Long memory and regime switching: A simulation study on the Markov Regime-Switching ARFIMA model

Date

2015

Authors

Shi, Yanlin
Ho, Kin-Yip

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Abstract

Recent research argues that if the cause of confusion between long memory and regime switching were properly controlled for, they could be effectively distinguished. Motivated by this idea, our study aims to distinguish between them of financial series. We firstly model long memory and regime switching via the Autoregressive Fractionally Integrated Moving Average (ARFIMA) and Markov Regime-Switching (MRS) models, respectively. Their finite-sample properties and the confusion are investigated via simulations. To control for the cause of this confusion, we propose the MRS-ARFIMA model. A Monte Carlo study shows that this framework can effectively distinguish between the pure ARFIMA and pure MRS processes. Furthermore, MRS-ARFIMA outperforms the ordinary ARFIMA model for data simulated from the MRS-ARFIMA process. Finally, empirical studies of hourly and five-minute Garman-Klass and realized volatility of the FTSE index is conducted to demonstrate the advantages and usefulness of the proposed MRS-ARFIMA framework compared with the ARFIMA and MRS models in practice.

Description

Keywords

Long memory; Regime switching; ARFIMA; Markov Regime-Switching ARFIMA

Citation

Source

Journal of Banking and Finance

Type

Journal article

Book Title

Entity type

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License Rights

DOI

10.1016/j.jbankfin.2015.08.025

Restricted until

2037-12-31