Application of Asymmetric GARCH Mixture Models to Export Price of Natural Gas in Nigeria

Abstract

This study aims to examine the volatility of Nigeria's natural gas export prices from 2015 to 2022 using asymmetric GARCH mixture models. It highlights significant price fluctuations, with a pronounced upward trend starting in 2020, likely driven by global market shifts such as the Russia-Ukraine conflict and related energy supply disruptions. The tGARCH-eGARCH model outperformed other GARCH mixtures, yielding the lowest Deviance Information Criterion (DIC) value of -949.3355. This suggests it best captures the volatility characteristics by effectively modeling heavy-tailed distributions and asymmetries in price behavior. The study reveals that Nigeria’s natural gas prices respond asymmetrically to market shocks, with negative events (like geopolitical tensions and supply disruptions) causing more significant volatility spikes than positive ones. High persistence in volatility, particularly evident in the eGARCH-eGARCH model, indicates that once volatility rises, it remains elevated for extended periods. The ARCH LM test detected significant effects at lag orders 4 and 8, but these effects dissipated by lag 12, indicating that recent shocks have a strong but diminishing impact on volatility over time. The data showed a slight right skew (skewness = 0.753), suggesting that extreme price increases were more frequent than sharp declines, possibly due to market asymmetries and supply constraints. The study concludes that the persistent and asymmetric nature of Nigeria’s natural gas price volatility mirrors broader global trends influenced by geopolitical events and macroeconomic instability. The findings underscore the importance of using flexible, hybrid models like tGARCH-eGARCH for accurate volatility forecasting and the study provides valuable insights for policymakers, investors, as well as risk managers navigating the complexities of the natural gas market.