| task_categories: | |
| - reinforcement-learning | |
| tags: | |
| - finance | |
| - quantitative-trading | |
| # Data4Fin | |
| This repository contains the multi-indicator dataset presented in the paper [QTMRL: An Agent for Quantitative Trading Decision-Making Based on Multi-Indicator Guided Reinforcement Learning](https://huggingface.co/papers/2508.20467). | |
| The dataset consists of 23 years of S&P 500 daily OHLCV data (2000-2022) for 16 representative stocks across 5 sectors. The raw data is enriched with trend, volatility, and momentum indicators to capture market dynamics for reinforcement learning-based trading agents. | |
| - **Paper:** [QTMRL: An Agent for Quantitative Trading Decision-Making Based on Multi-Indicator Guided Reinforcement Learning](https://huggingface.co/papers/2508.20467) | |
| - **Code:** [GitHub - QTMRL](https://github.com/ChenJiahaoJNU/QTMRL) | |
| ## Sample Usage | |
| You can download the dataset using the Hugging Face CLI: | |
| ```bash | |
| huggingface-cli download --repo-type dataset Changahou/Data4Fin Data4Fin.csv --local-dir ./ | |
| ``` | |
| ## Citation | |
| ```bibtex | |
| @article{Chenjh2025QTMRL, | |
| title={QTMRL: An Agent for Quantitative Trading Decision-Making Based on Multi-Indicator Guided Reinforcement Learning}, | |
| author={Xiangdong Liu, Jiahao Chen}, | |
| journal={arXiv preprint arXiv:2508.20467}, | |
| year={2025} | |
| } | |
| ``` |