Fund managers always knew that picking investments on the basis of an ethical rating depends on flawed and fuzzy information. Now, the economic shock of the past six months has revealed new gaps in the data that quant investors rely on for their environmental, social, and governance (ESG) models.

Employers across industries have reacted to the disruption of coronavirus by introducing workplace policies to help cash-strapped staff during lockdown. Others have pivoted their business to become more socially responsible, for example by producing medical equipment in the fight against the pandemic or by donating supplies to local communities.

The problem for systematic investors is how to quantify this new-found emphasis on social responsibility.

“ESG data is always tough but a lot of what we’re trying to measure now hasn’t been in focus before,” says Peg DiOrio, head of quantitative equity portfolio management at Voya Investment Management, a $250 billion US asset manager.

Quant models for ethical investment are generally constructed around a framework of ESG factors. The number of metrics in the matrix varies by firm. Schroders gathers 50 measures, including carbon emissions, wages, and workplace stress. Arabesque, a specialist sustainable investor, harvests 250 metrics.

The numbers are crunched to produce a series of scores for corporations or countries. These scores are often assembled in an index for comparison purposes.

With the pandemic forcing widespread change across industries, quant investors are having to tweak their models—perhaps by dialling up one metric or dialling down another. If gaps appear in the matrix, investors must source new data to fill them.

But data on social responsibility, in particular, is hard to come by. It takes time and resources to sift through numerous company filings or financial reports. And buying data off-the-shelf from vendors is expensive.

Some are even sceptical that such alternative data will give them an information edge. “A lot of the information is already priced in the markets and to access alternative data and to generate alternative data is a difficult task and always takes a lot of time,” says Daniel Seiler, head of multi-asset at Vontobel Asset Management. “By then, the information advantage has vanished already.”

Data can also give a misleading signal. An airline that is forced to stop flying due to coronavirus restrictions will have slashed its carbon emissions. This may result in the firm generating a higher ESG score, but this doesn’t necessarily mean ethically-minded investors should buy its stock.

Sustained effort

ESG funds are enjoying a boom. A record $71 billion of cash flowed into sustainable funds in the second quarter of 2020, Morningstar data shows. These funds now hold more than $1 trillion in assets under management.

Investors are not just attracted by the prospect of feeling virtuous; the solid returns of these funds have justified the interest. Over the past three years, sustainable funds delivered annualized returns of 11.3% compared to returns of 9.9% for traditional funds, according to a Morningstar study of US large-cap equity funds to the end of 2019.

The positive returns of investing in socially responsible companies goes hand in hand with the strong financial performance of the corporations that make up the funds. In the first quarter of 2020, names in the Russell 1000 index that ranked within the top quintile on social metrics—like how employers deal with contract workers, whether they cut loose employees or keep paying them during the pandemic, and if the company has a strong work-from-home policy—outperformed their lower-ranked peers by 4.65%, according to research from Goldman Sachs Asset Management.

Establishing a cause and effect between social metrics and financial success is not easy, though. Investors may conclude that a company with a strong financial record can afford better social support measures. Or they might judge that employees who feel supported are likely to perform to a higher level, lifting the bottom line. In other words, it’s unclear whether financial success is the chicken or the egg.

ESG models are not concerned with causality. Their main purpose is to give a score to would-be investments based on a set of predefined criteria for sustainability. Voya Investment Management uses what it calls a “materiality matrix” to measure the importance of ESG factors on a company’s financial performance. The firm converts data from its multi-factor model into numerical scores, all of which roll up into a final composite score.

S-Ray, a sustainability arm of investment firm Arabesque, uses self-learning quant models to analyse 7,000 corporations, and to produce four scores including an ESG score. The firm was in the midst of redesigning its matrixes before Covid-19 dug its claws in.

Schroders takes a different approach. The firm’s quantitative tool asks a simple question: if companies were given a bill for the cost they impose or benefit they generate from their ESG impact, how large would that credit or debit be? The firm has calculated that the translated financial costs from ESG would reduce the $4.1 trillion of profits generated by listed companies by 55%. Overnight, one-third of companies would become loss-making.

Franklin Templeton has developed an ESG index that assigns a score of 1 to 10 to individual countries. The index combines the views of the research team with a benchmark created from indexes from the World Bank, World Economic Forum and United Nations.

Julie Moret, head of ESG at Franklin Templeton, says social issues have come to the forefront as investors and civil society scrutinize how businesses act during the crisis, including the way they treat their workers. Post Covid-19, it is reasonable to expect sustained pressure on companies to improve labor rights and pay, she explains.

“These drivers will increasingly require us to reframe what a well-managed business looks like,” she says. “The crisis has served to shine a light on the growing relevance to corporates of models that provide equitable returns not just to shareholders but to employees, customers, and suppliers.”

Data hunt

Just as machines need fuel, models need data. But the information that powers ESG models has well-known deficiencies. Much of the data stretches back only 10 years, which is a skinny sample for back-testing. The figures are often self-reported, leading to problems with consistency and comparability. Scrubbing the data takes time and money.

For social factors—the S of ESG—the lack of data is even more acute. DeOrio says companies are focusing more on safety of employees and health care benefits, as well as engagement with local communities. Finding data to quantify these metrics is tricky.

“It requires different data, which we’re always searching for, and some different techniques, because a lot of that data just isn’t going to have a long history. And we need to use some different methods in order to even analyze that data,” she says.

One solution is to use third-party data providers. These vendors claim to offer ready-made, cleaned data, but their services come at a price.

Alternatively, investors can obtain their own data. DeOrio points to the US government’s Occupational Safety and Health Administration database as an example of a publicly available resource for social information. The website contains information on workplace injuries and violations. Investors can scrape the website for lists of prior violations, which could point to a persistent problem within a company.

Workplace safety is a reliable indicator of a company’s financial health, says Seiler at Vontobel.

“One area where we have a good understanding of how ESG impacts the financial condition of a company is safety measures. The link between these two topics is that the financially constrained companies invest less in workplace safety and therefore have more accidents. So this link is well established and could, going forward, be of interest with Covid-19,” he says.

The crisis has served to shine a light on the growing relevance to corporates of models that provide equitable returns not just to shareholders but to employees, customers and suppliers

Julie Moret, Franklin Templeton

Once an investment firm has exhausted the public troves of data, it may need to get creative. Some investors have taken to approaching companies directly to source information.

RBC Global Asset Management, which runs $360 billion in assets including several quant funds, engages with company boards to probe them on how they are addressing risks such as employee health and safety or supply chain risk. This information is “not typically available from a data source”, says Melanie Adams, head of corporate governance and responsible investment at the firm.

RBC GAM subscribes to a number of third-party ESG data sources as well, Adams says.

In addition to safety, many companies have pivoted their business models, such as automaker GM helping produce ventilators, and breweries making hand sanitisers using the alcohol. To capture this change of direction, Voya is vetting ideas not just with the quant team, but also with fundamental analysts, to make sure they make intuitive and economic sense.

Schroders owns a large position in a North American food and uniform services company, which has converted its manufacturing plants to produce respirator and medical masks, scrubs, and isolation gowns. Schroders uses this kind of social information to help build a list of “saints and sinners” to keep track of how companies have acted during the crisis, says Sarah Bratton, head of sustainability for North America at the firm.

A drawback with ESG data such as workplace safety is that it’s low frequency. Firms might report the data once every quarter, or every year, which makes it hard to model quantitatively.

For more up-to-date signals, some quant firms are using natural language processing. The technique allows users to filter through hundreds of news outlets to look for clues about corporations’ social activities. The analysis is either done by quants in-house or subcontracted to an external tech vendor.

Welton Investment Partners, a boutique quant investor, uses a data feed developed by S-Ray Arabesque. The tool parses 30,000 media outlets and uses natural language processing to identify a news story that may impact an ESG score negatively.