This paper uses the Geometric Brownian Motion (GBM) to model the behaviour of crude oil price in a Monte Carlo simulation framework. The performance of the GBM method is compared with the naïve strategy using different forecast evaluation techniques. The results from the forecasting accuracy statistics suggest that the GBM outperforms the naïve model and can act as a proxy for modelling movement of oil prices. We also test the empirical viability of using a call option contract to hedge oil price declines. The results from the simulations reveal that the single-step binomial price model can be effective in hedging oil price volatility. The findings from this paper will be of interest to the government of Nigeria that views the price of oil as one of the key variables in the national budget.
|Number of pages||1|
|Publication status||Published - 6 Apr 2017|
|Event||2nd Annual Research Conference of the Centre for African Research on Enterprise and Economic Development (CAREED) - University of the West of Scotland, Paisley, United Kingdom|
Duration: 6 Apr 2017 → 7 Apr 2017
|Conference||2nd Annual Research Conference of the Centre for African Research on Enterprise and Economic Development (CAREED)|
|Abbreviated title||CAREED 2017|
|Period||6/04/17 → 7/04/17|
- Oil price volatility
- Geometric Brownian Motion
- Monte Carlo Simulation
- Single-step Binomial Price Model
Nwafor, C. N., & Oyedele, A. A. (2017). Simulation and hedging oil price with Geometric Brownian Motion and Single-Step Binomial Price Model. 35-35. Paper presented at 2nd Annual Research Conference of the Centre for African Research on Enterprise and Economic Development (CAREED), Paisley, United Kingdom.