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Chinese Journal of Management Science ›› 2019, Vol. 27 ›› Issue (7): 23-34.doi: 10.16381/j.cnki.issn1003-207x.2019.07.003

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Forecasting Financial Distress of Listed Companies with Textual Content of the Information Disclosure: A Study based MD&A in Chinese Annual Reports

CHEN Yi-yun   

  1. School of Economics and Commerce, South China University of Technology, Guangzhou 510006, China
  • Received:2018-01-03 Revised:2018-08-10 Online:2019-07-20 Published:2019-08-01

Abstract: Traditionally the prediction of financial distress is based on the quantitative information such as accounting data and market trading data, which has been proved as inefficient with a series of debt crisis after the subprime mortgage crisis. Quantitative data reflect the financial position of the company directly, while the qualitative textual content in the information diclosure reports is an important supplement, which may provide new clues for the prediction of financial distress since the wording and style may change with the financial postion of the company.
With various studies on the automatic textual analysis in the field of corporate finance, mainly on the stock market related issues, bag of words methods are applied to measure the management tone reflected in the Management Discussion & Analysis (MD&A) of Chinese annual reports, and test whether the management tone can provide additional information for financial distress prediction empirically. With different dictionaries, word segmentation tools and term weighting methods, a series of management tone variables are created, and added to various traditional financial distress prediction models.
Taking the special treatment (ST) as the symbol of financial distress, a sample of 2024 Chinese listed companies is selected.The emprical results from estimations with discrete-time hazard model, information content tests, in-sample and out-of-sample forecasting indicate:(1) management tone can provide new information for the financial distress prediction, and improve the fitness and predictive power of the financial distress prediction models; (2) management tone is an important supplement to the quantitative financial data, which have not been fully reflected in the market price; (3) the negative tone can provide more information than the net tone reflected in the textual content; (4) the tone or sentiment analysis of financial text should be based on the dictionaries created on similar text, but not the list of words from other non financial fields.

Key words: financial distress, textual analysis, management tone

CLC Number: