We recently completed our research on quantitative equity market neutral strategies. We have now put together our first preferred list in this area. These strategies use a vast array of data inputs and invest in a systematic manner, going both long and short stocks in equal proportion.
During this process, we prodded and probed the managers on how much they looked at ESG factors when designing their investment strategies.
Quantitative equity market neutral managers are at the sharp end of the investment landscape. As pure alpha strategies, the managers look for new sources of alpha to enhance their return generation.
There has been an uptick in awareness around ESG factors. We thought they would likely be battering down the door to find opportunities!
Our experience was mixed at best. Let’s start with the good news.
Managers have looked closely at using ESG factors as inputs. Some are incorporating them (to a small extent) as a portion of their signal inputs. The consensus is that the most meaningful inputs are related to Governance and naturally fall into “Quality” buckets.
An interesting data source has emerged for quantitative equity market neutral managers… Glassdoor ratings. Managers pull ratings for every listed company to understand the wellbeing of employees. They believe this correlates with the long-term success of a firm. Within the context of ESG, this input relates most naturally to Governance.
One challenge quantitative managers face is the lack of engagement with company management.
Their processes do not prioritise meeting with firms with which they invest. At this true alpha generation end of the spectrum, inputs are data driven and decision making is free of qualitative assessment. Plus, managers’ holding periods are significantly shorter than the majority of equity strategies. As a result, any engagement benefits do not play out before the manager trades out of the stock.
At the moment, quantitative equity market neutral managers are dabbling with ESG factors as alpha sources. We would expect that, as the datasets’ track records build out, managers will start using these inputs more.