Long memory in time series
Level Shifts and the Illusion of Long Memory in Economic Time Series
... of long memory in time series processes dates back at least to Hurst (1951), and Granger and Joyeux (1980) and Granger (1981) introduced it to ...econometrics. Long- memory ...
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Long memory of volatility measures in time series
... meet long term storage needs, is ...the time series from the mean, rescaled by its standard ...called long-memory ...for long memory ...used long memory ...
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Long memory and structural breaks in time series models
... rithms introduced by Politis and Romano (1992), or sieve bootstrap proposed by Kreiss (1988) and explored by Btihlmann (1997, 1998). Frequency domain approaches have also been examined. Among others, we can cite the ...
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Inference of Bivariate Long-memory Aggregate Time Series
... the long-memory limiting aggregate process derived in Section 2 to data ...r-dimensional time series with its spectral density defined ...
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Long Memory Analysis of Daily Average Temperature Time Series
... Long memory models address the degree of persistence in the ...of long memory models, [7] defined a series as long memory based on a slowly declining autocorrelation ...
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Long Memory or Structural Breaks in Temperature and Proxy Time Series
... of time series of both atmospheric and oceanic temperatures from instrumental and proxy records on time scales of a few decades to several millenia in an effort to estimate the natural variability of ...
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Wavelet Estimation of Time Series Regression with Long Memory Processes
... have long memory ...a time series, the original time series is decomposed into coefficients at different time ...original series at different time scales, ...
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Nonparametric Beta kernel estimator for long memory time series
... unknown memory structure of the ...to time series of any type of memory, in contrast to most estimators who are applicable either to short or to long memory ...
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A STOCHASTIC PARAMETER REGRESSION MODEL FOR LONG MEMORY TIME SERIES
... shows long memory ...the time series analysis ...shows long memory and the coefficients describing the response’s linear relationship to the predictor are zero on average, since ...
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Long Memory and Fractional Integration in High Frequency Financial Time Series
... the long-memory properties of high frequency financial time ...four series examined, namely Open, High, Low and Last observations for the British pound/US dollar spot exchange ...
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Forecasting Time Series with Long Memory and Level Shifts, A Bayesian Approach
... between long memory and nonlinear ...of long memory and non-linearity into a single time series model to be able to assess their relative ...of long memory and ...
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Band Spectrum Regression for Cointegrated Time Series with Long Memory Innovations
... Abstract Band spectrum regression is considered for cointegrated time series with long memory innovations. The estimates we advocate are shown to be consistent when cointegrating ...
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Conditional-Sum-of-Squares Estimation ofModels for Stationary Time Series with Long Memory
... stationary time series with long ...of time series ...short memory models it is not straightforward to show the truncation has negligible ...
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Trimming and tapering semi-parametric estimates in asymmetric long memory time series
... of long range dependence. Yajima (1989) allowed for the possibility of long memory and gave the joint asymptotic distribution of the periodogram evaluated at a set of fixed frequencies not depending ...
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Searching for long memory effects in time series of central Europe stock market indices
... SUMMARY This article deals with searching for long memory eff ects in fi nancial time series. Source data are daily closing prices of Central Europe stock market indices – Bratislava stock index ...
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The usefulness of econometric models with stochastic volatility and long memory: Applications for macroeconomic and financial time series
... and long memory and gain an insight into the macroeconomic and …nan- cial time series, such as interest rates, in‡ation, output growth and stock ...the long-run Fisher relationship ...
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Seasonal and cyclical long memory in time series
... First we review some of th e work done to date on seasonality and long memory, and we focus on research th a t try to link both issues. One of the lim itations of th e existing work is the imposition of ...
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Long memory in time series: Semiparametric estimation and conditional heteroscedasticity
... of long-range dependent com ...e long m em ory specification gives a far b e tte r approxim ation of the tru e v o latility dynam ics th a n does th e autoregressive ...
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Long memory estimation for complex-valued time series
... magnitude series, shown in Figure 4, is visibly different to that of the real and imaginary component series shown in Figure ...the long memory parameter for this series is more ...
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Long memory estimation for complex valued time series
... magnitude series, shown in Figure 4, is visibly different to that of the real and imaginary component series shown in Figure ...the long memory parameter for this series is more ...
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