Journal Article10.1111/J.1467-9892.1980.TB00297.X
An introduction to long‐memory time series models and fractional differencing
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TL;DR: Generation and estimation of these models are considered and applications on generated and real data presented, showing potentially useful long-memory forecasting properties.
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Abstract: . The idea of fractional differencing is introduced in terms of the infinite filter that corresponds to the expansion of (1-B)d. When the filter is applied to white noise, a class of time series is generated with distinctive properties, particularly in the very low frequencies and provides potentially useful long-memory forecasting properties. Such models are shown to possibly arise from aggregation of independent components. Generation and estimation of these models are considered and applications on generated and real data presented.
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Citations
A generalised prediction model of first person shooter game traffic
Antonio Cricenti,Philip Branch +1 more
- 18 Dec 2009
TL;DR: In this article, the authors present techniques for creating representative models for N-player first person shooter games based on empirically measured traffic of 2-player games, which capture the packet size distribution as well as the time series behaviour of game traffic.
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Bayesian Inference for ARFIMA Models
TL;DR: Practical methods for Bayesian inference in the autoregressive fractionally integrated moving average (ARFIMA) model using the exact likelihood function, any proper prior distribution, and time series that may have thousands of observations are developed.
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The benefit of modeling jumps in realized volatility for risk prediction : evidence from Chinese mainland stocks
TL;DR: In this paper, the authors study the benefit of explicitly modeling jumps in this class of models for value at risk prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.
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•Posted Content
Simulation of Gegenbauer Processes using Wavelet Packets
Jérôme Collet,Jalal M. Fadili +1 more
TL;DR: An original algorithm is introduced, inspired by the one proposed by Coifman and Wickerhauser, to adaptively search for the best-ortho-basis in the wavelet packet library where the covariance matrix of the transformed process is nearly diagonal.
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References
Spurious regressions in econometrics
Clive W. J. Granger,P. Newbold +1 more
TL;DR: In this paper, it is pointed out that it is very common to see reported in applied econometric literature time series regression equations with an apparently high degree of fit, as measured by the coefficient of multiple correlation R2 or the corrected coefficient R2, but with an extremely low value for the Durbin-Watson statistic.
6.8K
Long memory relationships and the aggregation of dynamic models
TL;DR: In this paper, it was shown that the aggregate series may have univariate long-memory models and obey integrated, or infinite length transfer function relationships, and that if series obeying such models occur in practice, from aggregation, then present techniques being used for analysis are not appropriate.
1.7K
Fractional integrals of stationary processes and the central limit theorem
Abstract: A class of limit theorems involving asymptotic normality is derived for stationary processes whose spectral density has a singular behavior near frequency zero. Generally these processes have ‘long-range dependence’ but are generated from strongly mixing processes by a fractional integral or derivative transformation. Some related remarks are made about random solutions of the Burgers equation.
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