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Key Messages• There is increasing interest in the appraisal ofoptions, as adaptation moves from theory topractice. In response, a number of existingand new decision support tools are beingconsidered, including methods that addressuncertainty.• The FP7 MEDIATION project has undertaken adetailed review of these tools, and has testedthem in a series of case studies. It hasassessed their applicability for adaptation andanalysed how they consider uncertainty. Thefindings are including on the MEDIATIONAdaptation Platform and summarised in a setof policy briefing notes.• One of the tools recommended for adaptationis Portfolio Analysis (PA).• PA is a tool that helps in the design andevaluation of portfolios, i.e. in selecting a setof options which (together) are effective over arange of possible future climates, rather thana single option best suited to one possiblefuture.• The approach allows the identification ofefficient portfolios, i.e. those that have thehighest possible expected return for a givenrisk, or the lowest degree of risk for a givenrate of return. This then provides the investoror decision maker with a choice of alternative(efficient) portfolios, which they can choosefrom based on their risk-return preferences.• The approach has considerable potential foraddressing climate change uncertainty,through the use of portfolios of options ratherthan single solutions. It has a high resonancewith the concepts of iterative riskmanagement in its encouragement ofdiversification (a key part of riskmanagement). The approach can be usedwithin an economic analytical framework andcan also assess portfolios in terms of nonmonetary(physical) effectiveness.• The review has considered the strengths andweakness of the approach for adaptation. Themain strength of portfolio analysis is that itprovides a structured way of addressing(climate change) uncertainty through theidentification of suitable combinations ofoptions that – between them – reduce climateimpacts over the range of impact uncertainty,expressing the effectiveness of alternativeportfolios in quantitative terms.• This provides a way of managing uncertaintythat the analysis of individual adaptationoptions does not allow. It can also assessbenefits in economic or physical terms,allowing application in market and non-marketsectors.• The potential disadvantages are that it isresource intensive, requires a high degree ofexpert knowledge, and relies on theavailability of quantitative data. The approachalso requires the use of probabilities, whichcan prove challenging for the application toclimate change. The technique is obviouslynot relevant when one option addresses thefull range of uncertainty in climate impacts.• Previous applications of PA for adaptationhave been reviewed and a number ofadaptation case studies are summarisedwhich provide information on practicalapplications.• The review and case studies provide usefulinformation on the types of adaptationproblem types where PA might beappropriate, as well as data needs, resourcerequirements and good practice lessons.• PA is a key tool for helping to identify andanalyse alternative portfolios of adaptationoptions. It has a clear application in caseswhere adaptation actions are likely to becomplementary in reducing climate risks.
Portfolio AnalysisIntroductionThere is increasing policy interest in the appraisalof options, as adaptation moves from theory topractice. At the same time, it is recognised thatthe appraisal of climate change adaptationinvolves a number of major challenges,particularly the consideration of uncertainty inthe climate impacts addressed. In response, anumber of existing and new decision supporttools are being considered for adaptation.The European Commission FP7 fundedMEDIATION project (Methodology for EffectiveDecision-making on Impacts and AdaptaTION) islooking at adaptation decision support tools, inline with its objectives to advance the analysis ofimpacts, vulnerability and adaptation, and topromote knowledge sharing through aMEDIATION Adaptation Platform (http://www.mediation-project.eu/platform/). To complementthe information on the Platform, a series of PolicyBriefing Notes have been produced on DecisionSupport Methods for Climate Change Adaptation.An overview of all the decision support toolsreviewed is provided in Policy Briefing Note 1:Method Overview, which summarises eachmethod, discusses the potential relevance foradaptation and provides guidance on theirpotential applicability. The methods consideredinclude existing appraisal tools (cost-benefitanalysis, cost-effectiveness analysis and multicriteriaanalysis), as well as techniques that morefully address uncertainty (real options analysis,robust decision making, portfolio analysis anditerative risk (adaptive) management). It alsoincludes complementary tools that can assist inadaptation assessment, including analyticalhierarchic processes, social network analysisand adaptation turning points. Additionalinformation on each method is presented in aseparate Policy Briefing Notes (2 – 10).This Policy Brief (Note 5) provides a summary ofPortfolio Analysis. It provides a brief synthesisof the approach, its strengths and weaknesses,the relevance for adaptation, how it considersuncertainty, and presents case study examples.It is stressed that this note only provides anoverview: more detailed information is availablein MEDIATION deliverables, and sources andlinks on the MEDIATION Adaptation Platform.Description of the MethodPortfolio Analysis (PA) originated in the financialmarkets as a way of utilising portfolios of assetsto maximise the return on investments, subjectto a given level of risk. The principle is thatspreading investments over a range of assettypes also spreads risks.Since individual assets are likely to have differentand unpredictable rates of return over time, aninvestor may be better in maximising theexpected rate of return and minimising thevariance and co-variance of their asset portfolioas a whole, rather than managing assetsindividually (Markowitz, 1952).As long as the co-variance of assets is low, thenthe overall portfolio risk is minimised (for a givenrate of overall return). Aggregate returns for anindividual investor are therefore likely to behigher when low returns on an individual stockare at least partly offset by higher returns fromother stocks during the same period.PA helps in the design of such portfolios. Ithighlights the trade-off between the returns onan investment and the riskiness of thatinvestment, measuring risk by estimating thevariance (standard deviation) of the portfolioreturn: thus a portfolio with a relatively high (low)variance is judged to have a higher (lower) risk.The information on returns and risks is used toidentify a portfolio that most closely matches(risk) preferences.The overall concepts of the approach are fairlystraightforward, though the actual analysis isquite complex.An investor first identifies those portfolios thatare efficient (from a longer list of all feasibleportfolios). The efficient portfolios have thehighest possible expected return for a given risk,or the lowest possible degree of risk for a givenmean rate of return (Aerts et. al. 2008). Theinvestor is then able to choose a portfolio thatbest represents their balance of preferencesbetween risks and returns.A representation of this choice is given below,plotting the expected return against the variance.In this example, the small circles represent1
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Key Messages• There is increasing
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Method OverviewAs a result there is
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Adaptation Turning PointsLeary, D.
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