TY  - JOUR
T1  - Designing Bankruptcy Prediction System Using Artificial Neural Network
Based on Evidence from Iranian Manufacturing Companies
AU - Zeidi, Abbas Ramzanzadeh AU - Fadakar, Seyd Mehdy AU - Akbarpoor, Keyvan AU - Salimi, Maryam 
JO  - International Business Management
VL  - 10
IS  - 26
SP  - 5973
EP  - 5982
PY  - 2016
DA  - 2001/08/19
SN  - 1993-5250
DO  - ibm.2016.5973.5982
UR  - https://makhillpublications.co/view-article.php?doi=ibm.2016.5973.5982
KW  - Designing system
KW  -artificial neural network
KW  -bankruptcy prediction
KW  -Tehran Stock Exchange
AB  - Financial distress and bankruptcy result in a lot of costs. The costs will extend to different groups such as creditors, investors, managers, legal institutions and eventually capital owners. Bankruptcy prediction is a way that significantly can avoid financial distress. The purpose of the study is to design a system using artificial neural network to predict bankruptcy of companies listed in Tehran Stock Exchange before occurring bankruptcy, this system should be designed in a way that can predict the financial situation of company within the next three years. The research method is ex-post facto or survey and the statistical population of research including companies listed in Tehran Stock Exchange during 2001-2010. The data of 54 companies (30 bankrupt companies and 24 companies with Tobin Q above one) was tested by two parameters: 0.15 and 03% accuracy (optimism and pessimism).
ER  -