December 2020 / Multi-Asset And ESG ESG In Strategic Asset .
December 2020 / Multi-Asset and ESGESG in Strategic Asset Allocation (SAA): A practicalimplementation frameworkAuthors: Gunnar Friede, Guido Lombardi, Peter Warken, Jason Chen, Dirk Schlüter, Robert Bush,Francesco CurtoMuch research has been made in the past few years abouthow to integrate ESG in various asset classes; however, ESGresearch on a total portfolio level—or strategic assetallocation (SAA) level—is still very limited. As a 2019 PRIpublication put it, the integration of ESG aspects in SAA “isan area that has received relatively little coverage about whatit should mean in practice”1.This study seeks to address the current blind spot of researchto further facilitate ESG integration comprehensively at anoverall multi-asset portfolio level. The specific objective is on(i) understanding the potential impact of integrating ESGfactors on risk adjusted returns, (ii) what is the best approachto pursue to minimise impact. Our analysis concludes thatit is possible to have portfolios that reduce significantlyESG risks without meaningfully different risk-adjustedreturns vs traditional index SAAs at relatively low levelsof tracking error (“TE”). We estimate that the optimal ESGimpact can be achieved for TEs between 75 and 100bps,although an investor’s preference between their risk budgetand ESG utility function will determine their appropriate tradeoff between these two measures. Other findings: ESG integration can be run for either individual assetclasses or at a total portfolio level. The combinedapproach (optimizing the SAA and implementing viaESG indices) is the most efficient approach from thestandpoint of total ESG utility versus tracking error. Basic integration optimized across regional indices,sector indices and ESG Indexes provides different levelsof ESG improvement that depend highly on index/fundselection. The impact can vary from a reduction of 10%to F-rated (highest risks) stocks and carbon intensity toas much as 80% and 50% respectively for the sametracking error of 25bps. Changes in regional weights (e.g. having much moreEurope vs US than in the standard market cap-weighted12portfolio) improves the portfolio ESG characteristics onlyslightly. Better (ESG) results can be achieved constructing theSAA with traditional sector indexes instead of regionalones. Much better results can be achieved overall withallocating to ESG indexes. In this latter case, the shareof worst ESG-rated securities2 can be reduced by ca.80% and the carbon footprint by 50% vs the traditionalSAA – for tracking errors as low as 0.25%.In the spirit of simplicity and wide applicability, our work hasbeen focused primarily on liquid global asset classes forwhich there exist a replicable set of underlying indices. Assuch, we established this framework by leveraging readilyavailable passive ESG indices, which we find sufficient inachieving the various parameters such as climate riskalignment. While we recognize that alternative asset classesand instruments can play a significant role in enhancing theESG characteristics of a strategic portfolio, this framework isfocused on presenting an intuitive, implementable solution forliquid asset allocations.Literature ReviewThe existing work on ESG in SAA correctly identifies most ofthe principal issues for comprehensive ESG integration intoasset allocations; however discussions remains at apreliminary stage, stopping short of providing a simpleenough, yet widely applicable toolkit for effective ESG multiasset portfolios. Much research on this topic has focused onhighlighting the peculiarities one would have to consider for amore ESG-advanced SAA for different types of investors: e.g.how this exercise can be applied to Liability Driveninvestments, across different optimization techniques 1.Furthermore, both empirical and forward-looking researchsuggest a sanguine outlook for ESG investing in terms ofPrinciples for Responsible Investment. (September 2019). “Embedding ESG Issues into strategic asset allocation frameworks: Discussion paper.”Ratings are based on the DWS ESG Engine. See appendix for more details.MARKETING MATERIAL: For Qualified Investors (Art. 10 Para.3 of the Swiss Federal Collective Investment Schemes Act (CISA)) / For Professional Clients (MiFIDII Directive 2014/65/EU Annex II) only / For Australia: For wholesale Investors only. For institutional investors only. Further distribution of this material is strictlyprohibited. In the U.S. and Canada for Institutional Client and Registered Representative Use Only. Not for public viewing or distribution. Any hypothetical resultspresented in this report may have inherent limitations. Among them are the sharp differences which may exist between hypothetical and actual results which maybe achieved through investment in a particular product or strategy. Hypothetical results are generally prepared with the benefit of hindsight and typically do notaccount for financial risk and other factors which may adversely affect actual results of a particular product or strategy. Any forward looking statements (forecasts)are based on but not limited to assumptions, estimates, projections, opinions, models and hypothetical performance analysis. All of which are subject to change atany time, based upon economic, market and other considerations and should not be construed as a recommendation.
December 2020 / DWS Research Institutefinancial performance. DWS [2020]3 demonstrates ex postalpha across regional ESG indices was positive, and in somecases, statistically robust. Blackrock [2020]4 argues on hownew ESG trends and asset flows have been impactingexisting returns and will possibly result in newly emerging riskpremia across asset classes. Aberdeen Standard [2019]5posits on how a well-constructed SAA ESG aligned portfoliowould not necessarily result in lower expected returns and/orworse risk adjusted outcomes. Mercer [2019]6 specificallyhighlights the importance of analysing and mitigating ClimateChange risks in asset allocation decision making, which wehave also considered in our work via measuring a fewdifferent climate change-related ESG impact criteria. Finally,we also reviewed in depth the more inclusive ESG SAAapproaches vs those targeting the exclusions of somespecific asset classes, which might still be lagging in terms ofESG quality, from the asset allocation mix, a questionsimilarly posed by Schroders [2019]7.Further elaborating on these research pieces and the PAII,we wanted to add to the discussion more defined targets andvery practical outputs and implementable solutions. Bydeveloping this work, as per the summary/conclusions above,we find that not only do the final proposed portfolios achievethe desired ESG characteristics and substantialimprovements, but that they also do so within a reasonabletracking error budget, which we can break down transparentlyby scenario and asset class.DWS Approach to ESG in SAAIf investors want to assess the ESG implications on astrategic asset allocation level, they have to overcomeseveral restrictions, as the ESG impacts, because ofcomplexity, are often only measured on a portfolio subcomponent basis. Therefore a holistic view of portfolio ESGimpact is essential for comprehensive portfolio constructionof ESG portfolios.On the aforementioned point of inclusive versus exclusiveESG SAA approaches, we take the more inclusive approach.First, ‘ESG integration’ as for PRI is primarily a riskmanagement approach, i.e. the purposes is to ensure that themateriality of ESG risk is properly taken into account and theimpact on risk adjusted returns is properly considered.Second, we demonstrate that, with appropriate ESG Indexesand tilts, most of the traditional asset classes can be stillpresent within a very ESG-ambitious SAA framework. Wehave also taken stock of all the other issues discussed in ourliterature review, and while deferring the more macroconsiderations and work on strategic ESG risk premia to afuture paper, it is worth mentioning an additional andimportant aspect which we have added to the discussionhere. Specifically, we found that most of the proposedsolutions did not delve enough into the practicalities of suchESG-integrated SAAs and how these would be differentversus the more traditional SAAs and, ultimately, on what thiswould mean in terms of risk budget and tracking error for theaverage investor.DWS’ participation into the Paris Alignment InvestmentInitiative (PAII) and into its SAA work stream, morespecifically, has been another crucial milestone informing ourwork. The PAII is a program spearheaded by the InstitutionalInvestors Group on Climate Change (IIGCC), with over 70global investors (AMs and institutions) representing morethan 16 trillion in assets. In particular, we have fully factoredin the strategic prescription of the PAII of including specificESG metrics (and carbon emissions metrics, morespecifically) in the optimization process alongside the moretraditional portfolio risk, return, and correlation parameters.We will explain in the following how the SAA portfolio carbonfootprint has indeed been a key optimization metric across allthe various scenarios considered.With this framework, we are explicitly targeting alignmentbetween best-in-class Multi-Asset ESG integration and theDWS CIO framework, resulting in applicability in a variety ofcontexts. The aim is strategic, as ESG trends and implicationfor the various asset classes are mostly long-term andstructural in nature. As such, we choose not to focus on ESGtactical asset allocation (TAA) implications at this juncture.Starting points and potential challengesThe impact varies in dependency of the recalibrationapproach, the selected indices/universe, data availability,degrees of freedom, the ESG restrictions and different ESGtarget functions, the traditional risk/return restrictions, and thepotential trade-offs between ESG and financial metrics. Assuch, exploring this trade-off across a few simulatedapproaches allows investors to determine the appropriateESG SAA construction methodology by the comparingempirical output of both financial and ESG metrics for avariety of possible steps of ESG optimization.Last but not least, it is necessary to assess a representativeglobal investment universe not only on an ex-post basis, butalso on and ex-ante basis which requires a sophisticatedreturn forecasting model like the DWS Long Term CapitalMarkets Assumptions (LTCMA) framework.MethodologyOur methodology for ESG SAA constructions follows a fewsteps:1.2.Define the subset of appropriate asset classes andESG indices on which to construct ESG SAAs. ESGimplementation can take on a variety of differentcharacteristics. Therefore, for the purposes oftransparency, investability, and liquidity of our ESGSAAs, we chose the list of indices highlighted in thefollowing section on which to run our analysis.Define and quantify ESG metrics. In order to properlyaccount for various ESG metrics, we utilize a step-by-DWS Research Institute, (March 2020). ‘ESG investing – getting under the hood’.Sustainability: The tectonic shift transforming investments- BlackRock, February 20205Aberdeen Standard Inv. (October 2019). ”Strategic Asset Allocation: ESG’s new frontier”6Mercer (2019). “Investing in a Time of Climate Change – The Sequel”7Schroders, (May 2019). “The practical considerations of ESG in multi asset portfolios”342
December 2020 / DWS Research Institute3.4.5.step optimization of which each step incorporates anadditional ESG metric on which to optimize our SAAs. Inaddition, we illustrate how investors can increase theimpact across ESG metrics if they have increasedflexibility in their mandates in terms of tracking error.Establish risk parameters for initial optimizations.Maximum deviations of regions/sectors/sub-assetclasses of maximum 4x weight/minimum 1/4 weight ofthe traditional SAA. Absolute portfolio risk is controlled tomatch the volatility of the reference allocation of 50/50Equity/Fixed Income.Define our target scenarios based on ESG metrics andrisk parameters. See Figure 2.Run the optimizations for every scenario S1 to S4 fortraditional indices, sector indices, and ESG indices fortracking errors ranging from 25bps to 250bps in 25bpsincrements. In each of the scenarios, we maximize theESG composite score8 subject to the risk constraints.For our methodology, we ran each of the three followingiterations in order to compare results across different initialapproaches:1.2.3.Optimization within traditional regions/sectors/assetclassesReplacement of traditional regions/asset classes withESG versionCombined optimizations (main results section)Defining the index universeESG investing can take many forms, through either active orindex-based investing, through liquid public markets orthrough illiquid private investments, through exclusion criteriaor via impact scores. For the purpose of this analysis whichdetails DWS’ approach to creating liquid global strategicasset allocations, our empirical studies leverage a set of ESGmarket indices that are: investible, liquid, and transparent.FIGURE 1. EMPIRICAL RISK, RETURN, AND TRACKINGERROR OF ESG lityTE of ESGvs.standardindexMSCI USA ESG13.4%14.2%1.7%MSCI USAIndex14.2%14.7%MSCI Europe ESG4.9%13.0%MSCI Europe3.4%13.4%MSCI Japan ESG9.9%13.9%MSCI Japan9.4%13.7%MSCI EM ESG9.5%14.9%MSCI EM6.6%14.8%1.8%1.5%Euro Govt. ESG3.8%4.1%Euro Govt.3.8%4.2%US Treasury ESG2.0%3.8%US Treasury2.0%3.8%Euro Corp ESG2.6%3.8%Euro Corp2.7%4.0%US Corp ESG5.9%6.2%US Corp3.3%5.5%Euro HY ESG3.3%7.0%Euro HY3.5%7.3%US HY ESG7.6%9.2%US HY7.4%9.1%EM Sovereign ESG8.4%9.2%0.1%0.0%0.2%1.1%0.5%1.0%1.5%Source: DWS Investments UK Limited. Data from April 30 2014 to September 30 2020. Pastperformance is not a reliable indicator of future returns.The reference universes for the analysis are the MSCI ACWorld for equities and the Barclays Global Multiverse forbonds. The default allocation is determined by the currentweights of regions, sectors or sub-asset classes in theseindices. The equity/bond allocation is set at a static 50/50ratio. We have also calculated all scenarios with a dynamicequity/bond weighting. However, since the ESG effect is, inthis case, potentially distorted by allocation shifts, we apply astatic asset class weighting. The ESG optimization isperformed separately within the equity and fixed incomecomponents. The ESG metrics for the full index referenceuniverse for the traditional index components, as well as theESG equivalents is displayed in the appendix (Figure 10).On the equity side, the MSCI ESG Leaders indexes wereidentified as ensuring good ESG characteristics while at thesame time keeping the tracking error to the original/non-ESGindexes within a reasonable range. For these indexes, the top50% of companies in the ESG distribution are selected andthere is a further emphasis on low carbon emitters which atheme of outmost importance at DWS. Furthermore, whenlooking at the exclusions and UN norms alignment embeddedinto these indexes, we found a good degree of homogeneitywith the DWS ESG assessments.On the FI corporate (European IG) side, we chose theBloomberg Barclays MSCI Euro Sustainable and SRI TR,and the Bloomberg Barclays MSCI US Liquid CorpSustainable Index for the US IG Corporates asset class.In conjunction with these indices, DWS offers a broad set ofbest-in-class passive ESG solutions that can be used topractically construct these SAAs with relative ease.2.7%8For the indices of the asset class universe the quantified ESG scores (step 2) are joined in an ESG raw data matrix. By using the median 8 score of each metricand by using the weights of a reference allocation (benchmark), the raw data is normalized to ensure comparability. A scenario-specific scaling vector (step 4) isthen applied to the normalized ESG score matrix in order to assign the relative importance to each metric in the corresponding scenario. Finally, the ESGComposite Score is defined as weighted average of this normalized and scaled ESG score matrix and a portfolio allocation.By comparing the ESG Composite Score of two different allocations, a higher ESG Composite Score indicates a better ESG profile in the specific scenario (andvice versa). The optimization process aims to find the allocation that yields the maximum ESG Composite Score, i.e. the best ESG profile in the correspondingscenario.3
December 2020 / DWS Research InstituteDefining and quantifying ESG metricsFor our analysis, we find that the above subset of ESGindices can be used to establish a deep, impactful approachthat is consistent with our firm wide policy, which placessignificant focus on the climate change and engagementtopics along the lines of the UN Sustainable DevelopmentGoals (SDGs). Certain exclusions are also enforced acrossthese indices and, by consequence, our ESG SAAs (e.g.controversial weapons exclusion “CCW”).We recognize that our findings are based on parameterswe’ve established as meaningful but not absolute levels ofESG compliance; therefore, investors can toggle the ESGgoals we’re using as they deem fit. For our purposes, wedefine the below three methods of application for our ESGSAAs.Establishing risk parametersAs with ESG metrics, we recognize that investors can toggletheir relative and absolute risk criteria based on desiredoutcomes. In combination with ESG metrics, utilizing ouroptimization framework, one should be able to establish thetrade-off between risk and ESG efficacy.For the purposes of our analysis, we establish a simple set ofrelative risk parameters. First, we limit the maximumdeviations of the regions, sectors, and asset classes at amaximum of 4 times and minimum of ¼ times the weight ofthe traditional reference SAA. Absolute portfolio risk is madeequivalent to the reference allocation of a static 50/50traditional equity/fixed income allocation. We control therelative portfolio risk - the expected tracking error of theoptimized vs. reference allocation - to not exceed the definedTE limits.Defining the target scenarios based on ESG metrics andrisk parametersOnce we’ve established the appropriate index universe, theESG proper metrics, and clear parameters around relativeSAA risk, we define our target scenarios around thosedefinitions as shown in Figure 2.FIGURE 2. DEFINITION OF TARGET SCENARIOS BASED ONESG METRICS AND RISK PARAMETERSScenariosS1: Minimize Climate Transition Risks (“CTR”) and UNGlobal Compact (“UNGC”) risks via excluding F-ratedsecurities in the respective categories (Basic ESGIntegration)S2: (additionally) Minimize DWS Overall ESG Score Frated securities (S1 S2)S3: (additionally) Minimize CO2 intensity, maximizeSolutions Provider (A and B-rated securities for SDGRatings and CTR-Ratings (S1 S2 S3)S4: (additionally) Minimize controversial sectors minimize DWS Overall ESG Score for E-ratedsecurities (S1 S2 S3 S4)Source: DWS Investments UK Limited.We concentrate in the presentation of the results section onscenario 1—the basic optimization—and scenario 4.Scenario 4, as the most comprehensive ESG optimization,includes minimizing the carbon footprint, controversialactivities, and further weak ESG-rated securities and alsooptimizes positive criteria such as the share of solutionproviders.For the calculation of the ESG utility in the various scenarioswe normalize the respective ESG values. For thepresentation of the partial ESG utility (e.g. the share in Fratings, CO2 intensity) and the total ESG utility(improvements across different ESG criteria) we show theweighted overall improvements in percentages.This analysis is three-fold. First, assessing the ESG qualityof the unconstrained asset allocation along standard ESGparameters, the level of carbon risks and compliance withthe UN Global Compact norms. This analysis is carried outon a look-through basis across the incorporated indexholdings.As a second step, we perform a trim-and-fill analysis wherewe underweight
ESG quality, from the asset allocation mix, a question similarly posed by Schroders [2019]7. DWS Approach to ESG in SAA On the aforementioned point of inclusive versus exclusive ESG SAA approaches, we take the more inclusive approach. First, ‘ESG integration’ as for PRI is primarily a risk
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