Generalized autoregressive score model with high‐frequency data for optimal futures hedging

Yu‐Sheng Lai

Journal of Futures Markets, 2021, vol. 41, issue 12, 2023-2045

Abstract: This study compares the performance of hedged equity index portfolios constructed using either a generalized autoregressive score (GAS) or a realized GAS (GRAS) model. GAS models encompass popular models, and studies indicate that high‐frequency data improve a model's forecasting ability. The in‐sample estimation results demonstrate that the GRAS model has better explanatory power and more robust time‐varying variance and dependence parameters when fat‐tailed distributions are accounted for. The out‐of‐sample comparison confirms its superiority in reducing hedged portfolio variance and accruing economic benefits to highly risk‐averse hedgers.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/fut.22254

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:wly:jfutmk:v:41:y:2021:i:12:p:2023-2045

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0270-7314

Access Statistics for this article

Journal of Futures Markets is currently edited by Robert I. Webb

More articles in Journal of Futures Markets from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().