A Study on the Insolvency Prediction Model for Korean Shipping Companies

Kim, Myoung-Hee

doi:2024.48.2.109

J Navig Port Res > Volume 48(2); 2024 > Article

Article

Journal of Navigation and Port Research 2024;48(2):109-115.
DOI: https://doi.org/10.5394/KINPR.2024.48.2.109 Published online April 30, 2024.

A Study on the Insolvency Prediction Model for Korean Shipping Companies

Myoung-Hee Kim

Lecturer, Department of Shinpping Management, National Korea Maritime & Ocean University, Busan, Korea

Correspondence: Myoung-Hee Kim, Tel: 051)410-4380,
Email: kmusm@kmou.ac.kr

Received: 15 April 2024 • Revised: 19 April 2024 • Accepted: 26 April 2024

Abstract

To develop a shipping company insolvency prediction model, we sampled shipping companies that closed between 2005 and 2023. In addition, a closed company and a normal company with similar asset size were selected as a paired sample. For this study, data of a total of 82 companies, including 42 closed companies and 42 general companies, were obtained. These data were randomly divided into a training set (2/3 of data) and a testing set (1/3 of data). Training data were used to develop the model while test data were used to measure the accuracy of the model. In this study, a prediction model for Korean shipping insolvency was developed using financial ratio variables frequently used in previous studies. First, using the LASSO technique, main variables out of 24 independent variables were reduced to 9. Next, we set insolvent companies to 1 and normal companies to 0 and fitted logistic regression, LDA and QDA model. As a result, the accuracy of the prediction model was 82.14% for the QDA model, 78.57% for the logistic regression model, and 75.00% for the LDA model. In addition, variables ‘Current ratio’, ‘Interest expenses to sales’, ‘Total assets turnover’, and ‘Operating income to sales’ were analyzed as major variables affecting corporate insolvency.

Key Words: Korean shipping companies, insolvency prediction, financial ratio analysis, logistic regression, LDA, QDA.