Modeling Fluctuation of the Price of Crude Oil in Nigeria Using ARCH, ARCH-M Models

Abstract

As a mono-product economy, where the main export commodity is crude oil, volatility in oil prices has implications for the Nigerian economy and, in particular, exchange rate movements. The latter is particularly important due to the twin dilemma of being an oil exporting and oil-importing country, a situation that emerged in the last decade. The study examined the effects of oil price volatility, demand for foreign exchange, and external reserves on exchange rate volatility in Nigeria using monthly data over the period from May, 1989 to April 2019. Drawing from the works of Atoi [1] Having realized the potentials of an Autoregressive conditional heteroskedasticity (ARCH) model several studies have use it in modeling financial series. However, when using the ARCH model in determining the optimal lag length of variables the processes are very cumbersome. Therefore, often time users encounter problems of over parameterization. Thus, Rydberg (2016) argued that since large lag values are required in ARCH model therefore there is the need for additional parameters. Sequel to that, this research uses the ARCH-M to solve the challenges. The study reaffirms the direct link of demand for foreign exchange and oil price volatility with exchange rate movements and, therefore, recommends that demand for foreign exchange should be closely monitored and exchange rate should move in tandem with the volatility in crude oil prices bearing in mind that Nigeria remains an oil-dependent economy.

Arima-garch Modeling of Monthly Crude Oil Prices Volatility from Nigeria

“…This is as a result of high fluctuations in crude oil prices. Furthermore, the 10 month ahead forecast of the monthly crude oil price returns using ARIMA (2, 0, 5)-GARCH (1,4) showed an oil with an unstable monthly price movement. Fig.…”

“…Consequently, the ARIMA (2, 0, 5) was used as the conditional mean for the GARCH modeling of Nigeria crude oil price volatility within the period under consideration. It was observed that ARIMA (2, 0, 5)-GARCH (1,4) performed better than other ARIMA (2,0,5)-GARCH models with a minimum AIC of 7.1855. Also, the crude oil price return showed a persistent high volatility, this makes it difficult for Nigerian government to predict and plan her revenue from the sale of crude oil.…”

“…This research work focused on ARIMA-GARCH modeling of monthly crude oil price volatility from Nigeria for the period of January, 2010 to March, 2021. Consequently, ARIMA (2, 0, 5)-GARCH (1,4) model was selected to be the best fit model from other competing ARIMA-GARCH models. The selected model was found to be adequate for short-term forecast of the monthly crude oil price returns from Nigeria.…”