A new model for periodically correlated process with conditional heteroscedasticity

Document Type : Original Paper


1 Department of Statistic, ‎School of‎ ‎Mathematics and Computer Science‎, ‎Damghan ‎University, Damghan, Semnan, Iran

2 Faculty of Mathematics and Computer Science,. Amirkabir University of technology


In this paper, we study LARCH processes with periodic structure as a new class of time series with periodic conditional heteroscedasticity and long memory property. We characterize the structure of inter and intra season correlations.
Under the proposed assumptions, the long memory property for each season is studied too. Finally, by simulation study the efficiency of the R/S estimator for estimating long memory parameter of each season is shown.


Main Subjects

Volume 8, Issue 2
November 2018
Pages 38-53
  • Receive Date: 04 January 2017
  • Revise Date: 25 August 2018
  • Accept Date: 02 October 2018
  • First Publish Date: 23 October 2018