Andere Kunden interessierten sich auch für
![The Prediction and Optimization of Microwave Field Distribution in MLS]( "The Prediction and Optimization of Microwave Field Distribution in MLS")
The Prediction and Optimization of Microwave Field Distribution in MLS23,99 €![Rainfall Prediction using Machine Learning Algorithm]( "Rainfall Prediction using Machine Learning Algorithm")
Rainfall Prediction using Machine Learning Algorithm26,99 €![The prediction of Heterosis]( "The prediction of Heterosis")
The prediction of Heterosis32,99 €![Drawbar Performance Prediction of Agricultural Tractors]( "Drawbar Performance Prediction of Agricultural Tractors")
Drawbar Performance Prediction of Agricultural Tractors51,99 €![The prospects of production of perennial grasses in Ukraine]( "The prospects of production of perennial grasses in Ukraine")
The prospects of production of perennial grasses in Ukraine26,99 €![Water quality prediction of aqua ponds]( "Water quality prediction of aqua ponds")
Water quality prediction of aqua ponds46,99 €![PREDICTION OF CROP YIELD USING DEEP LEARNING]( "PREDICTION OF CROP YIELD USING DEEP LEARNING")
PREDICTION OF CROP YIELD USING DEEP LEARNING29,99 €
Agriculture is one of the most crucial industries in Ukraine and the distinctive feature of this sector is a heightened threat of bankruptcy. The aim of this research is to determine whether bankruptcy prediction models are applicable in the agricultural industry of Ukraine. Besides that, the study indicates the accuracy of each model. Additionally, this research focuses on answering the question of what are the main factors that lead a firm to insolvency. The data of bankrupt and non-bankrupt agricultural firms are used to estimate the prediction ability. The financial statements for analysis are collected from the Orbis Europe database. The paired sample consists of 20 Ukrainian agricultural enterprises with similar peers. In order to evaluate the relevancy of using each model, the dichotomous classification test is applied. To predict insolvency, William H. Beaver's univariable, Edward I. Altman's Z-score and Davydova and Belikov's models are used. The companies are studied within five years before bankruptcy from the period of 2017- 2018. The most accurate model is studied using the variance analysis.