Member Sign In | Not a member? Register Now
A Quant’s Take on ESG
Jon Quigley believes the “men and women in lab coats, thick glasses and hats with propellers” can deliver successful ESG strategies
When thinking of a quantitative investment firm, most immediately conjure images of men and women in lab coats, thick glasses and hats with propellers pouring over mountains of accounting and price data in an attempt to discover the causal relationships between these data points and excess stock returns. However, one should remember that “quants” have always reserved a special place for portfolio construction, particularly the essential link between client objectives and portfolio construction.
Unlike some of our esteemed colleagues in the ESG space, AIP was managing traditional equity strategies before a client approached us about customizing a socially responsible strategy which could be benchmarked to the S&P 500 Index®. The strategy would be able to anchor the US LargeCap allocation, rather than fit a smaller ESG niche.
Is there Gold in that Data Mine?
Philip Fisher, considered by many to be the pre-eminent Growth investor (including Warren Buffet, who credits Fisher with being second to Benjamin Graham as an
influence), listed “Fifteen Points to Look for in a Common Stock”. Among these:
• Point 7: Does the company have outstanding labor and personnel relations?
• Point 8: Does the company have outstanding executive relations?• Point 9: Does the company have depth to its management?
• Point 10: How good are the company’s cost analysis and accounting controls?
• Point 14: Does the management of the company talk freely to investors about its affairs when things are going well but “clam up” when troubles and disappointments occur?
• Point 15: Does the company have a management of unquestionable integrity?
As you can see, several of what Fisher considers important traits can be classified as Social or Governance concerns. Ignoring these characteristics is to miss important information.
However, while ESG data is rapidly improving, the data is very different from the data quants most often examine
Page 1 of 3 | Next »