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|Title:||Portfolio Optimization: Living Up to Expectations|
|Citation:||SPE Hydrocarbon Economics and Evaluation Symposium (2003, Dallas, Texas) pp.45-54.|
|Publisher Place:||Dallas, Texas|
|Conference Name:||SPE Hydrocarbon Economics and Evaluation Symposium (05 Apr 2003 - 08 Apr 2003 : Dallas, Texas)|
|Abstract:||<jats:sec> <jats:title>Abstract</jats:title> <jats:p>This paper addresses some of our experiences in working with practitioners dealing with the adoption and implementation of formal risk and portfolio decision methods. The emergence of project investment case histories based on formal Decision and Risk Assessment (D&RA) methods provides a mixed bag of results. Though generally better than historical deterministic methods, the failures are just as illuminating as the successes. In our analysis of the case histories, we find that some of the failures can be attributed to several simplifications formalized in the process. In this paper we explore the impacts of three areas of simplification that, whilst well-intentioned, have potential to cause adverse initial reactions by professionals and management.</jats:p> <jats:p>The first simplification covers the handling of the quality and validity of the input data used to generate the output metrics ultimately forming the foundation of the portfolio decisions. We show that ignoring intra-asset dependencies, or worse, using a P10,P50, P90 characterization derived from a base case plus an upside and downside (or even just guestimates) significantly distorts the real NPV distributions.</jats:p> <jats:p>The second area arises from simplifying or ignoring the dependencies (or correlations) between the various assets. These inter-asset dependencies may be regional, fiscal, financial, global, technical, or life-cycle, to name but a few.</jats:p> <jats:p>The final area of simplification is in optimizing against the expected value of the portfolio. The issue here is that there really is a distribution of possible returns for any given level of risk. If there are binding constraints then there is a substantial probability that the expected return will not be achieved. (This is analogous to the arguments that insist we need to look at the full distribution of NPV for an individual asset, not just its expected value). This problem can be overcome by applying stochastic optimization techniques.</jats:p> <jats:p>Using a typical suite of assets that a company might select a portfolio from, we demonstrate that these simplifications cause some very real and, economically, very significant concerns. They result in selection of a sub-optimal set of assets and participation levels, which potentially leads to a different portfolio risk profile and lower returns than expected.</jats:p> <jats:sec> <jats:title>Introduction</jats:title> <jats:p>The industry's interest in formal Decision and Risk Assessment (D&RA) over the last few years has been quite amazing. Overcoming the barriers to adoption of these methods', including cultural change, continues to amaze even the most devout practitioners. Whether the drivers for accepting change emanate from the fluctuating business climate that has been motivating recent mergers, political risks, a historical record of underperformance or just continued evolution of business practices, the desired objective remains the same - making good investment decisions.</jats:p> <jats:p>The growing popularity of D&RA - as indicated by the number of SPE sponsored forums and ATWs, alliances and industry courses on the subject and the general uptake of the language, like P10 and P90 - support the increasing awareness of D&RA methods as a mechanism for improving industry performance. The underperformance of petroleum stocks relative to the entire stock market has been cited by several to justify the even greater adoption of D&RA methods. Though artificial bubbles in telecommunications, dotcoms, and energy trading certainly explains part of the underperformance of traditional industry stocks, like petroleum, serious questions remain about the industry's ability to actually achieve the performance in its investments that is promises in its evaluations. The gap between the promises and performances and possible causes for the gap form the foundation of this paper.</jats:p> <jats:p>Applying D&RA methods to actual investments provides some lessons - some good and some less so - that provides an opportunity to reinforce some historical lessons about formal risk methods. One application of formal D&RA methods, Figure 1, demonstrates the actual performance for a capital expenditure relative to its forecasted distribution. The subjective distribution indicates the cost estimate range conveyed to management, with the written guarantee that costs would not go above $600 million. The solid, vertical line shows the actual expenditure. Such a significant underestimate of actual costs is not supposed to happen with D&RA; yet, this and other post appraisal comparisons, we have seen, suggest that something is amiss.</jats:p> </jats:sec> </jats:sec>|
|Appears in Collections:||Australian School of Petroleum publications|
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