0000000001219852

AUTHOR

Peter Martens

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Towards Bankruptcy Prediction: Deep Sentiment Mining to Detect Financial Distress from Business Management Reports

2018

Due to their disclosure required by law, business management reports have become publicly available for a large number of companies, and these reports offer the opportunity to assess the financial health or distress of a company, both quantitatively from the balance sheets and qualitatively from the text. In this paper, we analyze the potential of deep sentiment mining from the textual parts of business management reports and aim to detect signals for financial distress. We (1) created the largest corpus of business reports analyzed qualitatively to date, (2) defined a non-trivial target variable based on the so-called Altman Z-score, (3) developed a filtering of sentences based on class-co…

050208 financeComputer science05 social sciencesSentiment analysis050201 accountingData scienceTask (project management)VisualizationDistressBankruptcy0502 economics and businessTask analysisBankruptcy predictionBalance sheet2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA)
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