Creating an ESG framework for multi-strategy hedge fund manager research

BlackRock’s hedge fund solutions team, BlackRock Alternative Advisors (BAA), operates globally and invests more than US$26 billion across a broad range of hedge fund strategies, predominantly via third-party hedge fund managers.

Introduction

We recognise the importance of identifying, analysing and monitoring a wide array of risks, including ESG risks, associated with our investments. However, assessing ESG risks associated with hedge funds presents a series of challenges not found in more traditional asset classes, as hedge funds represent a diverse and complex array of strategies (see Figure 1).

Legacy ESG scoring methodologies do not account for the broader range of instruments, the blend of public and private markets exposure, and a hedge fund’s ability to opportunistically pursue an extended range of investment styles.

Consequently, we have developed a comprehensive, flexible framework for ESG scoring and assessment that allows us to understand material ESG issues across the full range of available hedge fund strategies in which we invest.

Figure 1. Notable differences between traditional asset classes and hedge funds

	Traditional asset classes	Hedge funds
1. Instrument types	Equities	Equities
	Fixed income	Fixed income
	Cash	Commodities
		Derivatives
	Use of other instruments subject to regulatory restrictions	Cash
2. Markets traded	Public	Public
		Private
3. Investment style	Typically long-only	Long
		Typically unconstrained
	Shorting typically prohibited	Short
		Arbitrage
4. Time horizon	Typically longer term	Varies

A flexible framework

Our ESG integration score for each hedge fund we invest in is based on the manager’s principles and processes for responsible investment (as expressed in its strategy), and on an assessment across four key areas, which are generally aligned with broader industry hedge fund DDQs, including the PRI’s:

1. Investment Philosophy

2. Team Structure

3. Investment Process

4. Monitoring & Reporting

Based on feedback in each of these areas from more than 100 hedge funds spanning 17 strategies, we have identified a series of ESG integration best practices amongst hedge fund managers. Importantly, the definition of best practice in each of these categories is currently: (i) generic across all hedge fund strategies; (ii) informed by our primary research across hedge fund managers (including those we have not invested in); and (iii) fluid, as we expect hedge fund managers to integrate ESG considerations with increasing levels of detail and sophistication over time.

Figure 2. BAA ESG integration assessment framework

BAA assessment category	Identified best practice examples
1. Investment philosophy	The hedge fund manager has a robust and thoughtful investment rationale for ESG integration. The hedge fund manager has a policy that provides a clear, specific summary as to how ESG information is considered within its investment process.
2.Team structure	Those who are responsible for ESG integration or have subject matter expertise are investment decision makers or work closely with the investment decision makers. The hedge fund manager emphasises ongoing education with respect to ESG topics. The manager has an inclusive culture and diverse team that consists of individuals from different identity, academic, and professional backgrounds.
3. Investment process	The hedge fund manager’s ESG framework extends to many aspects of its investment process and is a documented component of the process. The hedge fund manager can articulate how ESG information contributes to differentiated insights and investment decisions, leading to enhanced risk/return outcomes. The hedge fund manager uses a mix of third-party and proprietary ESG data to inform views, with a focus on materiality.
4. Monitoring & reporting	The hedge fund manager can share metrics that illustrate the impact of its ESG integration activities. Portfolio analysis validates the ESG integration framework.

We assess an individual manager’s practices relative to identified best practices within its peer group, resulting in a numerical ESG integration score:

1. Laggard: Falls below common practices employed amongst peers
2. Consistent with common practices employed amongst peers
3. Leader: Exceeds common practices employed amongst peers

These scores are reviewed at least annually and are adjusted if our view of hedge fund industry best practice changes or if a manager’s own approach to ESG integration evolves.

We include a manager’s ESG integration score in the initial and ongoing evaluation that we conduct of the manager’s edges and handicaps. Furthermore, we will not invest with a manager if it determines that a material and relevant ESG risk associated with them cannot be sufficiently qualified.

Supportive analytics

We take a targeted approach to supplementing our qualitative research on hedge fund ESG integration with data and analytics.

As no single dataset or analytical lens can fully assess the range of hedge fund strategies and trading styles found in a typical diversified hedge fund portfolio, we determine the relevance and materiality of analytics applied to each individual strategy.

For example, to supplement the qualitative ESG scoring framework described above, we assess the fundamental long/short equity and credit managers in which we invest using third-party data providers to score underlying portfolios, which are compared across time and peers.

These incremental data points are used to validate a manager’s claims around ESG integration and as an engagement tool for more nuanced discussions about the portfolio and individual positions.

We also seek to leverage internal tools made available by other teams within the firm. For example, we use a carbon beta stress-testing tool developed by BlackRock’s Sustainable Investing team to quantify climate transition risk across fundamental long/short equity portfolios.

These supportive analytics serve to corroborate and inform the ESG integration scores that we assign to each hedge fund and will lead to more robust datasets, including those focused on climate transition risk, that can be compared and assessed over time.