基于TEI@I方法论的企业财务风险预警模型研究

摘要/Abstract

摘要： 在当前经济面临较大下行压力的背景下，企业频繁出现业绩暴雷，如何"识雷防雷"进而重塑投资者信心、防范金融风险成为迫切需要研究的现实问题。本文基于TEI@I方法论的理论框架，集成文本挖掘和深度学习构建企业财务风险预警模型。基于新的视角，提出了融合卷积神经网络和长短期记忆网络的财务风险预警动态建模方法，并以中国信息服务业上市公司为样本开展实证研究。由于在预测模型中有效地考虑了影响企业财务危机的各项财务因素和非财务因素，因此对企业未来财务困境的预测效果明显优于其他模型。该方法具有较好的应用推广性，对于政府和投资者及时掌握企业经营动态、降低投资风险以及防范金融危机具有积极的辅助决策价值。

关键词: 财务风险预警, TEI@I方法论, 文本挖掘, 卷积神经网络, 长短期记忆网络

Abstract: With great economic downward pressure, many companies are facing performance thunder frequently. How to identify and guard against ‘traps’, reshape investors' confidence and prevent financial crisis has become a practical and urgent task. With the theoretical framework of TEI@I methodology, this paper integrates text mining and deep learning to construct a prediction model of enterprise financial crisis. From a new perspective, a dynamic modeling method for financial distress prediction which is based on convolutional neural networks and long-term and short-term memory networks is proposed. The empirical research is carried out with listed Chinese companies which in the information service industry as samples. With the effective considering of financial factors and non-financial factors that affect financial crisis of enterprises, the forecasting model has much better forecasting effect than others. This method can be applied and promoted easily, and has positive value for government and investors if they need to grasp the business dynamics, reduce investment risks and prevent financial crisis.

Key words: financial risk warning, TEI@I methodology, text mining, convolutional neural network, short-term memory network

肖毅, 熊凯伦, 张希. 基于TEI@I方法论的企业财务风险预警模型研究[J]. 管理评论, 2020, 32(7): 226-235.

Xiao Yi, Xiong Kailun, Zhang Xi. Enterprise Financial Risk Early Warning Model Based on TEI@I Methodology[J]. Management Review, 2020, 32(7): 226-235.

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