Predicting financial distress: the power of sentiment words in business plans
研究利用中国上市公司2001-2022年数据，提出结合商业计划文本情感与财务数据的新框架，通过‘转型’、‘低成本’等关键词和积极语气指标，提升短期和长期财务困境预测准确性。
Predicting financial distress is vital for banks, regulators, and investors to manage risks and make informed decisions. However, the specific role of business plans in companies’ annual reports has received limited attention. This study introduces a new prediction framework that combines insights from business plans with financial and non-financial data. A key innovation of the framework is its weighting mechanism for tone variables, which links them directly to financial distress status. Using data from Chinese listed companies (2001–2022), the model shows improved predictive performance over short-term and long-term timeframes. Key indicators include words like ‘transformation,’ ‘low cost,’ and ‘enhancement,’ alongside measures of positive tone that capture optimistic language in business plans. The framework outperforms other advanced models, offering a practical tool for identifying financially troubled firms and supporting timely interventions.