Almost 25,000 investors have signed up to trade alongside ChatGPT as they follow the GPT Portfolio experiment from copy trading firm Autopilot.
The traders have bet a combined $14.7 million on the AI’s stock picks, which would average about $600 each if they all invested after signing up. They’re hoping to take even a small slice of a purported 500% return from one of the strategies backtested in academic research.
This is absoutely isnane 🤯— AI Daily (@AlexAIDaily) May 10, 2023
A ChatGPT trading algorithm delivered 500% returns in the stock market.
A University of Florida study revealed ChatGPT achieved a staggering 500% return in one investing model
This outpaces conventional sentiment analysis models used by hedge funds… pic.twitter.com/8vxIWmpqrY
The GPT Portfolio gets the AI to analyze 10,000 news articles and 100 company reports to select 20 stocks for the $50,000 portfolio, updated each week. The initial picks included Berkshire Hathaway, Amazon, D.R. Horton and Davita Health. After two weeks, the portfolio is up around 2%, which is pretty much the same as the stock market.
Interestingly the bottom five picks lost more in percentage terms than the top five gained — Dollar Tree lost 17% after it missed earnings — so it might be more sensible in future to only invest in GPT-4’s best five or 10 ideas, but we’ll see how it works out.
The smaller-scale ChatGPT Crypto Trader account is tweaking a similar strategy that gets GPT-4s advice on when to go long on Ethereum. He says it shows a profit of 11,000% backtested to August 2017, but in the real-world experiment since January, the portfolio is up by a third, while the Ethereum price has gained 60%.
It’s worth being careful using AI for trading, however. Crypto derivatives platform Bitget recently abandoned its experiment of using AI on the platform due to the potential for misinformation. A survey of its users found 80% of users had a negative experience with the AI, including false investment advice and other misinformation.
Bitget Managing Director Gracy Chen says:
"AI tools, while robust and resourceful, lack the human touch necessary to interpret market nuances and trends accurately.”