Abstract
Abstract Over the past few years the global oil and gas industry has been going through a severe market downturn. Despite recent signs of stabilization, oil prices have a long history marked by volatility. In this context, it is imperative for oil companies to optimize their capital allocation, as this might support risk mitigation. The purpose of this paper is to offer a tool that might support the strategic decision-making process for companies operating in the oil industry. Our model uses Markowitz’ portfolio selection theory to construct the efficient frontier for currently producing fields and a set of investment projects. These relate to oil and gas exploration projects and projects aimed at enhancing current production. The net present value is obtained for each project under a set of usersupplied scenarios. For the base-case scenario we also model oil prices through Monte Carlo simulation. We run the model for a combination of portfolio items which include both currently producing assets and new exploration projects, using data characteristics of a mature region with a high number of low-production fields. Our objective is to find the vector of weights (equity stake in each project) which minimizes portfolio risk, given a set of expected portfolio returns. The model is of particular interest for companies operating in Eastern Europe, or in any other mature region. It can also support divestment and acquisition decisions since these may place the company’s portfolio closer or farther away from the efficient frontier. The model is highly versatile and can be implemented on any software with an optimization package such as Microsoft Excel.
Highlights
The performance of every company is affected by the dynamics of its environment
Our objective is to find the vector of weights for each portfolio item which minimizes the portfolio variance (1) subject to a portfolio expected return (2) and capital expenditure (CAPEX) (3) constraint
The stochastic simulation of the first approach may seem useful given the unpredictability of the oil price, but unlike this method which takes random numbers from the normal distribution, any scenarios used will not be random
Summary
The performance of every company is affected by the dynamics of its environment. For companies operating in commodity industries, external factors can be highly volatile. Despite currently displaying some signs of stabilization, in recent years the volatility on this market has been extreme, with oil prices coming down from highs above 100 dollars per barrel in September 2014 to lows under 30 dollars per barrel in January 2016 This is not a new development as significant price swings have been seen during the 2008 financial crisis. An event such as a major financial meltdown affects the entire global economy, but the oil market is susceptible to geopolitical events, especially those occurring in major producing countries.
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