US Macro
The daily financial-conditions tape crypto and macro desks watch: US net liquidity, key Treasury yields (2Y/10Y/30Y) and EUR/USD in one aligned table - the risk-asset backdrop, pre-joined on date so you can backtest against it directly.
- Source
- derived
- Licence
- Redistributable open data
- Updates
- Daily
- Data through
- 2026-07-31
- Quality
- QC clean · 0 failures
- Format
- Apache Parquet + dictionary
Safe to train on
Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.
What's included
- 5 variables daily: net liquidity, 2Y/10Y/30Y yields, EUR/USD
- Joined across Fed/Treasury net-liquidity + Treasury curve + ECB on date
- Long format; the macro overlay for any risk-asset model
- Source: U.S. Treasury + Federal Reserve + ECB (public domain / reuse, derived)
Schema
| Column | Type | Description | Filled | Distinct |
|---|---|---|---|---|
| zone | str | Always US | 100.0% | 1 |
| ts | timestamp (UTC) | Trading day | 100.0% | 6,836 |
| variable | str | Net liquidity / 2Y / 10Y / 30Y / EUR-USD | 100.0% | 5 |
| value | float | Daily value | 100.0% | 3,278 |
| unit | str | Unit (mixed) | 100.0% | 2 |
| res_min | int | Native resolution (daily) | 100.0% | 1 |
Sample & preview
Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: derived (redistributable open data; attribution passes through - see our Licence).
Don't trust screenshots - drop the sample into your notebook right now.
import pandas as pd df = pd.read_parquet("us-macro-liquidity-tape_sample.parquet") df.info() # typed columns, gap-aware, ready to join⬇ Download free Parquet sample or CSV for Excel
Coverage: 1 zones
US
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