Taxi drivers, stockbrokers and the bloke propping up the bar at your local have all, at one time or another, served as a source of share tips. Now there is a fresh seam of supposed wisdom for retail investors to mine: chatbots such as ChatGPT and Claude.
These artificial intelligence tools, known in the trade as large language models (LLMs), are increasingly being pressed into service by amateur and professional investors alike to generate investment ideas. Yet for all the awe AI has inspired, the jury is still out on whether the machines are actually any good at making money.
Back in 1973, the academic Burton Malkiel argued in his now-famous book that a blindfolded monkey throwing darts at the financial pages of a newspaper could pick a portfolio just as profitable as one chosen by highly paid professionals. His point, the bedrock of the efficient market hypothesis, was that returns on the stock market are essentially random and unpredictable, and that nobody can hold a lasting edge over anyone else.
The notion that LLMs might be superior stock pickers to humans would, of course, blow a hole in that theory. A clutch of start-ups has already set AI to work trading and investing, with markedly mixed results.
According to a recent test run by the US research lab Nof1, six of the eight most popular AI models lost money investing in American technology shares. Anthropic’s Claude Sonnet shed almost 60 per cent of its initial $10,000 (£7,500) stake, while Google’s Gemini gave up more than $5,000. Only two came out ahead: ChatGPT, which made nearly $900, and Elon Musk’s Grok, which roughly broke even.
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