qlib_csi300 / README.md
nielsr's picture
nielsr HF Staff
Link dataset to paper and official repositories
f127f7c verified
|
raw
history blame
2.58 kB
metadata
language:
  - en
  - zh
license: apache-2.0
task_categories:
  - time-series-forecasting
pretty_name: QuantaAlpha Qlib CSI300 Dataset
tags:
  - finance
  - quantitative
  - qlib
  - factor
  - time-series
arxiv: 2602.07085

QuantaAlpha Qlib CSI300 Dataset

Project Page | Paper | GitHub

Qlib market data and pre-computed HDF5 files for QuantaAlpha factor mining (A-share, CSI 300).

Dataset description

Filename Description
daily_pv.h5 Adjusted daily price and volume data.
daily_pv_debug.h5 Debug subset (smaller) of price-volume data.

How to load from Hugging Face

from huggingface_hub import hf_hub_download
import pandas as pd

# Download a file from this dataset
path = hf_hub_download(
    repo_id="QuantaAlpha/qlib_csi300",
    filename="daily_pv.h5",
    repo_type="dataset"
)
df = pd.read_hdf(path, key="data")

Note: The key is always "data" for all HDF5 files in this dataset.

How to read the files locally

If you have already downloaded the files:

import pandas as pd
df = pd.read_hdf("daily_pv.h5", key="data")

Field description (daily price and volume)

Field Description
open Open price of the stock on that day
close Close price of the stock on that day
high High price of the stock on that day
low Low price of the stock on that day
volume Trading volume on that day
factor Adjusted factor value

Citation

If you find QuantaAlpha useful in your research, please cite the following work:

@misc{han2026quantaalphaevolutionaryframeworkllmdriven,
      title={QuantaAlpha: An Evolutionary Framework for LLM-Driven Alpha Mining}, 
      author={Jun Han and Shuo Zhang and Wei Li and Zhi Yang and Yifan Dong and Tu Hu and Jialuo Yuan and Xiaomin Yu and Yumo Zhu and Fangqi Lou and Xin Guo and Zhaowei Liu and Tianyi Jiang and Ruichuan An and Jingping Liu and Biao Wu and Rongze Chen and Kunyi Wang and Yifan Wang and Sen Hu and Xinbing Kong and Liwen Zhang and Ronghao Chen and Huacan Wang},
      year={2026},
      eprint={2602.07085},
      archivePrefix={arXiv},
      primaryClass={q-fin.ST},
      url={https://arxiv.org/abs/2602.07085}, 
}