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FinBen · CIKM18 (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-cikm in FinBen.

Task stock movement prediction
Original dataset CIKM18 (Wu et al., 2018)
Evaluation metric Accuracy, MCC
Source license Public
Language en

Quick Start

from datasets import load_dataset

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

Example prompt

Scrutinize the data to envisage if the (adjusted) closing price of $GS will swell or contract at 2017-07-27. Please affirm either Rise or Fall.
Context: stock,date,open,high,low,close,adj_close,volume
GE,2017-05-31,164.11,164.78,163.27,164.41,152.89,5930217
GE,2017-06-01,165.2,167.42,165.14,166.46,154.79,5393524
GE,2017-06-02,167.36,167.78,165.86,167.42,155.68,6162876
GE,2017-06-05,167.54,168.56,1…

Dataset Structure

Split Rows
train 2,962
validation 100
test 766
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 paper lists the original data as publicly available without a specific license (FinBen paper, Table 2); refer to the original source for its terms.

Citation

Please cite FinBen and the original dataset (CIKM18 (Wu et al., 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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