Can ChatGPT Personalize Index Funds’ Voting Decisions?

Abstract

ChatGPT has risen rapidly to prominence due to its unique features and generalization ability. This article proposes using ChatGPT to assist small investment funds, particularly small passive funds, in making more accurate and informed proxy voting decisions.

Passive funds adopt a low-cost business model. Small passive funds lack financial incentives to make informed proxy voting decisions that align with their shareholders’ interests. This article examines the implications of passive funds on corporate governance and the issues associated with outsourcing voting decisions to proxy advisors. The article finds that passive funds underspend on investment stewardship and outsource their voting proxy decisions to proxy advisors, which could lead to biased or erroneous recommendations.

However, by leveraging advanced AI language models such as ChatGPT, small passive funds can improve their proxy voting accuracy and personalization, enabling them to better serve their shareholders and navigate the competitive market.

To test ChatGPT’s potential, this article conducted an experiment using its zero-shot GPT-4 model to generate detailed proxy voting guidelines and apply them to a real-world proxy statement. The model successfully identified conflicts of interest in the election of directors and generated comprehensive guidelines with weight for each variable. However, ChatGPT has some limitations, such as token limitations, long-range dependencies, and likely ESG inclination.

To enhance its abilities, ChatGPT can be fine-tuned using high-quality, domain-specific datasets. However, investment funds may face challenges when outsourcing voting decisions to AI, such as data and algorithm biases, cybersecurity and privacy concerns, and regulatory uncertainties.

Keywords: ChatGPT, Natural Language Processing (NLP), Artificial Intelligence (AI), corporate governance, institutional investors, proxy voting, index funds

JEL Classification: G23, G34, K22