چکیده:
Bankruptcy is an event with strong impacts on management, shareholders, employees, creditors, customers and other stakeholders, so as bankruptcy challenges the country both socially and economically. Therefore, correct prediction of bankruptcy is of high importance in the financial world. This research intends to investigate financial crisis prediction power using models based on Neural Networks and to compare it with Non-Linear Genetic Algorithm. Based on the available information and statistics of the listed companies on Tehran Stock Exchange (TSE) during 1997-2010, from among these companies subjected to article 141 of the Commercial Law, 72 firms, and from among other firms, 72 firms were selected. Results of McNemar Test for Non-Linear Genetic Algorithm and Neural Network indicated that although prediction accuracy of Non-Linear Genetic Algorithm (90%) was greater than that of Neural Network (70%), yet this difference was not statistically significant
خلاصه ماشینی:
Investigating Financial Crisis Prediction Power using Neural Network and Non-Linear Genetic Algorithm Receipt: 19, 6 , 2012 Acceptance: 25, 7 , 2012 Zahra Poorzamani Assistant Professor, Department of Accounting, Central Tehran Branch, Islamic Azad University, Tehran, Iran Corresponding Author, zpoorzamani@yahoo.
This research intends to investigate financial crisis prediction power using models based on Neural Networks and to compare it with Non-Linear Genetic Algorithm.
Many studies have been carried out on application of these techniques for prediction of businesses failure among which it can be referred to Etemadi, Rostami and Farajzadeh Dehkordi (2009), Huang, Tsai, Yen and Cheng (2008), Hung and Chen (2009), Lin et al (2009), Min an Jeong (2009), Min and Lee (2008), Ravi and Pramodh (2008), Sun and Li (2008), and Wu (2010).
6. Construction of financial crisis or bankruptcy prediction model using Non- Linear Genetic Algorithm The set of the understudy data which includes 72 bankrupt and 72 non-bankrupt firms has been randomly divided into two groups of training set and hold-out set.
Diagram 1: Best prediction model of financial crisis or bankruptcy obtained from Non-Linear Genetic Algorithm process Given the above figure, the obtained model can be presented as follows: 2 training set which is used for construction Y=(X16) + (X14 - X16 - ((X16 × X19) × 2 and training of the model includes 51 X14 × X19)) + ((-X18) × X14 × X18) bankrupt firms and 53 non-bankrupt firms.
کلیدواژه ها:
bankruptcy prediction
،
Linear Genetic Algorithm
،
Neural Network.
کلید واژه های ماشینی:
Linear Genetic Algorithm Neural Network
،
Linear Genetic Algorithm
،
Genetic Algorithm Neural Network Non
،
Prediction Power Neural Network Non
،
Neural Network
،
Linear Genetic Algorithm Neural Networks
،
This Neural Networks Non
،
Crisis Prediction Power Neural Network
،
Prediction
،
Artificial Neural Network Bankruptcy Prediction
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