PRI Awards 2019 case study: Pricing ESG risk in credit markets

Overview of the firm’s approach to ESG incorporation 

The origin of the ESG credit-risk initiative was the fixed-income team’s need for a model to price the ESG risk of credit instruments. While years of effort had been spent on pricing core operating and financial risks – there was no equivalent for ESG risk. In a collaborative effort working with teams across the firm, the fixed-income team developed a pricing model to capture the influence of ESG factors on credit spreads. 

To begin, a quantitative rendering of ESG risks for each credit issuer was required. The team had an advantageous starting point: the QESG Scores generated by Hermes Global Equities, which ranks each stock worldwide in accordance with its ESG risk. The scores combine quantitative, company-specific ESG research with qualitative insights from engagers in Hermes EOS. Importantly, the scores not only capture a company’s current level of ESG risk exposure, but also its direction of travel. The highest score, denoting superb ESG policies and practices, is 100, and the lowest is zero. 

The team used QESG Scores to rank each issuer according to its ESG quality, with the first decile containing those with the lowest scores and the 10th decile the highest. For each issuer, they calculated its average annual credit default swaps (CDS) spread and then the distribution of annual average spreads in each decile, for the six years from 2012-2018. These quantitative scores were regressed against the spreads of credit default swap instruments – which provide the purest reflection of credit risk – to determine the nature and strength of the relationship between the QESG Scores and credit spreads. A relationship was indeed found, as expressed in an ESG risk curve generated by the model. 

The curve shows a convincing relationship between ESG risk and credit spreads: companies with poor ESG practices tend to have wider and more volatile spreads, with the reverse being true for firms with good ESG characteristics. This enables the team to use a credit issuer’s QESG Score to identify its level of ESG risk – something that is now integral to its investment process.

Why this approach stands out in the market 

This is a unique research tool that enables ESG integration. It was built for a specific purpose, and uses proprietary ESG and engagement data. 

For years the team had known that poor ESG practices could erode a firm’s enterprise value. This has implications for both equity and credit investors, but the mathematical complexity of credit instruments - coupon, term structure, call structure and rates - all impact credit spreads. This makes it difficult to isolate the contribution of ESG risk to valuations, and has been a barrier to quantitatively assessing ESG risks. But these hurdles disappear if CDSs are analysed instead of bonds, providing the purest and most homogenous expression of credit risk. For the model, the team analysed the constituents of four CDS indices – the CDX High Yield, CDX Investment Grade, iTraxx Europe, and iTraxx Crossover – from 2012 to 2018. 

Until it developed this model, the team historically considered ESG risks in a qualitative sense alongside hard data for operating and financial risks. Now, using this tool, it can analyse ESG risk with greater quantitative rigour in a repeatable process. This complements the firm’s qualitative assessments and the insights gained from its engagement colleagues in Hermes EOS. 

That the pricing model was developed using proprietary inputs, such as the ESG Dashboard - a source of best-of-breed ESG research data and engagement insights from Hermes EOS - and the ESG integration expertise within the Hermes Responsibility Oce, makes it a unique resource for the Hermes fixed-income team.

Practical examples of how the approach was applied, and challenges overcome  

The team’s January 2018 investment in a perpetual bond from French utility firm EDF demonstrates the deep integration of the ESG risk-pricing model. 

The team’s macroeconomic and sector analyses identified utilities as an attractive area for investment. Due to market dynamics, it also sought subordinated bonds issued by companies with strong credit characteristics. EDF fitted that profile, so the team assessed its credit and ESG risks, and its valuation. From an ESG perspective, the company scored well because:

• It is governed by best-in-class French regulation concerning the disclosure of climate-change risks.
• It is a large green-bond issuer (€4.5bn outstanding).
• It reducing fresh water usage by drawing water from the sea.
• It has a shrinking carbon footprint, with CO2 emissions having declined from 80 mega tonnes in 2012 to 48 mega tonnes in 2016.

The team then analysed the performance of EDF’s CDS in the ESG risk-pricing model – and this led the firm to what it believed to be the most attractive subordinated bond in EDF’s capital structure – its perpetual bond. Using the model, the team priced the bond based on the improvement in EDF spreads given its positive ESG performance. It learned that EDF’s QESG Score had risen from 70 to 80, corresponding with a 30-basis point tightening in its spreads. 

In this way, the model provided the final element of vital information that the team needed to invest in subordinated debt within the utility sector.

Measurements for success and lessons learned 

Hermes is a long-term investor, and judges the outcome of a holding over a much broader time horizon than the four months since the team purchased the EDF perpetual bond. However, the team is confident this instrument was the best way of establishing climate-related risks and opportunities at utilities companies. It is also confident in the value brought by the ESG risk-pricing model in helping to identify the bond. 

The team has fast integrated the pricing model into its investment process – and it has become a core part of analysis. Gauging ESG risk is now as fundamental in Hermes’ decisions as measuring credit and operating risks. Time and again, the model illustrates how punitive an increase in ESG risk can be for a debt issuer: credit spreads widen sharply as ESG policies and practices worsen. Meaning that companies moving up the curve should be reassessed and the investment cases of those moving down the curve revisited.  

This helps Hermes to identify mispriced issuers based on their ESG characteristics. The process of developing, testing and using the pricing model also reinforces a theme that is common among Hermes’ investment teams, no matter which asset class they are focused on: the necessity of independent analysis due to the limited scope and retrospective data provided by external ESG researchers.