@article{MAKHILLIBM2016102627000,
    title = {Designing Bankruptcy Prediction System Using Artificial Neural Network
Based on Evidence from Iranian Manufacturing Companies},
    journal = {International Business Management},
    volume = {10},
    number = {26},
    pages = {5973-5982},
    year = {2016},
    issn = {1993-5250},
    doi = {ibm.2016.5973.5982},
    url = {https://makhillpublications.co/view-article.php?issn=1993-5250&doi=ibm.2016.5973.5982},
    author = {Abbas Ramzanzadeh,Seyd Mehdy,Keyvan and},
    keywords = {Designing system,artificial neural network,bankruptcy prediction,Tehran Stock Exchange},
    abstract = {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).}
    }