Loading...
Please wait, while we are loading the content...
Similar Documents
Comparing the Bank Failure Prediction Performance of Neural Networks and Support Vector Machines: The Turkish Case
| Content Provider | Scilit |
|---|---|
| Author | Ecer, Fatih |
| Copyright Year | 2013 |
| Description | Journal: Economic Research-Ekonomska Istraživanja Experience from the banking crises during the past two decades suggest that advanced prediction models are needed for helping prevent bank failures. This paper compares the ability of artificial neural networks and support vector machines in predicting bank failures. Although artificial neural networks have widely been applied complex problems in business, the literature utilizing support vector machines is relatively narrow and their capability for predicting bank failures is not very familiar. In this paper, these two intelligent techniques are applied to a dataset of Turkish commercial banks. Empirical findings show that although the prediction performance of the two models can be considered as satisfactory, neural networks show slightly better predictive ability than support vector machines. In addition, different types of error from each model also indicate that neural network models are better predictors. |
| Related Links | https://hrcak.srce.hr/file/160767 |
| Ending Page | 98 |
| Page Count | 18 |
| Starting Page | 81 |
| ISSN | 1331677X |
| e-ISSN | 18489664 |
| DOI | 10.1080/1331677x.2013.11517623 |
| Journal | Economic Research-Ekonomska Istraživanja |
| Issue Number | 3 |
| Volume Number | 26 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2013-01-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Economic Research-Ekonomska Istraživanja Current Account Balance of Payments Propast Banaka Ann (umjetne Neuronske Mreže) Svm (strojevi S Potpornim Vektorima) |
| Content Type | Text |
| Subject | Economics and Econometrics |
