ESG signals can give strong indications that a stock is primed for a downturn and might be a good target for a short. With reliable data as the foundation, solid analytics map a correlation between two ESG signals, in particular, that have been remarkably predictive and would have resulted in positive returns over the course of this year so far. 

By: Conor Platt, CEO of Confluence Analytics, and Rob Yates, OWL ESG Director of Communications

Confluence Analytics

Confluence Analytics has released its 3Q23 Short Report. Built on OWL ESG’s data, the Confluence Analytics Short Model portfolio would have produced roughly 1500 bps returns this year to date. Using ESG-based signals that incorporate corporate carbon emissions and social factors, the short model portfolio successfully predicts stocks that are likely to decline, at a success range in line with normal investor expectations. 

 
The model portfolio is built from a forward-looking ESG signal that includes carbon emissions combined with stocks ranked in the bottom half of the “Social” category for US Large Cap universe. As you can see from the chart below, an equally weighted portfolio of these stocks has underperformed the market consistently since 2019.

At the beginning of 2023, the short model identified several industry groups that were at elevated risk, with U.S. Banks a significant addition to the list of potentially concerning equities. Confluence published an article in mid-February of this year that gave investors a warning signal. The now-infamous SVB is right there.

Now, the fine print. A short-based strategy is risky. In fact, it is potentially much riskier than most others. Even sophisticated investors with years of experience get burned. If a share price goes up significantly, the person who shorted the stock is on the hook for the difference. This is what happened during the Wall Street Bets incident, and hedge fund Melvin Capital suffered for it.

Using reliable ESG data, however, opens up possibilities for market-driven investment considerations, leading to outcomes that both make money and support investor values. This goes for short-based investments and strategies just as much as any other.

The ability to successfully analyze data, identify signals, and apply that information to investment decisions that lead to positive returns is complicated in any situation; it is a significant hurdle to overcome for ESG investing. This analysis proves that it is possible to overcome that hurdle with a risk/reward reliability that is similar to any other strategy when using ESG signals for something like tapping potential targets to short.

Contact us to learn about our in-depth data, extensive coverage and custom solutions, and why so many organizations choose OWL to meet their needs for ESG data and analyses.

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