metadata
license: cc-by-4.0
language:
- en
pretty_name: USTECH (Nasdaq 100) Tick Data 2021-2026
size_categories:
- 100M<n<1B
task_categories:
- time-series-forecasting
- tabular-regression
tags:
- finance
- indices
- nasdaq
- nasdaq100
- ustech
- tech-stocks
- tick-data
- high-frequency
- backtesting
configs:
- config_name: default
data_files:
- split: train
path: year=*/month=*/*.parquet
USTECH (Nasdaq 100) Tick Data (May 2021 – May 2026)
Five years of tick-by-tick bid/ask quotes for the Nasdaq 100 index CFD (a.k.a. USTECH, US Tech 100) at millisecond resolution. Sourced from Dukascopy via Tickstory.
Dataset details
| Instrument | USTECH (Nasdaq 100 Index CFD) |
| Period | 2021-05-25 → 2026-05-24 |
| Granularity | Tick (millisecond timestamps) |
| Rows | ~376 million |
| Format | Apache Parquet (Snappy) |
| Partitioning | Hive-style by year/month |
Schema
| Column | Type | Description |
|---|---|---|
timestamp |
timestamp[ms] |
UTC tick time, millisecond precision |
bid_price |
float64 |
Best bid price (index points) |
ask_price |
float64 |
Best ask price (index points) |
bid_volume |
float64 |
Bid-side volume |
ask_volume |
float64 |
Ask-side volume |
Quick start
from datasets import load_dataset
ds = load_dataset("CarlosSilva1/ustech-ticks", split="train", streaming=True)
for row in ds.take(5):
print(row)
Or with pandas:
import pandas as pd
df = pd.read_parquet(
"https://huggingface.co/datasets/CarlosSilva1/ustech-ticks/resolve/main/"
"year=2024/month=03/USTECH-2024-03-part0001.parquet"
)
print(df.head())
Typical use cases
- Backtesting intraday Nasdaq strategies
- Correlation analysis vs. S&P 500, gold, VIX
- Tech sector volatility regimes (FOMC, earnings, CPI)
- Pair trading USTECH vs US500 (tech beta plays)
- ML/time-series forecasting on high-frequency tech data
Related datasets
- CarlosSilva1/xauusd-ticks - Gold/USD
- CarlosSilva1/us500-ticks - S&P 500
License
CC-BY-4.0. Provided as-is for research and educational purposes. Not investment advice.