M O D E L I N G O I L P R I C E S I N N A M I B I A N M A R K E T U S I N G Q U A N T I TAT I V E T E C H N I Q U E S - nangolo, w.; gnitchogna, r.b.; gideon, f.; lungu, e. (IJRDO-Journal of Applied Science, 2017)
This paper contributes to the debate on oil prices modelling by proposing a quantitative analysis of the dynamics of nominal oil prices in Namibia. The study carries out a post assessment and validation of Random Walk and Mean Reversion processes in modelling and forecasting futures dynamics of nominal oil prices . In this regard, the study used data from the Namibian oil market from April 1989 to April 2014. In essence, despite the recent trends of computational and VAR models for nominal oil prices, modelling and forecasting efforts have circumscribed random walks or mean reversion models as viable options. Popular baseline and benchmark models include Random Walk, Random Walk with drift, AR, MA, ARMA models. The study investigates the suitability of the models in capturing and predicting the data behaviours. Analysis are conducted on chosen sub-period as well as on the overall data. From our results, a major highlight is that there is enough evidence to conclude that oil nominal prices in Namibia are indeed stationary and therefore suitable for analysis. The results also indicated an increasing stochastic trend that confirms that oil prices behave randomly at times. Summary analysis pointing to the fact that oil prices are mean reverting with occurrences of random walk.