Tracking the Explosive World of Generative AI

ChatGPT Trading Algorithm Delivers 500% Returns in Stock Market

A University of Florida study reveals ChatGPT's prowess in predicting stock trends, achieving a staggering 500% return in one investing model and outpacing conventional sentiment analysis models used by hedge funds.

Researchers have found that ChatGPT can deliver up to 500% returns when incorporated into a trading strategy. Photo illustration: Artisana.

🧠 Stay Ahead of the Curve

  • A University of Florida study found that AI model ChatGPT can predict stock market trends with up to 500% returns.

  • Researchers found that ChatGPT outperforms traditional sentiment analysis tools and older language models in stock prediction.

  • Generative AI’s potential could spark a new arms race in the finance industry, potentially disrupting hedge fund strategies and empowering retail traders.

By Michael Zhang

May 10, 2023

Researchers from the University of Florida have released a study suggesting that the AI model ChatGPT can reliably predict stock market trends. Using public markets data and news from October 2021 to December 2022, their testing found that trading models powered by ChatGPT could generate returns exceeding 500% in this period. This performance stands in stark contrast to the -12% return from buying and holding an S&P 500 ETF during the same timeframe. The study also underscored ChatGPT's superior performance over other language models, including GPT-1, GPT-2, and BERT, as well as traditional sentiment analysis methods.

An In-depth Look into the Methodology

The team employed a rigorous methodology to backtest the efficacy of ChatGPT-driven trading strategies. They focused on examining a data set comprised of stock-related headlines from October 2021 to December 2022, ensuring that none of the news pieces were part of ChatGPT’s training data.

The researchers collated 67,586 headlines pertaining to 4,138 unique companies during this time, using web scraping techniques. These headlines were subsequently filtered for relevance, with the team narrowing their focus to full articles and press releases, excluding any stock-gain or stock-loss headlines. They also removed duplicate news to ensure only fresh information was used.

The research team used ChatGPT (powered by GPT-3.5) to evaluate whether a given headline was indicative of Good News, Bad News, or Unknown, also asking for a brief explanation. For instance, when presented with the headline "Rimini Street Fined $630,000 in Case Against Oracle," ChatGPT returned the nuanced response:

YES. The fine against Rimini Street could potentially boost investor confidence in Oracle’s ability to protect its intellectual property and increase demand for its products and services.

This response reflects the superior reasoning and natural language capabilities of ChatGPT, which deemed the headline positive for Oracle, whereas a market-leading sentiment analysis software labeled the headline as negative.

Impressive Results Across Several Strategies

The team tested six different investing strategies during the October 2021 to December 2022 period. 

  • The Long-Short strategy, which involved buying companies with good news and short-selling those with bad news, yielded the highest returns, at over 500%. 

  • The Short-only strategy, focusing solely on short-selling companies with bad news, returned nearly 400%. 

  • The Long-only strategy, which only involved buying companies with good news, returned roughly 50%. 

  • Three other strategies resulted in net losses: the “All News” hold strategy, the Equally-Weighted hold strategy, and the Market Value-Weight hold strategy.

When benchmarking against other methods, such as sentiment analysis and older language models like GPT-1, GPT-2, and BERT, ChatGPT consistently outperformed the competition. Traditional sentiment analysis methods produced markedly inferior results across all investment strategies, while GPT-1, GPT-2, and BERT failed to accurately predict returns.

A visualization of how various ChatGPT-powered strategies performed, with the long-short strategy delivering 500% returns. Credit: University of Florida

Implications for the Finance Industry

Two Sigma, DE Shaw, and Renaissance Technologies are several prominent hedge funds that incorporate sentiment analysis into their automated trading systems, and numerous other boutique hedge funds also utilize sentiment analysis signals as part of their proprietary strategies. ChatGPT’s strong performance in understanding headlines and their implications could add to a new arms race as funds compete to have an edge from Generative AI.

ChatGPT’s powerful natural language processing abilities could also threaten businesses that have developed their own proprietary sentiment analysis machine learning models, which could find themselves outperformed by a simple ChatGPT prompt. Notably, companies like Lexalytics that claim “world-leading NLP” could find themselves with both an opportunity and a challenge in this market as generative AI tools emerge and make past models obsolete.

The stock-picking edge that ChatGPT has demonstrated could also empower retail traders. Notably, subreddits like r/WallStreetBets are filled with due diligence posts (called “DDs”) and bragging posts on stock returns from various long and short strategies. ChatGPT, with its ability to deduce nuance and second-order implications from just understanding headlines, could help ambitious retail traders in their own efforts to generate outsized returns. 

Investors expect the next few years to be very dynamic in the finance space as generative AI takes hold. Unsurprisingly, the technology-focused ARK Investment Management is especially bullish. In her 2023 Big Ideas report, ARK’s founder Cathie Wood predicted AI as one of the trends that will define this technological era. “We've been working on artificial intelligence for a long time now,” said Wood, “and I think some of the things we're seeing are just the beginning of the impact that artificial intelligence is going to have on every sector, every industry, and every company.”

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