’à 20) — pas le jeu de données complet.

One row per Treasury business day of the official U.S. Treasury Daily Par Yield Curve Rates (keyless year-scoped CSV exports, https://home.treasury.gov/resource-center/data-chart-center/interest-rates/TextView?type=daily_treasury_yield_curve; the publisher's tenor grid evolved 2019-2026 and is normalized into canonical columns). Each row: 14 par-yield tenors (1m-30y, percent; honest nulls where a tenor did not exist that day/year), term spreads in basis points (10y-2y, 10y-3m, 30y-10y, 5y-2y), inversion flags + depth and per-episode tracking of consecutive inverted days (start date, day number, episode max depth), curve slope (10y-3m) and curvature (2*5y-3m-10y), 1/5/20-day 10y momentum, and a documented look-ahead-free 0-100 curve_stress score (0.40*inversion-depth(10y-2y) + 0.35*depth(10y-3m) + 0.25*inversion-breadth, each causal-rolling min-maxed over the trailing 10y window, null until 1y of history) with t1-t4 calm-to-severe tiers, plus flat-curve and deep-inversion flags. Fail-loud gates: closed tenor-label set, yields in [0,30]%, core tenors never null, unique dates, >=200 rows per full year. Units: percent, basis points, pp changes; row hashes are deterministic. Coverage: United States, 2019-01-02 -> latest published curve day (~1,900 rows; publisher publishes business days only, ~2 business-day lag at quarter-end). Provenance: keyless Treasury CSV downloads, U.S. public domain - cite the U.S. Department of the Treasury. Primary key: curve_date. Cadence: refreshed daily. Nullability: young tenor series (y_45d, y_4m, y_20y) null before introduction; episode columns null on non-inverted days; momentum null on the panel's first rows; stress_score/stress_tier null until 252 observations. Sample use: filter inv_10y2y_flag=1 to list every 2s10s-inverted day with its episode; order by stress_score desc to find the most strained curve days of the window.

Les titres et les descriptions proviennent des sources de données, en anglais.

Source: U.S. Department of the Treasury, Daily Treasury Par Yield Curve Rates
Lignes: 1 935
Colonnes: 38
Cadence de la source: Quotidienne
Dernière actualisation: 28 sept. 2026
Thème: markets

Colonne	Type	Description
curve_date	string	Treasury business day of the published par yield curve; the primary key. Weekends and federal holidays have no publication. (unit: ISO date)
as_of	string	Data vintage: the latest published curve date; identical upstream data gives an identical as_of, so re-ingests are no-ops. (unit: ISO date)
country_code	string	ISO alpha-3 country code (USA for every row; the publisher is the U.S. Treasury). (unit: ISO 3166-1 alpha-3)
y_1m	float	Par yield at the 1m tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_45d	float	Par yield at the 45d tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_2m	float	Par yield at the 2m tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_3m	float	Par yield at the 3m tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_4m	float	Par yield at the 4m tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_6m	float	Par yield at the 6m tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_1y	float	Par yield at the 1y tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_2y	float	Par yield at the 2y tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_3y	float	Par yield at the 3y tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_5y	float	Par yield at the 5y tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_7y	float	Par yield at the 7y tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_10y	float	Par yield at the 10y tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_20y	float	Par yield at the 20y tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
y_30y	float	Par yield at the 30y tenor, in percent (honest nulls where the publisher did not print this point that day/year). (unit: percent)
spread_10y2y_bp	float	10-year minus 2-year par yield, in basis points; negative = inverted. (unit: basis points)
spread_10y3m_bp	float	10-year minus 3-month par yield, in basis points; negative = inverted. (unit: basis points)
spread_30y10y_bp	float	30-year minus 10-year par yield, in basis points. (unit: basis points)
spread_5y2y_bp	float	5-year minus 2-year par yield, in basis points; negative = inverted. (unit: basis points)
inv_10y2y_flag	integer	1 when spread_10y2y_bp is strictly negative (2s10s inverted). (unit: 0/1)
inv_10y3m_flag	integer	1 when spread_10y3m_bp is strictly negative (3m10s inverted). (unit: 0/1)
inv_depth_10y2y_bp	float	Inversion depth: clip(2y - 10y, >= 0) in bp; 0 when the curve is not inverted. (unit: basis points)
inv_depth_10y3m_bp	float	Inversion depth: clip(3m - 10y, >= 0) in bp; 0 when the curve is not inverted. (unit: basis points)
inv_episode_10y2y_start	string	First curve_date of the current run of consecutive inverted days (null on non-inverted days). (unit: ISO date)
inv_episode_10y2y_day	float	1-based position within the current inversion episode (null on non-inverted days). (unit: count)
inv_episode_10y2y_max_depth_bp	float	Maximum 10y-2y inversion depth seen so far in the current episode, in bp (null on non-inverted days). (unit: basis points)
d1_10y_bp	float	10-year par yield change vs the prior published curve day, in basis points (null on the first row). (unit: basis points)
d5_10y_bp	float	10-year par yield change vs 5 published days ago, in basis points (null on the first 5 rows). (unit: basis points)
d20_10y_bp	float	10-year par yield change vs 20 published days ago, in basis points (null on the first 20 rows). (unit: basis points)
curve_slope_pp	float	Curve slope: 10y minus 3m par yield, in percentage points. (unit: percentage points)
curve_curvature_pp	float	Curve curvature: 2*5y - 3m - 10y par yields, in percentage points. (unit: percentage points)
flat_curve_flag	integer	1 when \|spread_10y2y_bp\| <= 25 bp (flat curve). (unit: 0/1)
deep_inversion_flag	integer	1 when inv_depth_10y2y_bp >= 50 bp (deep inversion). (unit: 0/1)
stress_score	float	Documented 0-100 composite: 100 * (0.40mm(inv_depth_10y2y clipped to 100bp) + 0.35mm(inv_depth_10y3m clipped to 100bp) + 0.25*mm(inversion breadth across 10y-2y/10y-3m/10y-1y/5y-2y)), each min-maxed over the causal trailing 2,520-observation window; null until 252 observations exist. (unit: 0-100)
stress_tier	string	stress_score bucket: t1 calm (<25), t2 mild (25-50), t3 elevated (50-75), t4 severe (>=75); null until the score exists. (unit: category)
row_hash	string	16-char SHA-256 of the canonical row tuple (floats rounded to 6 decimals, nulls normalized); identical input gives identical hashes. (unit: hash)

10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.

curve_date	as_of	country_code	y_1m	y_45d	y_2m	y_3m	y_4m	y_6m	y_1y	y_2y	y_3y	y_5y	y_7y	y_10y	y_20y	y_30y	spread_10y2y_bp	spread_10y3m_bp	spread_30y10y_bp	spread_5y2y_bp	inv_episode_10y2y_start	inv_episode_10y2y_day	inv_episode_10y2y_max_depth_bp	d1_10y_bp	d5_10y_bp	d20_10y_bp	curve_slope_pp	curve_curvature_pp	flat_curve_flag	stress_score	stress_tier	row_hash
2019-01-02	2026-09-25	USA	2,4	—	2,4	2,42	—	2,51	2,6	2,5	2,47	2,49	2,56	2,66	2,83	2,97	16	24	31	-1	—	—	—	—	—	—	0,24	-0,1	1	—	—	4fec588dbcc8965c
2019-01-03	2026-09-25	USA	2,42	—	2,42	2,41	—	2,47	2,5	2,39	2,35	2,37	2,44	2,56	2,75	2,92	17	15	36	-2	—	—	—	-10	—	—	0,15	-0,23	1	—	—	d7d4583f2c9b418d
2019-01-04	2026-09-25	USA	2,4	—	2,42	2,42	—	2,51	2,57	2,5	2,47	2,49	2,56	2,67	2,83	2,98	17	25	31	-1	—	—	—	11	—	—	0,25	-0,11	1	—	—	636485971bf42770
2019-01-07	2026-09-25	USA	2,42	—	2,42	2,45	—	2,54	2,58	2,53	2,51	2,53	2,6	2,7	2,86	2,99	17	25	29	0	—	—	—	3	—	—	0,25	-0,09	1	—	—	89b830f37134953b
2019-01-08	2026-09-25	USA	2,4	—	2,42	2,46	—	2,54	2,6	2,58	2,57	2,58	2,63	2,73	2,88	3	15	27	27	0	—	—	—	3	—	—	0,27	-0,03	1	—	—	8992a8023a8ccb7d
2019-01-09	2026-09-25	USA	2,4	—	2,42	2,45	—	2,52	2,59	2,56	2,54	2,57	2,64	2,74	2,9	3,03	18	29	29	1	—	—	—	1	8	—	0,29	-0,05	1	—	—	e8c647487485a224
2019-01-10	2026-09-25	USA	2,42	—	2,42	2,43	—	2,51	2,59	2,56	2,54	2,56	2,63	2,74	2,92	3,06	18	31	32	0	—	—	—	0	18	—	0,31	-0,05	1	—	—	377e32d7fb382d9e
2019-01-11	2026-09-25	USA	2,41	—	2,43	2,43	—	2,5	2,58	2,55	2,51	2,52	2,6	2,71	2,9	3,04	16	28	33	-3	—	—	—	-3	4	—	0,28	-0,1	1	—	—	f4f57852540a231e
2019-01-14	2026-09-25	USA	2,42	—	2,43	2,45	—	2,52	2,57	2,53	2,51	2,53	2,6	2,71	2,91	3,06	18	26	35	0	—	—	—	0	1	—	0,26	-0,1	1	—	—	7230c603c23013e2
2019-01-15	2026-09-25	USA	2,41	—	2,43	2,45	—	2,52	2,57	2,53	2,51	2,53	2,61	2,72	2,92	3,08	19	27	36	0	—	—	—	1	-1	—	0,27	-0,11	1	—	—	3c8054f304571554

Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).

cURL

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

Python

import requests

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

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

Point d’accès API : https://datazimuts.com/v1/datasets/us_treasury_curve_intel/us_treasury_yield_curve_daily

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.

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APA

U.S. Department of the Treasury, Daily Treasury Par Yield Curve Rates. (2026). US Treasury par yield-curve intelligence, daily [Data set, snapshot 20260928T084557Z-a1ee0522b765, sha256 a1ee0522b765]. Datazimuts. Retrieved 2026-09-28, from https://datazimuts.com/fr/datasets/us_treasury_curve_intel/us_treasury_yield_curve_daily?snapshot=20260928T084557Z-a1ee0522b765

BibTeX

@misc{dz_us_treasury_curve_intel_us_treasury_yiel_a1ee0522,
  title        = {{US Treasury par yield-curve intelligence, daily}},
  author       = {{U.S. Department of the Treasury, Daily Treasury Par Yield Curve Rates}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/fr/datasets/us_treasury_curve_intel/us_treasury_yield_curve_daily?snapshot=20260928T084557Z-a1ee0522b765}},
  note         = {Snapshot 20260928T084557Z-a1ee0522b765, sha256 a1ee0522b765d86022f3d8de7f73ff3839c29dd25afe59ef591817a0a6cab336; accessed 2026-09-28}
}

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