Dan Moczulski, the UK managing director of Etoro, expressed to Reuters that while AI models have immense potential, there’s a significant risk when individuals treat popular models like ChatGPT and Gemini as infallible guides. He cautioned that these models can misquote figures and dates, heavily lean on established narratives, and overly rely on historical price movements to forecast the future.
The Risks of AI in Stock Trading
In my opinion, utilizing AI for home stock trading represents, for better or worse, a significant step in the ongoing technological evolution that has made retail investing accessible to many. The history of personal computer-based trading goes back to Charles Schwab’s introduction of an electronic trading service for dial-up users in 1984. By 1992, E-Trade was released, and by the late 1990s, online brokerages had revolutionized how people invested, slashing transaction fees from hundreds to under ten dollars.
The concept of “robo-advisors” emerged after the 2008 financial crisis, leading to the rise of automated online services that used algorithms to adjust and manage portfolios based on client objectives. The first notable robo-advisor was launched in 2010, followed by others like Wealthfront in 2011, which adjusted portfolios automatically through algorithms. By the end of 2015, nearly 100 robo-advisors worldwide managed about $60 billion in client assets.
The launch of ChatGPT in November 2022 undeniably signals a shift, allowing retail investors to interact directly with AI models for stock price inquiries rather than depending solely on preset algorithms. However, Leung noted that ChatGPT lacks access to data behind paywalls. To obtain better insights, he formulates specific prompts, such as asking for a short analysis or requesting information exclusively from trusted resources like SEC filings.
Apart from chatbots, there’s an increasing dependence on financial algorithms. Research and Markets reports that the “robo-advisory” sector, which encompasses firms providing algorithm-driven financial advice from fintech startups to traditional banks, is expected to grow by approximately 600% by 2029.
Yet, with the rising use of AI tools for investment decisions, potential challenges loom. Leung cautioned that if individuals start relying on AI for comfortable investing, they might struggle during market downturns or crises. There’s growing concern about whether retail investors grasp risk management while using these AI tools, especially when the market trends downward.
