In an oil and gas industry full of acquisitions, divestitures and mergers, it is now more important than ever for an oil and gas producer to carefully plan its portfolio of assets. Efficiency and profitability must be balanced against overall risk. This paper re-introduces portfolio optimization via the efficient frontier theory and also investigates a worked example of portfolio optimization.

Petroleum companies are constantly faced with difficult investment decisions. Made in isolation, these investments will only maximize the value of the individual asset. In order to balance the risk and exploit project synergies, investment decisions should be made collectively. Portfolio optimization using the efficient frontier analysis is an investment decision making technique that quantifies the selection of multiple investment opportunities such that risk is minimized, and value is maximized – over a complete portfolio.

Modern portfolio theory is regarded as among 20th-century finance's most important analytical tools. Portfolio optimization was originally created as a securities investment optimization tool. This is based on the theory that given the expected return and risk of a security, along with its correlation with other securities in a portfolio, a selection of stocks can be chosen that maximizes the return for any level of risk.

Harry M. Markowitz, an economist at the University of Chicago, and William F. Sharpe at Stanford University, were awarded the Nobel Prize in 1990 for over twenty years work with modern portfolio theory. Markowitz’ original 1952 paper1 suggested that each portfolio of assets would have a given level of risk and reward, but that for any level of risk, there was only one portfolio that would return an optimum reward. Conversely, for any level of reward, there would be only one portfolio that would minimize the risk.

The discussion that follows presents the portfolio optimization theory as applied to an oil and gas portfolio of investments.

The worked example will look at a small collection of assets ranging from existing production to wildcat exploration opportunities. In the context of this example, the paper will explore the questions of:

  • What is the best mix of exploration opportunities vs. development opportunities?

  • What is the spectrum of possible outcomes of the portfolio?

  • What is the mixture of return/reward for the different portfolios?

The paper will also present a technique for the empirical generation of the efficient frontier via Monte Carlo simulation.

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