Long memory time series

By Peter M. Robinson. 2003

145 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0e3c71485df8fe8e7844788518f2a3028564a6a9

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Citations in the corpus

Time series interpolation via global optimization of moments fitting (2013, background): “The existence of missing values is a very common yet critical issue in data from a variety of fields such as engineering, physics, hydrology, finance, marketing or transportation; see [26,30,18,36,12,19,8,3].”
Modelling structural breaks, long memory and stock market volatility: an overview (2005, background): “Baillie (1996), Doukhan et al. (2003), and Robinson (1994a, 2003) have provided comprehensive surveys on long memory processes and fractional integration while a recent annals issue of this journal entitled Long Memory and Nonlinear Time Series, edited by Davidson and Terasvirta (2002), has dealt…”
Rescaled variance and related tests for long memory in volatility and levels (2003, unknown): “Modiÿed R/S statistic The rescaled range, or R/S analysis was introduced by Hurst (1951) and subsequently reÿned by Mandelbrot and his collaborators (see Mandelbrot and Wallis, 1969; Mandelbrot, 1972, 1975; Mandelbrot and Taqqu, 1979).”
A multivariate long-memory model with structural breaks (2009, methodology): “Parke [11] justifies fractional integration with an error duration model, while Diebold and Inoue [12] relates fractional integration with regime-switching models (see [13,14,15] for extensive surveys of I (d) processes).”
Semiparametric Estimation in Time‐Series Regression with Long‐Range Dependence (2005, unknown): “., p, since this is the dominant case in empirical research (see Robinson, 1994b, 2003; Beran, 1994, for a review of long-range dependent processes).”
Weak and Strong Cross Section Dependence and Estimation of Large Panels (2011, background): “Hence, both the spectral radius and the column norm of the covariance matrix of a CSD process are unbounded in N .”
Testing Models of Low‐Frequency Variability (2006, unknown): “…and Stock (1996), the stationarity test of Nyblom (1989) (using a HAC covariance matrix as suggested in Kwiatkowski, Phillips, Schmidt, and Shin (1992)), and the estimated values of d and standard errors from Geweke and Porter-Hudak (1983) or GPH regressions as described in the Robinson (2003).”
Low-Frequency Econometrics (2015, background): “A third is the ’fractional’ model (FRM) (1 − ) = where is (0) with −12 32 (cf. Baillie (1996) and Robinson (2003) for surveys).”
Asymptotic normality of narrow-band least squares in the stationary fractional cointegration model and volatility forecasting (2006, background): “For excellent surveys of long memory processes and fractional models see Robinson (1994c), Baillie (1996), and Robinson (2003), and for a textbook treatment see e.g. Beran (1994).”
Fully modified narrow‐band least squares estimation of weak fractional cointegration (2011, unknown): “For surveys see, e.g., Baillie (1996) and Robinson (2003).”
Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration (2005, methodology): “Comparing the LW estimator with the modifications by Shimotsu and Phillips (2005) and Shimotsu (2002) (FELW) and Andrews and Sun (2004) (LPW), we find the accuracy of the FELW estimator not to be noticeably different either in bias or in RMSE; see Table 3.”
Local Polynomial Whittle Estimation of Perturbed Fractional Processes (2008, background): “In general, when wt is not assumed to be i:i:d:, zt is referred to as a perturbed fractional process.1 For reviews of fractionally integrated processes and some applications, see Baillie (1996), Henry & Za¤aroni (2003), or Robinson (2003).”