Natural Language Processing (NLP) has the potential to improve ESG investing in a number of ways, from inventing alpha-generating tools to monitoring controversial risk across portfolios.
Using NLP technology, investors may capitalize on the worldwide trend of ESG investment. Analytics might be generated by scanning web news, identifying entities, linking them to events, and then measuring sentiment. It offers a comprehensive ESG event taxonomy that covers a wide range of issues, from news about firms being punished for pollution to labor problems and litigation. This permits the tracking of issues on a massive scale, spanning millions of listed and non-listed firms in numerous languages, from both domestic and foreign sources.
NLP processing data has the benefit of supplementing ‘conventional’ ESG ratings with ESG sentiment. Many ratings are updated rarely, and one significant benefit of leveraging news sentiment is that a company’s ESG score may now be cast, allowing for real-time monitoring.
ESG investing has grown in popularity not just because a new generation of investors is increasingly concerned with sustainability, but also because there is emerging evidence that highly-rated ESG firms outperform their lower-rated rivals.
Meanwhile, a news mood overlay can improve outcomes even more. Positive sentiment outperformed negative sentiment when it came to stocks having a high ESG rating. Similarly, when it came to equities with a low rating, those with a negative sentiment outperformed those with a favorable sentiment. Furthermore, investors’ rising emphasis on ESG considerations is to blame for the growth of unusual market events.
The ‘tick-shaped’ pattern began with the company’s share price plummeting sharply upon the revelation of the bad ESG news. It then gradually increased in the middle term. This has been defined as a “market overreaction” as a result of investors’ growing aversion to equities soiled by unfavorable ESG stories. It was driven by managers’ efforts to satisfy their customers’ ESG investing mandates, which resulted in the widespread unloading of such equities.
The pattern might be employed as part of an “Engagement Strategy,” in which the inciting occurrence would inspire activist investors to speak with the management team of the firm embroiled in controversy, prompting them to take action to remedy the problem. This might lead to the investor buying the stock at a greater price or just maintaining the firm in their portfolio.