Long Memory, Realized Volatility and Heterogeneous Autoregressive Models

  • Richard T. Baillie
  • , Fabio Calonaci
  • , Dooyeon Cho
  • , Seunghwa Rho

Research output: Contribution to journalArticlepeer-review

Abstract

The presence of long memory in realized volatility (RV) is a widespread stylized fact. The origins of long memory in RV have been attributed to jumps, structural breaks, contemporaneous aggregation, nonlinearities, or pure long memory. An important development has been the heterogeneous autoregressive (HAR) model and its extensions. This article assesses the separate roles of fractionally integrated long memory models, extended HAR models and time varying parameter HAR models. We find that the presence of the long memory parameter is often important in addition to the HAR models.

Original languageEnglish
Pages (from-to)609-628
Number of pages20
JournalJournal of Time Series Analysis
Volume40
Issue number4
DOIs
StatePublished - Jul 2019

Keywords

  • HAR models
  • Restricted ARFIMA models
  • TVP models
  • realized volatility

Fingerprint

Dive into the research topics of 'Long Memory, Realized Volatility and Heterogeneous Autoregressive Models'. Together they form a unique fingerprint.

Cite this