Financial Risk Prediction of Listed Companies based on Text and Financial Data

Xu Wei, Yonghui Chen

2022

Abstract

This paper uses the relevant financial data of 4348 A-share listed companies from 2010 to 2019 and the discussion and analysis of operation in the annual report as the research sample, and uses the Pytorch framework to build a neural network model to predict whether the listed companies fall into financial crisis. The experimental results show that when text data is combined with traditional financial index data, the prediction accuracy of the deep learning model can reach about 85%, which can significantly improve the accuracy of financial risk prediction compared with using only financial data.

Paper Citation

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,
TI - Financial Risk Prediction of Listed Companies based on Text and Financial Data
SN - 978-989-758-593-7
AU - Wei X.
AU - Chen Y.
PY - 2022
SP - 240
EP - 244
DO - 10.5220/0011172500003440

in Harvard Style

Wei X. and Chen Y. (2022). Financial Risk Prediction of Listed Companies based on Text and Financial Data. In Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM, ISBN 978-989-758-593-7, pages 240-244. DOI: 10.5220/0011172500003440

in Bibtex Style

@conference{bdedm22,
author={Xu Wei and Yonghui Chen},
title={Financial Risk Prediction of Listed Companies based on Text and Financial Data},
booktitle={Proceedings of the International Conference on Big Data Economy and Digital Management - Volume 1: BDEDM,},
year={2022},
pages={240-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011172500003440},
isbn={978-989-758-593-7},
}