Executives from AllianceBernstein, Two Centuries Investments, Applied AI, and Off-Script Systems share a litany of foundational and state-of-the-art natural language processing. Learn best practices for open-source models and proprietary fine tuning.
NLP Tools for the Investment Professional’s Arsenal
Natural language processing (NLP) can improve decision making by solving for human biases and overreliance on heuristic — no mean feat for an industry awash in data and under pressure to find a consistent edge. In Part II, you’ll discover how NLP, a specific form of machine learning, has a natural place in an asset manager’s decision-making framework. Here are some salient points made in three separate chapters.
In Chapter 4, data scientists from AllianceBernstein discuss in depth the infrastructure required to incorporate NLP at scale. Learn how NLP pipelines are created to generate signals used across teams to prompt investment actions and boost broader strategies. Peruse practical examples of NLP applications in asset management, including tracking sentiment analysis, extracting themes, uncovering risks in corporate filings, prioritizing sales efforts, and gathering business intelligence.
The founder of Applied AI, which supports organizations on the journey of adopting AI, shares insights from across the industry in Chapter 5. He describes NLP applications used by analysts and discretionary or systematic portfolio managers and characterizes emerging applications under development at leading quantitatively oriented funds.
If you choose to progress through this book’s contents sequentially, you’ll be well-positioned to grasp the significance of applying NLP modelling to environmental, social, and governance (ESG) investing, as detailed in the final chapter. In a joint contribution, the founders of Two Centuries Investments and Off-Script Systems illustrate how NLP is being used to address many of the most cited challenges faced by institutional ESG investors — namely, a lack of standardized third-party data, limited company disclosures, and subjective metrics. Advanced NLP techniques are deployed to help identify ESG themes at the broad market level, the sector level, and the company level. The authors illustrate the simplicity, effectiveness, and scale of third-party solutions and provide a hands-on guide for developing and applying custom metrics.