Fuzzy Auto-Regressive Integrated Moving Average (FARIMA) Model for Forecasting the Gold Prices

Sahed Abdelkader (), Mekidiche Mohammeed () and Kahoui Hacen ()
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Sahed Abdelkader: Department of Economics Sciences, the University center of Maghnia, Algeria
Mekidiche Mohammeed: Department of Economics Sciences, the University center of Maghnia, Algeria
Kahoui Hacen: Department of Economics Sciences, the University center of Maghnia, Algeria

Journal of Smart Economic Growth, 2020, vol. 5, issue 1, 1-13

Abstract: In this study, the Fuzzy Auto-Regressive Integrated Moving Average (FARIMA) Model has been used to predict gold prices, The main objective was to estimate the fractional parameters by using the fuzzy regression method of TANAKA. The prediction accuracy of the FARIMA method was measured and compared with the ARIMA method using mean square error (MSE) and mean square error (RMSE) for the time period from 2010 to 2018. Gold prices were also predicted using the two methods for the year 2019. The research concluded that FARIMA models are more efficient than ARIMA models in predicting gold prices.

Keywords: Gold Prices; Fuzzy Set; ARIMA; FARIMA (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:seg:012016:v:5:y:2020:i:1:p:1-13

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