Quants Say They Can Make Investing More Sustainable

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(Bloomberg Businessweek) -- On Jan. 14, the chief executive officer of the world’s largest asset manager warned that investors had to pay attention to global environmental risks. “Climate change has become a defining factor in companies’ long-term prospects,” wrote BlackRock Inc.’s Larry Fink in a letter to CEOs. “I believe we are on the edge of a fundamental reshaping of finance.” In fact, many big investors now incorporate environmental and other social factors into their stockpicking, for at least some of their funds. But they face a real obstacle: The data is a mess.

Some companies disclose a lot of information about sustainability, labor practices, or gender equity. Others say almost nothing. A fund manager buying a few dozen large-cap U.S. stocks may be able to have analysts dig up enough corporate info to make a decision. But things get harder if you want to be able to choose from thousands of stocks, or evaluate small companies or emerging-market equities.

Quantitative investors say they have a solution. These traders use computers to sort through reams of data, and they say they’re better than anyone else when it comes to making investment decisions based on messy or incomplete information. Quants are “used to filling in the gaps,” says Andrew Dyson, CEO of QMA, a quantitative investment firm that’s part of asset manager PGIM. It launched a socially conscious investment strategy in 2018.

QMA figured out a way to give companies a social and environmental score even when they don’t report a lot of data—tripling the number of stocks QMA can consider, Dyson says. It starts by looking at companies where there’s ample information. Companies can be dinged for things such as high greenhouse gas emissions or significant product recalls, and get good points for, say, having a human-rights policy. QMA analyzes returns to isolate the effect of responsible corporate citizenship. Then the money manager turns to the universe of companies where there’s not enough information. If a stock’s behavior is statistically similar to those that are known to be good, it can be classified as good, too.

For some socially conscious investors, this method might be unsatisfying—it doesn’t eliminate the possibility some of their money is going to companies with objectionable practices. But QMA says that it should produce a portfolio that overall is tilted toward better-behaved companies. And other quantitative tools may catch things traditional sustainability analysis might miss.

That’s because much of the data on environmental, social, and governance issues—ESG, in the investment world’s shorthand—comes from companies themselves. “The question is always whether ESG information is more of a PR marketing story,” says George Mussalli, chief investment officer and head of research for equities at PanAgora Asset Management, which describes its approach as fundamental quantitative investing. “You don’t just want to buy companies that have the highest ESG rating, you want to find the firms that are improving the most.” To try and dig deeper, PanAgora says it uses natural language processing tools to analyze how companies talk publicly about their ESG performance and get a sense of whether they’re backing up their claims with action. For example, a company that uses more negative-sounding words such as “spill” or “pollution” may be more honest about its problems and diligent about addressing them.

Arabesque Group, a Frankfurt- and London-based asset manager, is focused on running ESG quant portfolios. It says it runs artificial intelligence models across 6,000 machines in 11 different data centers to read and digest information sources ranging from company data to news reports. “We don't have a single sustainability analyst at Arabesque that goes through and says this company is good or bad on ESG—everything we do is based on big data and systematic,” says Yasin Rosowsky, co-CEO at Arabesque’s AI unit in London.

Boston-based Acadian Asset Management has used data on issues such as local corruption or carbon pricing from companies that provide them to estimate similar information for all of the 40,000 companies it tracks globally. It also uses ideas drawn from ESG data to improve its investment decisions. For example, Acadian has found that polluting companies trade at lower valuations than nonpolluters in places where there’s a carbon tax. That makes sense: The market figures a company should be worth less if it has to bear a cost for high emissions.

But Acadian also noticed the market seems to be pricing in the effect of a carbon tax even in countries that don’t have one yet. Perhaps traders are assuming a carbon tax or similar regulation is likely in the future. So Acadian now assumes carbon taxes should be part of its investment assumptions, no matter where a company is located. That’s helped it avoid some investments in high-emitting companies that might otherwise appear to be a bargain, says Asha Mehta, a portfolio manager and director of responsible investing at Acadian. As the amount of sustainability information expands, the hope is that more such insights will emerge. “ESG data is becoming relevant faster in our portfolios today,” Mehta says.

To contact the editor responsible for this story: Pat Regnier at pregnier3@bloomberg.net

©2020 Bloomberg L.P.

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