| Abstract [eng] |
This master thesis consists of 103 pages, 25 charts, 9 pictures The main purpose of this master thesis is to determine the suitability of bankruptcy forecasting models for Lithuanian construction sector companies in an economic shock environment. The work consists of three main parts; the analysis of literature, the research and its results, conclusion and recommendations. The literature analysis reviews the significance and benefits of bankruptcy research, analyzes the relationship between bankruptcy forecasting and financial indicators, bankruptcy forecasting models and their classification. Also the results of research by Lithuanian and foreign authors on this topic are reviewed. It has been observed in scientific studies that it is appropriate for each sector to create and use a bankruptcy forecasting model adapted only to it. Research conducted in the construction sector found that it is suggested to abandon the application of the Zavgren model for bankruptcy forecasting of companies in the construction sector, and to use the Taffler and Tisshaw, Springate, Liss models for bankruptcy forecasting, as profitability indicators are more significantly evaluated in them. It should be noted that a properly selected model can provide the company with a lot of information, while an improperly selected model can provide false information and thus cause damage. After predicting the bankruptcy of construction companies using the linear discriminant Altman, Lis, Taffler and Tisshaw, Springate and logistic regression Chesser methods, the following results were determined: The Altman model shows that the obtained Z values indicate a high risk of bankruptcy for almost all companies a year before bankruptcy. It is assumed that this corresponds to the real situation, since the accuracy of the forecasting model is 95 percent. In general, two models are distinguished in the result of this work, i.e. Altman and Springate, who most accurately calculate the probability of bankruptcy. However, the reliability of these models was clearly affected by the economic shock situation, as the reliability indicators are noticeably lower during the COVID-19 period. The conclusions and recommendations summarize the key concepts of the literature review and the results of the research conducted, which may be useful for identifying the probability of bankruptcy in the event of an economic shock such as in the context of COVID-19. |
