Welcome to the MarketProphet-SP500MediNews dataset, a groundbreaking resource designed for forecasting the S&P 500 index trends in the healthcare sector.
This dataset marks a significant shift from traditional financial datasets by:
- Multimodal Data Integration: Merging quantitative stock data with qualitative news and policy documents for a more comprehensive market view.
- Market-Influential Stock Selection: Prioritizing stocks with high trading volume and significant impact on the market.
- Filling the Research Gap: Unlike prior datasets focusing on individual stocks, this dataset provides insights into the S&P 500 index in the medical sector, a previously unaddressed domain.
@article{xuemarketprophet, title={MarketProphet-SP500MediNews: Forecasting Healthcare Sector S&P 500 Index Trends Using Data from 22 Key Stocks and Medical News Insights}, author={Xue, Haochen and Liang, Kaiyu and Zhang, Chong and Wang, Hongchen and Zhu, Xiaojun and Jin, Xiaobo} }
- Trading data from 22 select healthcare stocks, chosen for their market impact.
- S&P 500 healthcare sector index data.
- Note: News and policy information to be included in future updates.
Clone the repository:git clone https://github.com/tiuxuxsh76075/MarketProphet-SP500MediNews/tree/main
Ideal for data scientists, financial analysts, and policy researchers focusing on advanced time series forecasting in the healthcare market.
Look out for updates integrating daily news articles and policy information, enhancing the dataset's depth and predictive accuracy.
Contributed by Haochen Xue1, Kaiyu Liang2, Chong Zhang1, Mingyu Jin3, Hongchen Wang1, Zile Huang1, Zihong Luo1, Chengzhi Liu1, Xiaojun Zhu2, Xiaobo Jin1
1School of Advanced Technology, Xi'an Jiaotong Liverpool University
2School of Mathematics and Physics, Xi'an Jiaotong Liverpool University
3Department of Electrical and Computer Engineering, Northwestern University
@article{xuemarketprophet,
title={MarketProphet-SP500MediNews: Forecasting Healthcare Sector S\&P 500 Index Trends Using Data from 22 Key Stocks and Medical News Insights},
author={Xue, Haochen and Liang, Kaiyu and Zhang, Chong and Wang, Hongchen and Zhu, Xiaojun and Jin, Xiaobo}
}