Models for Predicting the Probability of Bankruptcy: Applying in Construction Companies
https://doi.org/10.26794/2408-9303-2021-8-1-13-23
Abstract
The paper examines some foreign and domestic methods of forecasting bankruptcy of enterprises in order to apply them in the largest construction organizations in Russia. The empirical basis of the study is the construction companies that are comparable in size, revenue, and market share. Their annual financial statements preceding the analysis are the information base of calculations. The quality of forecasts has been checked on independent indicators’ calculations of financial analysis, as well as using data from financial markets and share prices under studied companies. The result of the research is the selection of models that gives the most correct forecast of the financial situation of a company in the construction industry. It has been also revealed that models for predicting financial insolvency of enterprises has not been able to assess changes in financial stability in the short term. Therefore, the author compares calculation results with data of financial markets. As a result, it was found that models which demonstrate the greatest predictive ability correlate with the results of independent financial analysis, as well as with data of financial markets regarding the share price dynamics of construction companies. The paper provides recommendations on approaches to choosing models for analyzing the probability of bankruptcy and can be useful for specialists of financial and analytical services to predict the financial insolvency of construction business.
About the Author
A. V. Voiko
Financial University
Russian Federation
Russian Federation
Aleksandr V. Voiko — Cand. Sci. (Econ.), Associate Professor, Department of Corporate Finance and Corporate Governance
Moscow
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Review
For citations:
Voiko A.V. Models for Predicting the Probability of Bankruptcy: Applying in Construction Companies. Accounting. Analysis. Auditing. 2021;8(1):13-23. (In Russ.) https://doi.org/10.26794/2408-9303-2021-8-1-13-23
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