Predicting bank financial failures using neural networks, support vector machines and multivariate statistical methods: A comparative analysis in the sample of savings deposit insurance fund (SDIF) transferred banks in Turkey

A Comparative Approximate Economic Behavior Analysis Of Support Vector Machines And Neural Networks Models

Comparing the Bank Failure Prediction Performance of Neural Networks and Support Vector Machines: the Turkish Case

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 vecto...

A Guide to Deposit Insurance Reform

Deposit insurance was introduced in the United States during the Great Depression primarily to promote financial stability. Stability is enhanced because deposit insurance reduces the likelihood of a bank run. During its first four decades, deposit insurance appeared to work well as few banks failed. But in the 1980s, a wave of financial troubles in the banking and thrift industry exposed an un...

A Comparative Study of Extreme Learning Machines and Support Vector Machines in Prediction of Sediment Transport in Open Channels

The limiting velocity in open channels to prevent long-term sedimentation is predicted in this paper using a powerful soft computing technique known as Extreme Learning Machines (ELM). The ELM is a single Layer Feed-forward Neural Network (SLFNN) with a high level of training speed. The dimensionless parameter of limiting velocity which is known as the densimetric Froude number (Fr) is predicte...

Modeling of Banks ‌Bankruptcy in Iran (Multivariate Statistical Analysis)

In this paper we construct a modeling for detection of banks which are experiencing serious problems. Sample and variable set of the study contains 30 banks of Iran during 2006-2014 and their financial ratios. Well known multivariate statistical technique (principal component analysis) was used to explore the basic financial characteristics of the banks, and discriminant Logit and Probit models ...