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Speaker 1: Bloomberg Audio Studios, podcasts, radio news.

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Speaker 2: Index funds have dominated capital flows since the Great Financial Crisis.

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Speaker 2: One of the rare exceptions is the pursuit of alpha

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Speaker 2: via quant funds. These create very specific return characteristics that

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Speaker 2: aim at somewhat different goals than the big broad indexes.

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Speaker 2: I'm Barry Ritholtz, and on today's edition of At the Money,

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Speaker 2: we're going to discuss how to pursue alpha through exchange funds.

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Speaker 2: To help us unpack all of this and what it

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Speaker 2: means for your portfolio, let's bring in Wes Gray of

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Speaker 2: Alpha Architect. He's a quant who also specializes in ETF constructions.

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Speaker 2: Wes also runs ETF architect. So let's start very basically. Wes,

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Speaker 2: when you talk about alpha in an ETF rapper, what

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Speaker 2: do you actually mean? And we're talking about excess returns

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Speaker 2: over cap weighted beta or is it something else?

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Speaker 3: Yes, So let me frame it because alpha is obviously

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Speaker 3: a loaded word and can mean a lot of things

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Speaker 3: to a lot of people. On one extreme, you got

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Speaker 3: Jim Simons, you know, busting out fifty percent returns with

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Speaker 3: no risk. But guess what, you are never going to

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Speaker 3: be offered this ever in your life period, because if

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Speaker 3: I could do that, I would just manage my own

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Speaker 3: money and become a billionaire. Right. The alpha for the

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Speaker 3: rest of us, at least in my mind, is it's

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Speaker 3: basically delivering unique, differentiate strategies after fee and after taxes

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Speaker 3: that help you shape or differentiate your portfolio beyond the

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Speaker 3: core of what you already have there in the form

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Speaker 3: of your Vanguard Beta. Right. But let's be honest, we're

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Speaker 3: not gonna it's It's not the alpha in the rentec sense.

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Speaker 3: It's the alpha in unique different boutique helps you shape

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Speaker 3: your portfolio outcomes.

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Speaker 2: And just to clarify, if we are to believe Greg

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Speaker 2: Zuckerman's book on Jim Simon's it was sixty two percent

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Speaker 2: a year, and they did kick out everybody except the

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Speaker 2: founding partners in the Mendallion funds there there. It didn't

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Speaker 2: scale much beyond a few billion dollars, but still sixty

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Speaker 2: two percent annually for thirty years. Nobody's gaving in second place.

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Speaker 2: It's it's amazing. So so let's let's delve a little

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Speaker 2: deeper into alpha.

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Speaker 3: How do you.

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Speaker 2: Think of it? Is it behavioral? Is it structural? Is

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Speaker 2: it informational? Or is it simply here's where the model

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Speaker 2: generates returns above with the market is doing on average.

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Speaker 3: Yeah, So if we're going to talk about kind of

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Speaker 3: alpha or the kind of stuff that we want to

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Speaker 3: focus on in the context of the ETF rapper that's

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Speaker 3: public and has some capacity, I think it really boils

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Speaker 3: down to boring things like that Vanguard can't do, for example,

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Speaker 3: like how do I differ how do I deliver something

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Speaker 3: low cost, great tax outcomes that's also very unique, trades

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Speaker 3: a lot and is going to change or shape your

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Speaker 3: portfolio in ways that could be favorable for you beyond

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Speaker 3: just buying SB five hundred, and usually that's going to

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Speaker 3: be related to diversification benefits, portfolio insurance benefits and what

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Speaker 3: have you. So you know, it's it's the poor man's alpha.

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Speaker 3: It's not the it's not the two and twenty alpha.

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Speaker 3: But that's just the reality of, uh, you know, being

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Speaker 3: in a product with a lot of scale and serving

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Speaker 3: the public.

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Speaker 2: So it's funny you say that when I think of alpha,

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Speaker 2: I typically just think of factor exposure, value, momentum quality, etc.

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Speaker 2: How much of ETF based alpha poor Man's alpha is

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Speaker 2: really heavily focused on factor exposure yeah.

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Speaker 3: I would say pretty much all of it is. And

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Speaker 3: if it hasn't been a factor exposure yet, it will

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Speaker 3: be because people just need to invent the factor that

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Speaker 3: then explains that aspect of your performance. And obviously, if

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Speaker 3: you're in a transparent rapper like at ETF, everything can

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Speaker 3: be explained with factors at some level. It's just a

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Speaker 3: matter of did we think about that factor yet? And

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Speaker 3: so again, the alpha idea is like, we want to

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Speaker 3: deliver you these unique market factors, but we want to

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Speaker 3: make sure you capture all those efficiently low costs and

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Speaker 3: with good taxes. That's kind of the goal of ETF Alpha.

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Speaker 2: So I have an academic question for you, and you're

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Speaker 2: kind of an academic, so you're the right person to ask.

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Speaker 2: You know, you studied with gene fauma. All of these

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Speaker 2: factors are public and well known, and in an e

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Speaker 2: where it's transparent and disclosed, why doesn't this alpha just

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Speaker 2: get arbitraged away? How does it still persist if everybody

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Speaker 2: knows about it?

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Speaker 3: Yeah, so I think humans are going to human And

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Speaker 3: let's just take the most basic example, the value factor.

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Speaker 3: Buy cheap stuff everybody hates like, we all know that

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Speaker 3: over one hundred years or two hundred years. In every

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Speaker 3: market and every data set you can ever find, there's

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Speaker 3: typically some sort of edge to buying cheap stuff that

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Speaker 3: everyone hates. But then there's a dirty secret for ten

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Speaker 3: twenty years stretches, it can underperform your benchmark and you'll

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Speaker 3: look like the biggest idiot on the planet. Everybody knows

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Speaker 3: it has a long game, historical edge. Everyone knows if

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Speaker 3: you buy the cheap house in the neighborhood versus the

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Speaker 3: most expensive, you're probably going to make money on average

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Speaker 3: or a long haul. But that doesn't mean everybody is

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Speaker 3: going to go all in on buying like the value factor, right,

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Speaker 3: they're gonna go buy bitcoin, they're gonna go do momentum,

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Speaker 3: they're gonna do all kinds of other things. So I

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Speaker 3: think a lot of like the quote unquote alpha, it's

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Speaker 3: like alpha in plain sight, but it's that doesn't mean

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Speaker 3: it's like easy to do, because it you know, you

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Speaker 3: got to have discipline, you gotta have long time horizon,

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Speaker 3: you got to stick to the planet, you gotta stick

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Speaker 3: to the program. You know. It's it's kind of like

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Speaker 3: dieting and like being in shape, Like we all know

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Speaker 3: how to get ripped eat, exercise and sleep appropriately. Don't

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Speaker 3: eat bonbonds, don eat McDonald's. But the alpha is there.

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Speaker 3: We all know what you're supposed to do, but it

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Speaker 3: doesn't mean everybody does it. It's the same exact problem

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Speaker 3: with investing in these quote unquote alpha factors and why

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Speaker 3: they don't get arbitraged away.

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Speaker 2: You know, it's funny. I'm gonna paraphrase my favorite white

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Speaker 2: paper of yours that you put out quite a while ago.

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Speaker 2: Even God would get fired as an active value investor

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Speaker 2: or a fund manager. How is that possible? I love,

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Speaker 2: I love how you sum up so many different parts

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Speaker 2: in the title of that. But if God's going to

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Speaker 2: get fired as a value investor, what chance do the

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Speaker 2: rest of us have?

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Speaker 3: Well, exactly, and there's been fall on research. I think

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Speaker 3: someone here shop actually did it. Where what if we

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Speaker 3: were God the tactical asset allocating manager. Same problem, like

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Speaker 3: you could underperform the benchmark for a long period even

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Speaker 3: though you're literally perfect, and you're like Biff if you

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Speaker 3: remember Back to the Future where he's got like the

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Speaker 3: little Almanac. It's just that the reality is markets are

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Speaker 3: volatile and they generally work in a way that they're

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Speaker 3: going to push you to maximal pain before the gains

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Speaker 3: are there. And that's just the nature of how markets cleared,

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Speaker 3: how they work. So is what it is, and I

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Speaker 3: can't explain it. But like I said, humans are going

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Speaker 3: to human in the past, in the present, and in

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Speaker 3: the future.

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Speaker 2: So I have a couple of technical questions to ask you,

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Speaker 2: and then I want to dive into some of the

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Speaker 2: more really interesting ETF's alpha architect manages. But before we

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Speaker 2: get to that, the perennial challenge with everybody who is

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Speaker 2: a quant and everybody who works with factor investing is

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Speaker 2: that they do these back tests and there's a tendency

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Speaker 2: to either overfit. I mean, we've never seen a back

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Speaker 2: test that we didn't love. The problem is if the

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Speaker 2: future looks exactly like the past, well then the back

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Speaker 2: test is great. But most of the time that doesn't happen.

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Speaker 2: How do you prevent that sort of overfitting? How do

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Speaker 2: you prevent oh my god, here's the perfect back test

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Speaker 2: and not understand why that that model isn't really going

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Speaker 2: to work in the future.

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Speaker 3: Yeah, So, I mean I think at the outset, the

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Speaker 3: best rule is just never trust any past performance, especially hypothetical,

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Speaker 3: but even live past performance. The reality is what you

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Speaker 3: should understand is what is the process fundamentally, and then

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Speaker 3: obviously why has this work and why will it continue

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Speaker 3: to work. So, for example, if someone shows me a

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Speaker 3: back test that says, hey, I made fifty percent returns

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Speaker 3: a year with like no risk, and you don't have

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Speaker 3: a two hundred and fifty IQ like you know the

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Speaker 3: ren Tech guys, which nobody else does, I'm going to say, well,

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Speaker 3: that's great, it's in the back test, and I'll grant you.

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Speaker 3: Let's just assume it's true. That's pretty straightforward. Why would

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Speaker 3: it exist in the future. So unless you got a

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Speaker 3: great story about how terrible this is simultaneous to how

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Speaker 3: great it is, it's just not believable or credible, right,

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Speaker 3: And so that's my benchmark is, don't believe any back tests,

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Speaker 3: especially if it shows a great thing, unless it also

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Speaker 3: shows why it's so bad. Why is there so much careers?

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Speaker 3: Why is this underperformed the benchmark year and year out

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Speaker 3: potentially for decades. To get me fired and to want

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Speaker 3: to jump off a cliff, like I want to know

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Speaker 3: that information because now I'm like thinking, no, that back

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Speaker 3: test might actually be legit. Then, but there's but there's

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Speaker 3: a trade off. It's not like it's an easy thing

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Speaker 3: to deal with in the future. So, you know, that's

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Speaker 3: what i'd say.

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Speaker 2: Let's talk about some other risks from back tests, draw downs, tracking, error,

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Speaker 2: trail risk, crowding. What other things do investors tend to

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Speaker 2: underestimate or quants underestimate when they're looking at a model, Just.

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Speaker 3: Pick them all. They underestimate everything, and the reason is

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Speaker 3: because of incentives. So generally speaking, I only focus on

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Speaker 3: academic research and peer reviewed journals. Not because academics are

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Speaker 3: the best or smartest or most practical, but they have

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Speaker 3: the least warped incentives in a sense that they're also

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Speaker 3: warped too, like no one's buyable.

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Speaker 2: Well, they want, but they want exactly fabricating alpha.

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Speaker 3: Yes, their currency is like ego prestige, like getting published,

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Speaker 3: which is it's not show you this back test to

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Speaker 3: go buy my product. So so just because of the

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Speaker 3: incentive problem tied to like back test from an asset manager,

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Speaker 3: it's you know, it's just it's it's like kind of

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Speaker 3: like there's a there's a study on how do this

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Speaker 3: drug from like sponsored by Pfizer research, Like I just

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Speaker 3: can't believe it at the outset, right, Like it's similar,

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Speaker 3: And I think in our business where if it's a

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Speaker 3: back test and unfortunately is produced by an actual firm

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Speaker 3: that sells the product, you just have to discount it

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Speaker 3: damn near ninety nine percent. And you know, go look

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Speaker 3: for like other evidence from like quote unquote people who

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Speaker 3: are less biased, and and you know, unfortunately that that's

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Speaker 3: really boils down to academic researchers, but they have their

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Speaker 3: own biases as well. But as far as I know,

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Speaker 3: that's the best you can find out there.

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Speaker 2: So let's talk about some of the funds that you

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Speaker 2: help put together and help manage. Starting with both momentum

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Speaker 2: and value q MOM and I moom a US based

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Speaker 2: or international momentum strategies, and then q VAL and eyeval

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Speaker 2: is US based or international value strategies. These seem like

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Speaker 2: such core factor models. Tell us a little bit about

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Speaker 2: these four products and who tends to be the investors

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Speaker 2: in these Yeah.

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Speaker 3: So generally speaking, what's the genesis of these products and

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Speaker 3: why are they very different but also very bad potentially

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Speaker 3: for people? So I was an academic, right, I'm a

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Speaker 3: PhD sitting around here spending the data tapes, and I

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Speaker 3: just want to figure out how to invest my own money.

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Speaker 3: And I read all these papers. They're like, great, take

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Speaker 3: the thousand largest stocks, you buy the top ten percent

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Speaker 3: on book to market and this works over long haul.

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Speaker 3: So naturally, because I'm not in the investment management industry,

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Speaker 3: which we'll talk about in a second, like these products

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Speaker 3: are designed like that to deliver these kind of academic

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Speaker 3: y factor looking things like hey, top one thousand, let's

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Speaker 3: go buy the top five or ten percent on momentum

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Speaker 3: and call it a day a month of rebounds. I'm oversimplifying.

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Speaker 3: That's idea, and I like that because it's grounded in

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Speaker 3: the actual formation of how academic portfolios are actually creative.

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Speaker 3: Now that's not what normal people do. I learned. What

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Speaker 3: normal people do is you start with the S and

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Speaker 3: P five hundred index, and then you do little tilts

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Speaker 3: plus or minus, because why would you want to do

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Speaker 3: those academic factor things, because you're going to get your

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Speaker 3: booty fired real quick, because you're going to deviate like

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Speaker 3: a madman from those underlying core benchmarks. And that's just

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Speaker 3: the lot that we chose.

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Speaker 2: But that also means you have a very high active

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Speaker 2: score and you're not a closet indexer.

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Speaker 3: Yes, we are not a closet indexers, and we have

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Speaker 3: very high active share and we're definitely doing something different

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Speaker 3: and unique. But we don't like to sell our products

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Speaker 3: because it's really important that people buy our products to

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Speaker 3: understand what they're getting into because of this whole problem

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Speaker 3: that they can outperform and we look like heroes, they

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Speaker 3: can underperform, we look like zeros and everything in between.

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Speaker 3: It really does require kind of this ten year horizon

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Speaker 3: and a lot of understanding of the process and why

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Speaker 3: it works.

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Speaker 2: So let's talk about what's I think is your largest DTF.

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Speaker 2: It's based on a box spread that option writers have

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Speaker 2: been using for a long time to generate a low

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Speaker 2: cost lending situation against stocks. Boxx is the alpha architect

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Speaker 2: one to three month box etf that that's coming up

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Speaker 2: on ten billion dollars and then a little more intermediate

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Speaker 2: duration underlying box A tell us about these two strategies.

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Speaker 2: They seem really interesting.

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Speaker 3: Yeah, So the fundamental idea here is that we can

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Speaker 3: access the market price risk free rate through the box

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Speaker 3: spread market, which we could have a whole other podcast

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Speaker 3: on how the heck that works and what it is,

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Speaker 3: but just think about like, instead of going through the

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Speaker 3: treasury market, where I access what the government's going to

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Speaker 3: give me effectively, I can go through the box spread

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Speaker 3: market and access the implied risk free rate amongst like

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Speaker 3: broker dealers, banks and traders and everyone else, which.

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Speaker 2: Is much lower.

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Speaker 3: Yes, And so what Box is trying to do is

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Speaker 3: how do we deliver excess returns NETA fees and taxes

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Speaker 3: and all that good stuff over the equivalent duration. So

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Speaker 3: we're targeting one of three month duration. You know, obviously

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Speaker 3: if you're gonna do treasury bills, you could do one

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Speaker 3: to three month duration. There the key goal is how

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Speaker 3: do we beat that? And we and we have done this,

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Speaker 3: and the idea is like it's just that funding market

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Speaker 3: has a little bit less slack and there's some other

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Speaker 3: reasons why it outperforms, but we're just trying to capture

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Speaker 3: that net of fees and NETA taxes in box and

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Speaker 3: in box A there's also a trend component, but it's

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Speaker 3: the same idea, how do we how do we access

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Speaker 3: these funding markeskets and fixed income markets but deliver them

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Speaker 3: in such a way the idea that we can outperform

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Speaker 3: and and you know, potentially have other benefits along the way.

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Speaker 2: Let's talk about two really interesting funds. I love the

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Speaker 2: stock symbol Chaos c Aos the alpha architect tel risk.

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Speaker 2: I'm assuming that's exactly what it sounds like. You are.

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Speaker 2: You are managing the potential for there to be a

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Speaker 2: market crash.

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Speaker 3: Yes, so so one of the with a twist. And

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Speaker 3: again there is no free lunch in options and broad

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Speaker 3: market exposures, so I'm not here to say that this

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Speaker 3: is a alpha generator in some sense. But what that

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Speaker 3: product is doing is most tele risk funds, Like why

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Speaker 3: do you buy a tailerisk fund? I want to get

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Speaker 3: protected if the market blows up. Well, what's the downside

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Speaker 3: of a tele risk fund? Well, we bleed out to

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Speaker 3: zero over time because I'm buying puts all the time.

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Speaker 3: So what Chaos represents is a trade off where we say, listen,

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Speaker 3: we're going to buy the protection. So if the market

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Speaker 3: bombs out, it's gonna make money. However, we're going to

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Speaker 3: be selling put spreads to fund that, and we're gonna

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Speaker 3: invest your collaterals as efficiently as possible. And what does

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Speaker 3: that mean, Well, that means that we're not protecting you

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Speaker 3: in like say the zero to twenty percent range, and

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Speaker 3: like a slow bleedout, you're also going to lose money, right,

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Speaker 3: So so CASS is just saying, hey, we'll deliver the

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Speaker 3: deep tail risk, but we're gonna have to pay for

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Speaker 3: it by eating risk in like the small draw douns.

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Speaker 3: But that's what pays for our insurance. And then we're

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Speaker 3: just trying to deliver all that in a tax efficient,

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Speaker 3: you know, fee efficient manner, so you know people kind

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Speaker 3: of have terrorist protection but without the bleed. But again,

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Speaker 3: it's just reiterate, it's not a free lunch in the

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Speaker 3: sense that we just you know, sell you insurance that

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Speaker 3: always works and you never lose money. Just to be

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Speaker 3: clear on.

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Speaker 2: That, I do recall was it the first quarter of

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Speaker 2: A twenty twenty during the pandemic, this exploded upwards like

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Speaker 2: twenty five thirty percent? Am I remembering that?

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Speaker 1: Right?

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Speaker 3: Yes, it's designed where if the market blows up and

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Speaker 3: the VIX explodes, this thing. I mean, I can't guarantee anything,

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Speaker 3: but it's it should with very high expectations, make a

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Speaker 3: lot of money if that fact pattern is true. Yeah.

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Speaker 3: So so if you know Trump says something crazy, or

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Speaker 3: you know North Korea nukesas tomorrow and the VIX goes

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Speaker 3: to a hundred and the market's down by fifty, Chaos

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Speaker 3: will probably be doing pretty good.

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Speaker 2: And the last one I want to ask because I

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Speaker 2: love all of these unusual box chaos sort of things

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Speaker 2: that are not the typical ETF hide high inflation and deflation.

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Speaker 2: I love the symbol, Hey, you need a place to

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Speaker 2: hide during an inflation spike or deflation. Hide is the place?

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Speaker 2: Tell us a little bit about that ETF. Yeah, same idea.

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Speaker 3: We call this poor man's man's futures because it's twenty

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Speaker 3: nine basis point and we're trying to deliver that kind

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Speaker 3: of exposure if you're familiar with it. But basic idea

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Speaker 3: is like listen for your diverse fire. You want something

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Speaker 3: that could protect you if there's hyper inflation or potentially

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Speaker 3: protect you if there's deflation, but we don't know what

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Speaker 3: it's going to be. So all that product does is says, hey,

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Speaker 3: we're going to focus on bonds, what's going to help

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Speaker 3: you in deflation. We'll focus on commodities which will help

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Speaker 3: you in inflation, and then we have real estate as

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Speaker 3: kind of an in between her and we just trend

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Speaker 3: follow those exposures. So if the bonds are doing great

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Speaker 3: because we're trending towards deflation, own those. If you know,

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Speaker 3: if inflations look crazy, great, we're going to own commodities

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Speaker 3: to get ahead of that curve. And then if nothing's

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Speaker 3: got any movement, we're just going to own cash and

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Speaker 3: hide literally. So it's just you know, hyper inflation or

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Speaker 3: deflation protection in one products. They don't have to think

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Speaker 3: too hard.

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Speaker 2: So to wrap up, for those of you who have

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Speaker 2: a core index approach but want some satellite ideas to

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Speaker 2: surround the passive index, consider ETFs that focus. They're on

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Speaker 2: specific factor strategies or specific option strategies that could work

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Speaker 2: to your advantage, both in terms of diversification and non

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Speaker 2: correlation to what the core market is doing. I'm Barry Ridolts.

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Speaker 2: You're listening to Bloomberg's At the Money