An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the prediction of stock market return: The case of the Istanbul Stock Exchange

Authors:
Melek Acar Boyacioglu;Derya Avci
Affiliations:
Selcuk University, Faculty of Economics and Administrative Sciences, Department of Business Administration, Campus, 42031 Konya, Turkey;Firat University, Faculty of Technical Education, Department of Electronic and Computer Education, 23119 Elazig, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

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Abstract

Stock market prediction is important and of great interest because successful prediction of stock prices may promise attractive benefits. These tasks are highly complicated and very difficult. In this paper, we investigate the predictability of stock market return with Adaptive Network-Based Fuzzy Inference System (ANFIS). The objective of this study is to determine whether an ANFIS algorithm is capable of accurately predicting stock market return. We attempt to model and predict the return on stock price index of the Istanbul Stock Exchange (ISE) with ANFIS. We use six macroeconomic variables and three indices as input variables. The experimental results reveal that the model successfully forecasts the monthly return of ISE National 100 Index with an accuracy rate of 98.3%. ANFIS provides a promising alternative for stock market prediction. ANFIS can be a useful tool for economists and practitioners dealing with the forecasting of the stock price index return.