Gainesville, FL, June 9, 2025 — University of Florida finance professor Alejandro Lopez-Lira’s pioneering experiments with AI models like ChatGPT, DeepSeek, and Grok are revolutionizing retail investing by equipping everyday traders with tools to compete with professional analysts. As retail participation in the stock market grows in 2025, driven by accessible trading platforms, these AI-driven strategies are democratizing access to sophisticated financial analysis.
Lopez-Lira’s research highlights a future where individual investors can leverage technology to make informed decisions, challenging the dominance of institutional players.
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AI Tools Redefine Retail Investing
Lopez-Lira’s research has progressed from testing AI’s ability to interpret news headlines to developing advanced stock-picking models that rival human expertise. His methodology uses AI models to score stocks on a 1-100 scale, analyzing data such as company financials, macroeconomic trends, and market news.
In a test spanning September 2024 to May 2025, his AI-driven portfolio delivered a 47.8% return, outperforming the S&P 500’s 35.4% over the same period, according to results from the Autopilot investment app. This success has resonated with retail investors, who now represent nearly 27% of the trading volume in U.S. equities in 2025, per Bloomberg data.
Trading platforms like Robinhood and TradeRiser have integrated AI-driven tools, reporting a 32% increase in user engagement with these features in 2025. Lopez-Lira’s approach enables retail investors to build diversified portfolios without the high costs of traditional financial advisors, which can exceed 1% of assets annually.
However, he cautions that widespread adoption of AI tools could increase market efficiency, potentially reducing their long-term advantage. This shift is empowering individuals to make data-driven investment choices, previously accessible only to well-funded institutions.
Did you know?
In a 2024 test, Lopez-Lira's AI-driven portfolio in the Jakarta Stock Exchange outperformed the local benchmark by 10.7% over 60 trading days, highlighting AI's potential in less-covered markets.
Opportunities and Challenges for Retail Investors
AI stock-picking tools offer significant opportunities but come with risks. Lopez-Lira’s findings show that models like ChatGPT excel at interpreting market news for fundamental analysis, while DeepSeek is better suited for technical strategies, requiring investors to select the appropriate tool for their goals.
Misinterpreting AI outputs or over-relying on automation can lead to costly errors, a concern echoed in recent discussions among financial educators. The SEC’s ongoing 2025 efforts to regulate AI-driven trading further highlight the importance of understanding these tools’ limitations.
Despite these challenges, AI is enabling retail investors to explore new opportunities, such as small-cap stocks, which Lopez-Lira’s models identify as highly responsive to news-driven signals. AI platforms are often available for free or through low-cost subscriptions like SuperGrok on grok.com, making them more affordable compared to traditional advisory fees.
As retail investors embrace these tools, Lopez-Lira’s work points to a future where financial empowerment is within reach for individuals, though success hinges on their ability to use AI effectively in volatile markets.
Technical Insight
Lopez-Lira’s AI models use natural language processing (NLP) to analyze unstructured data, such as news articles and earnings reports, generating sentiment scores that predict stock price movements. While effective in less efficient markets like small caps, the models require frequent retraining to maintain accuracy in sectors where information is rapidly incorporated into prices, such as large-cap stocks.
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