Oil Price Volatility Models during Coronavirus Crisis: Testing with Appropriate Models Using Further Univariate GARCH and Monte Carlo Simulation Models


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Authors

  • Tarek Bouazizi
  • Mongi Lassoued
  • Zouhaier Hadhek

Abstract

Coronavirus (2019-nCoV) not only has an effect on human health but also on economic variables in countries around the world. Coronavirus has an effect on the price of black gold and on its volatility. The shock on all markets is already very strong. Volatility patterns in Brent crude oil simulation are examined during covid-19 crisis that significantly affected the oil market volatility. The selected crisis of coronavirus arose due to different triggers having diverse implications for oil returns volatility. Our findings indicate that model choice with data modeling is the same appropriate model EGARCH(0,2) with different parameters between pre-coronavirus and post-coronavirus. We find that oil prices are the most strongly and negatively influenced by the Coronavirus crisis. The downward movement post-covid-19 crisis is very noticeable in energy volatility. The return series, on the other hand, do not appear smooth, they rather appear volatile. We conduct a Monte Carlo simulation exercise during coronavirus crisis to investigate whether this decline is real or an artefact of the oil market. Our findings support the fact that the decline in oil prices volatility is an artefact of the covid-19 crisis.Keywords: Oil Returns Conditional Volatility, Coronavirus Crisis, Univariate GARCH Models, Mean Equation, Variance Equation, Monte Carlo Simulation.JEL Classifications: Q43, E44, C1, I15, C15DOI: https://doi.org/10.32479/ijeep.10374

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Author Biography

Zouhaier Hadhek

Research Professor in Economics, phd in economics

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Published

2020-12-01

How to Cite

Bouazizi, T., Lassoued, M., & Hadhek, Z. (2020). Oil Price Volatility Models during Coronavirus Crisis: Testing with Appropriate Models Using Further Univariate GARCH and Monte Carlo Simulation Models. International Journal of Energy Economics and Policy, 11(1), 281–292. Retrieved from https://econjournals.com/index.php/ijeep/article/view/10374

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