Articlegold2019

OBVIOUS AND HIDDEN FEATURES OF CORPORATE DEFAULT IN BANKRUPTCY MODELS

13 citations0/0 files storedJournal of Business Economics and Management

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Forecasting Techniques and Applications

Abstract

The aim of this article is to prove the key role of the structure of the research sample used for accuracy determining on the accuracy of bankruptcy models. The creators of these models report the accuracy usually in the range of 60 to 90%. The authors of this article claim that these values are inaccurate and misleading. The real I. type error should be detected on a sample where obvious features of financial default were eliminated. The research tested more than 1200 of thriving businesses and also 270 businesses in future bankruptcy. The research has determined real current accuracy of selected three bankruptcy models on the standard sample of Czech businesses amounting 67.77%, 62.27% and 74.36%. This confirmed hypothesis no. 1, which says that actual accuracy of bankruptcy model is lower than original accuracy indicated by model makers. An accuracy of 58.70%, 61.59% and 65.94% was measured on a sample where businesses with obvious features of financial distress were eliminated. Due to the modification of the test sample, the order of accuracy has changed. This confirmed hypothesis no. 2. The Index of Karas and Reznakova reached the highest overall accuracy of 80.31% including incorrect prediction of bankruptcy also.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 13 citations exist upstream.

References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions 1985ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS 2005Emphasis on Pro Forma versus GAAP Earnings in Quarterly Press Releases: Determinants, SEC Intervention, and Market Reactions 1991Neural network models and the prediction of bank bankruptcy 2011Impression management and retrospective sense‐making in corporate narratives 2004A threshold-varying artificial neural network approach for classification and its application to bankruptcy prediction problem

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.