Case study by Rockefeller Asset Management

In the spirit of showcasing leadership and raising standards of responsible investment among all our signatories, we are pleased to publish case studies of all the winning and shortlisted entries for the PRI Awards 2021.

Introduction: provide a short overview of the practice, process or product that is being proposed for the award

Rockefeller Asset Management (RAM) takes the view that investors will increasingly differentiate between ‘ESG Leaders’ and ‘ESG Improvers’, namely those firms showing the greatest improvement in their ESG footprint, and that these Improvers offer potential to generate uncorrelated alpha over the long run. After nearly two years of research, RAM built a proprietary process, which it calls Rockefeller’s ESG Improvers Score (REIS), to calculate a firm’s ESG trajectory.

A backtested, hypothetical portfolio of top-quintile ESG Improvers outperformed bottom-quintile ‘ESG Decliners’ by an average of 3.8% annually, in an analysis covering US all-cap equities from 2010 to 2020. The ESG Improvers factor generated excess returns even after controlling for other factor and sector biases and demonstrated correlation benefits when combined with traditional investment factors such as quality, low volatility and value.

The approach proved to have three wide-reaching implications for RAM, and led to its first quantitative multi-factor strategy:

  1. On product development, RAM partnered with Bloomberg to launch the first-of-its-kind Bloomberg Rockefeller Multi-Factor ESG Improvers strategy;

  2. In ESG integration, RAM used the approach to enhance its long-only and long-short fundamental research and idea generation process; and

  3. Regarding stewardship, the approach informs RAM’s engagement approach that seeks to create shareholder value and catalyse positive ESG improvement.

Process, practice or tool: Provide a description of the innovative approach to ESG incorporation, its coverage within your firm, why you decided to undertake this approach and the value it provided preferably using a practical example of how you have applied your approach to an investment (security/issuer/sector/asset class/portfolio) (600 words)

Rockefeller Asset Management’s ESG Improvers approach is based on its proprietary materiality assessment which spans the 77 SICs (Standard Industrial Classification) industries. The approach was developed in collaboration with equity and ESG analysts and is based on guidance from the Sustainability Accounting Standards Board. RAM then conducted an extensive data-mapping project to determine which metrics best quantify each material ESG issue.

After integrating various data providers, its analysts utilised academic imputation best practices to approximate missing values and developed a quantitative process to determine material issue weights, referred to as the Rockefeller ESG Relevance Ranking. Material ESG issues can have varying impacts on financial performance. Weights are therefore adjusted based on the statistical significance of regressions investigating the relationship between financial performance and material ESG metrics.

RAM then constructed the REIS to isolate the component of a firm’s ESG trajectory unexplained by variables such as return on assets, market cap, geography and sector. The process allows RAM to quantitatively assess a firm’s ESG trajectory. Backtested results indicate that ESG Improvers generate alpha on a standalone basis and enhance the signal of traditional multi-factor portfolios.

RAM’s investment analysts have long used ESG Improver analysis to enhance the fundamental research process, contributing to stocks either entering or not being considered for investment in bottom-up actively managed strategies. They believe that there is strong economic and market rationale for investing in ESG Improvers:

  • Improving ESG practices help to increase brand value, enhance customer and employee loyalty, reduce costs and create competitive advantage;
  • The market will continue to undervalue improvers;
  • Future ESG leaders may command a premium as investors reward sustainable firms; and
  • The ESG Improvers process represents an assessment of management quality.

RAM embarked on this research project two years ago to better assess the risk and return ramifications of ESG information and test its hypothesis about ESG Improvers. The underlying data, material issue weights and ESG Improvers scores for around 3,300 companies, spanning 23 developed markets, are now distributed via an online interface to all analysts and portfolio managers representing roughly 80% of RAM’s asset under management.

REIS has wide reaching applications across RAM’s platform of strategies:

  • Portfolio managers and analysts use REIS to enhance the research and idea generation process. Practical applications occur weekly as analysts assess a firm’s ESG trajectory in stock pitches using REIS.
  • The Bloomberg Rockefeller U.S. All Cap Multi-Factor ESG Improvers strategy, launched in December 2020, combines REIS with quality and low volatility factors to pursue outperformance over traditional market-cap weighted indices with low tracking error and minimal sector or other factor deviations. Given REIS is one of the three factors used, all security selection is impacted by REIS.
  • In October 2020, RAM launched the VantageRock Long Short Equity strategy, one of the few ESG integrated long-short strategies in the market. The portfolio managers incorporate REIS and the ESG Improvers philosophy within their research and idea generation process, sourcing long ideas from top quintile Improvers and short ideas from bottom quintile Decliners. One particularly innovative application is sourcing short candidates from ESG Decliners.
  • Shareholder engagement is a key component of RAM’s approach for multiple strategies. RAM’s managers believe that constructively engaging with companies to improve their ESG footprint will lead to stronger financial performance over time. REIS helps assess and inform their shareholder engagement targets and priorities.

Outcomes, benefits, challenges and next steps: provide an example of the outcomes, outline the benefits and challenges associated with the introduction of this initiative and what you have learned from this approach that can be applied more broadly. How might you intend to develop the process or practice? (500 words)


  • Alpha: Top quintile ESG Improvers outperformed the Bloomberg US 3000 Index by 3.0% annualised, while decliners underperformed by -0.8% annualised in analysis covering US equities from 2010 to 2020. The signal is monotonic, in that outperformance grows with each quintile. On a risk-adjusted basis, top and bottom quintile information ratios were 0.8 and -0.2, respectively. When tightly controlling for sector and other factors biases such as size, value, momentum, growth, quality, etc., RAM found that a portfolio tilting toward REIS with low tracking error generated 0.5% annualised excess returns over the same period. Performance attribution shows returns were generated predominantly from an unexplained security selection effect. From a fundamental investor’s standpoint, RAM also believes the enhancements to its research and idea generation process contributed to positive performance.

  • Correlation benefits: The ESG Improvers factor showed low or negative excess return correlations when assessing daily excess returns relative to the Bloomberg US 3000 Index. Using Bloomberg’s Fundamental Factor Model, correlations between growth, size, momentum and value were 0.04, -0.13, -0.09 and 0.24, respectively. As a result, incorporating REIS with a two-factor quality and low volatility portfolio enhanced excess returns by 0.45% annualised and the information ratio by approximately 50%. More pronounced risk and return benefits occurred when incorporating REIS with value and momentum factor portfolios.

  • New innovative strategies: As mentioned above, REIS was critical in the creation of the Bloomberg Rockefeller U.S. All Cap Multi-Factor ESG Improvers quantitative strategy and was integrated into the VantageRock Long-Short Equity fundamental strategy.

  • Engagement process: The score and underlying data is leveraged by RAM’s engagement team to help drive shareholder value and catalyse ESG improvement.

(The performance information presented is from hypothetical backtested results. See the disclosures and methodology below for additional information regarding the universe, methodology and inherent limitations.)

Challenges: The investment team faced two major challenges in developing the factor:

  • While the methodology was grounded in academic research from George Serafeim, a Harvard professor and leading ESG academic, there had been little practical application of quantifying ESG improvement and integrating it with traditional investment factors in a live environment.
  • ESG data suffers from limited history, coverage gaps and inherent biases, increasing the importance of data mapping, imputation and controlling for unintended exposures.

Improvements: Next steps for advancing the methodology and process include:

  • Understanding the risk and return implications across geographies, publishing the results of RAM’s recent analysis covering 23 developed equity markets, and extending the research to emerging markets.
  • While REIS quantifies and integrates environmental material issues such as air quality, physical climate risk, climate transition risk, energy management and GHG emissions, and social issues such as diversity, equity, and inclusion, RAM has yet to explore the implications of combining REIS with decarbonisation and 2°-aligned strategies.
  • Quantitatively connecting the ESG Improvers approach with RAM’s shareholder engagement process for systematic multi-factor strategies.
  • Attempting to expand the research to other asset classes including municipal, corporate, agency and government bonds.

Important Disclaimers

The content and information contained in this submission is suitable for professional and institutional investors only and is not intended for and may not be read and relied upon by other persons or redistributed to retail investors. These materials may not be reproduced or distributed without Rockefeller Capital Management’s prior written consent. Materials are for informational purposes only and not as research report or recommendation to buy/sell securities, to adopt investment strategy, or to constitute accounting, tax, legal advice. The Rockefeller ESG Improvers Score TM and Rockefeller ESG Relevance Ranking TM are trademarks of Rockefeller Capital Management. We continue to refine our methodology with these scores and rankings, as findings presented are subject to change. Forward-looking statements are uncertain, future events may differ materially.

Performance for hypothetical portfolio is backtested and does not represent the performance of any index or any managed account, but were achieved by means of the retroactive application of the methodologies described herein, certain aspects of which have been designed with the benefit of hindsight. Examples of back-tested performance have several inherent limitations. Unlike an actual performance record, back-tested results do not represent actual performance of a portfolio managed by Rockefeller Asset Management (RAM) over the period shown, are generally prepared with the benefit of hindsight and do not reflect the impact that material economic and market factors might have had on the management of the portfolio during the periods shown. There are numerous factors related to the markets in general or to the implementation of any specific investment program, which cannot be fully accounted for in the preparation of back-tested performance results and all of which can adversely affect actual investment results.


Our process centers around RAM’s proprietary materiality map, which was developed in collaboration with our equity and ESG analysts and based on guidance from SASB. We then conducted an extensive data mapping project to determine which metrics best quantify each material ESG issue. After integrating data from various data providers, we utilized academic imputation best practices to approximate missing values which is especially important given that ESG data is not always available and is not reported in a consistent manner. Approximately 30-50% of the data used was derived in this manner. If ESG data were available for all issuers over all periods covered by this presentation, the hypothetical back-tested performance shown would likely have been different. We then developed a quantitative process to determine material issue weights referred to as Rockefeller ESG Relevance RankingTM. Material ESG issues can have varying impacts on financial performance. Weights are adjusted depending on the historical relationship between financial performance and material ESG metrics. The Rockefeller ESG Improvers Score™ (REIS) was then constructed to isolate the component of a firm’s ESG trajectory unexplained by traditional financial variables.


ESG data is subjective and non-standardized, has a limited history, coverage gaps, challenges with timeliness and inherent biases. The analysis does not incorporate transaction costs.


The universe consists of US equities across the market capitalization spectrum. There were structural shifts in constituents based on data availability. For example, little data exists for small cap firms prior to 2016.

Backtested Performance

The input to the backtesting code is the quarterly time series of data, cleaned and imputed with fundamental financial data and Bloomberg ESG data using the methodologies described below.

  • A regression is carried out every quarter. The residual of this regression is the component of the ESG Improvers that cannot be explained by the change in key financial variables.

  • Stocks are demarcated by REIS quintiles for backtesting purposes.

  • Rebalancing of the index+ based on REIS occurs quarterly, based on the rolling 12-month ESG momentum. Within each quarter, portfolio constituent weights are adjusted every month based on market cap.

  • Every quarter quintiles index are constructed based on REIS and are market cap weighted.


The backtested results were rebalanced quarterly based on REIS and monthly based on market capitalization.

Hypothetical and Backtested Results Disclaimer

The performance of any account or investment strategy managed by RAM will differ from the hypothetical backtested performance results shown herein for a number of reasons, including the following:

  • Although RAM may consider from time to time one or more of the factors noted herein in managing any account, it may not consider all or any of such factors. RAM may (and will) from time to time consider factors in addition to those noted herein in managing any account.

  • RAM may rebalance an account more frequently or less frequently than quarterly and at times other than presented herein. We have assumed quarterly rebalancing to create the back-tested results. RAM generally does not rebalance according to any predetermined schedule, and reviews rebalancing periodically based on substantive changes in market outlook or asset class valuations and client investment guidelines. This investment approach difference should be considered when evaluating the back-tested performance results presented herein.

  • RAM may from time to time manage an account by using non-quantitative, subjective investment management methodologies in conjunction with the application of factors.

  • The hypothetical backtested performance results assume full investment, whereas an account managed by RAM may have a positive cash position upon rebalance. Had the hypothetical backtested performance results included a positive cash position, the results would have been different and generally would have been lower.

  • The hypothetical backtested performance results for each factor do not reflect any transaction costs of buying and selling securities, investment management fees (including without limitation management fees and performance fees), custody and other costs, or taxes – all of which would be incurred by an investor in any account managed by RAM. If such costs and fees were reflected, the hypothetical backtested performance results shown would have been lower. For instance, a portfolio valued at $1,000 achieving an average annual return of 10 percent over a period of five years, before deducting a 1 percent per annum advisory fee paid monthly, would total approximately $1,611 but only $1,532 after deduction of fees. The performance would be lower if all investment related fees, expenses and taxes were factored into the example.

  • The hypothetical performance reflects the total return including reinvestment of dividends.

  • Accounts managed by RAM are subject to additions and redemptions of assets under management, which may positively or negatively affect performance depending generally upon the timing of such events in relation to the market’s direction.

  • Simulated returns may be dependent on the market and economic conditions that existed during the period. Future market or economic conditions can adversely affect the returns.

  • Actual performance will differ. Future results may vary substantially from the back-tested results. There can be no guarantee that investment objectives or projected outcomes will be achieved.

RAM considers the information in this material to be accurate, but does not represent that it is complete or should be relied upon as the sole basis for assessing investment performance or suitability for investment.