Risk contagion of COVID-19 to oil prices: A Markov switching GARCH and PCA approach

Nida Siddiqui; Haslifah Mohamad Hasim

doi:10.1371/journal.pone.0312718

Risk contagion of COVID-19 to oil prices: A Markov switching GARCH and PCA approach

Nida Siddiqui, Haslifah Mohamad Hasim^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

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Abstract

The COVID-19 pandemic and its impact on crude oil prices created additional risks throughout the financial industry. To contribute to the ongoing debates, this paper empirically examined the risk contagion of COVID-19 to oil prices by incorporating a Markov-Switching GARCH (MS-GARCH) framework and the multivariate GARCH time series model, BEKK-GARCH model. The study examines data collected between 27 January 2020 and 31 December 2020. Further, we used principal component analysis (PCA) to find principal factors explaining the overall variability of the global economic indicators that contribute to the risk. Finally, to support the risk transmission effects between COVID-19 and oil prices, we conducted regression analysis, while controlling for the factors extracted from the PCA method.

Original language	English
Article number	e0312718
Journal	PLoS ONE
Volume	19
Issue number	12
DOIs	https://doi.org/10.1371/journal.pone.0312718
Publication status	Published - 5 Dec 2024

Keywords

COVID-19
Commerce
Humans
Markov Chains
Models, Economic
Pandemics
Petroleum
Principal Component Analysis
SARS-CoV-2

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© 2024 Siddiqui, Mohamad Hasim.
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Risk contagion of COVID-19 to oil prices: A Markov switching GARCH and PCA approach

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