Modelling and Forecasting Crude Oil Prices During Covid-19 Pandemic

Abstract

Currently, the world suffers from the COVID-19 pandemic, which affects almost every aspect of daily life, giving rise to recession and affecting the world prices of crude oil. The study aims to model the high uncertainty of volatility as well as to forecast the daily prices of crude oil during the pandemic. One econometric model applied in this study is the Generalised Autoregressive Conditional Heteroscedasticity (GARCH) that allows more accurate and appropriate statistical analyses. Particularly, this study also discusses solving economic issues on the condition of any disturbances in the stability of daily crude oil prices. The findings suggest that the AR(1)-GARCH(1,1) model is a well-fitted model to predict relatively small errors. This model can act as a foundation for determining strategies in the future while facing such uncertain circumstances.

Public Sector Policy of Estimating Model for Renewable Energy

“…Gunarto et al (2020) added to the literature by studying high volatility of crude oil price, showing that the urge for use of crude oil as a renewable energy source was predicted to be more costly. A current study on crude oil prices during the Covid-19 pandemic which employes the GARCH(1,1) model confirmed a high level of uncertainty for oil prices, showing that renewable energy then is urgently needed (Hendrawaty et al, 2021).…”

Directional Spillover of Fossil Fuels Prices on a Hydrothermal Power Generation Market

“…The sample period was selected due to the data available with no methodological changes, and the current supply scheme for the generation sector is included (CREG 051 of 2009, article 10). Likewise, 2020 data were not selected because the Colombian electricity demand decreased significantly during the first quarterly of the COVID-19 pandemic, and the fossil fuel prices slumped, especially the oil prices that reached negative values (Hendrawaty et al, 2021;Oviedo-Gómez et al, 2021b). Thus, Table 2 describes the variables, specifying data sources and units.…”

Application of the geometric Brownian motion model in West Texas Intermediate crude oil price prediction

“…Therefore, it is essential to predict crude oil commodity prices to reduce the negative impact of fluctuations in crude oil commodity prices. Applied mathematical models, artificial intelligence, big data, and forecasting models are used to predict future crude oil commodity prices (Hendrawaty et al, 2020). One model that can be used is the Geometric Brownian Motion model, also known as the Wiener process.…”