Analysis of return on investment in some Niger-Delta oil field projects: using the variance-gamma process

Chisara Peace Ogbogbo

doi:10.4314/gjpas.v25i1.9

Abstract

Oil field development projects face market risks, largely because the parameter of key importance, the oil price, fluctuates rapidly over time. The decision to invest or not in an oil field project is therefore very challenging, because information concerning the field is often scarce. Neither the future production, nor sales prices are known with certainly. Constraints on production level also exist, in addition to OPEC quota, which is used in this work as proxy for other production limitations. The price process that best describes the fluctuations in oil price is expected to yield better analysis with respect to expected returns (viability of the project). The Variance Gamma process which is a subordinated Lévy process effectively captures jumps in a process. Thus, Variance Gamma process and a mean reverting process are considered in the analysis. The expected revenue was found to be higher, when the variance Gamma process is used as the model for oil price. This indicates that the variance Gamma process performs better than the Ornstein-Uhlenbeck process as a model for oil price. It therefore provides a good basis for price forecasting, and optimality of investment decision.Keywords: Variance Gamma Process, Mean Reverting Process, Parameters, Niger-Delta Oil Field Projects, Expected Return, OPEC constraint

Highlights

This paper discusses findings that emerged while seeking an answer to a different question
A computational attempt is made at obtaining maximum return, using two different price processes: - a mean reverting process, and a subordinated Levy processes, the Variance Gamma, (VG) process
This is done in the face of Organization of petroleum exporting countries, OPEC constraints, which is a proxy for other production limitations

Summary

INTRODUCTION

This paper discusses findings that emerged while seeking an answer to a different question. A computational attempt is made at obtaining maximum return, using two different price processes: - a mean reverting process, and a subordinated Levy processes, the Variance Gamma, (VG) process This is done in the face of Organization of petroleum exporting countries, OPEC constraints, which is a proxy for other production limitations. Brief Review of Work on Oil Price Modeling and Useful Information about OPEC Quota Crude oil price futures have been studied by Krichene (2006), (2008) He modeled oil futures price returns as a Lévy process, in particular as a Variance Gamma process. S୲ = S଴exp ሾμt + X୲ሿ He used data on daily oil futures prices January 2, 2002July 7, 2006, to estimate the parameters of the VG process using Empirical characteristic function, ECF He obtained the following parameters Drift μ, Skewness α, Volatility σ, Variance of VG, ν.

Mean Reverting process

Ornstein-Uhlenbeck Process

The Variance Gamma Process

CONCLUSION