Forecasting Realised Volatility Using ARFIMA and HAR Models

Hassan, Kabir, Marwan, Izzeldin, Pappas, Vasileios (2019) Forecasting Realised Volatility Using ARFIMA and HAR Models. Quantitative Finance, . ISSN 1469-7688. (doi:10.1080/14697688.2019.1600713) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

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https://doi.org/10.1080/14697688.2019.1600713

Abstract

Recent literature provides mixed empirical evidence with respect to the forecasting performance of ARFIMA and HAR models. This paper compares the forecasting performance of both models using high frequency data of 100 stocks representing 10 business sectors for the period 2000-2010. We allow for different sectors, changing market conditions, variation in the sampling frequency and forecasting horizons. For the overall sample and using the 300 sec sampling frequency, the forecasting performance of both models is indistinguishable. However, differences arise under different market regimes, forecasting horizons and sampling frequencies. ARFIMA models are superior for the crisis and pre-crisis sub-samples. HAR forecasts are less sensitive to regime change and to longer forecasting horizons. Variations in forecasting performance could also be explained by the level of persistence.

Item Type: Article
DOI/Identification number: 10.1080/14697688.2019.1600713
Uncontrolled keywords: High-Frequency data ; Market conditions ; Market Sectors ; Realised Variance ; HAR ; ARFIMA
Divisions: Faculties > Social Sciences > Kent Business School > Accounting and Finance
Depositing User: Vasileios Pappas
Date Deposited: 28 Mar 2019 10:23 UTC
Last Modified: 03 Jun 2019 09:37 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/73245 (The current URI for this page, for reference purposes)
Pappas, Vasileios: https://orcid.org/0000-0003-1885-4832
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