Skip to main content
Kent Academic Repository

A generalized heterogeneous autoregressive model using market information

Hizmeri, Rodrigo, Izzeldin, Marwan, Nolte, Ingmar, Pappas, Vasileios (2022) A generalized heterogeneous autoregressive model using market information. Quantitative Finance, . ISSN 1469-7688. (doi:10.1080/14697688.2022.2076606) (KAR id:94915)

PDF Publisher pdf
Language: English

Download this file
[thumbnail of A generalized heterogeneous autoregressive model using market information.pdf]
Request a format suitable for use with assistive technology e.g. a screenreader
PDF Author's Accepted Manuscript
Language: English

Restricted to Repository staff only
Contact us about this Publication
[thumbnail of Draft_Revised2_2022.pdf]
Official URL:


This paper introduces a novel class of volatility forecasting models that incorporate market realized (co)variances and semi(co)variances within the framework of a heterogeneous au­toregressive (HAR) model. Our empirical analysis shows statistically and economically significant forecasting gains. For our most parsimonious market-HAR specification, stock volatility forecasting is improved by 9.80\% points. Using a mixed sampling frequency market-HAR variant with low (high) sampling frequency for the stock (market) improves forecasting by a further 6.90\% points. Our paper also develops noise-robust estimators to facilitate the use of realized semi(co)variances at high sampling frequencies.

Item Type: Article
DOI/Identification number: 10.1080/14697688.2022.2076606
Uncontrolled keywords: Realized volatility; Microstructure noise; Pre-averaged estimators; Semi-variance; Semi-covariance; Volatility forecasting
Subjects: H Social Sciences > HG Finance
Divisions: Divisions > Kent Business School - Division > Department of Accounting and Finance
Depositing User: Vasileios Pappas
Date Deposited: 06 May 2022 16:16 UTC
Last Modified: 04 Jul 2023 11:12 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.