US-China bilateral trade signals (decoupling tracker)

Name: US-China bilateral trade signals (decoupling tracker)
Creator: US-China Trade Signals (derived)
License: https://fred.stlouisfed.org/legal/
Keywords: china, trade, bilateral-trade, imports, exports, decoupling, deficit, census, macroeconomics, anomaly-detection, forecasting, signals, fred

US-China bilateral goods-trade signals (Census via FRED, monthly 1985 ->): import/export momentum, 30-period change volatility, 3-sigma shock flags, drift forecasts, the bilateral deficit tracker, its 5-year z-score and the export reciprocity gauge. The bilateral lens: where the decoupling story shows up in the numbers. US government data via FRED (free, keyless-by-reuse of the existing FRED key).

Source: US-China Trade Signals (derived)998 lignesMis à jour: 22/09/2026

chinatradebilateral-tradeimportsexportsdecouplingdeficitcensusmacroeconomicsanomaly-detectionforecastingsignalsfred

Qualité

99.5

Attribution

U.S. Census Bureau via FRED; derived signals by Frontier Data Hub

Schéma

Colonne	Type	Description
date	string	Reference month (FRED observation date; monthly, seasonally adjusted).
country	string	United States (all series are US bilateral).
country_code	string	ISO 3166-1 alpha-3 code: USA.
series_id	string	FRED series ID: IMPCH (U.S. imports of goods from China) or EXPCH (U.S. exports of goods to China).
series_label	string	Official FRED series title as published in the series metadata.
value	float	U.S. goods trade flow with China in millions of dollars, seasonally adjusted (imports on a customs basis; exports on an FAS basis); U.S. Census Bureau via FRED.
yoy_change_pct	float
momentum_3m	float
volatility_30d	float
anomaly_flag	integer
forecast_1m	float
bilateral_deficit	float
deficit_yoy_change	float
deficit_z_5y	float
export_share_of_bilateral	float

Exemple de lignes

date	country	country_code	series_id	series_label	value	yoy_change_pct	momentum_3m	volatility_30d	forecast_1m	bilateral_deficit	deficit_yoy_change	deficit_z_5y	export_share_of_bilateral
1985-01-01	United States	USA	EXPCH	U.S. Exports of Goods by F.A.S. Basis to Mainland China	319.2	—	—	—	—	-26.099999999999966	—	—	1.089048106448311
1985-02-01	United States	USA	EXPCH	U.S. Exports of Goods by F.A.S. Basis to Mainland China	222.7	—	—	—	—	58.30000000000001	—	—	0.7925266903914591
1985-03-01	United States	USA	EXPCH	U.S. Exports of Goods by F.A.S. Basis to Mainland China	239.5	—	—	—	—	53.5	—	—	0.8174061433447098
1985-04-01	United States	USA	EXPCH	U.S. Exports of Goods by F.A.S. Basis to Mainland China	265.6	—	-16.79197994987468	—	—	17.69999999999999	—	—	0.9375220614189905
1985-05-01	United States	USA	EXPCH	U.S. Exports of Goods by F.A.S. Basis to Mainland China	329.3	—	47.86708576560397	—	—	-34.19999999999999	—	—	1.115892917655032

Télécharger un échantillon

Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).

Télécharger l'exemple CSV Télécharger l'exemple JSON

Utiliser avec un LLM

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/china_trade_signals/us_china_trade_signals" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/china_trade_signals/us_china_trade_signals").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/china_trade_signals/us_china_trade_signals

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