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Information Journal Paper

Title

EXCHANGE MARKET FORECASTING USING HYBRID FUZZY AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODELS WITH PNNS

Pages

  97-113

Keywords

FUZZY AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (FARIMA)Q2
ARTIFICIAL NEURAL NETWORKS (ANNS)Q2
PROBABILISTIC NEURAL NETWORKS (PNNS)Q2

Abstract

 Fuzzy autoregressive integrated moving average models are improved versions of the classic autoregressive integrated moving average (ARIMA) models, proposed in order to overcome the data limitation of ARIMA models. In this paper, FARIMA models are combined with probabilistic classifiers in order to yield a more accurate model than FARIMA in financially incomplete data situations. Empirical results of using proposed hybrid model in EXCHANGE RATE market forecasting indicate that the proposed model exhibits effectively improved forecasting accuracy. Thus, the proposed model can be used as an alternative to EXCHANGE RATE forecasting tools, especially when the scant data is made available over a short span of time.

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    APA: Copy

    KHASHEI, M., BIJARI, M., & MOKHATAB RAFIEI, F.. (2012). EXCHANGE MARKET FORECASTING USING HYBRID FUZZY AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODELS WITH PNNS. JOURNAL OF COMPUTATIONAL METHODS IN ENGINEERING (ESTEGHLAL), 31(1), 97-113. SID. https://sid.ir/paper/173596/en

    Vancouver: Copy

    KHASHEI M., BIJARI M., MOKHATAB RAFIEI F.. EXCHANGE MARKET FORECASTING USING HYBRID FUZZY AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODELS WITH PNNS. JOURNAL OF COMPUTATIONAL METHODS IN ENGINEERING (ESTEGHLAL)[Internet]. 2012;31(1):97-113. Available from: https://sid.ir/paper/173596/en

    IEEE: Copy

    M. KHASHEI, M. BIJARI, and F. MOKHATAB RAFIEI, “EXCHANGE MARKET FORECASTING USING HYBRID FUZZY AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODELS WITH PNNS,” JOURNAL OF COMPUTATIONAL METHODS IN ENGINEERING (ESTEGHLAL), vol. 31, no. 1, pp. 97–113, 2012, [Online]. Available: https://sid.ir/paper/173596/en

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