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# PriceSeer Dataset

## Introduction
PriceSeer was designed to provide a professional framework for LLMs stock prediction, including external and internal data. For detailed information about how to collect it and how to use it, please refer to: https://arxiv.org/abs/2601.06088

## Stock Coverage
This dataset collected totally 110 stocks across 11 sectors in the U.S. stock market, 10 stocks per sector, covers all industries in the market. The stocks are: 

```

"Technology": ["NVDA", "MSFT", "AAPL", "AVGO", "ORCL", "PLTR", "AMD", "CSCO", "IBM", "CRM"],

"Financial Services": ["BRK-B", "JPM", "BAC", "MA", "V", "MS", "C", "WFC", "GS", "AXP"],

"Consumer Cyclical": ["AMZN", "TSLA", "HD", "MCD", "NKE", "LOW", "BKNG", "TJX", "DASH", "MELI"],

"Communication Services": ["GOOG", "META", "NFLX", "CMCSA", "DIS", "APP", "SPOT", "T", "VZ", "TMUS"],

"Healthcare": ["UNH", "JNJ", "ISRG", "MRK", "LLY", "ABT", "DHR", "ABBV", "TMO", "AMGN"],

"Industrials": ["UNP", "GEV", "CAT", "HON", "RTX", "DE", "LMT", "GE", "ETN", "BA"],

"Consumer Defensive": ["PG", "KO", "PEP", "COST", "WMT", "MDLZ", "CL", "MO", "PM", "MNST"],

"Energy": ["XOM", "CVX", "COP", "WMB", "EPD", "EOG", "PSX", "KMI", "ET", "MPC"],

"Basic Materials": ["LIN", "SHW", "FCX", "SCCO", "NEM", "CRH", "APD", "ECL", "CTVA", "VMC"],

"Utilities": ["NEE", "DUK", "SO", "EXC", "AEP", "SRE", "XEL", "VST", "D", "CEG"],

"Real Estate": ["WELL", "PLD", "AMT", "EQIX", "SPG", "DLR", "O", "PSA", "CBRE", "CCI"]

```

## Data Type
There are 4 data types in the dataset: 

- **Raw data**: the historical stock data in the past 1 year were directly downloaded from open source financial website, including opening price, closing price, daily highest price, daily lowest price, and trading volume. 

- **Financial indicators**: professional financial indicators that can reflect the price trend are calculated based on the raw data. The indicators used are: Simple Return & Log Return, Simple Moving Average (SMA), Relative Strength Index (RSI), Moving Average Convergence/Divergence (MACD) & Signal Line, and Bollinger Bands (BB). 

- **News data**: top 10 the most relavant news on Google research about each stock were downloaded. It consists of the publish date, source, news title, and content.

- **Fake news data**: we generate fake news by manipulating numbers, introducing fictional elements, and employing superlative language in the news data, to introduce perturbations.


## Citation
If you find our work interesting, please feel free to cite our dataset:

```

@misc{liang2025priceseerevaluatinglargelanguage,

      title={PriceSeer: Evaluating Large Language Models in Real-Time Stock Prediction}, 

      author={Bohan Liang and Zijian Chen and Qi Jia and Kaiwei Zhang and Kaiyuan Ji and Guangtao Zhai},

      year={2025},

      eprint={2601.06088},

      archivePrefix={arXiv},

      primaryClass={q-fin.ST},

      url={https://arxiv.org/abs/2601.06088}, 

}

```