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Seasonally and Fractionally Differenced Time Series [PDF]
Hitotsubashi journal of economics, 2007 openaire +1 more source
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Analysis of Fractionally Differenced Processes with Heteroscedastic Errors
2018The prime goal of this research is to model the long-range dependency and volatility factors fitting in fractionally differenced ARMA (ARFIMA) and Gegenbauer ARMA processes (GARMA) in financial time series. This extends the efficiency in computing the exact maximum likelihood established by Sowell through conditional quasi maximum likelihood (QMLE) for
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No-cointegration test based on fractional differencing: Some Monte Carlo results
Journal of Statistical Planning and Inference, 1999Y K Tse, V V Anh
exaly
Advancement of Fractionally Differenced Gegenbauer Processes with Long Memory
2015The class of long memory time series models involving Gegenbauer processes is investigated in detail in terms of formulation, parameter estimation, prediction and testing. Corresponding truncated AR (autoregressive) and MA (moving average) approximations driven by Gaussian white noise are analysed through state space modelling and Kalman filtering to ...
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Editors' introduction: Fractional differencing and long memory processes
Journal of Econometrics, 1996Richard T. Baillie, Maxwell L. King
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Fractional Differencing Predictive Power in FOREX Market
SSRN Electronic Journal, 2019openaire +1 more source
FDSM: A Program for a Fractional-Differencing Seasonal Model
The American Statistician, 1988openaire +1 more source
Identification of fractional differencing autoregressive modelsâ€
Communications in Statistics - Theory and Methods, 1995exaly
FRACTIONAL DIFFERENCING MODELING IN HYDROLOGY
Journal of the American Water Resources Association, 1985exaly