elkassabgi/hfdatalibrary

HF Data Library: High-Frequency U.S. Equity Data

Free, research-grade collection of OHLCV (Open-High-Low-Close-Volume) data for 1,391 U.S. equities and ETFs, covering December 2002 through the present (45 tickers extending to January 1991). Data is available in multiple timeframes from 1-minute up to monthly. Updated weekly via automated pipeline.

Maintainer: Ahmed Elkassabgi, University of Central Arkansas ORCID: 0000-0002-5926-7493 Permanent DOI: 10.5281/zenodo.19501605

Where to download

This Hugging Face repository contains documentation only. The actual data is hosted at:

➡️ https://hfdatalibrary.com

Free registration required (email, ORCID, or Google). Data is available as direct downloads (Parquet or CSV) or via REST API at https://api.hfdatalibrary.com.

What's in the dataset

• 1,391 tickers of U.S. equities and ETFs
• 1.53 billion 1-minute bars (clean version)
• December 2002 – present (with 45 tickers extending to January 1991)
• Weekly automated updates

Cleaning versions

Two cleaning versions are provided:

• Raw: as received from the source, no modifications
• Clean: nine-step cleaning pipeline applied (outside-hours removal, OHLC violations, duplicates, Brownlees-Gallo outlier filter, splice-boundary adjustment)

A gap-filled version is intentionally not distributed — see the accompanying paper for documented biases introduced by LOCF gap-filling. Researchers who need a regular grid can apply LOCF to the Clean version themselves.

Available timeframes

All cleaning versions are aggregated into multiple timeframes:

Timeframe	Description
1-minute	Base data (highest resolution)
5-minute	Aggregated from 1-minute
15-minute	Aggregated from 1-minute
30-minute	Aggregated from 1-minute
Hourly	Aggregated from 1-minute
Daily	Open-to-close per trading day
Weekly	Aggregated to trading weeks
Monthly	Aggregated to calendar months

Pre-computed academic variables

25 variables computed daily for each ticker in each cleaning version:

Volatility (5): Realized variance (1-min and 5-min sampling), bipower variation (BNS 2004), Parkinson (1980), Yang-Zhang (2000)

Spreads (2): Roll (1984) implied spread, Corwin-Schultz (2012) high-low spread

Autocorrelation (3): First-order return autocorrelation, variance ratio (5-min), variance ratio (10-min)

Jump detection (3): BNS z-statistic, BNS jump indicators at 1% and 5% levels

Liquidity (4): Amihud (2002) illiquidity ratio, daily dollar volume, share volume, observed trade count

Data quality (4): Gap rate, observed bars per day, longest gap, max bars since last trade

Returns (4): Open-to-close return, overnight return, daily high-low range, intraday return standard deviation

Data sources

• Pre-March 2022: PiTrading, derived from the consolidated tape (CTA/UTP)
• Post-March 2022: IEX Exchange HIST

Quick start (Python)

import requests
import pandas as pd
from io import BytesIO

# Register at https://hfdatalibrary.com to get an API key
API_KEY = "your-key-here"

# Get a download token (links expire after 10 minutes)
r = requests.get(
    "https://api.hfdatalibrary.com/v1/download-token/AAPL",
    params={"version": "clean", "format": "parquet", "timeframe": "1min"},
    headers={"X-API-Key": API_KEY}
)
url = r.json()["url"]

# Download the file
data = requests.get(url).content
df = pd.read_parquet(BytesIO(data))
print(df.head())

File schema

Each ticker is a single Parquet (or CSV) file. For 1-minute data:

Column	Type	Description
datetime	datetime64	Bar timestamp (Eastern Time)
Open	float64	Opening price (split/dividend adjusted)
High	float64	Highest price during the bar
Low	float64	Lowest price during the bar
Close	float64	Closing price
Volume	int64	Shares traded
source	string	"pitrading" (pre-2022) or "iex" (post-2022)

Higher timeframes (5-min, 15-min, daily, etc.) follow the same schema but with the datetime column resampled to the chosen interval.

License

This dataset is licensed under Creative Commons Attribution 4.0 International.

You are free to share and adapt the material for any purpose, including commercially, provided you give appropriate credit.

How to cite

@dataset{elkassabgi2026hfdatalibrary,
  author    = {Elkassabgi, Ahmed},
  title     = {{HF Data Library: High-Frequency U.S. Equity Data (1-Minute OHLCV)}},
  year      = {2026},
  version   = {1.0},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.19501605},
  url       = {https://hfdatalibrary.com}
}

Links

• Website: https://hfdatalibrary.com
• API: https://api.hfdatalibrary.com
• Documentation: https://hfdatalibrary.com/pages/docs.html
• Data dictionary: https://hfdatalibrary.com/pages/dictionary.html
• Code samples: https://hfdatalibrary.com/pages/code.html
• GitHub: https://github.com/elkassabgi/hfdatalibrary
• Zenodo: https://zenodo.org/records/19501605
• Contact: admin@hfdatalibrary.com