Almost overnight, ChatGPT, the runaway, conversational, large language model (LLM) AI hit created by OpenAI has found itself yet another role to play within American society -- that of stock market guru.
In a survey of 2,000 Americans conducted by investment advice website The Motley Fool, 47% of US adults reported using ChatGPT to glean advice on stock market picks. In a sign of things to come, 45% said that they would be comfortable with only using the AI model for stock picking.
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Hopefully, the survey respondents -- as well as all other aspirant Midases in waiting -- are aware that ChatGPT-3.5 was trained on contents of the internet up to 2021. To be closer to the pulse of today's market, they would have to pay for ChatGPT Plus, powered by GPT-4.
Even then, GPT-4 is already dated. There is no current system of feeding generative language AIs with new and dynamic information on the internet, such as stock price or interest rate fluctuations. So, if you're thinking about taking a plunge into day-trading, this would not work well for you.
However, for those looking at slightly broader movements, ChatGPT seems to serve admirably well, and younger Americans, many of them digital natives, have wholeheartedly embraced AI for investing advice.
According to The Motley Fool survey, 50% of Millennials and 53% of Gen Zers used the AI LLM to unearth stock picks. Meanwhile, only 25% of Baby Boomers -- a cohort that still remembers how fax machines and floppy discs work -- felt comfortable doing so.
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Unsurprisingly, the survey also found that income levels can be good predictors of who tends to use the service for stock research. As many as 77% of high-income Americans say they have used ChatGPT for investment recommendations, compared to 43% of middle-income Americans and just 23% of low-income Americans.
Gender differences also turned out to be significant: women -- who have outperformed men as investors recently -- tend to be more conservative in money matters, according to The Motley Fool analyst Asit Sharma, being less impulsive and calmer during market volatility. So, it's no surprise that only 41% of women used ChatGPT versus 55% of men.
In total, just over two-thirds (69%) of American adults said that they would consider using ChatGPT for investment advice in the future. This move to AI could be nothing short of a seismic upheaval in the economics of money management, thanks to the democratization of a tool that even someone like a hedge fund trader is simultaneously salivating over.
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One recent survey of the top 50 hedge fund managers by London-based Market Makers found nine out of 10 hedge fund traders are planning to use AI to manage their portfolios for the rest of 2023.
Already, the news doesn't look too rosy for the money men and women -- such as institutional fund managers -- who control and attempt to grow the vast assets of American savers.
For instance, a hypothetical fund of 38 stocks, chosen by ChatGPT and based on criteria (such as low debt, high growth) culled from the portfolios it was competing against, rose by 4.93% in the first eight weeks since its creation on March 6, 2023, versus an average of -0.78% posted by the 10 most popular funds in the UK. In fact, the hypothetical fund outperformed the top 10 on 34 of the 39 days the market was open.
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Another potential nail in the coffin is a recent ChatGPT-based study conducted at the University of Florida, which suggests even more dire implications for fund managers worldwide.
In a paper published this week in the Social Science Research Network, professors Alejandro Lopez-Lira and Yuehua Tang described how they decided to test ChatGPT in how well it could conduct 'Sentimental Analysis' -- essentially looking at headlines in articles to determine stock-picking strategy.
Again, ChatGPT is not trained beyond September 2021, so the researchers fed the AI model 67,586 headlines pertaining to 4,138 unique companies between then and now.
This kind of analysis has already been taking place in the trading rooms of hedge funds for some time now, but it was the first time that ChatGPT was tested to perform tasks almost identical to expensive proprietary trading platforms and with customized sentiment analysis built-in.
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The ChatGPT trading model, using sentiment analysis, posted returns in excess of 500% during this period against the -12% from buying and holding an S&P 500 ETF during the same period.
If that isn't bad news for the finance industry -- and lower-rung research analysts, in particular, almost every day marks the emergence of new APIs and plug-ins that can integrate with ChatGPT.
For example, PortfolioPilot is a freshly released and verified ChatGPT plugin that allows portfolios to be dumped into it for analysis and recommendations -- all for free.
Considering AI's existing ability to best the most blue-chip of money managers out there, the days of paying mutual funds management fees for middling returns, at least in the current structure, may be winding to a close.
All of this sounds like investing nirvana, but before you plunge into the fray, buying and selling with your favorite investing bot, there are a few things you should keep in mind.
ChatGPT's training ended in September 2021, so anything you ask it will not reflect the time period since. And that gap brings us to the tendency for generative AI to make up things when it doesn't have answers to your questions -- referred to as AI hallucinations.
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Generative AI detects patterns really well, which it does by scraping data from pre-existing texts. However, it does not do well in causal reasoning and you could be lured into believing what it says through its glib conversational abilities. It's also bad at math. Therefore, information or insights have to be double-checked for accuracy.
It also doesn't read facial expressions well, which many investigative journalists and stock pickers rely on when watching CEO or CFO interviews to gauge the actual health of a company.
Finally, according to investment professionals, while it has amazed and delighted with its polished responses, many of these suggestions are still way too generalized to be helpful. It doesn't ask the kind of sophisticated questions that any portfolio manager would.
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Of course, AI can get better at all of these tasks in time, and each version that has come out has proven to be astonishingly better than its predecessor. But we're not quite at investing nirvana yet.
And, when it gets there, we may have to negotiate a slightly larger headache -- how do you make money in a market where information and analysis for any conceivable asset anywhere in the world is not at a premium, but just an AI prompt away?