ESG

section bg image

ESG (Environmental, Social and Governance) is a major topic in asset management, as stakeholders become increasingly aware of the impact of their activities and investment decisions on the environment and society. At LFIS, we recognise the importance of ESG and are actively assessing integration of ESG criteria into our investment strategies.

ESG at LFIS

“It is not enough to do good; you need to do it well.”

Denis Diderot (1713 – 1784)
French philosopher and writer. A prominent figure during the Age of Enlightenment.

LFIS Capital is engaged in an on-going, strategic effort to transition certain investment strategies towards a socially responsible investment approach. In this effort, as for all our investment strategies, our commitment to deliver long-term, risk-adjusted returns to our investors is the guiding principle. LFIS’ ESG effort is steered by an ESG Research Committee focused on assessing the integration of ESG criteria and sustainability risks into our investment strategies.

ESG risks and opportunities vary significantly across investment approaches. Integration of ESG criteria therefore varies across LFIS’ investment strategies, however, all funds managed by LFIS exclude investments in issuers related to the production of controversial weapons.

The Data Challenge

ESG is an important, but challenging topic. If most investors take ESG criteria into account when selecting assets, this can ultimately lead issuers to act for a better world. For asset managers like LFIS who manage quantitative, alternative portfolios, a key challenge is ESG data.

Technology firms and data providers have rushed to meet the demand for ESG data. Providers range from specialized firms that calculate specific ESG metrics like carbon scores or gender diversity, to broad-based services that rate companies based on several hundred ESG-related metrics. To paraphrase Cochrane on factors, ESG has become a “zoo” of data with nearly 100 different providers but with issues of homogeneity, comprehensiveness, opacity, point-in-time, and reactivity across the board.

LFIS’ answer to this challenge is to access the rich store of ESG indicators available in the mass of available textual data. LFIS has partnered with French FinTech SESAMm to apply SESAMm’s advanced machine learning and natural language processing technology to generate faster, more transparent and reliable ESG data.

ESG in Practice

As a natural extension of our research efforts, LFIS is able to offer investors access to a variety of strategies founded on our specific ESG approach. Possible approaches include long-short, long-only and 130/30 strategies, and commingled or dedicated formats.