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We examine the ARCH-GARCH models for the forecasting of the bond price time series provided by VUB bank and make comparisons the forecast accuracy with the class of RBF neural network models. A limited statistical or computer science theory exists on how to design the architecture of RBF networks for some specific nonlinear time series, which allows for(More)
At first, we discuss the basic structure of the fuzzy system as a simple yet powerful fuzzy modeling technique. Neural networks and fuzzy logic models are based on very similar underlying mathematics. The similarity between RBF networks and fuzzy models is noted in detail. Then, we propose the extension of RBF neural networks by the cloud model. Time series(More)
This paper considers the use of ANN methodology for parameters estimation of the autoregressive conditional heteroscedastic (ARCH) processes. The paper provides heuristic approach of ARCH processes modelling. This approach is often employed to estimate the values of financial variables as rates of return, exchange rates, means and variances of inflation,(More)