@techreport{Heinen2009Forecasting,
abstract = {We consider the problem of forecasting time series with long memory when the memory parameter is subject to a structural break. By means of a large-scale Monte Carlo study we show that ignoring such a change in persistence leads to substantially reduced forecasting precision. The strength of this effect depends on whether the memory parameter is increasing or decreasing over time. A comparison of six forecasting strategies allows us to conclude that pre-testing for a change in persistence is highly recommendable in our setting. In addition we provide an empirical example which underlines the importance of our findings.},
address = {Hannover},
author = {Florian Heinen and Philipp Sibbertsen and Robinson Kruse},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {C15; C22; C53; 330; Zeitreihenanalyse; Strukturbruch; Simulation; Prognoseverfahren},
language = {eng},
number = {433},
publisher = {Wirtschaftswiss. Fak., Leibniz Univ.},
title = {Forecasting long memory time series under a break in persistence},
type = {Diskussionspapiere der Wirtschaftswissenschaftlichen Fakult\"{a}t // Wirtschaftswissenschaftliche Fakult\"{a}t, Leibniz Universit\"{a}t Hannover},
url = {http://hdl.handle.net/10419/37129},
year = {2009}
}
