ANN Forecasting Models for ISE National-100 Index

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ÖZDEMİR Ö., ASLANARGUN A., ASMA Ş.

JOURNAL OF MODERN APPLIED STATISTICAL METHODS, vol.9, no.2, pp.579-583, 2010 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 9 Issue: 2
  • Publication Date: 2010
  • Doi Number: 10.22237/jmasm/1288585440
  • Journal Name: JOURNAL OF MODERN APPLIED STATISTICAL METHODS
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus
  • Page Numbers: pp.579-583
  • Keywords: ISE stock market, time series modeling, artificial neural network, forecasting
  • Anadolu University Affiliated: Yes

Abstract

Prediction of the outputs of real world systems with accuracy and high speed is crucial in financial analysis due to its effects on worldwide economics. Because the inputs of the financial systems are timevarying functions, the development of algorithms and methods for modeling such systems cannot be neglected. The most appropriate forecasting model for the ISE national-100 index was investigated. BoxJenkins autoregressive integrated moving average (ARIMA) and artificial neural networks (ANN) are considered by using several evaluations. Results showed that the ANN model with linear architecture better fits the candidate data.