CarlosSilva1/xauusd-ticks

XAU/USD Tick Data (May 2021 – May 2026)

Five years of tick-by-tick bid/ask quotes for gold against the US dollar (XAU/USD) at millisecond resolution. Suitable for backtesting high-frequency strategies, market-microstructure research, and time-series modeling.

Dataset details

Instrument	XAU/USD (spot gold)
Period	2021-05-24 → 2026-05-24
Granularity	Tick (millisecond timestamps)
Rows	~hundreds of millions
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 in USD
ask_price	float64	Best ask price in USD
bid_volume	float64	Bid-side volume
ask_volume	float64	Ask-side volume

Layout

year=2021/
├── month=05/XAUUSD-2021-05-part0000.parquet
├── month=05/XAUUSD-2021-05-part0001.parquet
├── month=06/XAUUSD-2021-06-part0000.parquet
└── ...
year=2022/
└── ...
year=2026/
└── month=05/XAUUSD-2026-05-part000N.parquet

Hive partitioning lets you read a single month without scanning the rest:

import pyarrow.dataset as ds
dataset = ds.dataset(".", partitioning="hive")
march_2024 = dataset.to_table(filter=(ds.field("year") == 2024) & (ds.field("month") == 3))

Quick start

Hugging Face datasets library

from datasets import load_dataset

ds = load_dataset("CarlosSilva1/xauusd-ticks", split="train", streaming=True)
for row in ds.take(5):
    print(row)

Streaming mode avoids downloading the whole dataset upfront.

Direct Parquet with pandas

import pandas as pd

# Read a single month part
df = pd.read_parquet(
    "https://huggingface.co/datasets/CarlosSilva1/xauusd-ticks/resolve/main/"
    "year=2024/month=03/XAUUSD-2024-03-part0001.parquet"
)
print(df.head())

Bulk download via huggingface_hub

from huggingface_hub import snapshot_download

local_path = snapshot_download(
    repo_id="CarlosSilva1/xauusd-ticks",
    repo_type="dataset",
)
print("Downloaded to:", local_path)

Typical use cases

• Backtesting intraday and high-frequency trading strategies
• Studying bid-ask spread dynamics for gold
• Training time-series forecasting models (transformers, LSTM, N-BEATS, etc.)
• Volatility and market microstructure research
• Calibrating execution simulators

Source and provenance

Aggregated tick feed reconstructed from broker data for personal backtesting research. Timestamps are in UTC. Prices reflect the broker feed at the time of capture and may differ slightly from other venues.

License

Creative Commons Attribution 4.0 (CC-BY-4.0).

You may use, share and adapt the data, including commercially, provided you give appropriate credit. Citation suggestion:

Silva, C. (2026). XAU/USD Tick Data (May 2021 – May 2026)
[Data set]. Hugging Face. https://huggingface.co/datasets/CarlosSilva1/xauusd-ticks

Disclaimer

This dataset is provided as-is for research and educational purposes. It is not investment advice. Past price action is not indicative of future performance. The author is not responsible for any losses incurred from strategies developed using this data.