# At The Money: Finding Alpha via Unique ETF Strategies

An episode of [Masters in Business](https://invisiblenetwork.ai/podcast/730188152), 11 Mar 2026, 20 min.

Audio: https://podtrac.com/pts/redirect.mp3/traffic.omny.fm/d/clips/e73c998e-6e60-432f-8610-ae210140c5b1/4e4cd910-40a1-4619-a5f3-ae2b0012ffff/bd967b6d-afba-470e-a38e-b40a0182b410/audio.mp3?utm_source=Podcast&in_playlist=5873a3cb-298f-40bc-b71f-ae2b0013000d

If you want market performance (beta), you buy broad index funds. But what if you want to use a portion of your portfolio to try to beat the market (alpha)? One option is to pursue alpha via quantitative ETFs. Wes Gray is a quant and former military intelligence analyst who is CIO/CEO of Alpha Architect. The firm specializes in specific quant ETFs. Each week, “At the Money” discusses an important topic in money management. From portfolio construction to taxes and cutting down on fees, join Barry Ritholtz to learn the best ways to put your money to work. See omnystudio.com/listener for privacy information.

## Transcript

[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.
[0:52] 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,
[1:18] Speaker 2: when you talk about alpha in an ETF rapper, what
[1:21] 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?
[1:29] Speaker 3: Yes, So let me frame it because alpha is obviously
[1:32] Speaker 3: a loaded word and can mean a lot of things
[1:34] 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.
[2:12] Speaker 3: It's the alpha in unique different boutique helps you shape
[2:16] Speaker 3: your portfolio outcomes.
[2:18] Speaker 2: And just to clarify, if we are to believe Greg
[2:21] Speaker 2: Zuckerman's book on Jim Simon's it was sixty two percent
[2:26] 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
[2:35] Speaker 2: scale much beyond a few billion dollars, but still sixty
[2:38] 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
[2:46] Speaker 2: deeper into alpha.
[2:48] Speaker 3: How do you.
[2:49] Speaker 2: Think of it? Is it behavioral? Is it structural? Is
[2:51] Speaker 2: it informational? Or is it simply here's where the model
[2:56] 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
[3:04] 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
[3:08] Speaker 3: public and has some capacity, I think it really boils
[3:12] Speaker 3: down to boring things like that Vanguard can't do, for example,
[3:16] Speaker 3: like how do I differ how do I deliver something
[3:19] 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
[3:27] Speaker 3: portfolio in ways that could be favorable for you beyond
[3:30] Speaker 3: just buying SB five hundred, and usually that's going to
[3:33] 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.
[3:41] Speaker 3: It's not the it's not the two and twenty alpha.
[3:44] Speaker 3: But that's just the reality of, uh, you know, being
[3:47] Speaker 3: in a product with a lot of scale and serving
[3:49] Speaker 3: the public.
[3:50] Speaker 2: So it's funny you say that when I think of alpha,
[3:54] Speaker 2: I typically just think of factor exposure, value, momentum quality, etc.
[4:01] Speaker 2: How much of ETF based alpha poor Man's alpha is
[4:06] Speaker 2: really heavily focused on factor exposure yeah.
[4:11] Speaker 3: I would say pretty much all of it is. And
[4:14] Speaker 3: if it hasn't been a factor exposure yet, it will
[4:17] Speaker 3: be because people just need to invent the factor that
[4:20] 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
[4:30] Speaker 3: matter of did we think about that factor yet? And
[4:32] Speaker 3: so again, the alpha idea is like, we want to
[4:35] Speaker 3: deliver you these unique market factors, but we want to
[4:40] Speaker 3: make sure you capture all those efficiently low costs and
[4:42] Speaker 3: with good taxes. That's kind of the goal of ETF Alpha.
[4:46] Speaker 2: So I have an academic question for you, and you're
[4:48] Speaker 2: kind of an academic, so you're the right person to ask.
[4:51] Speaker 2: You know, you studied with gene fauma. All of these
[4:55] 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
[5:04] Speaker 2: get arbitraged away? How does it still persist if everybody
[5:10] Speaker 2: knows about it?
[5:12] Speaker 3: Yeah, so I think humans are going to human And
[5:15] Speaker 3: let's just take the most basic example, the value factor.
[5:19] 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
[5:26] Speaker 3: market and every data set you can ever find, there's
[5:29] Speaker 3: typically some sort of edge to buying cheap stuff that
[5:32] Speaker 3: everyone hates. But then there's a dirty secret for ten
[5:36] Speaker 3: twenty years stretches, it can underperform your benchmark and you'll
[5:40] Speaker 3: look like the biggest idiot on the planet. Everybody knows
[5:44] Speaker 3: it has a long game, historical edge. Everyone knows if
[5:47] Speaker 3: you buy the cheap house in the neighborhood versus the
[5:50] Speaker 3: most expensive, you're probably going to make money on average
[5:53] Speaker 3: or a long haul. But that doesn't mean everybody is
[5:56] Speaker 3: going to go all in on buying like the value factor, right,
[6:00] 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
[6:05] 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
[6:11] 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.
[6:34] Speaker 3: We all know what you're supposed to do, but it
[6:36] Speaker 3: doesn't mean everybody does it. It's the same exact problem
[6:39] Speaker 3: with investing in these quote unquote alpha factors and why
[6:42] Speaker 3: they don't get arbitraged away.
[6:44] Speaker 2: You know, it's funny. I'm gonna paraphrase my favorite white
[6:47] Speaker 2: paper of yours that you put out quite a while ago.
[6:51] Speaker 2: Even God would get fired as an active value investor
[6:55] Speaker 2: or a fund manager. How is that possible? I love,
[6:59] Speaker 2: I love how you sum up so many different parts
[7:03] Speaker 2: in the title of that. But if God's going to
[7:06] Speaker 2: get fired as a value investor, what chance do the
[7:09] Speaker 2: rest of us have?
[7:11] 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
[7:22] Speaker 3: you could underperform the benchmark for a long period even
[7:25] Speaker 3: though you're literally perfect, and you're like Biff if you
[7:29] 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
[7:35] 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
[7:41] 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.
[7:54] 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
[8:00] Speaker 2: more really interesting ETF's alpha architect manages. But before we
[8:06] Speaker 2: get to that, the perennial challenge with everybody who is
[8:12] Speaker 2: a quant and everybody who works with factor investing is
[8:16] Speaker 2: that they do these back tests and there's a tendency
[8:20] 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
[8:28] 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.
[8:34] 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
[8:42] Speaker 2: and not understand why that that model isn't really going
[8:46] Speaker 2: to work in the future.
[8:48] 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
[9:12] 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,
[9:39] Speaker 3: And so that's my benchmark is, don't believe any back tests,
[9:43] 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?
[9:49] Speaker 3: Why is this underperformed the benchmark year and year out
[9:52] 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
[10:01] Speaker 3: test might actually be legit. Then, but there's but there's
[10:04] Speaker 3: a trade off. It's not like it's an easy thing
[10:06] Speaker 3: to deal with in the future. So, you know, that's
[10:08] Speaker 3: what i'd say.
[10:09] Speaker 2: Let's talk about some other risks from back tests, draw downs, tracking, error,
[10:15] Speaker 2: trail risk, crowding. What other things do investors tend to
[10:20] Speaker 2: underestimate or quants underestimate when they're looking at a model, Just.
[10:26] 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
[10:41] Speaker 3: the best or smartest or most practical, but they have
[10:43] 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.
[10:54] Speaker 3: Yes, their currency is like ego prestige, like getting published,
[10:59] 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,
[11:10] 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
[11:18] Speaker 3: can't believe it at the outset, right, Like it's similar,
[11:22] Speaker 3: And I think in our business where if it's a
[11:24] Speaker 3: back test and unfortunately is produced by an actual firm
[11:28] Speaker 3: that sells the product, you just have to discount it
[11:31] 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.
[11:48] 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
[11:57] 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
[12:07] Speaker 2: is US based or international value strategies. These seem like
[12:11] 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
[12:19] Speaker 2: in these Yeah.
[12:21] Speaker 3: So generally speaking, what's the genesis of these products and
[12:25] 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
[12:40] Speaker 3: the thousand largest stocks, you buy the top ten percent
[12:44] Speaker 3: on book to market and this works over long haul.
[12:47] 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.
[13:06] 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.
[13:41] Speaker 2: But that also means you have a very high active
[13:44] Speaker 2: score and you're not a closet indexer.
[13:47] Speaker 3: Yes, we are not a closet indexers, and we have
[13:50] 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
[14:04] 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.
[14:10] 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.
[14:48] Speaker 2: They seem really interesting.
[14:51] 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.
[15:17] Speaker 2: Is much lower.
[15:18] 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

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