Finance QC clean AI-training-safe

US Net Liquidity Index

The net-liquidity curve crypto and macro desks actually trade: Fed balance sheet - Treasury General Account - Reverse Repo, in $ billions, daily. The exact formula, pre-computed and aligned (weekly Fed balance sheet forward-filled onto the daily TGA/RRP) so you can backtest it directly.

3K
rows
1
zones
2010-2026
coverage
0.1 MB
download
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

  • Net Liquidity = balance sheet - TGA - Reverse Repo, $ bn, daily
  • The exact formula macro/crypto Twitter talks about - done for you
  • Weekly Fed balance sheet forward-filled onto daily TGA/RRP
  • Source: U.S. Federal Reserve + U.S. Treasury + NY Fed (public domain, derived)

Schema

ColumnTypeDescriptionFilledDistinct
zone str Always US 100.0% 1
ts timestamp (UTC) Trading day 100.0% 3,221
net_liq_bn float Balance sheet - TGA - RRP, $ billions 100.0% 2,769
unit str Unit 100.0% 1
res_min int Native resolution (daily = 1440) 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-net-liquidity_sample.parquet")
df.info()   # typed columns, gap-aware, ready to join
⬇ Download free Parquet sample or CSV for Excel
Coverage: 1 zones

US