Flexible HAR Model for Realized Volatility

Item Type Journal paper
Abstract The Heterogeneous Autoregressive (HAR) model is commonly used in modeling the dynamics of realized volatility. In this paper, we propose a flexible HAR(1,...,p) specification, employing the adaptive LASSO and its statistical inference theory to see whether the lag structure (1, 5, 22) implied from an economic point of view can be recovered by statistical methods. The model differs from Audrino and Knaus (2016) where the authors apply LASSO on the AR(p) model, which does not necessarily lead to a HAR model. Adaptive LASSO estimation and the subsequent hypothesis testing results fail to show strong evidence that such a fixed lag structure can be recovered by a flexible model. We also apply the group LASSO and related tests to check the validity of the classic HAR, which is rejected in most cases. The results justify our intention to use a flexible lag structure while still keeping the HAR frame. In terms of the out-of-sample forecasting, the proposed flexible specification works comparably to the benchmark HAR(1, 5, 22). Moreover, the time-varying model combinations show that when the market environment is not stable, the fixed lag structure (1, 5, 22) is not particularly accurate and effective.
Authors Audrino, Francesco; Huang, Chen & Ostap, Okhrin
Journal or Publication Title Studies in Nonlinear Dynamics and Econometrics
Language English
Subjects economics
HSG Classification contribution to scientific community
HSG Profile Area SEPS - Quantitative Economic Methods
Refereed Yes
Date August 2019
Volume 23
Number 3
ISSN 1558-3708
Contact Email Address francesco.audrino@unisg.ch
Depositing User Prof. Ph.D Francesco Audrino
Date Deposited 20 Sep 2018 08:53
Last Modified 01 Jul 2022 00:25
URI: https://www.alexandria.unisg.ch/publications/255033


Full text not available from this repository. (Request a copy)


Audrino, Francesco; Huang, Chen & Ostap, Okhrin (2019) Flexible HAR Model for Realized Volatility. Studies in Nonlinear Dynamics and Econometrics, 23 (3). ISSN 1558-3708


Edit item Edit item