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At The Money: Finding Alpha via Unique ETF Strategies · Masters in Business

0:02
Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
0:30
Speaker 2: Index funds have dominated capital flows since the Great Financial Crisis.
0:37
Speaker 2: One of the rare exceptions is the pursuit of alpha
0:41
Speaker 2: via quant funds. These create very specific return characteristics that
0:47
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,
0:55
Speaker 2: we're going to discuss how to pursue alpha through exchange funds.
1:01
Speaker 2: To help us unpack all of this and what it
1:03
Speaker 2: means for your portfolio, let's bring in Wes Gray of
1:07
Speaker 2: Alpha Architect. He's a quant who also specializes in ETF constructions.
1:13
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
1:25
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
1:36
Speaker 3: Jim Simons, you know, busting out fifty percent returns with
1:40
Speaker 3: no risk. But guess what, you are never going to
1:43
Speaker 3: be offered this ever in your life period, because if
1:46
Speaker 3: I could do that, I would just manage my own
1:48
Speaker 3: money and become a billionaire. Right. The alpha for the
1:51
Speaker 3: rest of us, at least in my mind, is it's
1:54
Speaker 3: basically delivering unique, differentiate strategies after fee and after taxes
1:59
Speaker 3: that help you shape or differentiate your portfolio beyond the
2:03
Speaker 3: core of what you already have there in the form
2:05
Speaker 3: of your Vanguard Beta. Right. But let's be honest, we're
2:09
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
2:30
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.
2:43
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.
3:02
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
3:06
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
3:23
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
3:38
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
4:24
Speaker 3: you're in a transparent rapper like at ETF, everything can
4:27
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
5:00
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
5:23
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,
6:03
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
6:08
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
6:14
Speaker 3: got to have discipline, you gotta have long time horizon,
6:17
Speaker 3: you got to stick to the planet, you gotta stick
6:18
Speaker 3: to the program. You know. It's it's kind of like
6:21
Speaker 3: dieting and like being in shape, Like we all know
6:24
Speaker 3: how to get ripped eat, exercise and sleep appropriately. Don't
6:29
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
7:15
Speaker 3: someone here shop actually did it. Where what if we
7:17
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
7:31
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
7:38
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,
7:45
Speaker 3: how they work. So is what it is, and I
7:47
Speaker 3: can't explain it. But like I said, humans are going
7:49
Speaker 3: to human in the past, in the present, and in
7:53
Speaker 3: the future.
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Speaker 2: So I have a couple of technical questions to ask you,
7:58
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
8:24
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
8:30
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
8:37
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
8:51
Speaker 3: best rule is just never trust any past performance, especially hypothetical,
8:56
Speaker 3: but even live past performance. The reality is what you
8:59
Speaker 3: should understand is what is the process fundamentally, and then
9:03
Speaker 3: obviously why has this work and why will it continue
9:07
Speaker 3: to work. So, for example, if someone shows me a
9:09
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
9:15
Speaker 3: a two hundred and fifty IQ like you know the
9:17
Speaker 3: ren Tech guys, which nobody else does, I'm going to say, well,
9:21
Speaker 3: that's great, it's in the back test, and I'll grant you.
9:24
Speaker 3: Let's just assume it's true. That's pretty straightforward. Why would
9:28
Speaker 3: it exist in the future. So unless you got a
9:30
Speaker 3: great story about how terrible this is simultaneous to how
9:35
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
9:46
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
9:56
Speaker 3: to jump off a cliff, like I want to know
9:57
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
10:31
Speaker 3: because of incentives. So generally speaking, I only focus on
10:36
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
10:47
Speaker 3: warped too, like no one's buyable.
10:48
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
11:02
Speaker 3: go buy my product. So so just because of the
11:05
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
11:12
Speaker 3: like there's a there's a study on how do this
11:15
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
11:35
Speaker 3: for like other evidence from like quote unquote people who
11:38
Speaker 3: are less biased, and and you know, unfortunately that that's
11:41
Speaker 3: really boils down to academic researchers, but they have their
11:43
Speaker 3: own biases as well. But as far as I know,
11:46
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
11:51
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
12:01
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
12:15
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
12:29
Speaker 3: for people? So I was an academic, right, I'm a
12:32
Speaker 3: PhD sitting around here spending the data tapes, and I
12:35
Speaker 3: just want to figure out how to invest my own money.
12:38
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,
12:51
Speaker 3: which we'll talk about in a second, like these products
12:54
Speaker 3: are designed like that to deliver these kind of academic
12:57
Speaker 3: y factor looking things like hey, top one thousand, let's
13:01
Speaker 3: go buy the top five or ten percent on momentum
13:03
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
13:10
Speaker 3: the actual formation of how academic portfolios are actually creative.
13:15
Speaker 3: Now that's not what normal people do. I learned. What
13:19
Speaker 3: normal people do is you start with the S and
13:21
Speaker 3: P five hundred index, and then you do little tilts
13:24
Speaker 3: plus or minus, because why would you want to do
13:27
Speaker 3: those academic factor things, because you're going to get your
13:30
Speaker 3: booty fired real quick, because you're going to deviate like
13:34
Speaker 3: a madman from those underlying core benchmarks. And that's just
13:38
Speaker 3: the lot that we chose.
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Speaker 2: But that also means you have a very high active
13:44
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
13:53
Speaker 3: and unique. But we don't like to sell our products
13:57
Speaker 3: because it's really important that people buy our products to
14:01
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
14:06
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
14:13
Speaker 3: and a lot of understanding of the process and why
14:16
Speaker 3: it works.
14:16
Speaker 2: So let's talk about what's I think is your largest DTF.
14:21
Speaker 2: It's based on a box spread that option writers have
14:24
Speaker 2: been using for a long time to generate a low
14:29
Speaker 2: cost lending situation against stocks. Boxx is the alpha architect
14:35
Speaker 2: one to three month box etf that that's coming up
14:39
Speaker 2: on ten billion dollars and then a little more intermediate
14:43
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
14:54
Speaker 3: access the market price risk free rate through the box
14:57
Speaker 3: spread market, which we could have a whole other podcast
15:01
Speaker 3: on how the heck that works and what it is,
15:02
Speaker 3: but just think about like, instead of going through the
15:05
Speaker 3: treasury market, where I access what the government's going to
15:07
Speaker 3: give me effectively, I can go through the box spread
15:10
Speaker 3: market and access the implied risk free rate amongst like
15:14
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
15:22
Speaker 3: how do we deliver excess returns NETA fees and taxes
15:27
Speaker 3: and all that good stuff over the equivalent duration. So
15:30
Speaker 3: we're targeting one of three month duration. You know, obviously
15:33
Speaker 3: if you're gonna do treasury bills, you could do one
15:35
Speaker 3: to three month duration. There the key goal is how
15:38
Speaker 3: do we beat that? And we and we have done this,
15:43
Speaker 3: and the idea is like it's just that funding market
15:46
Speaker 3: has a little bit less slack and there's some other
15:48
Speaker 3: reasons why it outperforms, but we're just trying to capture
15:51
Speaker 3: that net of fees and NETA taxes in box and
15:53
Speaker 3: in box A there's also a trend component, but it's
15:56
Speaker 3: the same idea, how do we how do we access
15:58
Speaker 3: these funding markeskets and fixed income markets but deliver them
16:02
Speaker 3: in such a way the idea that we can outperform
16:05
Speaker 3: and and you know, potentially have other benefits along the way.
16:08
Speaker 2: Let's talk about two really interesting funds. I love the
16:14
Speaker 2: stock symbol Chaos c Aos the alpha architect tel risk.
16:20
Speaker 2: I'm assuming that's exactly what it sounds like. You are.
16:24
Speaker 2: You are managing the potential for there to be a
16:27
Speaker 2: market crash.
16:29
Speaker 3: Yes, so so one of the with a twist. And
16:33
Speaker 3: again there is no free lunch in options and broad
16:37
Speaker 3: market exposures, so I'm not here to say that this
16:39
Speaker 3: is a alpha generator in some sense. But what that
16:43
Speaker 3: product is doing is most tele risk funds, Like why
16:46
Speaker 3: do you buy a tailerisk fund? I want to get
16:48
Speaker 3: protected if the market blows up. Well, what's the downside
16:51
Speaker 3: of a tele risk fund? Well, we bleed out to
16:54
Speaker 3: zero over time because I'm buying puts all the time.
16:57
Speaker 3: So what Chaos represents is a trade off where we say, listen,
17:01
Speaker 3: we're going to buy the protection. So if the market
17:04
Speaker 3: bombs out, it's gonna make money. However, we're going to
17:08
Speaker 3: be selling put spreads to fund that, and we're gonna
17:11
Speaker 3: invest your collaterals as efficiently as possible. And what does
17:14
Speaker 3: that mean, Well, that means that we're not protecting you
17:17
Speaker 3: in like say the zero to twenty percent range, and
17:20
Speaker 3: like a slow bleedout, you're also going to lose money, right,
17:23
Speaker 3: So so CASS is just saying, hey, we'll deliver the
17:25
Speaker 3: deep tail risk, but we're gonna have to pay for
17:28
Speaker 3: it by eating risk in like the small draw douns.
17:32
Speaker 3: But that's what pays for our insurance. And then we're
17:34
Speaker 3: just trying to deliver all that in a tax efficient,
17:37
Speaker 3: you know, fee efficient manner, so you know people kind
17:39
Speaker 3: of have terrorist protection but without the bleed. But again,
17:43
Speaker 3: it's just reiterate, it's not a free lunch in the
17:45
Speaker 3: sense that we just you know, sell you insurance that
17:47
Speaker 3: always works and you never lose money. Just to be
17:50
Speaker 3: clear on.
17:50
Speaker 2: That, I do recall was it the first quarter of
17:54
Speaker 2: A twenty twenty during the pandemic, this exploded upwards like
17:58
Speaker 2: twenty five thirty percent? Am I remembering that?
18:01
Speaker 1: Right?
18:01
Speaker 3: Yes, it's designed where if the market blows up and
18:05
Speaker 3: the VIX explodes, this thing. I mean, I can't guarantee anything,
18:08
Speaker 3: but it's it should with very high expectations, make a
18:12
Speaker 3: lot of money if that fact pattern is true. Yeah.
18:16
Speaker 3: So so if you know Trump says something crazy, or
18:20
Speaker 3: you know North Korea nukesas tomorrow and the VIX goes
18:22
Speaker 3: to a hundred and the market's down by fifty, Chaos
18:25
Speaker 3: will probably be doing pretty good.
18:27
Speaker 2: And the last one I want to ask because I
18:29
Speaker 2: love all of these unusual box chaos sort of things
18:34
Speaker 2: that are not the typical ETF hide high inflation and deflation.
18:40
Speaker 2: I love the symbol, Hey, you need a place to
18:42
Speaker 2: hide during an inflation spike or deflation. Hide is the place?
18:47
Speaker 2: Tell us a little bit about that ETF. Yeah, same idea.
18:51
Speaker 3: We call this poor man's man's futures because it's twenty
18:54
Speaker 3: nine basis point and we're trying to deliver that kind
18:57
Speaker 3: of exposure if you're familiar with it. But basic idea
19:00
Speaker 3: is like listen for your diverse fire. You want something
19:04
Speaker 3: that could protect you if there's hyper inflation or potentially
19:07
Speaker 3: protect you if there's deflation, but we don't know what
19:10
Speaker 3: it's going to be. So all that product does is says, hey,
19:13
Speaker 3: we're going to focus on bonds, what's going to help
19:16
Speaker 3: you in deflation. We'll focus on commodities which will help
19:19
Speaker 3: you in inflation, and then we have real estate as
19:22
Speaker 3: kind of an in between her and we just trend
19:24
Speaker 3: follow those exposures. So if the bonds are doing great
19:27
Speaker 3: because we're trending towards deflation, own those. If you know,
19:30
Speaker 3: if inflations look crazy, great, we're going to own commodities
19:34
Speaker 3: to get ahead of that curve. And then if nothing's
19:37
Speaker 3: got any movement, we're just going to own cash and
19:40
Speaker 3: hide literally. So it's just you know, hyper inflation or
19:43
Speaker 3: deflation protection in one products. They don't have to think
19:46
Speaker 3: too hard.
19:47
Speaker 2: So to wrap up, for those of you who have
19:50
Speaker 2: a core index approach but want some satellite ideas to
19:55
Speaker 2: surround the passive index, consider ETFs that focus. They're on
20:00
Speaker 2: specific factor strategies or specific option strategies that could work
20:06
Speaker 2: to your advantage, both in terms of diversification and non
20:10
Speaker 2: correlation to what the core market is doing. I'm Barry Ridolts.
20:15
Speaker 2: You're listening to Bloomberg's At the Money