Predicting Bankruptcy of Companies using Data Mining Models and Comparing the Results with Z Altman Model

Authors

  • Samira Saif Department of Accounting, Payame Noor University, Nahavand, Hamadan, Iran
  • somaye fathi Department of Accounting, Boroujerd Girls' Technical University, Lorestan, Iran (Corresponding author)
  • Zohre Heydari Department of Accounting, Kosar University of Bojnord, Bojnord, Iran
Abstract:

One of the issues helping make investment decisions is appropriate tools and models to evaluate financial situation 0f the organization.  By means of these tools, investors can analyze financial situation of the organization and identify financial distress or an ideal condition, they become aware of making decisions to invest in appropriate conditions.  The main objective of this study is to evaluate the power of using data mining models which are among new tools of prediction.  This tool was used to predict the bankruptcy of companies listed in Tehran stock exchange and comparison the results with the Altman model as one of the prevalent methods of prediction the bankruptcy of a company. The research data includes information of all companies listed in Tehran stock exchange during the years 2013 to 2018 subjected to Title 141 of the law of trade and were bankrupt. Variables used in both models were five financial ratios. The data mining models on the average in the base year had a predictive ability of 92.4 percent and the Altman model had a predictive ability of 82.41 percent. Considering the results, it was shown that the data mining model has more power to predict bankruptcy. 

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

Investigating the Risk of Paying Loans to Public and Private Companies Using the Logit Model and Comparing it with Altman Z (Case Study: A Private Bank in Iran)

The design of a credit risk measurement model in the monetary and banking system will play an important role in increasing the profitability of banking resources. This article attempts to use two models of Logit and Z Altman to determine and predict the credit risk of facilities provided to legal entities at a private bank in Iran. The variables studied in this research include qualitative vari...

full text

the clustering and classification data mining techniques in insurance fraud detection:the case of iranian car insurance

با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...

data mining rules and classification methods in insurance: the case of collision insurance

assigning premium to the insurance contract in iran mostly has based on some old rules have been authorized by government, in such a situation predicting premium by analyzing database and it’s characteristics will be definitely such a big mistake. therefore the most beneficial information one can gathered from these data is the amount of loss happens during one contract to predicting insurance ...

15 صفحه اول

Predicting the Credit Risk of Loans Using Data Mining Tools

 One of the most common causes or credit phenomenon that is taken into account for credit risk is the customer’s noncompliance with the commitments. Thus, by predicting the behavior of loan applicants, the growth rate of debts can be decreased. Hence, this study is conducted on corporate applicants for loans in one of the public banks in Iran. In this paper, the main elements comprising the cus...

full text

Predicting Type2 Diabetes Using Data Mining Algorithms

Background and purpose: Today, information systems and databases are widely used and in order to achieve higher accuracy and speed in making diagnosis, preventing the diseases, and choosing treatments they should be merged with traditional methods. This study aimed at presenting an accurate system for diagnosis of diabetes using data mining and a heuristic method combining neural network and pa...

full text

the use of appropriate madm model for ranking the vendors of mci equipments using fuzzy approach

abstract nowadays, the science of decision making has been paid to more attention due to the complexity of the problems of suppliers selection. as known, one of the efficient tools in economic and human resources development is the extension of communication networks in developing countries. so, the proper selection of suppliers of tc equipments is of concern very much. in this study, a ...

15 صفحه اول

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 3  issue 10

pages  33- 46

publication date 2018-08-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023