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Corporate Bankruptcy Prediction

Corporate Bankruptcy Prediction

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Bankruptcy prediction is one of the most important research areas in corporate finance. Bankruptcies are an indispensable element of the functioning of the market economy, and at the same time generate significant losses for stakeholders. Hence, this book was established to collect the results of research on the latest trends in predicting the bankruptcy of enterprises. It suggests models developed for different countries using both traditional and more advanced methods. Problems connected with predicting bankruptcy during periods of prosperity and recession, the selection of appropriate explanatory variables, as well as the dynamization of models are presented. The reliability of financial data and the validity of the audit are also referenced. Thus, I hope that this book will inspire you to undertake new research in the field of forecasting the risk of bankruptcy.

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Keywords

  • Artificial Neural Networks
  • audit expectation gap
  • bagging
  • bankruptcy
  • bankruptcy model
  • bankruptcy prediction
  • bankruptcy risk
  • boosting
  • chapter 11
  • citation mining
  • Classification
  • company performance
  • corporate bankruptcy
  • corporate failure
  • credit risk modelling
  • Czech Republic
  • decision trees
  • default
  • Economics, finance, business & management
  • ensemble classifiers
  • European large companies
  • failure
  • financial distress
  • financial ratios
  • Forecasting
  • forecasting methods
  • Fuzzy sets
  • insolvency
  • ISA 701
  • key audit matters
  • literature review
  • manufacturing insolvency
  • Materiality
  • Meta-analysis
  • models predicting financial distress
  • neural networks
  • payment defaults
  • phases of economic cycle
  • Poland
  • prediction
  • principal component analysis
  • rating systems
  • regression count
  • scoring models
  • stacking
  • support vector machine
  • tax arrears

Links

DOI: 10.3390/books978-3-03928-912-7

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