PRI Awards 2019 case study: UNEP FI investor case study – applying climate scenario analysis to actively managed strategies

Project overview, objectives and why the research breaks new ground

Rockefeller Asset Management (RAM), a division of Rockefeller Capital Management, had always identified climate-related risks to portfolio companies via a bottom-up assessment. These assessments considered the companies’ past emissions performance, strategy to reduce future emissions, regulatory and physical risks within their operations, as well as risks to their product portfolio from demand and technology disruption.

The Task Force on Climate-related Financial Disclosures (TCFD) guidelines for asset managers challenged the firm to incorporate top-down scenario analysis and modelling into its bespoke process. RAM felt that if it were to engage its portfolio companies on the importance of disclosing along the TCFD recommendation guidelines, then it would understand the process of what the disclosure framework entails.

As a result, RAM joined the UN Environment Finance Initiative TCFD (UNEP TCFD) pilot project to run its assumptions through climate models that consider the different regulatory and physical risks associated with different emissions pathways. The firm contributed to developing the model within the project group, and then applied the model to approximately 90% of its assets under management.

The working group approach differed from previous attempts at modelling climate risk to portfolios in a few ways:

• Firstly, the modelling was determined through a comprehensive and fully collaborative approach, across a range of asset owners and asset managers on four continents.
• Secondly, it attempted to model whole portfolios, not just assets tied to the fossil-fuel value chain.
• Thirdly, it used enhanced modelling for transition and physical risk assessments, incorporating over 60 datasets.

Report methodology

The UN Environment Finance Initiative brought 20 institutional investors together with the data analytics firm Carbon Delta, to develop a methodology to assess how physical and transition risks of underlying portfolio companies would manifest themselves under various climate scenarios.

The Investor pilot group met on weekly calls with Carbon Delta to refine the financial modelling and explore various assumptions within the datasets. This work resulted in a climate value-at-risk (VaR) metric, which measures the impact on market value of assets under various climate scenarios over a 15-year time horizon.

The final scenarios included numerous datasets covering land-use models, energy system models, climate models, hazard models, macroeconomic models and integrated assessment models.

In order to determine physical risks, the projected extreme-weather events were not just applied to company headquarters and the macro environment, but applied throughout the value chain, incorporating operations and assets, supply chains and end-markets.

Transition and opportunity risks looked at the regulatory and demand implications across the value chain of each company, as well as an analysis of individual company intellectual property towards low-carbon solutions.

RAM applied the model to 90% of its assets under management, but focused its research on the results from its global equity and global ESG equity strategies. These were selected due to their similar beta and performance track record. RAM felt it would be interesting to see if considering physical and policy risks would create more dispersion between these two strategies, or at least alter the perception of their risk profiles, which had been generated from a bottom-up, bespoke process. RAM also considered the results from its global ESG fossil-fuel-free equity strategy, to examine whether excluding the energy sector proved beneficial or detrimental under the pilot project model.

How the findings have been applied and the wider benefits to investors

The findings from running the top-down model on concentrated portfolios diverged from conclusions derived from RAM’s bottom-up approach to assessing climate risk. This was likely due to the top-down approach’s reliance on current scope-one emissions for determining the forward emissions trajectory of a company. RAM found that since the model (like many others) only considers scope-one emissions, there is a sector bias depending on how carbon is consumed along a company’s value chain. A majority of emissions for companies in the materials sector fall into the scope-one category, whereas the majority of emissions in the energy and transportation sectors would be considered scope three. As a result, companies in the materials sector contributed the highest policy risk on an absolute and portfolioweighted basis for all three strategies, followed by transportation and energy.

The intrinsic and macro context of the sector is critical to consider as well. For example, while materials companies would need to evolve their operations away from fossil fuel power and heat generation, energy companies would have to change their business models entirely. This is a dynamic that clearly shows a greater inherent risk to energy companies as changing an entire business model requires substantially more investment than merely shifting operational infrastructure (such as kilns and power plants). Additionally, demand for materials such as cement is less likely to be disrupted by emerging technologies when compared to the potential demand for fossil fuels to be displaced by renewables and electric vehicles.

The broader implications for investors are important to note, as many begin to make commitments to low-carbon portfolios, or to divest from energy stocks completely. How are low-carbon elements determined? Since the most commonly used and comprehensive datasets out there are for scope-one emissions, an investor could potentially end up with a portfolio that is underweight materials or industrials instead of energy.

Most scenarios do not include an individual company’s commitments to decarbonize when assessing policy risk. RAM is currently building out a dataset for its investible universe that attempts to track a company’s trajectory by focusing on elements such as research and development towards low-carbon operational expenditure, and an emissions-reduction compound annual growth rate.

If the intention is to divest from fossil fuels or decrease fossil-fuel exposure, current lowcarbon scenario modelling could create portfolios that run counter to investor preferences. Further, if these types of analysis are used to make portfolio construction decisions, there could be unintended consequences that could potentially conflict with fiduciary duty.

RAM concluded that even though the model was as comprehensive as any to date, until greenhouse-gas datasets improve and until individual underlying portfolio companies begin to disclose along the TCFD recommendation guidelines, it will be challenging for investors to accurately assess the climate risks and opportunities to their portfolios on solely a top-down basis.

In order for asset owners and asset managers to produce meaningful climate change disclosures, they will need to exert pressure on their portfolio holdings to do the same. This is a critical innovation of the TCFD Recommendations, and ultimately the one that will drive robust and comparable reporting on climate change risks and opportunities. This material is provided for informational purposes only and should not be construed as investment advice.