Long Memory, Realized Volatility and Heterogeneous Autoregressive Models

20 Pages Posted: 29 May 2020

See all articles by Richard Baillie

Richard Baillie

Michigan State University - The Eli Broad College of Business and The Eli Broad Graduate School of Management

Fabio Calonaci

Queen Mary University of London

Seunghwa Rho

Emory University

Dooyean Cho

Sungkyunkwan University

Date Written: July 2019

Abstract

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

Keywords: Restricted models, realized volatility, models, models

Suggested Citation

Baillie, Richard and Calonaci, Fabio and Rho, Seunghwa and Cho, Dooyean, Long Memory, Realized Volatility and Heterogeneous Autoregressive Models (July 2019). Journal of Time Series Analysis, Vol. 40, Issue 4, pp. 609-628, 2019, Available at SSRN: https://ssrn.com/abstract=3612275 or http://dx.doi.org/10.1111/jtsa.12470

Richard Baillie (Contact Author)

Michigan State University - The Eli Broad College of Business and The Eli Broad Graduate School of Management ( email )

East Lansing, MI 48824-1121
United States

Fabio Calonaci

Queen Mary University of London

Seunghwa Rho

Emory University

201 Dowman Drive
Atlanta, GA 30322
United States

Dooyean Cho

Sungkyunkwan University

53 Myeongnyun-dong 3-ga Jongno-ju
Guro-gu
Seoul, 110-745
Korea, Republic of (South Korea)

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