How people use AI for stock market decisions

ChatGPT’s popularity has exploded since the AI ​​chatbot was released to the public last fall. In just a few months, it gained more than 100 million users.

It can write haiku, pass law school entrance tests, and help you plan your dinner, but can it make you money in the stock market?

It’s a perspective many people are intrigued by, according to a new survey by The Motley Fool.

The investment advisory platform polled 2,000 Americans about their interest in using ChatGPT for stock selection.

Asit Sharma, senior analyst at The Motley Fool, says the practice is already widespread. Marketplace’s Meghan McCarty Carino recently spoke with Sharma about the survey and her analysis of the results.

The following is an edited transcript of their conversation.

AsitSharma: We found that nearly 50% of Americans used ChatGPT for stock recommendations. We should say that we haven’t asked very specific questions about how people use ChatGPT. But I can tell you from what we’ve observed interacting with our members, people are using it in all sorts of ways. They’re asking ChatGPT to provide, for example, a list of small-cap stocks in the biotech space, or “Hey ChatGPT, tell me about a key risk associated with investing in, say, Nvidia.” Or “Could you tell me some safe stocks to invest in in a choppy market?”

Meghan McCarty Cute: Now, was this a case of people who were new to stock trading using this as sort of a beginner’s guide or something else?

Sharma: So we’re seeing real interest from a broad spectrum of investors. We’re seeing this from people who understand that this could be a technology that gives you a more robust answer than just Googling a question about stocks. And we’re seeing very sophisticated investors who have been in the markets for a long time who are cutting and pasting, say, financial statements into ChatGPT and asking for very specific insights to see if there’s anything they might have missed in their analysis.

McCarty Cute: You sort of broke demographic trends in that. Can you tell me about some of the trends that were found in this survey?

Sharma: Safe. So I said earlier, 47% of Americans have used ChatGPT for stock recommendations, that’s nearly 50% I was referring to. Here’s an interesting one: 77% of high-income Americans have used ChatGPT to try to discover some stock recommendation. This makes sense to us because we’ve consistently observed over the years that higher-income Americans typically have access to tools earlier than lower-income ones, and also have a little more free time to test out the latest technology. .

McCarty Cute: Who in the survey was most likely to use this technology and who was a little more skeptical about it?

Sharma: So we found that while 47% used ChatGPT for stock picking, the number of lower-wage workers who used it is still, I think, desirable. Men are more comfortable using ChatGPT than women. 51% of men feel more comfortable relying solely on ChatGPT for investment advice compared to 41% of women surveyed who are more deliberate and less likely to jump headlong into an investment trend. Millennials tend to trust ChatGPT fairly but are still skeptical, as are Gen X and Gen Z respondents. But baby boomers are less likely to express confidence in the accuracy and reliability of ChatGPT’s stock picks. And I will reflect [on] That. You know, baby boomers started investing in a day and age where you picked up a rotary phone to call your broker to place a trade with a high commission. They have seen every single evolution up to the present day from those days. And they’re naturally skeptical of any new wave of technology, not that they’re superlative adopters, they’ve just seen it all. So they are less likely to be confident in the accuracy and reliability of these choices.

McCarty Cute: What are the risks of relying on tools like this for investment advice?

Sharma: One risk I think most people will know about is ChatGPT’s tendency to hallucinate, i.e. create responses that have no basis in reality. We know that ChatGPT is not the most accurate result provider because it was not built to be a search engine. It’s a great language model. So we should be careful to assume that any result ChatGPT gives us is gospel truth. We have to be a little skeptical about what we are reading. I think another risk is the risk that the average investor might mistake ChatGPT’s insights for the only insights or the correct insights. He’s just trying to figure out what the most likely outcome might be. ChatGPT may refer you to an investment view that is not the most important to focus on.

McCarty Cute: Yeah, I think the concept that it’s a large language model but it’s kind of predictive text is an important thing to understand when you think about, you know, data analytics that could go into investment advice, right ?

Sharma: Yes, totally. There is also something that we should say could be very powerful in the future. The nature of ChatGPT is the model of the transformer. It focuses on what it sees is important in a given context versus trying to sequentially figure out what might be more important. This is really interesting when you think about investing because investors tend to look for patterns. Every investor has their own idea of ​​what makes a great stock. The longer you play this game, the more you will get a personalized view of it. ChatGPT, large language patterns, they’re really, really good at spotting patterns. If you feed them what you’re looking for, they have this innate ability to see patterns to bring together disparate qualities and say, “Hey, Meghan, check out this company because it might fit what you’re looking for.”

McCarty Cute: What [could] are tools like these missing that a human analyst like you might not?

Sharma: So these models are really good at gathering information from different sources. They are good at sentiment analysis, so they can spot different emotional indicators in earnings call transcripts or trends and highlight them to a human. What they’re really not good at, though, is taking the time to open YouTube and watch a video of a CEO who might look like he’s covering when asked a tough question in an interview. They really don’t demonstrate the ability to hone in on what I call the BS factor. If we relied too much on these models, just to scrape data and words from pre-existing texts and confuse them with real insight, I think we could stumble there. They haven’t really shown any real reasoning ability or reasoning faculty, but I think over time they could improve. Companies like Meta are developing technologies that read human facial expressions minutely because they are trying to create lifelike avatars. In theory, that technology could be used down the road to map the human face. And maybe a large language model could splice something like this and say, “Hey, Asit, there’s a little BS factor going on in the CEO interview, you should pay attention.”

McCarty Cute: Do you think this kind of technology can replace what you do as an analyst?

Sharma: I still feel that I will have a job in the near future. The funny thing is that ChatGPT [and] large language models are evolving very rapidly. And our understanding of how to use them is also evolving. There are a bunch of fun new plugins coming to OpenAI, which knocks out ChatGPT, as well as standalone filters, front-end filters in the investment world. So I think this is going to be really cool for those who want to experience the technology. I think that’s going to be a big help with how we evaluate inventory recommendations. Myself, I don’t tend to outsource investment decisions to anyone, but this is what I do every day. I have a lot of friends who are very comfortable investing [exchange-traded funds], where you simply give your money to someone who manages a portfolio and check those results after some time, and I think they are naturally investors who will feel perfectly comfortable at some point as the models improve by asking ChatGPT for insights based on their preferences, building a portfolio and only checking quarterly. So I don’t know about my work in the next few years. In the immediate future, maybe I can still come to work.

Financial comparison site Finder recently ran an experiment testing ChatGPT’s stock recommendations against several major UK investment funds

The ChatGPT portfolio outperformed other funds and the S&P 500 index over the same period.

Among the companies chosen by ChatGPT for investment was Microsoft, which appears to be a major backer of ChatGPT’s maker, OpenAI, and has integrated the chatbot into its own products.

Which, I don’t know, looks like maybe a conflict of interest?

My Marketplace colleague Janet Nguyen also explored whether ChatGPT could be used to predict future monetary policy by analyzing Federal Reserve Chairman Jerome Powell’s public comments. Overall, the chatbot was good at providing short summaries of Powell’s talks.

But when it comes to more nuanced takes, you might still want to tune into “Marketplace” for it.

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