APPLICATION OF ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM IN INTEREST RATES EFFECTS ON STOCK RETURNS
Journal Title: Indian Journal of Computer Science and Engineering - Year 2011, Vol 2, Issue 1
Abstract
In the current study we examine the effects of interest rate changes on common stock returns of Greek banking sector. We examine the Generalized Autoregressive eteroskedasticity (GARCH) process and an Adaptive Neuro-Fuzzy Inference System (ANFIS). The conclusions of our findings are that the changes of interest rates, based on GARCH model, are insignificant on common stock returns during the period we examine. On the other hand, with ANFIS we can get the rules and in each case we can have positive or negative effects depending on the conditions and the firing rules of inputs, which information is not possible to be retrieved with the traditional econometric modelling. Furthermore we examine the forecasting performance of both models and we conclude that ANFIS outperforms GARCH model in both in-sample and out-of-sample periods.
Authors and Affiliations
ELEFTHERIOS GIOVANIS
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