Asian Basic and Applied Research Journal

This study models the temporal dynamics of Nigerian crude-oil price activity by treating unusually large daily volatility observations (squared log-returns) as point events and modelling the trading-day durations between such events with symmetric Autoregressive Conditional Duration (ACD) models. Using daily closing prices from 3 November 2009 to 22 April 2025, log-returns were computed and squared to form a volatility proxy; events were defined as squared-return exceedances above a pre-specified threshold and event clusters were collapsed to produce a duration series. Stationarity of the duration series was assessed using the KPSS stationarity test, and strong serial dependence motivated ACD-type modelling. A range of ACD(2,3) and Log-ACD(2,3) model specifications were estimated under Weibull and log-Weibull error distributions, respectively; information criteria identified Log-ACD(2,3) as the preferred model, with statistically significant lag coefficients and a sum of autoregressive parameters below unity (i.e., ∑ α_i +∑ β_j <1), indicating persistent but mean-reverting duration dynamics. Diagnostics (Ljung-Box on standardised residuals) indicated that the selected models effectively captured serial dependence, with residuals resembling white noise. The results indicate that durations between volatility spikes in the Nigerian crude-oil market exhibit predictable temporal structure and that log-linear duration specifications (Log-ACD) provide a better fit and forecasting potential than the standard ACD form. These findings provide a point-process perspective on volatility clustering and complement traditional volatility models used in risk management and policy analysis. The study suggests that Nigerian fiscal authorities could consider incorporating Log-ACD-based volatility forecasts as part of their fiscal risk management framework. This approach could help them anticipate shocks in the crude oil market and respond promptly through measures such as expenditure control, hedging, and reserve adjustments, thereby supporting budget stability and more consistent revenue flows.