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FinBen · ACL18 (stock movement) (long-context)

📄 Paper · 💻 Code · 🏆 Leaderboard · 🌐 The Fin AI

Part of FinBen — FinBen: A Holistic Financial Benchmark for Large Language Models (arXiv:2402.12659).

Long-context variant of flare-sm-acl in FinBen.

Task stock movement prediction
Original dataset ACL18 (Xu and Cohen, 2018)
Evaluation metric Accuracy, MCC
Source license MIT License
Language en

Quick Start

from datasets import load_dataset

ds = load_dataset("TheFinAI/en-sm-acl-long", split="test")
print(ds[0])

Example prompt

### Input
Examine the data to deduce if the (adjusted) closing price of $MSFT will boost or lower at 2015-04-02. Kindly confirm either Rise or Fall.
Context: stock,date,open,high,low,close,adj_close,volume
SNY,2015-02-04,46.16,47.0,46.0,47.0,33.27,3341300
SNY,2015-02-05,48.07,48.7,47.89,48.42,34.28,2380600
SNY,2015-02-06,48.16,48.5,47.84,48.05,34.01,7486100
SNY,2015-02-09,47.48,48.13,47.48,47.8,33…

Dataset Structure

Split Rows
train 9,934
validation 100
test 2,509
Field Description
index
query Full instruction prompt given to the model
answer Gold answer / label text
choices Label space
gold Index of the gold label in choices

License

The original data is released under MIT License (FinBen paper, Table 2).

Citation

Please cite FinBen and the original dataset (ACL18 (Xu and Cohen, 2018)):

@misc{xie2024finbenholisticfinancialbenchmark,
      title={FinBen: A Holistic Financial Benchmark for Large Language Models},
      author={Qianqian Xie and Weiguang Han and Zhengyu Chen and Ruoyu Xiang and Xiao Zhang and Yueru He and Mengxi Xiao and Dong Li and Yongfu Dai and Duanyu Feng and Yijing Xu and Haoqiang Kang and Ziyan Kuang and Chenhan Yuan and Kailai Yang and Zheheng Luo and Tianlin Zhang and Zhiwei Liu and Guojun Xiong and Zhiyang Deng and Yuechen Jiang and Zhiyuan Yao and Haohang Li and Yangyang Yu and Gang Hu and Jiajia Huang and Xiao-Yang Liu and Alejandro Lopez-Lira and Benyou Wang and Yanzhao Lai and Hao Wang and Min Peng and Sophia Ananiadou and Jimin Huang},
      year={2024},
      eprint={2402.12659},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2402.12659},
}
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