The adaptive neuro-fuzzy model for forecasting the domestic debt

Authors:
Ayturk Keles;Mensure Kolcak;Ali Keles
Affiliations:
Department of Computer Engineering, Faculty of Engineering, Atatürk University, TR-25240 Erzurum, Turkey;Vocational Higher School, Accounting Program, Atatürk University, TR-25240 Erzurum, Turkey;Department of Computer Education and Instructional Technology, Faculty of K.K.E.F, Atatürk University, TR-25240 Erzurum, Turkey
Venue:
Knowledge-Based Systems
Year:
2008

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Abstract

Artificial intelligence technologies have been used in a number of fields such as engineering, education, medicine and industry successfully. These technologies, likewise, can be applied to finance and economies to solve complex problems for example; the problems about the predicting of the domestic debt stock. The correct prediction of borrowing for the determination of macroeconomic targets concerning the future economic plans is of great importance, because, the fact that the correct prediction (or forecast) will bring about successful decisions and will provide benefit maximizing has increased the interest in Forecast Modeling. In this study, using 10 years' monthly values of Currency Issued (CI), Total Money Supply (TMS), Consumer Price Index (CPI) and Interest Rate (IR), by means of Adaptive Neuro-Fuzzy Inference System, we have created a forecast model MFDD (Model of Forecasting the Domestic Debt) in order to predict domestic debt. It can be said that our MFDD model is very good with a strong estimation capability according to the findings in this study.