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Speaker 1: Welcome to Crash Course, a podcast about business, political, and

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Speaker 1: social disruption and what we can learn from it. I'm

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Speaker 1: Tim O'Brien. Today's Crash Course AI versus Money Managers, as

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Speaker 1: we've all heard by now, AI or artificial intelligence has

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Speaker 1: arrived courtesy of chat GPT, the large language model software

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Speaker 1: that already has more than one hundred million users. It

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Speaker 1: processes questions and turns out brilliant answers in the blink

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Speaker 1: of an eye. It isn't sentiented at software after all,

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Speaker 1: but still it gives every appearance of having the ability

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Speaker 1: to learn and adapt to refine its output in increasingly

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Speaker 1: sophisticated ways. We're also used to economic and technological revolutions

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Speaker 1: battering blue collar workers the hardest, but chat GPT's debut

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Speaker 1: signals that any number of white collar jobs could be

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Speaker 1: disrupted and replaced by bots. Writing, tea, teaching, programming, client services,

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Speaker 1: analysis of many stripes, consulting, healthcare, and many other professions

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Speaker 1: may all be up for grabs in this brave new world.

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Speaker 1: Money management, the science and art of successfully investing for

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Speaker 1: institutions and individuals could also be in ais crosshairs. Investing

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Speaker 1: has already been transformed over the last several decades by computers,

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Speaker 1: an avalanche of ubiquitous global market, corporate and financial data,

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Speaker 1: oceans of liquidity, stronger risk management tools, and evermore probing

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Speaker 1: and state of the art quantitative analysis. AI promises to

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Speaker 1: up the ante even further, joining me to talk about

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Speaker 1: whether or not bots are going to devour money. Manager's

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Speaker 1: business and livelihoods are Aaron Brown and Near Kasar. Both

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Speaker 1: of these gentlemen are contributing columnists for Boomberg Opinion, and

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Speaker 1: both of them are successful investors. Aaron, you're the former

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Speaker 1: chief risk officer for one of the world's largest funds,

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Speaker 1: AQR Capital Management, and a prolific author. Welcome to the show.

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Speaker 2: Thank you very much.

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Speaker 1: Tim, and Niir you're the founder of Unison Advisors, an

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Speaker 1: investment firm specializing in multi asset portfolios. Thanks for joining us.

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Speaker 1: Thanks Tim okay. So, this is the first time I've

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Speaker 1: had two guests on simultaneously, So let's see how this goes.

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Speaker 1: I'd like you both to jump in when you feel inspired,

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Speaker 1: but I'll also try to steer things along so our

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Speaker 1: listeners can keep track. And a warning, guys, if you

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Speaker 1: start throwing around alpha's beta's VARs and other fancy lingo.

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Speaker 1: I'm going to stop you and ask you to explain yourselves.

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Speaker 1: All right, Eron, let's start with you, and let's move

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Speaker 1: through some of the basics. What is money management? To

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Speaker 1: find it for me? And I'm looking for an umbrella

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Speaker 1: term here, which is why I chose money management. Maybe

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Speaker 1: I should have stuck with plain old investing. Anyway, have

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Speaker 1: at it. What is money management?

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Speaker 2: Well, from a practical business standpoint, there are two main

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Speaker 2: things you have to do. One of them is to

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Speaker 2: get people to trust you with their money, and the

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Speaker 2: second is to either convince them that you're doing this

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Speaker 2: or to actually do this is to provide them any

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Speaker 2: better return they can get from purely passive index funds

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Speaker 2: or other inexpensive simple techniques. And you know it can

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Speaker 2: range from while even running index funds on one hand,

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Speaker 2: just getting them more cheaply than other people, to some

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Speaker 2: of the most sophisticated strategies where you demand fifty percent

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Speaker 2: of the profits in return for delivering or promising really

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Speaker 2: exceptional returns.

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Speaker 1: Do you agree with that definition?

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Speaker 3: I agree with what Erin has said. I would just

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Speaker 3: take one step back and say we all have a

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Speaker 3: practical problem that we face, and the practical problem that

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Speaker 3: we have is if we are fortunate enough to have

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Speaker 3: savings in our life, then we have to do something

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Speaker 3: with those savings. And you can put that in the

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Speaker 3: bank or there's various places that you can put in,

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Speaker 3: but you have to do something with it, and primarily

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Speaker 3: you have to put it. It's great if you can

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Speaker 3: grow it, but you don't want to lose the money

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Speaker 3: that you save, and so you have an issue, and

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Speaker 3: the question is what is the best way to handle

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Speaker 3: that money. There are professionals money managers, let's say, who

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Speaker 3: will come along and we'll manage it for you, just

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Speaker 3: like there are people who will do any number of

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Speaker 3: services in your life, and we'll charge your fee to

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Speaker 3: do it. Increasingly, it's getting easier to do that yourself.

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Speaker 3: But at the end of the day, money management seeks

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Speaker 3: to solve a very simple problem, which is I have savings.

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Speaker 3: I want to preserve and grow those savings.

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Speaker 1: So now that we know what money management is, let's

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Speaker 1: take that up a step further than here. What is

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Speaker 1: successful money management?

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Speaker 3: Well, that's a trickier question, and you're going to get

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Speaker 3: a far broader range of opinions on that. I think

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Speaker 3: what I would say is, ultimately, this also is a

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Speaker 3: practical question, which is, you have savings that we have

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Speaker 3: said you want to preserve and grow, and at the

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Speaker 3: same time you have inflation nipping at your heels. In

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Speaker 3: other words, every single day that you hold a dollar,

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Speaker 3: the value of that dollar goes down because inflation is

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Speaker 3: catching up to it. So at the very least, if

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Speaker 3: you want to preserve the value of your savings, you

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Speaker 3: have to make it grow faster than the rate of inflation.

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Speaker 3: And there are various ways that you can do that.

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Speaker 3: You can invest in bonds, you can invest in stocks,

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Speaker 3: all things you can get into if you want. But

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Speaker 3: the important thing to know is you can't just take

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Speaker 3: and stuff it in your mattress, because if you do,

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Speaker 3: the value of that will go down over time.

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Speaker 1: And so expertise matters in this realm.

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Speaker 3: Expertise is important, I would say, to avoid many of

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Speaker 3: the pitfalls. However, one of the things that's interesting about

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Speaker 3: technology and the way that markets have evolved is expertise

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Speaker 3: is becoming less and less important if your goal is

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Speaker 3: merely to try to grow your money faster than the

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Speaker 3: rate of inflation.

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Speaker 1: So Aaron jump in, do you agree with Near's notion

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Speaker 1: of what successful money management.

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Speaker 2: Is, I don't disagree with him, but most of successful

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Speaker 2: money management is in the head of the investor or

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Speaker 2: the beneficial owner. Yes, it's nice if your money grows

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Speaker 2: faster than inflation, but it's more important that you sleep

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Speaker 2: at night, that you feel financially secure, that you trust

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Speaker 2: what's going on. And so a lot of money management

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Speaker 2: is about either reassuring individuals or explaining to them precisely

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Speaker 2: what you are going to do when you are going

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Speaker 2: to lose or make money, or, in the case of institutions,

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Speaker 2: dealing with their institutional constraints peer risk. You know, chief

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Speaker 2: investment officers of pension funds seem to spend a lot

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Speaker 2: more time worrying about how they're outperforming their peers than

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Speaker 2: about any kind of absolute goal. So I think money

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Speaker 2: management goes well beyond getting an inflation beating return or

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Speaker 2: reducing risk. The investor has to understand and appreciate it.

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Speaker 1: So you think it actually goes into being a nanny

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Speaker 1: or a therapist.

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Speaker 2: Well, there is quite a lot of that. You spend

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Speaker 2: an awful lot of time as a money manager on

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Speaker 2: the phone with clients, prepairing presentations, that make people feel

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Speaker 2: good about what you're doing.

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Speaker 1: I guess you know, boy, we could really just go

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Speaker 1: off on that one, because obviously comes out of the

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Speaker 1: fact that people are ignorant, as we all are, about

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Speaker 1: any number of things, including money, and if they're not

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Speaker 1: doing the hard work to get up to speed on

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Speaker 1: how they're investing their money, it opens up an ability

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Speaker 1: for a money manager to give them calming advice, soothing advice,

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Speaker 1: stuff that'll let them sleep well at night. That's a

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Speaker 1: different kind of intelligence, and I'm not saying it's not worthy,

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Speaker 1: but that's eq to a certain extent as opposed to IQ.

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Speaker 2: Right, I would agree with that, Yes, it is, or

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Speaker 2: in the case of institutions, it's I don't know, there's

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Speaker 2: a thing for that, you know, institutional queue.

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Speaker 1: And I guess it can open the door to hucksterism too, Right,

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Speaker 1: If you're able to soothe people's nerves who actually aren't

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Speaker 1: up to speed fully on how the markets work or

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Speaker 1: what they should do with their money, they can also

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Speaker 1: become marks, can't they.

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Speaker 2: Yeah, that's absolutely true, but I think people tend to

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Speaker 2: veer too quickly in that direction. Traditional financial advisors, the

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Speaker 2: kind of people we used to used you used to

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Speaker 2: work with individuals. Some of them were hucksters, some of

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Speaker 2: them were just churning for commissions and putting people in

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Speaker 2: all kinds of bad stuff, But many of them really

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Speaker 2: gave their clients a secure, happy financial life. They understood

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Speaker 2: insurance and taxes and wills and other matters. They took

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Speaker 2: care of a million details that keep people up at night.

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Speaker 2: A lot of people today are unhappy with all the

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Speaker 2: choices and information and things they have to worry about.

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Speaker 2: And the old fashioned financial advisor, even charging fairly high fees,

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Speaker 2: really gave many people a great service.

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Speaker 1: There's also a lot more information because of technological developments

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Speaker 1: available to investors now. There's a certain amount of transparency

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Speaker 1: and intellectual dexterity that's available to average investors that wasn't present, say,

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Speaker 1: even three decades ago. Isn't that right, Neir?

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Speaker 3: Certainly, there are a lot of people doing a lot

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Speaker 3: of great things within money management, and there are some

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Speaker 3: people I would say the bias here here it tends

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Speaker 3: to be more sort of in the direction of Wall Street.

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Speaker 3: There's still a lot of shenanigans that go on. I

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Speaker 3: would say the industry taking advantage of people who aren't

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Speaker 3: as well versed, but certainly there are more tools available

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Speaker 3: to ordinary investors today than there have ever been, and

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Speaker 3: it's easier for them to manage their money if they

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Speaker 3: want to manage their money, and cheaper for them to

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Speaker 3: do it than it has ever been. And it's so

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Speaker 3: cheap and easy actually that it's hard to imagine it

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Speaker 3: moving further in that direction. The question is whether we

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Speaker 3: can get the information we as an industry can get

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Speaker 3: that information to ordinary investors, and maybe more importantly, whether

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Speaker 3: we have the financial incentive to get that information to investors.

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Speaker 3: And that's something that the industry has been grappling with

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Speaker 3: for probably ten or twenty years, as this information and

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Speaker 3: the ability to invest cheaply and yourself has become available.

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Speaker 1: So in that context, then what goal ideally does successful

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Speaker 1: investing serve from.

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Speaker 3: The perspective of the investor? Yes, I mean I think

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Speaker 3: I will marry sort of the two perspectives that are complimentary,

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Speaker 3: not opposing that Aaron and I have both offered. I mean, ultimately,

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Speaker 3: what you want is you want to preserve and grow

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Speaker 3: your money, and you also want to be at peace

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Speaker 3: with your money. I mean, there are a lot of

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Speaker 3: people and everybody knows people like this who are just

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Speaker 3: constantly anxious about how much money they have and do

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Speaker 3: they have enough money? And are they going to lose

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Speaker 3: their money? And you know, money is a big deal.

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Speaker 3: And ultimately, yes, you want your money to be in

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Speaker 3: a good place and you want it to grow, but

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Speaker 3: you also want to be in harmony with your money.

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Speaker 3: You don't want to have to be anxious about it

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Speaker 3: all the time. And so that is the picture in

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Speaker 3: my view of like a full life in relation to

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Speaker 3: your money.

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Speaker 1: Is that sort of where you come down erin?

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Speaker 2: Yeah, personally, I kind of I'm perfectly happy to put

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Speaker 2: a lot of my money in index funds and just

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Speaker 2: take the average and you know, if it goes up,

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Speaker 2: goes up. If it goes down, it goes down. But

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Speaker 2: many people are not you know, many people want to

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Speaker 2: know that someone's looking at their money. That person may

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Speaker 2: not be able to prove they actually do any good

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Speaker 2: that you know, when they pull out of companies, those

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Speaker 2: companies go down. When they overinvest overweight a company, it

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Speaker 2: goes up, but it's very reassuring to people and know

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Speaker 2: someone is watching it.

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Speaker 3: The question, though, I would ask Tim and Aaron, is

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Speaker 3: the people who don't prefer to invest in index funds?

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Speaker 3: Are they doing that from a knowing place? In other words,

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Speaker 3: Aaron I would argue, the reason you prefer index funds

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Speaker 3: is because you're highly sophisticated about financial markets, and you

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Speaker 3: have all of the evidence in a peer of view literature,

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Speaker 3: et cetera at your fingertips, and you know what it says,

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Speaker 3: and you probably know that you're best off in index funds.

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Speaker 3: The question is, are most people that's sophisticated when they

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Speaker 3: say they prefer something other than an index fund? Are

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Speaker 3: they making a knowing decision? Are they making a decision

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Speaker 3: out of ignorance? Or have they been directed by an

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Speaker 3: industry to more expensive products? And index funds is an

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Speaker 3: alternative fully sort of on a fully informed basis.

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Speaker 2: Yeah, yeah, my argument, And of course maybe I'm the

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Speaker 2: last person to tell how good my thinking is, but yeah,

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Speaker 2: I mean I like the index funds, and I also

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Speaker 2: likes I pay very high fees or use some very

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Speaker 2: sophisticated strategies where I think I have an edge. There

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Speaker 2: is a middle ground of sort of your traditional actively

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Speaker 2: managed mutual fund that has no strong track record of

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Speaker 2: success that I think are pretty clearly not good that

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Speaker 2: pretty clearly lose money to inflation and taxes in the

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Speaker 2: long run after fees, and especially do not outperform index funds.

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Speaker 2: And that is clearly a marketing effort that this product

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Speaker 2: has been sold more or less for the same reason

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Speaker 2: that you know, people pick a name brand Coca Cola

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Speaker 2: over a generic store cola with identical ingredients. You know,

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Speaker 2: it's the branding.

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Speaker 3: But Aaron, this is what I mean by making a

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Speaker 3: knowing decision. I think when we say there are some

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Speaker 3: good managers some bad managers, I think we underestimate the problem.

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Speaker 3: I mean, the evidence is that the vast majority of

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Speaker 3: people who are going to try to beat the index

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Speaker 3: are going to use to the index, and that includes

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Speaker 3: the most sophisticated managers charging the highest fees. So it's

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Speaker 3: not just that, yes, you could find a manager who's

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Speaker 3: going to beat the index, but the probability of your

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Speaker 3: doing that, and you're doing that in advance, is very,

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Speaker 3: very very low. Would you agree with that?

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Speaker 2: No, No, I wouldn't. I believe that if you apply

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Speaker 2: sensible filters, so you kind of filter out the people

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Speaker 2: who aren't doing anything than people with actually bad track

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Speaker 2: records and so on, I think that certainly an institution

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Speaker 2: can do a much better job combining some low fee

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Speaker 2: index products with some very sophisticated high fee products. Not

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Speaker 2: necessarily that we'll beat the index, but that will combine

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Speaker 2: with the index to give a better risk adjusted return.

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Speaker 2: The average retail investor who doesn't have access to the

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Speaker 2: good hedge funds, who doesn't have the time or expertise

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Speaker 2: to pick solid mutual funds from just branded ones that

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Speaker 2: have no advantage, I think that person is much better

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Speaker 2: off sticking with the cheapest, most tax efficient, well DIVERSI

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Speaker 2: fied index funds.

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Speaker 1: Now, we could stay on this particular topic for the

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Speaker 1: rest of the show, but we're not doing index funds.

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Speaker 1: We're going to get into AI. The only reason I'm

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Speaker 1: calling a halt to this avenue of discussion is because

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Speaker 1: we'll never keep going on to the other ones, which

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Speaker 1: means you guys will have to come back again so

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Speaker 1: we can talk about other things. One other foundational idea

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Speaker 1: I want to lay down now as we continue to

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Speaker 1: talk about this is the idea of is investing different

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Speaker 1: from trading? And I want to make that distinction now

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Speaker 1: because I want to come back to it later when

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Speaker 1: we talk about AI's role in all of this. I

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Speaker 1: think of trading as a time constrained tool that might

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Speaker 1: involve strategy, but I think of investing as a less

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Speaker 1: time constrained philosophy that has to involve strategy. But go ahead,

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Speaker 1: erin school me if you disagree with how I've partsed

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Speaker 1: the differences between these two things.

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Speaker 2: Yeah, that's a good way to do it. And in

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Speaker 2: the context of AI and machine learning, they've been enormously

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Speaker 2: successful than trading, and in fact, really for about thirty

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Speaker 2: years now, computers have done all the serious trading, not

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Speaker 2: necessarily with artificial intelligence, the original algorithms and systematic things.

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Speaker 2: We're very simple. Now you think, you know, trading is machines.

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Speaker 2: It's like, you know, the autopilot and an airplane. It's

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Speaker 2: just much much better than humans investing. So far, we

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Speaker 2: have not seen much real success from artificial intelligence.

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Speaker 1: Near Where do you reside on that?

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Speaker 3: I agree with all that, I would just add for me,

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Speaker 3: there's an element of duration, So I tend to think

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Speaker 3: of trading as just a short term bet, whereas investing

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Speaker 3: is a longer term bet, and it's not necessarily binary.

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Speaker 3: You know, one can sort of define those in different ways,

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Speaker 3: but certainly the longer term your horizon, the more you're

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Speaker 3: investing in, the less you're trading.

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Speaker 1: Okay, now that we've cleared up all of that, I

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Speaker 1: want to take a brief break to hear from one

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Speaker 1: of our sponsors, and then we'll be right back. We're

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Speaker 1: back with two smarties, Aaron Brown in their case, are

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Speaker 1: and we're talking about whether AI is going to up

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Speaker 1: end Wall Street and the legions of people who work

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Speaker 1: as money managers in one form or another. So Aaron,

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Speaker 1: let's continue. We've tried to define what investing is. Now

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Speaker 1: let's talk about how AI might tip the entire Apple card.

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Speaker 1: Lead us off with that thought, what do you think

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Speaker 1: the arrival of AI means for the investing world?

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Speaker 2: Well, okay, so we're talking about investment here, not trading.

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Speaker 2: I spent an awful out of the last fifteen years

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Speaker 2: trying to use advances and machine learning and artificial intelligence

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Speaker 2: and data science to improve investing decisions. I mean, in theory,

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Speaker 2: you can turn your algorithm loose unlimited amounts of data

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Speaker 2: in any language, reacting instantly to news announcements before a

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Speaker 2: human has read the first word. It can digest whether

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Speaker 2: it's positive or negative and put in trades. And this

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Speaker 2: huge broad perspective, able to instantly correlate information of totally

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Speaker 2: different accounting data, research reports of government statistics and so on,

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Speaker 2: should allow you to make much better investment decisions. Should

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Speaker 2: be able to tell you you know which companies are

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Speaker 2: going to succeed and grow and which ones are going

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Speaker 2: to stumble and fall. It just doesn't yet seem to work,

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Speaker 2: and I don't know why.

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Speaker 1: Last year you wrote, and I'll quote you, that a

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Speaker 1: tireless machine, able to digest all information and immune to

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Speaker 1: biases should be clearly superior to humans when it comes

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Speaker 1: to investing. Except it's not close.

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Speaker 2: Quote.

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Speaker 1: You've also said that humans are essential in the investment process.

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Speaker 1: So how so why does warm blood matter in this argument?

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Speaker 2: Well, that's a dated quote. The humans being essential in

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Speaker 2: the investment process. I said was that machine learning tends

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Speaker 2: to be a black box and it can't explain itself.

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Speaker 2: You can't give it new information and come up with

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Speaker 2: a better joint decision. But chat GPT kind of blew

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Speaker 2: that out of the water. Now computers are actually better

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Speaker 2: at explaining their decisions and conversing with you. You can

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Speaker 2: give it new information, you can ask it questions and

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Speaker 2: you can change it OWT comes. Unfortunately, what we know

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Speaker 2: about chat GPT is that it often gives very, very convincing,

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Speaker 2: persuasive answers that sound like the world's greatest expert that

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Speaker 2: are completely wrong. So we need to take that next step.

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Speaker 2: But if we can take that next step and chat

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Speaker 2: chief TP confine itself to actual things, it knows. Yeah,

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Speaker 2: I'm not sure we do need humans anymore.

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Speaker 1: You know, you cited to research papers in a more

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Speaker 1: recent column you wrote, and you noted that the interpretation

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Speaker 1: of text and financial price movements may forecast a different

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Speaker 1: outcome with AI. You said, it's a long way from

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Speaker 1: taking over Wall Street, but there's no reason to think

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Speaker 1: it can't. Is that how you see it? Still?

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Speaker 2: Yeah, what we've seen, the successes we have seen is

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Speaker 2: you know what I call the wrong answer Faster machines

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Speaker 2: are getting pretty good at guessing how humans will interpret something,

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Speaker 2: and they can do it in microseconds instead of half

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Speaker 2: an hour, So you get a huge trading advantage from that,

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Speaker 2: But you're still only predicting how humans will view something.

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Speaker 2: You're not actually getting at fundamental economic reality.

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Speaker 1: So near is AI going to eat money? Manager's lunch.

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Speaker 3: I think it's entirely plausible that AI will displace what

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Speaker 3: humans do now. But I think to fully understand that

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Speaker 3: we have to set the stage of what is happening

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Speaker 3: today before you inject AI into it. And that is

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Speaker 3: to say, you have the market at large, the stock

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Speaker 3: market A lot of people look at, say the SP

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Speaker 3: five hundred or whatever it is. You have the market

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Speaker 3: on the stock side. You have the market on the

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Speaker 3: bond side, and that is already automated. If you want

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Speaker 3: to buy the market, the bond market or the stock market,

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Speaker 3: you can do that now with very little interference from

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Speaker 3: human beings, and so technology has already taken that. Over

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Speaker 3: on the other side, you have a bunch of humans

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Speaker 3: running around and there has been for a couple of

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Speaker 3: decades trying to do better than that. And this is

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Speaker 3: the part that it's entirely plausible that AI will come

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Speaker 3: in and replace those people. So now AI is going

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Speaker 3: to try to do better than the market. And the

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Speaker 3: thing that we have to understand about that is that

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Speaker 3: the vast majority of these humans running around trying to

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Speaker 3: do this are wasting their time because the vast majority

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Speaker 3: of them will fail at it. Over any reasonable period,

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Speaker 3: more than ninety percent of them will not be able

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Speaker 3: to do it, And so you can stop and ask

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Speaker 3: yourself philosophically, why are they doing this if they can't win.

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Speaker 3: Let's leave that aside for one second, although we can

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Speaker 3: come back to it if you want. Now inject AI

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Speaker 3: into those people's chairs and ask yourself a couple of questions.

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Speaker 3: One is, Okay, if the AI replaces the humans and

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Speaker 3: the humans can't do it, is there a reason to

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Speaker 3: believe that AI is going to do it any better

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Speaker 3: than them? And the truth is, we don't know the

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Speaker 3: answer to that question. But let's give AI the benefit

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Speaker 3: of the doubt, and let's say that AI is so

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Speaker 3: much smarter than what humans can do that it will

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Speaker 3: now be able to beat the market to do what

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Speaker 3: humans have always wanted to do. The problem with that

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Speaker 3: is the first person in the AI is going to

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Speaker 3: have an advantage, clearly, but as AI becomes more adopted,

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Speaker 3: because ultimately profits are going to attract competition, everybody has

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Speaker 3: an AI, then no one can beat the market.

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Speaker 1: In other words, you lose the first mover advantage over time.

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Speaker 3: Exactly if it turns out that AI will be as

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Speaker 3: good as an investor. As we think, then what will

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Speaker 3: happen is markets will become more efficient. Whatever advantages AI

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Speaker 3: finds in the markets will disappear, and ultimately no one

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Speaker 3: will be able to win.

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Speaker 1: You know that ties in. I guess to the argument

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Speaker 1: you made earlier that people are better off investing in

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Speaker 1: index funds because anything that tracks a broad market will

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Speaker 1: generally outperform what individual stock pickers or people trying to

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Speaker 1: beat averages are going to be able to do over time.

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Speaker 1: Based on the performance data. We already know that's out there,

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Speaker 1: and you would say that that's going to occrue to

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Speaker 1: AI as well.

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Speaker 3: Well, Yes, one of two things is going to happen.

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Speaker 3: Either AI is as good as the human but no better,

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Speaker 3: in which case that's a fail. Or AI is a

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Speaker 3: lot better than the humans, in which case the competition

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Speaker 3: among all the AI bots is going to basically the

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Speaker 3: profits from that activity will disappear, which, by the way,

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Speaker 3: it's worth just saying we have a history here active managers'

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Speaker 3: humans have gotten better over time. If you went and

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Speaker 3: you looked at the average stock picker in the nineteen

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Speaker 3: sixties and nineteen seventies, that person was a lot less

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Speaker 3: skilled than the active managers today. And so we have

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Speaker 3: a history of humans becoming better at their craft, and

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Speaker 3: we also have a track record. And what do we

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Speaker 3: know about that track record is as the humans became

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Speaker 3: better at their craft, counterintuitively, their ability to generate excess returns,

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Speaker 3: in other words, to beat the market went down.

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Speaker 1: Because so many other people were developing the same expertise contemporaneously.

436
00:22:46,480 --> 00:22:50,680
Speaker 3: Exactly. Competition makes it harder to make money, not the reverse.

437
00:22:51,080 --> 00:22:53,480
Speaker 3: I think what that history tells you is that AI

438
00:22:53,560 --> 00:22:55,400
Speaker 3: is likely to do the same thing. If it turns

439
00:22:55,440 --> 00:22:56,840
Speaker 3: out that AI is better than the humans.

440
00:22:57,040 --> 00:22:58,640
Speaker 1: I was going to say, we could put Warren Buffett

441
00:22:58,680 --> 00:23:01,360
Speaker 1: off to the side in this equation, although even more

442
00:23:01,400 --> 00:23:03,720
Speaker 1: recently he hasn't had the same kind of fantastic returns

443
00:23:03,760 --> 00:23:04,800
Speaker 1: he had early in his career.

444
00:23:05,160 --> 00:23:07,200
Speaker 3: That's right, and that might explain part of it.

445
00:23:07,440 --> 00:23:10,320
Speaker 1: So, Aaron, you work for a large hedge fund, come

446
00:23:10,359 --> 00:23:13,800
Speaker 1: to the defense of hedges and active stock picking. Here.

447
00:23:14,280 --> 00:23:17,840
Speaker 1: If no active stock pickers can reliably beat the market,

448
00:23:18,000 --> 00:23:20,879
Speaker 1: then maybe AI can either Or am I wrong headed

449
00:23:20,920 --> 00:23:21,879
Speaker 1: in that perspective?

450
00:23:22,600 --> 00:23:25,359
Speaker 2: Yes, you and near are wrong headed. And this is

451
00:23:25,400 --> 00:23:30,040
Speaker 2: a fundamental issue. And I think the view expressed byoneer

452
00:23:30,680 --> 00:23:35,439
Speaker 2: is deeply pessimistic and ignores the connections between finance and

453
00:23:35,440 --> 00:23:38,800
Speaker 2: the real economy. Here's how I see it. The reason

454
00:23:39,040 --> 00:23:42,840
Speaker 2: the index funds are both so cheap and efficient and

455
00:23:43,000 --> 00:23:46,199
Speaker 2: produce such a great return, it's not magic. It is

456
00:23:47,160 --> 00:23:50,800
Speaker 2: ordained by God. When the world began, it's because of

457
00:23:50,960 --> 00:23:55,840
Speaker 2: work by more aggressive investors. That's individuals who are aggressive

458
00:23:56,000 --> 00:23:59,159
Speaker 2: and talented, and also hedge funds. And the way I

459
00:23:59,160 --> 00:24:02,360
Speaker 2: think about it is, these investors go out, they look

460
00:24:02,400 --> 00:24:07,640
Speaker 2: for exotic assets, liquid assets, They trade things in new ways,

461
00:24:08,240 --> 00:24:12,040
Speaker 2: and they generate alpha. They beat the market. Of course,

462
00:24:12,119 --> 00:24:14,960
Speaker 2: as they do this, you get more liquidity in those assets,

463
00:24:14,960 --> 00:24:18,119
Speaker 2: you get more familiarity and information, and so what I

464
00:24:18,200 --> 00:24:20,920
Speaker 2: call hedge fund beta comes up. These are people who

465
00:24:21,359 --> 00:24:24,359
Speaker 2: perform sort of well known hedge fund strategies like merger

466
00:24:24,480 --> 00:24:28,200
Speaker 2: arbitrage or convertible arbitrage or something like that. But they

467
00:24:28,280 --> 00:24:29,960
Speaker 2: learned how to do it, you know, from a paper

468
00:24:30,080 --> 00:24:31,840
Speaker 2: or from working at some other place, and they kind

469
00:24:31,840 --> 00:24:34,560
Speaker 2: of do it mechanically, and that's worth some fees to

470
00:24:34,640 --> 00:24:39,199
Speaker 2: investors more than index funds. But it's nothing special, and

471
00:24:39,320 --> 00:24:43,359
Speaker 2: eventually it turns into beta. It turns into what anybody

472
00:24:43,400 --> 00:24:45,919
Speaker 2: can get in an index fund, but it's a continuous process.

473
00:24:45,960 --> 00:24:47,359
Speaker 1: I told you at some point i'd stop you. I

474
00:24:47,440 --> 00:24:50,320
Speaker 1: knew you'd say beta. So let's just tell our listeners

475
00:24:50,400 --> 00:24:52,200
Speaker 1: right now what is beta and what is alpha.

476
00:24:52,840 --> 00:24:55,960
Speaker 2: Well, for the purposes of this discussion, beta is something

477
00:24:56,000 --> 00:24:59,199
Speaker 2: anybody can get cheap or free. So beta is what

478
00:24:59,240 --> 00:25:02,239
Speaker 2: you get from an index fun. Alpha is what it

479
00:25:02,280 --> 00:25:04,840
Speaker 2: takes work and money to get. So it's an additional

480
00:25:04,840 --> 00:25:07,280
Speaker 2: return you can get, but only by investing more in

481
00:25:07,359 --> 00:25:11,480
Speaker 2: systems and people, in information whatever. But the point is

482
00:25:11,840 --> 00:25:14,800
Speaker 2: this is a continuous process, and this does two things.

483
00:25:15,000 --> 00:25:19,240
Speaker 2: It makes the economy more efficient, and it gives index

484
00:25:19,320 --> 00:25:23,359
Speaker 2: funds eventually, not immediately, but eventually the index funds improve

485
00:25:23,400 --> 00:25:26,840
Speaker 2: their risk adjusted returns because they're embracing more and more

486
00:25:27,200 --> 00:25:31,000
Speaker 2: strategies that used to be alpha and now have migrated

487
00:25:31,000 --> 00:25:33,639
Speaker 2: all the way to beta. The promise of AI and

488
00:25:33,800 --> 00:25:39,040
Speaker 2: investing is in making the economy better, in directing capital

489
00:25:39,040 --> 00:25:40,520
Speaker 2: to the firms that are going to use it to

490
00:25:40,600 --> 00:25:43,640
Speaker 2: grow and succeed, and directing capital away from those people

491
00:25:43,640 --> 00:25:46,000
Speaker 2: who are going to waste it. And you know, if

492
00:25:46,040 --> 00:25:48,800
Speaker 2: it can do this, then a long term expected return

493
00:25:48,880 --> 00:25:52,000
Speaker 2: on the market above inflation could move up from you know,

494
00:25:52,040 --> 00:25:55,960
Speaker 2: the six percent it was in a twentieth century to eight, ten,

495
00:25:56,080 --> 00:25:59,560
Speaker 2: twelve percent. And what this does is it means more

496
00:25:59,600 --> 00:26:03,200
Speaker 2: and more people, ordinary people with median or below median

497
00:26:03,280 --> 00:26:08,400
Speaker 2: incomes can save money from their own work and have

498
00:26:08,440 --> 00:26:12,359
Speaker 2: financial security and retire and comfort. The higher the return

499
00:26:12,440 --> 00:26:15,879
Speaker 2: you can get from real economy, the more financially secure

500
00:26:15,880 --> 00:26:17,760
Speaker 2: people could be. So this is how we will measure

501
00:26:17,760 --> 00:26:21,160
Speaker 2: the return of AI. It may be absolutely the case

502
00:26:21,200 --> 00:26:24,520
Speaker 2: that in fifty years AI is just beating the index funds,

503
00:26:24,520 --> 00:26:27,760
Speaker 2: but only because AI made the index funds so much better.

504
00:26:28,440 --> 00:26:30,600
Speaker 1: Near you, you had a broad smile on your face

505
00:26:30,680 --> 00:26:33,240
Speaker 1: at a couple different moments here, tell me what's on

506
00:26:33,280 --> 00:26:33,680
Speaker 1: your mind.

507
00:26:34,640 --> 00:26:36,760
Speaker 3: Well, you know, I have a column for Bloomer Opinion

508
00:26:36,760 --> 00:26:38,560
Speaker 3: about A and investing, and one of the things that

509
00:26:38,600 --> 00:26:42,000
Speaker 3: I mentioned in there half jokingly is that one of

510
00:26:42,040 --> 00:26:45,720
Speaker 3: the things that indexers, people who are fans of index

511
00:26:45,800 --> 00:26:48,879
Speaker 3: funds often here from active managers, is that active managers

512
00:26:48,920 --> 00:26:52,080
Speaker 3: are very important because it is their function. It is

513
00:26:52,119 --> 00:26:55,439
Speaker 3: what they do that allows index funds to work. Along

514
00:26:55,520 --> 00:26:57,440
Speaker 3: the lines of what Aaron laid out. And while all

515
00:26:57,480 --> 00:26:59,960
Speaker 3: of that is true, what amuses me, is this idea

516
00:27:00,200 --> 00:27:03,320
Speaker 3: that AI could come in and do that function along

517
00:27:03,359 --> 00:27:05,919
Speaker 3: the lines of what Aaron is describing. And the reason

518
00:27:05,920 --> 00:27:08,720
Speaker 3: that's humorous to me is because indexers can finally stop

519
00:27:08,840 --> 00:27:11,359
Speaker 3: listening to the winding from active managers that what they

520
00:27:11,400 --> 00:27:13,600
Speaker 3: do is so important that they didn't go away, and

521
00:27:13,680 --> 00:27:15,639
Speaker 3: if they went away, that it would be difficult for

522
00:27:15,640 --> 00:27:17,919
Speaker 3: indexers to do what they do. But that's where I

523
00:27:17,960 --> 00:27:20,560
Speaker 3: am optimistic. I think that to the except that AI

524
00:27:20,800 --> 00:27:23,320
Speaker 3: can come along and do the job of active managers

525
00:27:23,359 --> 00:27:26,239
Speaker 3: and can take over from Wall Street, then perhaps that

526
00:27:26,280 --> 00:27:29,160
Speaker 3: function can be done more cheaply, perhaps markets can become

527
00:27:29,200 --> 00:27:31,920
Speaker 3: even more efficient than they are, and perhaps we can

528
00:27:31,920 --> 00:27:34,880
Speaker 3: stop having these discussions about the fact that if there

529
00:27:34,880 --> 00:27:37,960
Speaker 3: weren't any active managers, then indexers would ruin the world.

530
00:27:38,320 --> 00:27:40,639
Speaker 3: So from that perspective, I'm relatively optimistic.

531
00:27:41,359 --> 00:27:44,320
Speaker 1: Okay, on that note of optimism, let's take another break.

532
00:27:44,480 --> 00:27:46,680
Speaker 1: I want to hear from our sponsor, and we will

533
00:27:46,680 --> 00:27:52,800
Speaker 1: come right back. We're back with Aaron Brown in their

534
00:27:52,880 --> 00:27:55,919
Speaker 1: CaSR and we're talking about whether AI is going to

535
00:27:56,040 --> 00:28:00,560
Speaker 1: upend professional investing near You've gone so far as to

536
00:28:00,600 --> 00:28:05,920
Speaker 1: say that large language models like chat, GPT looking at

537
00:28:06,040 --> 00:28:10,040
Speaker 1: FED statements on inflation or looking at financial news aren't

538
00:28:10,080 --> 00:28:13,919
Speaker 1: really going to make a difference because both of those

539
00:28:14,000 --> 00:28:19,119
Speaker 1: things FED statements and financial news have very little or

540
00:28:19,160 --> 00:28:23,439
Speaker 1: perhaps no predictive value. So it doesn't matter who's analyzing

541
00:28:23,440 --> 00:28:26,680
Speaker 1: them that there's no inherent predictive value in them. Am

542
00:28:26,680 --> 00:28:29,400
Speaker 1: I interpreting your thoughts on that correctly? Yeah, that's right.

543
00:28:29,440 --> 00:28:31,879
Speaker 3: I mean, I think the point of departure question that

544
00:28:31,920 --> 00:28:34,680
Speaker 3: we should ask ourselves about anything that is being automated.

545
00:28:35,160 --> 00:28:42,000
Speaker 3: Is that process worth automating to begin with? And you have,

546
00:28:42,320 --> 00:28:46,240
Speaker 3: and you have long had humans on Wall Street and

547
00:28:46,240 --> 00:28:49,760
Speaker 3: elsewhere looking for advantages, looking for ways to outsmart the market,

548
00:28:50,240 --> 00:28:55,760
Speaker 3: reading headlines, mining headlines for information, looking at the pronouncements

549
00:28:55,800 --> 00:28:59,000
Speaker 3: of central bankers and other policy makers to see what

550
00:28:59,000 --> 00:29:03,000
Speaker 3: that would portend markets. And you know, the best evidence

551
00:29:03,000 --> 00:29:05,000
Speaker 3: that we have is that none of this is useful,

552
00:29:05,040 --> 00:29:06,680
Speaker 3: because at the end of the day, most of those

553
00:29:06,680 --> 00:29:09,560
Speaker 3: people don't do any better than the market. And so

554
00:29:09,600 --> 00:29:11,800
Speaker 3: you have to stop and ask yourself, why are we

555
00:29:11,840 --> 00:29:15,240
Speaker 3: automating something that, by all available evidence, has no use

556
00:29:16,320 --> 00:29:18,200
Speaker 3: The only answer that you can really come up with,

557
00:29:18,320 --> 00:29:22,560
Speaker 3: I think, is to say, well, there's information there humans

558
00:29:22,600 --> 00:29:25,400
Speaker 3: may just not be smart enough to glean it, whereas

559
00:29:25,440 --> 00:29:27,160
Speaker 3: AI may come along and be able to do a

560
00:29:27,160 --> 00:29:27,920
Speaker 3: better job of that.

561
00:29:28,200 --> 00:29:30,920
Speaker 1: In fact, it's quite possible that AI could be better

562
00:29:30,920 --> 00:29:34,719
Speaker 1: at pattern recognition than humans are, and all of that

563
00:29:34,800 --> 00:29:38,000
Speaker 1: documentation and data may have a predictive value in it

564
00:29:38,040 --> 00:29:40,440
Speaker 1: that we haven't discovered yet for sure.

565
00:29:40,640 --> 00:29:43,040
Speaker 3: But I guess the point is we should be skeptical

566
00:29:43,080 --> 00:29:45,960
Speaker 3: about that. We should be open minded about that, but

567
00:29:46,000 --> 00:29:48,000
Speaker 3: we should be skeptical, and we should be mindful that

568
00:29:48,120 --> 00:29:50,719
Speaker 3: ultimately what we're asking AI to do is something that

569
00:29:50,760 --> 00:29:54,160
Speaker 3: we have really very little evidence that that activity has

570
00:29:54,200 --> 00:29:55,320
Speaker 3: any value today.

571
00:29:56,040 --> 00:29:58,240
Speaker 1: Erin, I want to jump in here with a counter

572
00:29:58,360 --> 00:30:00,840
Speaker 1: argument to near that. I will ask you to voice

573
00:30:00,840 --> 00:30:02,720
Speaker 1: for me, because you're smarter than I am. But I

574
00:30:02,760 --> 00:30:05,920
Speaker 1: think of a firm like Renaissance. They've had one fund

575
00:30:05,960 --> 00:30:10,400
Speaker 1: that specializes in quantitative analysis. They've beat the market for

576
00:30:10,480 --> 00:30:14,440
Speaker 1: decades with that fund. It's a boutique fund. It is

577
00:30:14,520 --> 00:30:17,840
Speaker 1: not a large fund by many hedge fund firms, sizes

578
00:30:17,920 --> 00:30:22,040
Speaker 1: maybe ten billion dollars in assets. Why couldn't AI eventually

579
00:30:22,160 --> 00:30:25,040
Speaker 1: just be a version of that Renaissance fund on steroids?

580
00:30:26,000 --> 00:30:27,840
Speaker 2: I think not only could it it might already be.

581
00:30:27,960 --> 00:30:30,240
Speaker 2: We don't. Renaissance, of course, is one of the most

582
00:30:30,240 --> 00:30:33,440
Speaker 2: intensely secretive firms, and we don't really know exactly what

583
00:30:33,520 --> 00:30:36,920
Speaker 2: they do. But that's almost just a change of degree.

584
00:30:37,040 --> 00:30:41,440
Speaker 2: Renaissance has always done the kinds of models that are

585
00:30:41,480 --> 00:30:44,560
Speaker 2: similar to artificial intelligence, and in fact, what I would

586
00:30:44,600 --> 00:30:47,880
Speaker 2: say is that the key difference or the key you know,

587
00:30:47,920 --> 00:30:50,800
Speaker 2: the rubicon you cross, is when you let the model

588
00:30:50,880 --> 00:30:54,840
Speaker 2: start updating itself. So Renaissance, what it seems to be

589
00:30:55,240 --> 00:30:58,680
Speaker 2: is that people are using very similar kind of pattern recognition.

590
00:30:58,960 --> 00:31:01,600
Speaker 2: Many of the original algorithms they used were based on

591
00:31:01,640 --> 00:31:05,600
Speaker 2: speech recognition, which is an area of artificial intelligence, but

592
00:31:06,360 --> 00:31:09,080
Speaker 2: they did not allow the models to update themselves. They

593
00:31:09,120 --> 00:31:12,280
Speaker 2: did not use machine learning. They used human learning to

594
00:31:12,840 --> 00:31:16,680
Speaker 2: monitor these models. They may already have switched over, and

595
00:31:16,760 --> 00:31:18,760
Speaker 2: I would be surprised if they haven't at least looked

596
00:31:18,840 --> 00:31:21,880
Speaker 2: very hard at it to let the models update themselves.

597
00:31:22,200 --> 00:31:25,360
Speaker 2: But I think Renaissance moving to artificial intelligence would be

598
00:31:25,520 --> 00:31:28,000
Speaker 2: sort of a minor tweak to their operation.

599
00:31:28,920 --> 00:31:31,880
Speaker 1: I guess you've raised an interesting point in that Renaissance's

600
00:31:32,080 --> 00:31:37,080
Speaker 1: outperformance existed in a black box and their own internal

601
00:31:37,120 --> 00:31:39,800
Speaker 1: model that no one else can see, and we're lying

602
00:31:39,800 --> 00:31:42,920
Speaker 1: on their own reporting that they've outperformed. No one's thought

603
00:31:42,960 --> 00:31:45,840
Speaker 1: that they've been lying about that, including their very happy

604
00:31:45,880 --> 00:31:50,200
Speaker 1: investors for decades. But if that black box essentially comes

605
00:31:50,200 --> 00:31:53,920
Speaker 1: out into the open through AI and becomes a tool

606
00:31:54,000 --> 00:31:56,720
Speaker 1: for the masses, you no longer have to have vast

607
00:31:56,760 --> 00:32:01,160
Speaker 1: computing power, You no longer have to have spoke inputs

608
00:32:01,520 --> 00:32:07,120
Speaker 1: to have a quantitative model that produces superlative returns. Doesn't

609
00:32:07,120 --> 00:32:10,520
Speaker 1: that mean then that over time everything will revert to

610
00:32:10,560 --> 00:32:14,000
Speaker 1: the mean, and that your advantage in data processing and

611
00:32:14,080 --> 00:32:18,360
Speaker 1: data analytics gets shaved because everyone has the same tool

612
00:32:18,440 --> 00:32:18,680
Speaker 1: you do.

613
00:32:20,080 --> 00:32:23,200
Speaker 2: Well. Yes, that's true. So Renaissance may be out of

614
00:32:23,240 --> 00:32:27,800
Speaker 2: business in ten years because there's a Renaissance GPT out

615
00:32:27,840 --> 00:32:30,960
Speaker 2: there that anybody can get free on the Internet. But

616
00:32:32,160 --> 00:32:35,480
Speaker 2: if that's true, I think that will mean the economy

617
00:32:35,600 --> 00:32:37,840
Speaker 2: is growing faster than it otherwise would have. I think

618
00:32:37,880 --> 00:32:41,200
Speaker 2: that means there will be generally smarter investment decisions.

619
00:32:42,080 --> 00:32:45,040
Speaker 1: And I suppose if an important role in your worldview

620
00:32:45,040 --> 00:32:48,120
Speaker 1: of money managers is they allow people to sleep soundly

621
00:32:48,160 --> 00:32:51,320
Speaker 1: at night, because it nurses you to sleep with the

622
00:32:51,360 --> 00:32:53,720
Speaker 1: thought that your money will be all well, and good

623
00:32:54,760 --> 00:32:57,680
Speaker 1: bots probably can't do a great job of that part

624
00:32:57,720 --> 00:33:01,480
Speaker 1: of investment advice. Right maybe two hundred years from now,

625
00:33:01,520 --> 00:33:03,560
Speaker 1: some will to listen to this podcast and laugh at

626
00:33:03,640 --> 00:33:06,479
Speaker 1: us because there's a loving robot sitting next to someone's

627
00:33:06,480 --> 00:33:08,920
Speaker 1: bed patting their wallet. But at least in the near

628
00:33:09,040 --> 00:33:12,000
Speaker 1: term right now, that's really not on the horizon, the

629
00:33:12,120 --> 00:33:13,520
Speaker 1: sort of EQ side of this.

630
00:33:13,520 --> 00:33:16,920
Speaker 2: Equation, right, No, I would disagree with that. I mean,

631
00:33:17,040 --> 00:33:21,440
Speaker 2: chat GPT is very reassuring. The problem is it's not

632
00:33:21,960 --> 00:33:24,640
Speaker 2: right often enough, and so we have to solve that

633
00:33:24,760 --> 00:33:25,840
Speaker 2: problem eron.

634
00:33:25,920 --> 00:33:28,959
Speaker 1: I think chat GPT might be reassuring to you because

635
00:33:29,000 --> 00:33:31,080
Speaker 1: you're an expert and you're in the markets every day.

636
00:33:31,480 --> 00:33:33,440
Speaker 1: But I don't know that someone at home who's worried

637
00:33:33,480 --> 00:33:36,240
Speaker 1: about their mortgage or their IRA or their kids' college

638
00:33:36,280 --> 00:33:38,880
Speaker 1: savings would feel an answer coming back out of a

639
00:33:38,920 --> 00:33:41,640
Speaker 1: machine is the same as a human being saying you

640
00:33:41,720 --> 00:33:43,160
Speaker 1: might want to do this with your money, you might

641
00:33:43,160 --> 00:33:44,240
Speaker 1: want to do that with your money.

642
00:33:44,600 --> 00:33:47,520
Speaker 2: I don't know. I mean, it produces much more reassuring

643
00:33:47,640 --> 00:33:49,920
Speaker 2: answers than a human If you called up your stockbroker

644
00:33:49,960 --> 00:33:52,360
Speaker 2: and say, how come the stock you recommended last week

645
00:33:52,400 --> 00:33:55,040
Speaker 2: went down. You know, he's going to scramble around. He's

646
00:33:55,040 --> 00:33:58,000
Speaker 2: going to give you some platitudes. Chat Gep is going

647
00:33:58,080 --> 00:34:00,560
Speaker 2: to say, well, you know, there was dis announcement this day,

648
00:34:00,760 --> 00:34:02,719
Speaker 2: but I'm not really worried about it because of this

649
00:34:02,800 --> 00:34:05,320
Speaker 2: and that, And it will give you a very You

650
00:34:05,400 --> 00:34:07,920
Speaker 2: will feel that you are speaking to an expert who

651
00:34:07,920 --> 00:34:10,799
Speaker 2: really knows and is honest and never admits any kind

652
00:34:10,840 --> 00:34:14,120
Speaker 2: of doubt about things. Whether or not people are going

653
00:34:14,160 --> 00:34:15,839
Speaker 2: to trust that. I mean, granted, a lot of people

654
00:34:15,880 --> 00:34:17,360
Speaker 2: are going to say, well, that comes from a computer,

655
00:34:17,400 --> 00:34:20,040
Speaker 2: I can't trust it, just like many people would be

656
00:34:20,080 --> 00:34:22,239
Speaker 2: nervous if they knew that a computer was flying their

657
00:34:22,239 --> 00:34:25,320
Speaker 2: airplane or a computer was running their electrical grid or

658
00:34:25,400 --> 00:34:27,960
Speaker 2: things like that. But that's been true for decades, and

659
00:34:28,080 --> 00:34:31,680
Speaker 2: many essential functions that your life depends on are decisions

660
00:34:31,719 --> 00:34:32,759
Speaker 2: made by computers.

661
00:34:33,440 --> 00:34:35,640
Speaker 1: So then that aspect of this that you raised being

662
00:34:35,640 --> 00:34:37,680
Speaker 1: in the show that an important part of money management

663
00:34:38,000 --> 00:34:42,080
Speaker 1: is padding people on the hand, is actually completely dispensable.

664
00:34:42,719 --> 00:34:47,360
Speaker 2: Well except that some of those very convincing answers are true,

665
00:34:47,840 --> 00:34:52,280
Speaker 2: and until you solve that problem that it's equally convincing

666
00:34:52,280 --> 00:34:54,719
Speaker 2: when it's right and when it's wrong, people are going

667
00:34:54,760 --> 00:34:55,759
Speaker 2: to have trouble trusting it.

668
00:34:57,080 --> 00:34:59,160
Speaker 1: Neier. Would you turn your money over to a bot?

669
00:35:00,000 --> 00:35:03,839
Speaker 3: Well, I mean I would argue that I mostly do,

670
00:35:04,600 --> 00:35:07,239
Speaker 3: because you know, like I said, most index funds, I

671
00:35:07,239 --> 00:35:10,319
Speaker 3: would argue, are bots. And one of the things that

672
00:35:10,360 --> 00:35:13,040
Speaker 3: we haven't touched on yet, but it's I think worth mentioning,

673
00:35:13,760 --> 00:35:18,960
Speaker 3: is that a lot of the methods that historically humans

674
00:35:19,640 --> 00:35:23,200
Speaker 3: used to try to beat the market to generate what

675
00:35:23,400 --> 00:35:28,040
Speaker 3: Aaron called alpha, and alpha just define as returns above

676
00:35:28,080 --> 00:35:30,400
Speaker 3: the market. It's a little bit more complicated than that,

677
00:35:30,400 --> 00:35:33,400
Speaker 3: but I think it's a good, useful, simple definition. A

678
00:35:33,440 --> 00:35:36,359
Speaker 3: lot of those methods have already been automated and now

679
00:35:36,360 --> 00:35:39,360
Speaker 3: are indexes. So a lot of the ways that we

680
00:35:39,440 --> 00:35:42,279
Speaker 3: traditionally thought of as alpha are now just wrapped in

681
00:35:42,320 --> 00:35:43,839
Speaker 3: an index fund. You can buy it and a bot

682
00:35:43,840 --> 00:35:46,600
Speaker 3: will do it for you, and that's great too. And

683
00:35:46,640 --> 00:35:49,000
Speaker 3: so one of the things just thinking about this sort

684
00:35:49,000 --> 00:35:52,520
Speaker 3: of from a financial evolution perspective, what's going to happen

685
00:35:52,640 --> 00:35:54,719
Speaker 3: is AI is going to come along and is going

686
00:35:54,760 --> 00:35:58,080
Speaker 3: to say, hey, I found alpha, and that alpha will

687
00:35:58,080 --> 00:36:00,840
Speaker 3: be automated delivered on mass, and all of a sudden,

688
00:36:00,840 --> 00:36:03,880
Speaker 3: it will no longer be alpha, and you could imagine

689
00:36:03,880 --> 00:36:08,400
Speaker 3: a scenario where that just keeps going endlessly. But the

690
00:36:08,440 --> 00:36:11,480
Speaker 3: thing is, the more likely outcome is that and we're

691
00:36:11,480 --> 00:36:14,160
Speaker 3: seeing this already. When you look at traditional sources of alpha,

692
00:36:14,200 --> 00:36:16,680
Speaker 3: what you see is that the excess return that they

693
00:36:16,719 --> 00:36:20,800
Speaker 3: generated historically is higher than the alpha that they produce today.

694
00:36:21,040 --> 00:36:24,000
Speaker 3: And that's just because of adoption. You could imagine a

695
00:36:24,120 --> 00:36:28,080
Speaker 3: world where both the number of sources of alpha diminishes

696
00:36:28,239 --> 00:36:31,759
Speaker 3: and their impact also diminishes. And so you have these

697
00:36:31,840 --> 00:36:34,880
Speaker 3: bots phonetically going out there trying to find new sources,

698
00:36:34,920 --> 00:36:39,440
Speaker 3: new sources, new sources, and their efficacy diminishes over time.

699
00:36:39,600 --> 00:36:42,360
Speaker 1: Because ALPA is always getting absorbed and then replicated.

700
00:36:42,680 --> 00:36:45,040
Speaker 3: Right, and ask yourself, I mean, is there an infinite

701
00:36:45,239 --> 00:36:47,200
Speaker 3: amount of alpha in the universe? I don't know the

702
00:36:47,239 --> 00:36:50,160
Speaker 3: answer to that. My guess is probably not. But what

703
00:36:50,200 --> 00:36:52,440
Speaker 3: does that do to the pricing power of the industry?

704
00:36:52,840 --> 00:36:56,000
Speaker 3: In other words, thirty forty years ago, what was alpha?

705
00:36:56,320 --> 00:36:58,480
Speaker 3: People charged one to two percent of your money a year.

706
00:36:58,480 --> 00:37:02,680
Speaker 3: For now they're charging zero point one percent four Right, Well,

707
00:37:02,719 --> 00:37:05,279
Speaker 3: there's two reasons. One is it's become automated, but also

708
00:37:05,480 --> 00:37:07,400
Speaker 3: because it just doesn't generate as much alph as it

709
00:37:07,480 --> 00:37:10,520
Speaker 3: used to, right, And so you could imagine a world

710
00:37:10,560 --> 00:37:14,640
Speaker 3: where AI becomes ubiquitous, where AI is awesome in terms

711
00:37:14,640 --> 00:37:18,320
Speaker 3: of investing, and it just brings down the cost of everything.

712
00:37:18,719 --> 00:37:21,919
Speaker 3: So that this world that we inhabit now that Aaron

713
00:37:22,040 --> 00:37:25,160
Speaker 3: is describing, where you have hedge funds and other people

714
00:37:25,160 --> 00:37:27,920
Speaker 3: at the top of the mountain who are deemed to

715
00:37:28,000 --> 00:37:30,879
Speaker 3: be worth paying two and twenty two percent of your

716
00:37:30,880 --> 00:37:33,120
Speaker 3: money a year plus twenty percent of the profits, where

717
00:37:33,200 --> 00:37:36,600
Speaker 3: they just can't demand those kinds of fees anymore. And

718
00:37:36,800 --> 00:37:39,960
Speaker 3: that's quite an optimistic picture, indeed, from my perspective.

719
00:37:40,360 --> 00:37:42,279
Speaker 1: So infinite alpha would be a good name for a

720
00:37:42,280 --> 00:37:44,760
Speaker 1: hedge fund since you brought it up, or an AI

721
00:37:45,040 --> 00:37:45,560
Speaker 1: or an AI.

722
00:37:46,040 --> 00:37:48,480
Speaker 2: But I'd like to say we can measure the amount

723
00:37:48,520 --> 00:37:52,360
Speaker 2: of potential alpha. It's not infinite. It's roughly three times

724
00:37:52,520 --> 00:37:54,920
Speaker 2: the current value of everything in the world. And the

725
00:37:54,920 --> 00:37:57,080
Speaker 2: way I get to that figure is if we had

726
00:37:57,600 --> 00:38:01,440
Speaker 2: infinite alpha, if we had you know, perfect AI systems,

727
00:38:01,840 --> 00:38:04,640
Speaker 2: then every investment would return the risk free rate because

728
00:38:04,680 --> 00:38:07,080
Speaker 2: there would be no risk. And in that case, the

729
00:38:07,120 --> 00:38:09,439
Speaker 2: world is worth about three times what it's worth today,

730
00:38:09,440 --> 00:38:11,800
Speaker 2: at least I'm talking about the financial assets of the world,

731
00:38:12,200 --> 00:38:14,200
Speaker 2: so that makes a lot of people rich. I mean,

732
00:38:14,280 --> 00:38:16,759
Speaker 2: that would be a really really good world if we

733
00:38:16,800 --> 00:38:18,880
Speaker 2: could do it, and we've got lots and lots of

734
00:38:18,920 --> 00:38:21,799
Speaker 2: work to make that happen. And if that's the case,

735
00:38:21,800 --> 00:38:24,319
Speaker 2: and if computers are running everything and everybody is three

736
00:38:24,320 --> 00:38:26,680
Speaker 2: times as rich as they are now, well maybe that's

737
00:38:26,719 --> 00:38:29,360
Speaker 2: an okay world and we can stop worrying about investing.

738
00:38:30,120 --> 00:38:33,480
Speaker 1: Arin. We don't let anybody escape the show without telling

739
00:38:33,600 --> 00:38:37,680
Speaker 1: us what they've learned from some of the collisions we're

740
00:38:37,680 --> 00:38:42,400
Speaker 1: observing and the disruptions we've observed. What have you learned

741
00:38:42,560 --> 00:38:47,920
Speaker 1: watching the advent of chat GPT and AI's future coming

742
00:38:48,080 --> 00:38:51,120
Speaker 1: a little closer to the present as it pertains to

743
00:38:51,200 --> 00:38:51,920
Speaker 1: money management.

744
00:38:52,320 --> 00:38:55,400
Speaker 2: Well before last fall, before the chat GPT and the

745
00:38:55,440 --> 00:38:58,759
Speaker 2: reaction to it, I would have said humans are going

746
00:38:58,800 --> 00:39:02,239
Speaker 2: to be essential to the money management process for decades

747
00:39:02,640 --> 00:39:05,800
Speaker 2: at least, because they can explain what they do, because

748
00:39:05,800 --> 00:39:10,560
Speaker 2: they can have conversations with their investors. Chat GPT convinces

749
00:39:10,600 --> 00:39:14,560
Speaker 2: me that's no longer a barrier, both the quality of

750
00:39:14,640 --> 00:39:18,080
Speaker 2: the program itself and how people react to it. We

751
00:39:18,120 --> 00:39:21,720
Speaker 2: still have the problem of getting artificial intelligence and machine

752
00:39:21,800 --> 00:39:24,760
Speaker 2: learning to make good investment decisions, or better investment decisions

753
00:39:24,800 --> 00:39:27,520
Speaker 2: than humans. That has not been solved that I haven't

754
00:39:27,560 --> 00:39:30,440
Speaker 2: learned much about in the last six months, but what

755
00:39:30,520 --> 00:39:33,239
Speaker 2: I previously saw as the main barrier to adoption and

756
00:39:33,280 --> 00:39:33,919
Speaker 2: has gone away.

757
00:39:34,600 --> 00:39:35,920
Speaker 1: No, how about you, what have you learned?

758
00:39:36,320 --> 00:39:39,320
Speaker 3: I mean, I would echo largely what Aaron has said,

759
00:39:39,360 --> 00:39:43,200
Speaker 3: which is, it's shocking how human like chat GPT can be,

760
00:39:43,880 --> 00:39:48,759
Speaker 3: and it's shocking how early in this whole process we are,

761
00:39:48,800 --> 00:39:51,680
Speaker 3: and it's as good as it is, and so, you know,

762
00:39:51,920 --> 00:39:55,360
Speaker 3: having no other information, I'm inclined to extrapolate into the

763
00:39:55,400 --> 00:39:59,200
Speaker 3: future and say I don't see why it couldn't do

764
00:39:59,360 --> 00:40:02,680
Speaker 3: everything that that everyone in the money management business does,

765
00:40:02,840 --> 00:40:06,640
Speaker 3: from back office people on Wall Street to client facing advisors.

766
00:40:08,239 --> 00:40:11,799
Speaker 3: But this is my real concern about it from an

767
00:40:11,800 --> 00:40:14,319
Speaker 3: investing perspective. If I can bring it up here, which

768
00:40:14,400 --> 00:40:18,919
Speaker 3: is I think all new technology eventually, and I think

769
00:40:19,040 --> 00:40:22,000
Speaker 3: we're probably closer to that day than even I think,

770
00:40:22,920 --> 00:40:26,080
Speaker 3: takes on an air of a can't miss investing opportunity,

771
00:40:26,800 --> 00:40:29,719
Speaker 3: and I worry as I listen to these kinds of conversations,

772
00:40:29,719 --> 00:40:31,399
Speaker 3: as I read a lot of the coverage about AI

773
00:40:31,440 --> 00:40:34,760
Speaker 3: and chat, GPT, et cetera, that that hype is quickly

774
00:40:34,800 --> 00:40:37,799
Speaker 3: revving up in the AI space. What that means is

775
00:40:37,800 --> 00:40:40,480
Speaker 3: that a lot of people, and those people are already

776
00:40:40,640 --> 00:40:43,359
Speaker 3: invested in AI. The early investors, the people with their

777
00:40:43,440 --> 00:40:45,600
Speaker 3: chips already on the table, are going to make a

778
00:40:45,600 --> 00:40:47,719
Speaker 3: fortune on it. But what's going to happen is this

779
00:40:47,840 --> 00:40:51,160
Speaker 3: going to attract a lot more investment later on, and

780
00:40:51,360 --> 00:40:53,560
Speaker 3: those people, inevitably a lot of those people are going

781
00:40:53,640 --> 00:40:56,040
Speaker 3: to get in late in the game, just before sort

782
00:40:56,040 --> 00:40:59,120
Speaker 3: of all the hype pops and the prices for AI

783
00:40:59,400 --> 00:41:01,799
Speaker 3: as it's rest in financial markets come down, and people

784
00:41:01,800 --> 00:41:03,680
Speaker 3: will lose a lot of money. I mean, we've seen

785
00:41:03,719 --> 00:41:06,000
Speaker 3: this just in the last couple of decades. We've seen

786
00:41:06,000 --> 00:41:09,279
Speaker 3: this with Internet, with crypto, with almost everything. And I

787
00:41:09,400 --> 00:41:12,040
Speaker 3: worry that from that perspective, AI is going to cost

788
00:41:12,040 --> 00:41:13,319
Speaker 3: people more money that's going to make.

789
00:41:13,239 --> 00:41:17,120
Speaker 1: Them Aaron and Nere, we're out of time. Thanks for

790
00:41:17,160 --> 00:41:20,120
Speaker 1: helping us sort out a complex topic, the collision of

791
00:41:20,160 --> 00:41:21,200
Speaker 1: bots with humans.

792
00:41:21,440 --> 00:41:23,200
Speaker 2: Thank you very much, Miir Tiem.

793
00:41:23,320 --> 00:41:23,600
Speaker 1: Thank you.

794
00:41:23,800 --> 00:41:24,000
Speaker 3: Erin.

795
00:41:24,560 --> 00:41:27,239
Speaker 1: You can find Aaron brown in near Kasar's columns on

796
00:41:27,239 --> 00:41:30,000
Speaker 1: the Bloomberg Opinion website, and you can follow Near on

797
00:41:30,040 --> 00:41:33,680
Speaker 1: Twitter at near Kasar and if you want to learn

798
00:41:33,680 --> 00:41:36,640
Speaker 1: more about AI chatbots, we did another episode with fellow

799
00:41:36,640 --> 00:41:40,319
Speaker 1: columnists parme Elsen and Tyler Cowen. You can find that

800
00:41:40,360 --> 00:41:43,920
Speaker 1: in the crash Course show feed here at crash Course.

801
00:41:44,080 --> 00:41:48,759
Speaker 1: We believe that collisions can be messy, impressive, challenging, surprising,

802
00:41:49,239 --> 00:41:53,520
Speaker 1: and always instructive. In today's crash Course, I learned that AI,

803
00:41:53,960 --> 00:41:57,439
Speaker 1: while it seems to have an advantage that's unbeatable, may

804
00:41:57,920 --> 00:42:02,600
Speaker 1: just like humans, loses it over time. What did you learn?

805
00:42:03,120 --> 00:42:05,680
Speaker 1: We'd love to hear from you. You can tweet at

806
00:42:05,680 --> 00:42:09,439
Speaker 1: the Bloomberg Opinion handle at Opinion or me at Tim

807
00:42:09,480 --> 00:42:13,719
Speaker 1: O'Brien using the hashtag Bloomberg crash Course. You can also

808
00:42:13,800 --> 00:42:16,960
Speaker 1: subscribe to our show wherever you're listening right now and

809
00:42:17,080 --> 00:42:19,760
Speaker 1: leave us a review. It helps people find the show.

810
00:42:20,719 --> 00:42:24,799
Speaker 1: This episode was produced by the Indispensable Animasarakus, moses On,

811
00:42:24,920 --> 00:42:29,279
Speaker 1: Dam and Me. Our supervising producer is Magnus Hendrickson, and

812
00:42:29,320 --> 00:42:33,200
Speaker 1: we had editing help from Stage Bauman, Katie Boyce, Jeff Grocott,

813
00:42:33,560 --> 00:42:37,880
Speaker 1: Mike Nizza, and Christine Banden Bilart. Blake Maples says our

814
00:42:37,920 --> 00:42:41,319
Speaker 1: sound engineering and our original theme song was composed by

815
00:42:41,400 --> 00:42:45,400
Speaker 1: Luis Gara. I'm Tim O'Brien. We'll be back next week

816
00:42:45,680 --> 00:42:46,760
Speaker 1: with another crash course.