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 aquantitative analysis of the dynamics of nominal oil prices in Namibia. Thestudy carries out a post assessment and validation of Random Walk andMean Reversion processes in modelling and forecasting futures dynamicsof nominal oil prices . In this regard, the study used data from the Namibianoil market from April 1989 to April 2014. In essence, despite the recenttrends of computational and VAR models for nominal oil prices, modellingand forecasting efforts have circumscribed random walks or mean reversionmodels as viable options. Popular baseline and benchmark models includeRandom Walk, Random Walk with drift, AR, MA, ARMA models. Thestudy investigates the suitability of the models in capturing and predictingthe data behaviours. Analysis are conducted on chosen sub-period as wellas on the overall data. From our results, a major highlight is that there isenough evidence to conclude that oil nominal prices in Namibia are indeedstationary and therefore suitable for analysis. The results also indicated anincreasing stochastic trend that confirms that oil prices behave randomly attimes. Summary analysis pointing to the fact that oil prices are mean revertingwith occurrences of random walk.