Journal Article10.1016/S0169-2070(99)00040-0
Do long-memory models have long memory?
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TL;DR: The predictability memory of fractionally integrated ARMA processes is examined to find out whether negative AR parameters absorb, to a great extent, the memory generated by a positive fractional difference.
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About: This article is published in International Journal of Forecasting. The article was published on 01 Jan 2000. The article focuses on the topics: Predictability.
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References
An introduction to long‐memory time series models and fractional differencing
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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How far can changes in general business activity be forecasted
TL;DR: In this article, a 10-year pattern in Finnish GDP is introduced as a "seasonal" in an ARMA-model, which raises doubts both about model memory and model validity.
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Bias in an estimator of the fractional difference parameter
TL;DR: In this article, an estimator of the difference parameter in a class of long-memory time series models is examined, and it is shown that, in particular circumstances, the estimator can be badly biased, and tests based on it consequently seriously misleading.
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