A discussion on the robustness of conditional heteroskedasticity models: Simulation evidence and applications of the crude oil returns

Yanlin Shi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper discusses the inherent robustness of the generalized autoregressive score (GAS) model, such that consistent estimators can still be obtained when large outliers do exist. A recent example includes the historical-writing negative price of the West Texas Intermediate (WTI) crude oil future in early-2020. Via simulation studies, we demonstrate that GAS can produce much more robust estimates than the popular GARCH model. Empirical analysis using the WTI returns over 2017–2020 further supports the superiority of GAS over GARCH models.

Original languageEnglish
Article number102053
JournalFinance Research Letters
DOIs
Publication statusE-pub ahead of print - 8 Apr 2021

Bibliographical note

Funding Information:
The authors would like to thank the Macquarie University for the research support. We particularly thank the Editor-in-Chief (Samuel Vigne) and the anonymous referee for providing valuable and insightful comments on earlier drafts. The usual disclaimer applies.

Publisher Copyright:
© 2021 Elsevier Inc.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Keywords

  • Conditional volatility
  • Crude oil
  • GARCH
  • Generalized autoregressive score
  • Robustness

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