Real Options Analysis

Submitted by Michael Rastall 18th November 2013 15:32


Key Messages

  • There is increasing interest in the appraisal of options, as adaptation moves from theory to practice. In response, a number of existing and new decision support tools are being considered, including methods that address uncertainty.

  • The FP7 MEDIATION project has undertaken a detailed review of these tools, and has tested them in a series of case studies. It has assessed their applicability for adaptation and analysed how they consider uncertainty. The findings have been used to provide information and guidance for the MEDIATION Adaptation Platform and are summarised in a set of policy briefing notes.

  • One of the tools recommended for adaptation is Real Options Analysis (ROA). Options analysis derives from the financial markets, where it has been used to assess the valuation of financial options and risk transfer. The same insights are also useful when there is risk or uncertainty involved with investment in physical assets, hence ‘real’ options

  • Real Options Analysis quantifies the investment risk associated with uncertain future outcomes. It is particularly useful when considering the value of flexibility of investments. This includes the flexibility over the timing of the capital investment, but also the flexibility to adjust the investment as it progresses over time, i.e. allowing a project to adapt, expand or scale-back in response to unfolding events. The approach can therefore assess whether it is better to invest now or to wait – or whether it is better to invest in options that offer greater flexibility in the future.

  • ROA has considerable potential for adaptation, and aligns with the concepts of iterative adaptive (risk) management, providing a means to undertake economic appraisal of future option values the value of information and learning, and the value of flexibility, under conditions of uncertainty. It can therefore justify options (or decisions) that would not be taken forward under a conventional economic analysis.

  • The application to adaptation has often used dynamic programming, which is an extension of decision-tree analysis. This defines possible outcomes and decision points, and assigns probabilities and estimates expected values.

  • The review has considered the strengths and weakness of ROA for adaptation. The key strength of the approach is the information it provides on large investment decisions, allowing economic analysis of the benefits of information and flexibility under conditions of uncertainty. The use of decision trees also provides a useful way to visualise the context of adaptive management. The main disadvantage relates to the complexity of the formal economic approach, which is likely to need expert application and significant resources, and the need to input probabilities and multiple risk points for climate change.

  • Previous applications of ROA for adaptation have been reviewed, and adaptation case studies are summarised. The majority of applications to date have been for large coastal protection projects, though there is also an application for large water projects.

  • The review and case studies provide useful information on the types of adaptation problem types where ROA might be appropriate, as well as data needs, resource requirements and good practice lessons. This identifies that ROA is most useful for large capital investments (project level), especially where there is a large adaptation deficit or a significant potential for learning or flexibility. It also requires good quality data on climate risks and cost/benefit components. Given the high resource requirements, the review also identifies the potential for more informal application of ROA, e.g. through the use of decision trees and more qualitative analysis of information and flexibility. 

Suggested Citation

Watkiss, P. and Hunt, A, Blyth, W (2013). Real Options Analysis: Decision Support Methods for Adaptation, MEDIATION Project, Briefing Note 4. 

The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 244012.