Results 11 to 20 of about 4,901 (213)
Cumhuriyet Science JournalThe research delved into analysing the stochastic characteristics of Nigeria's Real GDP, the exchange rate of the Naira to US Dollar, and the inflation rate employing Autoregressive fractionally integrated moving average (ARFIMA) and the Autoregressive ...
Ayoade Adewole
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BOOTSTRAP ASSISTED SPECIFICATION TESTS FOR THE ARFIMA MODEL [PDF]
Econometric Theory, 2011 This paper proposes bootstrap assisted specification tests for the autoregressive fractionally integrated moving average model based on the BartlettTp-process with estimated parameters whose limiting distribution under the null depends on the estimated model and the estimation method employed.
Delgado, Miguel A. +2 more
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Forecasting realised volatility using ARFIMA and HAR models [PDF]
Quantitative Finance, 2019 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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SMALL-SAMPLE LIKELIHOOD-BASED INFERENCE IN THE ARFIMA MODEL [PDF]
Econometric Theory, 2000 The autoregressive fractionally integrated moving average (ARFIMA) model has become a popular approach for analyzing time series that exhibit long-range dependence. For the Gaussian case, there have been substantial advances in the area of likelihood-based inference, including development of the asymptotic properties of the maximum likelihood ...
Offer Lieberman +2 more
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Kubik, 2015 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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MODELLING FOR THE WAVELET COEFFICIENTS OF ARFIMA PROCESSES [PDF]
Journal of Time Series Analysis, 2014 AbstractWe consider a model for the discrete nonboundary wavelet coefficients of autoregressive fractionally integrated moving average (ARFIMA) processes in each scale. Because the utility of the wavelet transform for the long‐range dependent processes, which many authors have explained in semi‐parametrical literature, is approximating the transformed ...
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InPrime, 2019 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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Forecasting energy futures volatility based on the unbiased extreme value volatility estimator
IIMB Management Review, 2017 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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Predicting BRICS stock returns using ARFIMA models [PDF]
Applied Financial Economics, 2014 This article examines the existence of long memory in daily stock market returns from Brazil, Russia, India, China and South Africa (BRICS) countries and also attempts to shed light on the efficacy of autoregressive fractionally integrated moving average (ARFIMA) models in predicting stock returns.
Aye, Goodness Chioma +5 more
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Journal of Hydrology and Hydromechanics, 2014 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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