Stationarity and functional central limit theorem for ARCH(∞) models

Oesook Lee

Research output: Contribution to journalArticlepeer-review


In this paper, we study the stationarity and functional central limit theorem for (random coefficient) ARCH(∞) models including HYAPGARCH and mixture memory GARCH models. Those models are able to cover long memory property with fewer parameters and have finite variances. The functional central limit theorems for ut and the squared processes ut 2 and σt 2 are proved. Sufficient conditions for L2-NED property to hold are established and the FCLT for mixture memory GARCH model as an example of a random coefficient ARCH(∞) process is derived via L2-NED condition.

Original languageEnglish
Pages (from-to)107-111
Number of pages5
JournalEconomics Letters
StatePublished - Jan 2018

Bibliographical note

Funding Information:
I am grateful to the Editor and an anonymous referee for their helpful comments. This research was supported by Basic Science Research Program through the NRF funded by the Ministry of Education, Science and Technology ( 2014R1A1A2039928 ).

Publisher Copyright:
© 2017


  • Functional central limit theorem
  • L-NED property
  • Mixture memory GARCH process
  • Random coefficient ARCH(∞) process


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