ADAPTIVE RANGE-BASED VOLATILITY MODELLING OF OIL AND GAS STOCK RETURNS IN NIGERIA

Abstract

In this article, a range based volatility model that integrated robust hybrid range-based estimators with exogenous variables was proposed for oil and gas sector. The study employed historical daily data on opening, closing, high, and low prices of stocks from Chevron, Conoil, Oando Plc, and Total Energies, spanning 1^st January, 2012 to 12^th September, 2025, alongside daily Brent crude oil prices as an exogenous variable. The model and exogenous influences on volatility was examined. The study showed that Range-Based Generalised Autoregressive Conditional Heteroskedasticity with Exogenous variable (RB-GARCH-X) models, especially the non-zero drift version, captured volatility in Nigeria’s oil and gas sector effectively, while the adaptive RB-GARCH-X model that adapt to both drift-free and drift-present conditions performed best for highly volatile stocks. The results also revealed that range-based estimation techniques improved model robustness against microstructure noise and estimation errors in both drift-free and drift-present conditions. Parameter estimates indicated strong volatility persistence (β: 0.71–0.99), moderate short-term effects (α: 0.03–0.21), and significant influence of crude oil prices (γ: ≈2.0E-07 to -1.25E-07). The adaptive model provided a more effective balance between short- and long-term effects, demonstrating its robustness for stocks characterised by heightened instability like the Nigeria Oil and Gas stock.