FinSeer StockLLM Open-source Large Model - Freely Empower Precise Financial Time-series Prediction

Stockllm

Developed by TheFinAI

FinSeer StockLLM is an open-source 1-billion-parameter large language model specifically designed for financial time series forecasting, utilizing a Retrieval-Augmented Generation (RAG) framework.

Large Language Model

Transformers

English#Financial Time Series Forecasting #Retrieval-Augmented Generation #1 Billion Parameters

Downloads 29

Release Time : 3/15/2025

Model Overview

This model is the first core of a Retrieval-Augmented Generation (RAG) framework specifically designed for financial time series forecasting, aiming to improve the accuracy of financial time series predictions.

Model Features

Retrieval-Augmented Generation (RAG) Framework

Adopts the RAG framework, combining retrieval and generation capabilities to enhance the accuracy of financial time series forecasting.

Open Source Model

The model is fully open-source, facilitating research and educational purposes.

Designed for Finance

The model is specifically optimized for financial time series forecasting tasks.

Model Capabilities

Financial Time Series Forecasting

Retrieval-Augmented Generation

Time Series Analysis

Use Cases

Financial Forecasting

Stock Price Prediction

Utilize the model to predict future trends in stock prices.

Market Trend Analysis

Analyze financial market trends and provide predictive recommendations.

🚀 FinSeer Model Card

FinSeer is a retrieval - augmented generation (RAG) framework for financial time - series forecasting, leveraging a fine - tuned large language model.

🚀 Quick Start

This README provides detailed information about the FinSeer model, including its type, related resources, disclaimers, and citation details.

✨ Features

Specialized for Finance: Specifically designed for financial time - series forecasting.
Retrieval - Augmented Generation: Utilizes a retrieval - augmented generation (RAG) framework.
Open - Source: An open - source fine - tuned 1B large language model as the backbone.

📚 Documentation

Model details

Property	Details
Model Type	StockLLM is an open - source fine - tuned 1B large language model as the backbone of our first retrieval - augmented generation (RAG) framework specifically designed for financial time - series forecasting.
Paper or resources for more information	https://arxiv.org/pdf/2502.05878

Disclaimer

⚠️ Important Note

This repository and its contents are provided for academic and educational purposes only. None of the material constitutes financial, legal, or investment advice. No warranties, express or implied, are offered regarding the accuracy, completeness, or utility of the content. The authors and contributors are not responsible for any errors, omissions, or any consequences arising from the use of the information herein. Users should exercise their own judgment and consult professionals before making any financial, legal, or investment decisions. The use of the software and information contained in this repository is entirely at the user's own risk.

By using or accessing the information in this repository, you agree to indemnify, defend, and hold harmless the authors, contributors, and any affiliated organizations or persons from any and all claims or damages.

Citaion

@misc{xiao2025enhancingfinancialtimeseriesforecasting,
      title={Enhancing Financial Time - Series Forecasting with Retrieval - Augmented Large Language Models}, 
      author={Mengxi Xiao and Zihao Jiang and Lingfei Qian and Zhengyu Chen and Yueru He and Yijing Xu and Yuecheng Jiang and Dong Li and Ruey - Ling Weng and Min Peng and Jimin Huang and Sophia Ananiadou and Qianqian Xie},
      year={2025},
      eprint={2502.05878},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2502.05878}, 
}

📄 License

This project is licensed under the MIT license.

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