Speaker 1: Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2: You're listening to Bloomberg BusinessWeek with Carol Masser and Tim
Speaker 2: Stenoveek on Bloomberg Radio.
Speaker 1: It's one of the most read stories on the Bloomberg terminal.
Speaker 1: It's about how Jenai is transforming retail investing. It's enabling
Speaker 1: individual traders to build and execute institutional grade quant strategies
Speaker 1: that have once been reserved for major Wall Street hedge funds.
Speaker 1: Bernard Guider is one half of the duo behind this story.
Speaker 1: He's US Options reporter for Bloomberg News. He joins us
Speaker 1: here in the Bloomberg Interactive Broker's Studio. Congratulations on the story.
Speaker 1: I'm struck by all of the individuals you highlighted in
Speaker 1: the story because there's this pattern that has emerged. They
Speaker 1: were doing one thing before they quit that job to
Speaker 1: vibe code or create some sort of AI solution to
Speaker 1: trading that they think can get them of salary. How
Speaker 1: are they doing it?
Speaker 3: Yeah, I think it. It's really indicative of that broader
Speaker 3: trend in retail investing we've seen since the pandemic, with
Speaker 3: people putting aside what they were doing before and jumping
Speaker 3: in and trying to make a living out of trading, really,
Speaker 3: and these are some of the more professional side of
Speaker 3: the retail investing world. I think we often like to
Speaker 3: characterize retail investors as having this really high risk appetite,
Speaker 3: But if you're doing this as a job, actually your
Speaker 3: risk appetite is going to be pretty low and reasonable.
Speaker 3: So I think one of the guys had he put
Speaker 3: five percent of his portfolio into this kind of magic
Speaker 3: money machine that's trading for him. Somebody else was doing
Speaker 3: one trade a day on robin Hood, but it was
Speaker 3: an agentic AI, and he goes and does his day
Speaker 3: job in it and lets this thing in the background.
Speaker 3: He'll get a notification on his phone sometime during the
Speaker 3: day being like your trade went through. And that's just
Speaker 3: the way these people are doing. I mean, there's another
Speaker 3: guy who's got to stop loss at ten percent once
Speaker 3: his portfolio. Once his position drops by more than ten percent,
Speaker 3: that stop lost kicks in automatically. And that's the same
Speaker 3: as if you were in a seat at a hedge fund.
Speaker 3: It's a similar kind of system. And I think what
Speaker 3: the AI has done is it's grabbed all of that
Speaker 3: information and from all of the best practices across Wall
Speaker 3: Street and is now giving that to ordinary people.
Speaker 4: So right, I think folks have always tried to kind
Speaker 4: of crack the code right of what goes on at
Speaker 4: some of these elite firms and these hedge funds. But
Speaker 4: AI has given them a tool that's getting them closer
Speaker 4: to it.
Speaker 2: It has.
Speaker 3: But bear in mind that this is giving people the
Speaker 3: same kind of tools that maybe Wall Street had eight
Speaker 3: years ago, which probably means that Wall Street is way, way,
Speaker 3: way further ahead of some of these people. But it
Speaker 3: definitely makes it definitely makes it more viable to try
Speaker 3: and execute trades automatically using AI, and more and more
Speaker 3: people seem to be taking that on. I'm Vlad the
Speaker 3: CEO of Robin Hood posted that one hundred thousand people
Speaker 3: had plugged into their Argentic AI system. They're one of
Speaker 3: the brokers that offers this is.
Speaker 1: Other brokers operate apart from Robin who you read about,
Speaker 1: Futoo Holdings, Moomu Public Holdings all rolling this out. Are
Speaker 1: there notable holdouts of retail trading firms or firms that
Speaker 1: are popular with retail traders are that are saying no
Speaker 1: to this tech as of now?
Speaker 3: I wouldn't I think some firms are more cautious, So
Speaker 3: traditionally Charles Schwab is generally on the more cautious end
Speaker 3: in terms of in terms of this stuff, they do
Speaker 3: have API technology you can plug into, plug a system
Speaker 3: into Schwab, but in terms of like enabling people to
Speaker 3: kind of trade automatically through AI, I definitely point to them.
Speaker 3: And the big one is really the banks.
Speaker 2: A lot of.
Speaker 3: People will use their use that the brokerage that they're
Speaker 3: bank owns to trade through, and those really aren't offering
Speaker 3: that at this point. They're still kind of pushing people
Speaker 3: towards more traditional wealth management services.
Speaker 4: I mean, is this the you know, we always talk
Speaker 4: about financial disruption, right, We talked about fintech and all
Speaker 4: these different things. But I feel like, is this the
Speaker 4: thing that really disrupts kind of Wall Street and trading
Speaker 4: as we know it.
Speaker 3: I think that's what some people in the industry would
Speaker 3: like to think. So Anthony Dennya, the we Will president,
Speaker 3: was quoted in the story as saying, this is zero
Speaker 3: commission two point zero.
Speaker 1: And I thought that was a remarkable thing for him
Speaker 1: to saying, because that changed for trading.
Speaker 2: It completely revolutionized it.
Speaker 3: So there is a I think it's I think you've
Speaker 3: got to kind of separate the people that are very
Speaker 3: much keen for just trading to happen. And Matt Levine
Speaker 3: makes this point in today's newsletter as well in Money Stuff,
Speaker 3: that there's a lot of people who are incentivized just
Speaker 3: to have loads and loads of trading happening, and they
Speaker 3: don't really care what happens to it. I think it
Speaker 3: can have a big impact. I think it's easy to
Speaker 3: overstate what AI does, but I think ultimately one of
Speaker 3: the big changes could actually be the business model, because
Speaker 3: ultimately the payment for order flow, which is this idea
Speaker 3: that you can get free commission free trading, and marketmakers
Speaker 3: are happy to get that. The more sophisticated that these
Speaker 3: retail traders become, the worse a business proposition it becomes
Speaker 3: to trade against them, and that could actually change the
Speaker 3: economics of some of the payment for order flow models.
Speaker 1: I'm laughing when you mentioned payment for order flow, because
Speaker 1: it was just what five years ago at this point,
Speaker 1: that we were talking about payment for order flow every
Speaker 1: single day, and it was seen as a really pretty
Speaker 1: controversial way for us to be able to do free
Speaker 1: trades and essays as retail participants. Okay, so I want
Speaker 1: to talk Oregon.
Speaker 4: Say just one thing though, like if Wall Street's always
Speaker 4: eight you know, eight steps ahead or whatever it is,
Speaker 4: So yeah, I.
Speaker 1: Don't think Jane Street is doing this.
Speaker 4: So is it mean that the retail investor, Yeah, may
Speaker 4: have some fun and do well, but there's always there
Speaker 4: are still ahead wels Like how does that impact this?
Speaker 2: Yeah, I think it's a great question.
Speaker 3: I would say that there are definitely there are definitely
Speaker 3: situations where Main Street is catching up with Wall Street.
Speaker 3: But ultimately, when it comes to market making, when it
Speaker 3: comes to the kind of stuff that Jane Street does
Speaker 3: and sit at our securities and yeah, Hudson River Trading
Speaker 3: in the equity market, Yes, those firms aren't many multiple
Speaker 3: steps ahead, and they're the main counterparty to retail in
Speaker 3: prediction markets as well. Now that in terms of Susquehanna
Speaker 3: is one of the big counter parties Jump Trading as well.
Speaker 3: So yeah, I mean retail is facing off against very
Speaker 3: very powerful professional firms.
Speaker 2: What I'm saying is that.
Speaker 3: Retail has a lot more tools in their arsenal than
Speaker 3: they used to, Okay, to play this game, and maybe
Speaker 3: it's less of an unfair fight.
Speaker 2: Than it used to be.
Speaker 1: We're speaking with Bernard Goiter, options reporter for Bloomberg News.
Speaker 1: He joins us here on set in New York. Bernard,
Speaker 1: I'm wondering about and my question will show that I
Speaker 1: am not a vibe coder, but one question that I've
Speaker 1: had wants trying to be I'll get there one day.
Speaker 1: If if retailers, or if retail participants rather are using
Speaker 1: the same tools to create agents to do this work
Speaker 1: on behalf of them, does that mean that they're sort
Speaker 1: of making the same trades as each other and there's
Speaker 1: going to be like less of an opportunity for them
Speaker 1: to sort of find something that's unique to what they
Speaker 1: actually believe. Does that make sense?
Speaker 2: Yes, it does.
Speaker 3: So there is this question of crowding of people going
Speaker 3: to make a load of the same same decisions. And
Speaker 3: funnily enough, that's also that something that happens on traditional
Speaker 3: markets with Wall Street, you see that with the pun
Speaker 3: shops all entering the same trades, whether that's equity dispersion
Speaker 3: trade is one example that very very popular trade that
Speaker 3: lots of the hedge funds all did at the same time.
Speaker 3: You have it with the in the treasury market. You
Speaker 3: have it with the with the basis trades between treasuries
Speaker 3: and treasury futures. So it's a common problem that exists,
Speaker 3: and maybe it's going to come more so on. But
Speaker 3: I think as long as as long as there are
Speaker 3: some as long as some people are bullish and some
Speaker 3: people are parished, then there should be enough enough kind
Speaker 3: of mix in there.
Speaker 1: It's sort of the same argument that people use about
Speaker 1: investing in index funds, right, or they're going to be
Speaker 1: too many index funds investors, then you won't actually see
Speaker 1: the daily movements. We have not seen that play out,
Speaker 1: and we still have pretty big daily movements in individual stocks. Yeah.
Speaker 4: Absolutely, Like I think, you know, all right, so this
Speaker 4: is the way everything's going. I just think about, like,
Speaker 4: so what happens in a crisis or do we.
Speaker 3: One issue is that some of the model sets that
Speaker 3: people are using, they don't go back that far. So
Speaker 3: if you're trading zero day options, that's only really been
Speaker 3: an asset class that people have been trading in and
Speaker 3: out of since twenty twenty two, that hasn't really seen
Speaker 3: a proper bet market yet, So you could have a
Speaker 3: situation a bit like the run up to two thousand
Speaker 3: and eight housing crisis, where none of the models were
Speaker 3: trained on a scenario where house prices get go down
Speaker 3: in the same way. None of these models are necessarily
Speaker 3: trained in a scenario where share prices fall significantly and
Speaker 3: then and then stay there. So that's definitely a concern
Speaker 3: for people. But people often kind of are interrogating these
Speaker 3: models and asking the right question. But you've got to
Speaker 3: sometimes you've got to push it. You've got to push
Speaker 3: it to be like, hey, did you think of this
Speaker 3: kind of thing? Right?
Speaker 4: That's interesting I would imagine I would have thought that
Speaker 4: the models would be tested or they're getting there.
Speaker 3: Well, it depends there only is there only? It depends
Speaker 3: what data set it's been trained. Yeah, and it depends
Speaker 3: on what questions you ask it. You as a human
Speaker 3: ultimately have to be the one that interrogates it. You
Speaker 3: have to you have a human As a human, you
Speaker 3: have to say, Okay, what happens if there's a two
Speaker 3: thousand and eight style crisis on this on this kind
Speaker 3: of model portfolio, or on this on this trading system.
Speaker 3: So ultimately a lot of it still goes back to
Speaker 3: the decisions being made by the individual, but instead of
Speaker 3: it being a human kind of picking specific trade. It's
Speaker 3: more about designing a model, so your job becomes a
Speaker 3: lot more like a quant at a hedge fund and
Speaker 3: much less like an individual punter kind of throwing darts
Speaker 3: at a dartboard.
Speaker 1: You just very briefly you got to see how these
Speaker 1: models work in the real world and how these agents
Speaker 1: work in the real world. Is there how much further
Speaker 1: does it go in the next couple of years.
Speaker 2: I think.
Speaker 3: I was very surprised by how sophisticated these these these
Speaker 3: trading tools have become, and I think it will go
Speaker 3: a lot further. I think it's going to become a
Speaker 3: lot more mainstream, partly because one of the one of
Speaker 3: the downsides of trading is that it's very labor intensive
Speaker 3: and actually quite boring just sitting there being like, oh,
Speaker 3: it's hit the Bollinger band, Like that's not that fun
Speaker 3: for most people, like unless you're kind of a strange person.
Speaker 2: But I like the idea if I can if it's
Speaker 2: strange here, yeah, but you know, apart.
Speaker 3: From you know, because I'm sure a couple of our listeners,
Speaker 3: that's not actually that exciting.
Speaker 2: Whereas if you can.
Speaker 3: Get a lot of that boring stuff being done for
Speaker 3: you by an AI and it makes money in a
Speaker 3: safe way.
Speaker 2: Yeah. I think it's going to become superbul.
Speaker 1: You can go out and go for a walk.
Speaker 2: Well, what do you do right for a walk? Yeah,
Speaker 2: you're going you go and neicate you the real world.
Speaker 1: YEA touch good.
Speaker 2: They don't want
Speaker 1: Bernard guiter Us options reported for Bloomberg News.