Bankruptcy Prediction Analysis: A Case Study of Retail Companies in Indonesia
Available Online 15 September 2020.
- https://doi.org/10.2991/aebmr.k.200915.073How to use a DOI?
- bankruptcy, Altman Z score, Springate, Zmijewski, retail companies
- This research aims to predict bankruptcy on retail companies in Indonesia. A total sample consist of 22 retail companies in Indonesia Stock Exchange for the period of 2015 to 2018 have been assessed by using Altman, Springate, and Zmijewski model whether those companies are potentially bankrupt or not. There are 4 companies potentially bankrupt (18.18%) by using Altman model, 8 companies are potentially bankrupt (36.36%) by Springate model and 6 companies are potentially bankrupt (27.27%) using Zmijewski model. Refer to Conformity Level, Springate model is most accurate model. The data observed only one industry and one capital market in short time period. A wider research sample, longer period, and more bankruptcy prediction model is needed in future to make better result. This research result can be used by management as information to solve firm financial problem and change business strategy in the uncertain world economic condition. Beside, this also can be used as information for investors, creditors, auditors and other stakeholders to make better financial decision. This research uses data of retail companies in Indonesia and adopted Altman, Springate, and Zmijewski model to predict bankruptcy within period 2015-2018. The Novelty of this research is to combine three analyses, those are bankruptcy prediction, if there is any different result between each Model and the most accurate model.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Fredella Colline PY - 2020 DA - 2020/09/15 TI - Bankruptcy Prediction Analysis: A Case Study of Retail Companies in Indonesia BT - International Conference on Management, Accounting, and Economy (ICMAE 2020) PB - Atlantis Press SP - 326 EP - 330 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.200915.073 DO - https://doi.org/10.2991/aebmr.k.200915.073 ID - Colline2020 ER -