Augmenting the Realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects

Ioannis Papantonis, Rompolis Leonidas S., Elias Tzavalis and Agapitos Orestis
Additional contact information
Rompolis Leonidas S.: Department of Accounting and Finance, Athens University of Economics and Business, 10434 Athens, Greece
Agapitos Orestis: Department of Economics, Athens University of Economics and Business, 10434 Athens, Greece

Studies in Nonlinear Dynamics & Econometrics, 2023, vol. 27, issue 2, 171-198

Abstract: This paper extends the Realized-GARCH framework, by allowing the conditional variance equation to incorporate exogenous variables related to intra-day realized measures. The choice of these measures is motivated by the so-called heterogeneous auto-regressive (HAR) class of models. Our augmented model is found to outperform both the Realized-GARCH and the various HAR models in terms of in-sample fitting and out-of-sample forecasting accuracy. The new model specification is examined under alternative parametric density assumptions for the return innovations. Non-normality seems to be very important for filtering the return innovations to which variance responds and helps significantly upon the prediction performance of the suggested model.

Keywords: HAR; heterogeneous auto-regressive; NIG; realized variance; Realized-GARCH; SGED (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/snde-2020-0131 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:sndecm:v:27:y:2023:i:2:p:171-198:n:8

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/snde/html

DOI: 10.1515/snde-2020-0131

Access Statistics for this article

Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach

More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().