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
Pages (from-to)1-8
Number of pages8
JournalFinance Research Letters
Volume44
Early online date8 Apr 2021
DOIs
Publication statusPublished - Jan 2022

Keywords

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

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