Decision tree combined with neural networks for financial forecast

Abstract

In this article I would like to introduce a hybrid adaptive method. There is wide range of financial forecasts. This method is focusing on the economical default forecast, but the method can be used generally for other financial forecasts as well, for example for calculating the Value at Risk.

This hybrid method is combined by two classical adaptive methods: the decision trees and the artificial neural networks. In this article I will show the structure of the hybrid method, the problems which occurred during the construction of the model and the solutions for the problems. I will show the results of the model and compare them with the results of another financial default forecast model. I will analyse the results and the reliability of the method and I will show how the parameters can influence the reliability of the results.