Forecasting volatility in oil returns using asymmetric GARCH models: evidence from Tanzania
Haika Andrew Mbwambo ORCID ↗ · Laban Gaspe Letema ORCID ↗
International Journal of Research in Business and Social Science · 2023 · Vol. 12 / Issue 1 · 204-211
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Abstract
Crude oil is, without a doubt, one of the most significant commodities in the modern world. The highly contagious coronavirus, the conflict between Ukraine and Russia, and not to mention the unusual turn of events worldwide have all significantly impacted crude oil prices. Since oil is required for all critical economic activities, such as production and transportation, a forecast for crude oil prices is essential. Using a range of GARCH models at such an intense time, this study attempted to close this gap by forecasting crude oil volatility. To forecast the returns of Brent crude oil prices from January 2002 to February 2022, this study uses a family of GARCH models. In the respective family of models, GJRGARCH (1,1) was the most effective in predicting the volatility of crude oil prices. The GJRGARCH model was chosen since it had a higher likelihood value and a lower information criteria value. A diagnostic check was done to evaluate the produced model further to ensure that the proposed model was good enough for forecasting crude oil volatility. The study suggests employing the GJRGARCH technique to predict future fluctuations in exceptional circumstances.
Keywords: {'name': 'Brent, crude oil, GJRGARCH, forecasting, returns, volatility'}
Authors & affiliations
Haika Andrew Mbwambo
Affiliation not supplied
Laban Gaspe Letema
Affiliation not supplied
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