Forecasting realised volatility using ARFIMA and HAR models

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 dif...

Full description

Saved in:
Bibliographic Details
Published in:Quantitative finance 2019-10, Vol.19 (10), p.1627-1638
Main Authors: Izzeldin, Marwan, Hassan, M. Kabir, Pappas, Vasileios, Tsionas, Mike
Format: Article
Language:English
Subjects:
ARFIMA
Economic models
Forecasting
Forecasting techniques
HAR
High-frequency data
Market conditions
Market sectors
Realised variance
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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 using differences in the levels of persistence underlying each model.
ISSN:1469-7688
1469-7696
DOI:10.1080/14697688.2019.1600713