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Model ARFIMA (Autoregressive Fractionally Integrated Moving Average) merupakan pengembangan dari model ARIMA yang pertama kali dikenalkan oleh Granger dan Joyeux (1980). Sedangkan Hosking (1981) memperkenalkan sifat jangka panjang (long memory) pada data
Rini Cahyandari, Rima Erviana
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A Study of Nigeria Monthly Stock Price Index Using ARTFIMA-FIGARCH Hybrid Model
Long memory is a phenomenon in time series analysis that is exhibited by a slow decay of the autocorrelation function. It has been observed that the presence of long memory in both mean and volatility can complicate model fitting and compromise ...
A G Umar, H G Dikko, J Garba, M Tasi’u
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Short term streamflow forecasting is important for operational control and risk management in hydrology. Despite a wide range of models available, the impact of long range dependence is often neglected when considering short term forecasting.
Szolgayová Elena +3 more
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Wind speed is one of the most important weather factors in the landing and takeoff process of airplane because it can affect the airplane's lift. Therefore, we need a model to predict the wind speed in an area.
Devi Ila Octaviyani +2 more
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On the invertibility in periodic ARFIMA models
The present paper, characterizes the invertibility and causality conditions of a periodic ARFIMA (PARFIMA) models. We first, discuss the conditions in the multivariate case, by considering the corresponding p-variate stationary ARFIMA models. Second, we construct the conditions using the univariate case and we deduce a new infinite autoregressive ...
Amimour, Amine, Belaide, Karima
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A Forecasting Model for Japan's Unemployment Rate [PDF]
This note aims to achieve a parsimonious fractionally-integrated autoregressive and moving average (ARFIMA) model for recent time series data of Japan's unemployment rate. A brief review of the ARFIMA model is provided, leading to econometric modeling of
Takamitsu KURITA
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Forecasting energy futures volatility based on the unbiased extreme value volatility estimator
This paper uses the opening, high, low, and closing prices of five energy futures to estimate and model volatility based on the unbiased extreme value volatility estimator (the Add RS estimator).
Dilip Kumar
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Forecasting realised volatility using ARFIMA and HAR models [PDF]
Recent literature provides mixed empirical evidence with respect to the forecasting performance of ARFIMA and HAR models. This paper compares the forecasting performance of both models using high frequency data of 100 stocks representing 10 business sectors for the period 2000-2010.
Marwan Izzeldin +3 more
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FORECASTING THE UNEMPLOYMENT RATE IN MALAYSIA DURING COVID-19 PANDEMIC USING ARIMA AND ARFIMA MODELS
The unemployment issue is one of the most common problems faced by many countries around the world. The unemployment rates in developed countries often fluctuate throughout time.
Nur Afiqah Ismail +2 more
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Bu çalışmada, Türkiye’nin 2010 – 2020 dönemine ait ülke Kredi Temerrüt Takası Primlerinin finansal zaman serisi olarak özellikleri araştırılmış, parametrik ve yarı parametrik ön testler uygulanmıştır.
Mustafa Çevik, Süleyman Serdar Karaca
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