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Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is Masters in

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Speaker 1: Business with Barry Ritholtz on Bloomberg Radio.

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Speaker 2: On the latest Masters in Business podcast, I sit down

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Speaker 2: with Jeff Chang. He's co founder and president of vest.

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Speaker 2: They are a firm that specializes in defined outcome investing

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Speaker 2: buffered ETFs. They try and remove the uncertainty of outcomes

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Speaker 2: of your investing by using options and derivatives to come

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Speaker 2: up with very very specific products. I thought our conversation

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Speaker 2: was fascinating and I think you will also with no

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Speaker 2: further ado, my podcast with Jeff Chang. Jeff Chang, Welcome

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Speaker 2: to Bloomberg.

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Speaker 3: Great to be here and thanks for having me.

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Speaker 2: Well, thank you so much for coming. I'm kind of

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Speaker 2: always fascinated by people who have unusual or diverse backgrounds.

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Speaker 2: You in particular US Naval Academy and then an NBA

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Speaker 2: from Georgetown. Is that right? What was the original career plan?

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Speaker 3: So I grew up in Annapolis.

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Speaker 4: The original career plan was to be, you know, be

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Speaker 4: part of the Navy, and unfortunately I got medically discharged

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Speaker 4: for asthma and then then decided to pursue more of

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Speaker 4: a business path. And that's what kind of led me

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Speaker 4: to Georgetown, and then after Georgetown, I actually right after

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Speaker 4: I actually always wanted to start my own company. Right.

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Speaker 4: In fact, this is kind of a funny thing. Most

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Speaker 4: people don't know this. I've never actually said this when

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Speaker 4: I first started. I actually started a flat screen TV

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Speaker 4: company in twenty twelve, oem ing them from China. And

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Speaker 4: do you remember back in the day, like flat screen

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Speaker 4: TV's used to be like twenty five.

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Speaker 2: Oh yeah, when they first came out, they were crazy.

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Speaker 4: Yeah, So I was in DC selling those. In fact,

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Speaker 4: I remember selling TVs to Reagan National Airport. So when

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Speaker 4: you like, look at what terminal you are back in

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Speaker 4: the early two thousands, So those were Jeff Chang TVs

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Speaker 4: that were there. I think another client was six Flags.

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Speaker 4: Like when you the weak, how long the week?

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Speaker 3: Yeah, yeah, exactly exactly.

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Speaker 4: But then, you know, as TVs became further and further down,

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Speaker 4: I was like, hey, that's not.

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Speaker 3: The business I wanted to be in.

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Speaker 2: We'll commoditized. I don't want to be there.

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Speaker 4: Yeah, all commoditized. So it taught me a lot about

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Speaker 4: uh starting a business. On you know that in about

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Speaker 4: life is that I realized that I needed actual hard

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Speaker 4: skills that created a you know, value add And also

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Speaker 4: the other component was I also realized that doing my

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Speaker 4: accounting books, I didn't pay too much attention in accounting.

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Speaker 4: So I actually, uh, for six months, went and studied

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Speaker 4: for the CPA exam and took the CPA exam to

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Speaker 4: be accounting.

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Speaker 3: Which was actually a twofold kind of reason.

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Speaker 4: I think one of my mentors has told me is

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Speaker 4: that like, hey, there there is for the better word,

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Speaker 4: there's few money and few skills. Right, you don't have

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Speaker 4: that money, so make sure you build skills in which

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Speaker 4: you're not always beholden to other people. And if you

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Speaker 4: thought about it, that you know the two guaranteed things

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Speaker 4: in life is death and taxes, right, And so in

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Speaker 4: my head was I didn't want to be an undertaker,

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Speaker 4: but I could take the CPA exam and sure that

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Speaker 4: participate in taxes exactly exactly growth industry. So that was

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Speaker 4: the reason why I took the CPA exam, was that, like, hey,

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Speaker 4: I know I would never starve because you know, after

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Speaker 4: the failure of my first firm, I was like, hey, uh,

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Speaker 4: there's you always have to have at least a safety night.

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Speaker 4: And that also informed me that when I started a

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Speaker 4: new company, accounting is actually extremely important when you're starting

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Speaker 4: a firm or even a start for that matter, And

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Speaker 4: it actually came to pass that that has been a

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Speaker 4: very very important part of my career path as well.

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Speaker 2: So it's certainly a useful set of skills. But I'm

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Speaker 2: going to assume the first business didn't fail because of

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Speaker 2: bad accounting. It's just a hyper competitive market with razor

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Speaker 2: thin margins and as stuff as economies of scale came out,

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Speaker 2: that's right, the market just dies for that.

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Speaker 4: Yeah, And that really informed me is that you have

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Speaker 4: to have an edge.

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Speaker 3: I think.

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Speaker 4: Over the thirteen years of founding this company, I noticed

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Speaker 4: that there were actually key features that I noticed, even

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Speaker 4: going through y Combinator, of my classmates and people that

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Speaker 4: built very successful companies, they had very common characteristics for

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Speaker 4: their success.

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Speaker 1: Right.

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Speaker 4: In fact, I had Asian parents. They optimized for intelligence,

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Speaker 4: which was very u you know, you guess trade as

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Speaker 4: you play the violin or the piano, and you kind

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Speaker 4: of go through that.

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Speaker 2: They're optimizing for Ivy League admission is what you're.

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Speaker 4: Imploying exactly exactly, and or be a doctor for that matter.

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Speaker 2: It's so different Jewish.

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Speaker 3: Parents, Yeah, exactly so it was.

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Speaker 4: And then as kind of over the years, I realized

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Speaker 4: that the optimization like if you know, when I have kids,

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Speaker 4: because you know, I don't have kids, always none that

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Speaker 4: I know of, but if I did, I would optimize

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Speaker 4: for Actually number one is grit like that, and that

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Speaker 4: grit is the not giving up, like like you know,

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Speaker 4: your company fails, what's the next thing? Like you know,

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Speaker 4: you pick up yourself from your bootstraps and you get

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Speaker 4: up and go. It's almost like the thing is like,

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Speaker 4: as an example, my parents didn't let me play video games, right,

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Speaker 4: but I realized video games actually if you introduce grit,

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Speaker 4: like you know, if you play Call of Duty, like

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Speaker 4: I was the guy that when I play Call Duty

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Speaker 4: in my twenties, I would buy the the headphones that

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Speaker 4: would let me hear whether or not someone's behind me,

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Speaker 4: because whatever it takes to win like that type of

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Speaker 4: you ever see that kid that does not want to

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Speaker 4: lose that like fails but then gets up and figures

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Speaker 4: out a way to win.

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Speaker 3: That is grit, And I.

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Speaker 2: Think resilience is more important.

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Speaker 4: And then the second is I realized that nothing in

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Speaker 4: this world can be done alone, that success requires you

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Speaker 4: to have partnerships, friendships, and know people that can help

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Speaker 4: build great things. Great things don't come by yourself, and

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Speaker 4: that's what I think. Second is influence, your ability to

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Speaker 4: let people see your dream and believe in your dream.

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Speaker 4: Think about this, like if you're starting a company, not

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Speaker 4: just selling your product requires influence. Like convincing your first investors,

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Speaker 4: your first employees to quit their jobs they're high paying jobs,

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Speaker 4: to make almost nothing and take equity.

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Speaker 3: That's talk about like selling a dream. That's influence.

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Speaker 4: Like think about you know, some of the greatest entrepreneurs

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Speaker 4: out there. They you know, you probably heard like Steve

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Speaker 4: Jobs is a reality distortion field.

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Speaker 2: You know what that is.

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Speaker 3: That's influence, right.

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Speaker 4: That is one of the key things I think when

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Speaker 4: when you're looking at business, influence is such a key

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Speaker 4: thing of something that required to have success because, like

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Speaker 4: I said, nothing in the world is done loan. This third,

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Speaker 4: which comes back to my point, is creativity, the ability

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Speaker 4: to spot things that other people don't see, right to

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Speaker 4: basically be to see opportunity, to see things, to combine

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Speaker 4: things together and have that opportunity. And then the last

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Speaker 4: if you combine it is intelligence. If you do all

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Speaker 4: four and I can give you examples that people are

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Speaker 4: immensely successful just with grit. And by the way, it's

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Speaker 4: in that order influence, uh, grit, influence creativity and last

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Speaker 4: as intelligence.

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Speaker 2: So so I want to I want to stop you

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Speaker 2: there for sex because I want to spend time going

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Speaker 2: over y combinator. I want to talk about this, but

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Speaker 2: before we get there, I mentioned the Naval Academy of

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Speaker 2: such an unusual background, talk a little bit about what

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Speaker 2: your experiences were like at places like Freddie Mack, the

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Speaker 2: World Bank FBR, and pro shares. That's such a diverse

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Speaker 2: set of experiences. Is what did you take away from

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Speaker 2: that life experience and how did that ultimately lead you

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Speaker 2: to launching your own.

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Speaker 4: From Yeah, so I could tell you one of the

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Speaker 4: best things about what the military teaches you is not

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Speaker 4: just teamwork and looking after the people next to you

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Speaker 4: and really making a commitment. But there's also another thing

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Speaker 4: is work ethic. Like I could tell you that I'm

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Speaker 4: a morning person. I didn't grow up a morning person,

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Speaker 4: but it's like five am, I'm up. And the funny

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Speaker 4: thing is my girlfriend's a night person. She's like, how

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Speaker 4: are you like sprightly at five thirty? And I was like,

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Speaker 4: that is actually learned behavior, right, So that was like

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Speaker 4: kind of the first thing of learning grit and you know,

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Speaker 4: tackling the day early on making your bed, things those

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Speaker 4: small things in life. I think it had been really

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Speaker 4: I say important and you know, kind of keystone in

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Speaker 4: that process.

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Speaker 3: The second is actually.

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Speaker 4: When I first started my first job at the World Bank,

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Speaker 4: after trying to start my company, I had to translate

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Speaker 4: energy companies in China, and I had two problems. Number

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Speaker 4: one was I didn't my Chinese wasn't good enough, and secondly,

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Speaker 4: my accounting wasn't good enough. Hence the CPA came and

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Speaker 4: I was like, at least I got to learn one.

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Speaker 4: And then I cut over to Freddie Mac. And if

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Speaker 4: you remember during the two thousand and two two thousand

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Speaker 4: and three time frames when Freddy Mack went into restatement

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Speaker 4: so as a certified public count and I was extremely

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Speaker 4: sought after at that time. So I worked at Freddy

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Speaker 4: Mack and I realized that I really wanted to I

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Speaker 4: read Liar's Poker by Michael Lewis, and I realized that I, hey,

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Speaker 4: I really wanted to trade mortgagees.

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Speaker 2: So I started to which by the way, he said,

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Speaker 2: he is horrified because he thought this was a portionary

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Speaker 2: tale and all it did was encourage more people.

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Speaker 4: To do totally totally reading that book really made me

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Speaker 4: want to be you know what he said in the

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Speaker 4: book big swinging right like everybody. It was just such

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Speaker 4: a fun story. It almost painted Wall Street in a

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Speaker 4: specific way, but it was just the interesting part. And

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Speaker 4: by the way, it also got me into reading Foobozi

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Speaker 4: about fixed income, about the mortgage market. And then I

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Speaker 4: wanted to be a trader. So, you know, I studied

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Speaker 4: for the CFA exam, I got my CFA charter. I

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Speaker 4: didn't know that would lead me to over a decade

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Speaker 4: of teaching CFA, but that was really fun to do

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Speaker 4: that and kind of give back. But so trading mortgages

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Speaker 4: Freddy and an FBR I got to trade during two

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Speaker 4: thousand and eight. I got to have a front row

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Speaker 4: seat to seeing the you know, Bear Stearns Lehman. You know,

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Speaker 4: I remember trading Repo during the September eight It's the

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Speaker 4: month I lost all my chest hair in one month.

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Speaker 4: But it was fascinating. I mean that's what I thought

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Speaker 4: finance was like. So then you know, later on I

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Speaker 4: cut over to le bonds and options. Then the flash

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Speaker 4: crash in twenty ten, which was, by the way, I'd

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Speaker 4: never seen an entire trading desk stand up within one

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Speaker 4: minute of everybody's like, what's going on? Uh So, yeah,

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Speaker 4: I got to see a lot of Wall Street in

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Speaker 4: my twenties and thirties. It was It was definitely a

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Speaker 4: formative time of understanding, you know, kind of what what

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Speaker 4: made capital markets take and understanding and also understanding the

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Speaker 4: pitfalls the hubris of finance that you know, well.

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Speaker 2: That has to be the big takeaway from eighth nine

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Speaker 2: is that markets go up and down, and if you're leveraged, exactly,

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Speaker 2: it's a problem. And if you're highly leveraged, it's usually

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Speaker 2: pretty fatal.

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Speaker 3: Yeah exactly.

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Speaker 4: And you know, and disasters are are always clear in hindsight, right,

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Speaker 4: And you you look back and you're looking at twenty

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Speaker 4: thirty percent of fault rates, you're like, what that would

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Speaker 4: that would have been so clear in your mind when

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Speaker 4: you started to look at some of the data, And

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Speaker 4: so that was really formative. And the other component is

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Speaker 4: is kind of like what Warren Buffet says, you always

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Speaker 4: know who's not wearing pants when the water goes out. Yeah, exactly,

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Speaker 4: and so I always i'd say think about, hey, if

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Speaker 4: the tide goes out, make sure the money we manage

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Speaker 4: for our clients that were we got pants on.

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Speaker 2: Risk management turns out to be more than just a phrase.

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Speaker 2: It's really important if you're running other people.

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Speaker 4: Exactly, and it's something that you live and breathe and

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Speaker 4: what I actually, you know a lot of our investment

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Speaker 4: processes to try to get our clients to understand that,

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Speaker 4: and you utilize kind of a lot of the tools

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Speaker 4: that we build are basically pants like, you know, when

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Speaker 4: the water goes out, and make sure that you have

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Speaker 4: something there because of uncertainty.

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Speaker 2: That's to say the very least. So let's talk a

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Speaker 2: little bit about that. You come out of this experience

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Speaker 2: on a desk through the financial crisis, you launch vest

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Speaker 2: Than twenty twelve. What was the motivator? What led you

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Speaker 2: to say, Hey, I think we could do this better.

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Speaker 3: Yeah.

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Speaker 4: So I had a very short stint at pro Shares

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Speaker 4: where I met my co founder Kuran Suit he worked

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Speaker 4: on the structuring desk at Barclays, and we talked about,

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Speaker 4: you know, like hey, let's start our own firm. And

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Speaker 4: then our first idea was going to be you know,

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Speaker 4: buffers like downside protection that we saw in the structure

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Speaker 4: note market. And by the way, this actually segued into

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Speaker 4: the mortgage crisis because in two thousand and eight, the

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Speaker 4: largest issue or structure notes was Lehman Brothers. Right like,

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Speaker 4: you have a one hundred percent protected note, and then now

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Speaker 4: you're standing in bankruptcy court. So that was a big

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Speaker 4: change in the industry. I think the structure note industry

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Speaker 4: went from one hundred and twenty billion to thirty billion

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Speaker 4: in that timeframe from after the two thousand and eight crisis.

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Speaker 2: So I'll tell you a funny story. I was a

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Speaker 2: market strategist out of brokerage firm in two to three

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Speaker 2: and we got pitched a downside protected SMA and I

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Speaker 2: was just sitting in a conference room hearing this pitch.

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Speaker 2: What are the any questions? And I didn't ask the

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Speaker 2: obvious question that I thought, which was well, great, the

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Speaker 2: NASA's down eighty one percent, where were you five years ago?

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Speaker 2: Who needs this now? But the question I asked and

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Speaker 2: got called into the Corporate Council's office for was Hey,

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Speaker 2: what about counterparty risk? How do we know that you

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Speaker 2: guys are going to be there? To make the trade good. Sir,

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Speaker 2: Lehman Brothers has been here for one hundred and eighty

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Speaker 2: nine years. It'll be here long after you're gone. I'm like, okay, No,

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Speaker 2: it's an actual risk that no one was even discussing.

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Speaker 2: It was just assumed. So it turned out that you know,

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Speaker 2: counterparty risk is is a real thing.

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Speaker 3: Oh it is. It's a very real thing.

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Speaker 2: So we're going to talk little more about Vest and

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Speaker 2: buffer funds in a moment, but I just want to

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Speaker 2: get the timing right and talk a little bit about

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Speaker 2: your experiences at y Combinator. You launch Vest with your

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Speaker 2: co founder in twenty twelve, you join y Combinator in

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Speaker 2: twenty fifteen. What led you to saying, Hey, let's let's

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Speaker 2: see if we can hook up with the guys over

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Speaker 2: at y Combinator.

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Speaker 3: Yeah.

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Speaker 4: So that's the thing in finance is there's not too

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Speaker 4: much innovation, right because there's a lot of regulation and

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Speaker 4: so on and so forth. And so even at our company,

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Speaker 4: we we always even our identity today is still you know,

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Speaker 4: Silicon Valley meets Wall Street, Right. I always think that, like,

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Speaker 4: in my mind, if you know, someone in Silicon Valley

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Speaker 4: were to come into our business, they could end up

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Speaker 4: in jail, right or if Wall Street ends up in

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Speaker 4: Silicon Valley, you know, yeah you might be you know,

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Speaker 4: just end up in a dish because you know you'll

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Speaker 4: run over for sure.

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Speaker 3: Yeah, exactly.

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Speaker 4: Because at the end of the day, is you know,

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Speaker 4: we went four years with no income. Wow, right, like

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Speaker 4: lived off our Wall Street bonuses me and my co

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Speaker 4: founder Cronzu, Like we didn't get paid for you know,

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Speaker 4: four plus years.

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Speaker 3: To found this company.

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Speaker 4: Like that's how much you have to the grit and

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Speaker 4: the belief in something and that culture really really I

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Speaker 4: think comes out of kind of startup kind of the

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Speaker 4: Silicon Valley area y Combinator at the time.

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Speaker 2: Run by Paul Graham is it.

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Speaker 4: Paul Graham at that was the first year Paul Graham

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Speaker 4: U stepped down and Sam Ollman when I showed Upcha

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Speaker 4: was president of y Combinator. So twenty fifteen, twenty fifteen, yeah,

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Speaker 4: Sam was president y Combinator. For the folks out there

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Speaker 4: that don't know so why see, uh you know, similar

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Speaker 4: to like a college application. You you thought an online

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Speaker 4: college application, you actually don't need a company they help

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Speaker 4: you form the firm and uh, you know, the companies

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Speaker 4: that have come out of that program. You know, Airbnb, Reddit,

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Speaker 4: coin based store dash open Ai was funded by YC Research,

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Speaker 4: So all of that, all of those firms came out

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Speaker 4: of y C. So in fact, I think I read

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Speaker 4: a book called The launch Pad which talks about y

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Speaker 4: C the companies that they're I mean, the first class

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Speaker 4: of YC included Sam Altman, Justin Kahn who found a Twitch,

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Speaker 4: and Alexis O'Hannon who founded Reddit. And I think there

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Speaker 4: was like, correct, my maybe nine companies. I mean, that's

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Speaker 4: an all star cast if you ask me for a class.

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Speaker 4: And so it was definitely someplace that we wanted to

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Speaker 4: be around. There weren't a lot of finance firms. In fact,

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Speaker 4: this is the largest asset manager to merge out of

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Speaker 4: y C. Uh So it was definitely something to try

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Speaker 4: something different and really and get into the Silicon valley

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Speaker 4: and really pushed the innovation, uh within within finance.

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Speaker 2: I don't know if this is still the case, but

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Speaker 2: a couple of years ago the standard deal was something

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Speaker 2: like half a million dollars for seven percent of the company,

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Speaker 2: plus a three month program of building, iterating, pitching, et cetera.

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Speaker 2: Is that more or less sound right?

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Speaker 3: That's right, that's the deal today. Our deal was probably

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Speaker 3: close to one fifth of that.

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Speaker 2: Oh really yeah, well ten years ago, a lot of

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Speaker 2: each over the last second.

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Speaker 4: And they have done a great job. I think they

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Speaker 4: have maintained their I think the stat was since two

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Speaker 4: thy twelve, twenty percent of the super Unicorns were funded.

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Speaker 3: By Y Combinator.

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Speaker 2: Wow, that's me.

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Speaker 4: And then like second place is like three percent and

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Speaker 4: plus or something like that.

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Speaker 2: And this is like a full on boot camp where

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Speaker 2: it's three months and they are really taking you through

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Speaker 2: the process. Here's how you build a startup, here's how

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Speaker 2: you iterate. When you first joined Y see, did you

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Speaker 2: have any idea what the final product a vest was

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Speaker 2: going to be or did that experience clarify what you

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Speaker 2: want to do.

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Speaker 3: There were certain.

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Speaker 4: We went in with the idea of buffers and downside protection.

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Speaker 4: There were certain pivots as far as like, hey, what's

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Speaker 4: the best delivery vehicle to start with?

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Speaker 2: Meaning an ETF asposed to an.

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Speaker 4: S exactly exactly, But that was the foundational If you

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Speaker 4: even look at our application and our pitch, it was

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Speaker 4: exactly talking about the need for downside protection, the need

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Speaker 4: to you know, fix liquidity and credit risk and other

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Speaker 4: types of instruments. Those were kind of the foundational problems

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Speaker 4: because YC always says that, like, make something that people want,

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Speaker 4: and then don't just come up with the ideas. Start

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Speaker 4: with the problem solving your solving, and the problem needs

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Speaker 4: to be painful enough.

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Speaker 3: And so anybody out there that's ever thinking about starting.

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Speaker 4: A startup, always start with the problem first and make

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Speaker 4: sure the problem is painful enough for your customer that

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Speaker 4: that becomes you know, how you solve it can change

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Speaker 4: little bit, but the problem always existed, and we thought

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Speaker 4: that that was a noble problem to and.

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Speaker 3: Painful enough problem to seek.

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Speaker 2: That's a very customer focused approach to building a business.

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Speaker 2: I don't know if Wall Street necessarily thinks in those terms.

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Speaker 2: There tends to be an attitude of this is how

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Speaker 2: it's been, it's been successful. Why do you think you're

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Speaker 2: smarter than everybody else, smarter than the market. Like that's

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Speaker 2: a sort of pushback you've gotten and that you tend

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Speaker 2: to get when you roll out a different approach. How

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Speaker 2: has the experience been marrying the Wall Street ethos where

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Speaker 2: failure is abhorrent and the Silicon Valley mindset, which is

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Speaker 2: hey failure just gets you to the solution. It's just

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Speaker 2: one more step.

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Speaker 4: And that's where kind of the ethos of our Silicon

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Speaker 4: Valley meets Wall Street is that we live in both worlds.

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Speaker 4: Like our background me and Kuran's are Wall Street backgrounds.

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Speaker 4: That there is no move fast and break things mentality

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Speaker 4: on our Wall Street ethos, right, it is measure four

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Speaker 4: times cut once. This is people's livelihoods, their their wealth.

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Speaker 4: So that part we did not adopt, not like break

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Speaker 4: things type mentality that is not hard to.

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Speaker 2: Do that when you're highly regulated.

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Speaker 4: Its exactly exactly second is that we also realized you

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Speaker 4: can't do this alone. It's not like we're starting an

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Speaker 4: Airbnb where we can just kind of do x, y

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Speaker 4: and z. We needed partnerships. We needed like coming back

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Speaker 4: to the point of influence, like we needed people that

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Speaker 4: really could help us with innovation. Hence we actually only

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Speaker 4: have two investors. One is Seeble Global Markets Chicago Board

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Speaker 4: Option Exchange, the largest option exchange in the world, and

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Speaker 4: First Trust, one of the largest ETF providers here in

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Speaker 4: the United States that has been intricate in the ability

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Speaker 4: to shape and the industry.

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Speaker 3: Just like even with the exchange.

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Speaker 2: Wait let me roll you back. You said you only

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Speaker 2: had two investors. Now today, now today, all right, So

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Speaker 2: let's before we get there, let's let's talk about the

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Speaker 2: post y combin interor experience. So they give you barely

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Speaker 2: six figures for a small chunk of the company. They

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Speaker 2: they take you through a boot camp that teaches you

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Speaker 2: all these different things from focus on problem sovereign to

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Speaker 2: iteration to pitching. Investors who were the early investors invest so.

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Speaker 4: We had our lead coming out of y Comedy was

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Speaker 4: first Round Capital people an't familiar.

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Speaker 2: That's a great name if you're doing venture invests exactly.

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Speaker 4: They were one of the first investors in a small

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Speaker 4: company called.

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Speaker 2: Uber that worked out them.

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Speaker 3: Yeah, they got a lot of big wins there.

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Speaker 4: And after that, you know, we had kind of a

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Speaker 4: party round of a lot of different like Angels and

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Speaker 4: other smaller vcs. But after that, that's when Cibo came

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Speaker 4: in and wanted a bigger stake of the firm. But

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Speaker 4: the whole y C experience was very much like the

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Speaker 4: show Silicon Valley, right.

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Speaker 2: Which I which I just loved so great.

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Speaker 4: And to the point where like when we got to YC,

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Speaker 4: we rented a hacker house by the way. House that

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Speaker 4: we rented was called Hacker House and it was a

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Speaker 4: one story building with like three bedrooms, not enough bedrooms

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Speaker 4: for all of us that we're working there. I think

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Speaker 4: Karan had to sleep on the floor on a mattress

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Speaker 4: for three months. And by the way, this is coming

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Speaker 4: from being over a decade on Wall Street. Like we're

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Speaker 4: in house sleeping on the floor. Hey, there's nothing to

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Speaker 4: do but get this done exactly. And this is why

440
00:23:48,040 --> 00:23:49,960
Speaker 4: I say, like sometimes like if a former trader on

441
00:23:50,000 --> 00:23:51,679
Speaker 4: Wall Street ends up in Silka Valley, they may end

442
00:23:51,800 --> 00:23:53,439
Speaker 4: up in a dish because, like you have to go

443
00:23:53,600 --> 00:23:56,000
Speaker 4: four years no pay, sleep on the floor. It's not

444
00:23:56,119 --> 00:23:59,159
Speaker 4: fun where you're used to like wearing you know, suits

445
00:23:59,160 --> 00:24:02,520
Speaker 4: and loafers on Park Avenue. It's a big shock to

446
00:24:02,560 --> 00:24:05,720
Speaker 4: the system. But that's the thing is like, you know,

447
00:24:05,800 --> 00:24:08,120
Speaker 4: the same time, it's okay sleeping on the floor. It's

448
00:24:08,119 --> 00:24:10,760
Speaker 4: better than sleeping on the ground when you're in the military.

449
00:24:10,800 --> 00:24:14,000
Speaker 4: But that's the grit that you kind of go through.

450
00:24:14,080 --> 00:24:17,679
Speaker 2: Right coming up, we continue our conversation with Jeff Chang,

451
00:24:17,880 --> 00:24:22,560
Speaker 2: co founder and president of vest, talking about his experiences

452
00:24:22,680 --> 00:24:26,960
Speaker 2: at y Combinator. I'm Barry Ridults, you're listening to Masters

453
00:24:27,000 --> 00:24:43,200
Speaker 2: in Business on Bloomberg Radio. I'm Barry Ridults. You're listening

454
00:24:43,240 --> 00:24:47,280
Speaker 2: to Masters and Business on Bloomberg Radio. My extra special

455
00:24:47,280 --> 00:24:50,040
Speaker 2: guest this week is Jeff Chang. He is the co

456
00:24:50,160 --> 00:24:54,320
Speaker 2: founder and president of Vest. The firm manages fifty billion

457
00:24:54,440 --> 00:25:00,840
Speaker 2: dollars in ETFs that are described as outcome orient investing.

458
00:25:00,960 --> 00:25:04,280
Speaker 2: Some people call them buffer funds. So you have this

459
00:25:04,400 --> 00:25:09,840
Speaker 2: experience with y Combinator, any of that graduating class with you,

460
00:25:09,840 --> 00:25:11,480
Speaker 2: you're still in touch with who else were?

461
00:25:11,640 --> 00:25:14,880
Speaker 4: Yeah, so I'm not sure folks out there. No get

462
00:25:14,960 --> 00:25:17,640
Speaker 4: Lab sid was our group.

463
00:25:18,600 --> 00:25:20,200
Speaker 2: My no relationship to get Hub.

464
00:25:21,920 --> 00:25:24,600
Speaker 4: Yeah, but yeah, but get Lab was our I think

465
00:25:24,600 --> 00:25:28,560
Speaker 4: they iPod on the Nasdaq. I think over five billion

466
00:25:28,600 --> 00:25:31,560
Speaker 4: or something like that. They're doing really well. Uh, there's

467
00:25:31,600 --> 00:25:34,600
Speaker 4: the equipment share was also our our batch.

468
00:25:35,800 --> 00:25:36,960
Speaker 3: A lot a lot of a lot.

469
00:25:36,760 --> 00:25:40,080
Speaker 4: Of big winners in our And by the way, you've

470
00:25:40,119 --> 00:25:42,720
Speaker 4: probably been to college where you go into lecture hall,

471
00:25:42,840 --> 00:25:44,640
Speaker 4: right and you have your first day class the first

472
00:25:44,680 --> 00:25:45,159
Speaker 4: day of y C.

473
00:25:45,359 --> 00:25:46,120
Speaker 3: You know what they tell you.

474
00:25:46,520 --> 00:25:50,080
Speaker 4: They're like, you know, four percent of you guys in

475
00:25:50,160 --> 00:25:55,439
Speaker 4: this room will be billionaires, right, you know, no intimidation

476
00:25:55,520 --> 00:25:57,480
Speaker 4: factor By the way, that's the math, right, Like, on

477
00:25:57,600 --> 00:25:59,720
Speaker 4: average it's a four percent I think right now is

478
00:25:59,760 --> 00:26:02,160
Speaker 4: like I have to six percent Unicorn rate. But how

479
00:26:02,160 --> 00:26:04,480
Speaker 4: many classes can you go through that? Like you're like, hey,

480
00:26:05,040 --> 00:26:08,320
Speaker 4: h four to five percent of you guys are gonna

481
00:26:08,359 --> 00:26:11,080
Speaker 4: have extremely successful companies coming out of clays And by

482
00:26:11,080 --> 00:26:12,639
Speaker 4: the way, you look around, you're like, oh, man, is

483
00:26:12,640 --> 00:26:17,320
Speaker 4: that really possible? And then you blank. Thirteen years later

484
00:26:17,400 --> 00:26:21,480
Speaker 4: you're like, wow, it really did happen. Like there's incredibly

485
00:26:22,119 --> 00:26:25,879
Speaker 4: successful firms and incredibly successful when you look back, and

486
00:26:26,040 --> 00:26:29,200
Speaker 4: like even now I look at my group partners. I

487
00:26:29,480 --> 00:26:32,440
Speaker 4: look back, my group partners were incredible. I had Gary

488
00:26:32,520 --> 00:26:37,639
Speaker 4: Tann founded Initialized and also is now the president Coy combinator,

489
00:26:37,640 --> 00:26:41,440
Speaker 4: Alexis Ohanden founder Reddit, Justin con founded Twitch, Kat Melanek,

490
00:26:42,000 --> 00:26:45,000
Speaker 4: who is like an all star and marketing and pr

491
00:26:45,160 --> 00:26:46,960
Speaker 4: like I had an all star group.

492
00:26:47,760 --> 00:26:50,800
Speaker 2: Yeah, no, it definitely definitely sounds like it. We're talking

493
00:26:50,840 --> 00:26:55,879
Speaker 2: about winners, but Silicon Valley, where's losers like a badge

494
00:26:55,880 --> 00:26:59,879
Speaker 2: of pride? Yeah, Like it's hey, this is what's expected,

495
00:27:00,200 --> 00:27:03,240
Speaker 2: which is very different than the way the East Coast

496
00:27:03,240 --> 00:27:07,919
Speaker 2: tends to approach things. Tell us about that not being

497
00:27:08,080 --> 00:27:12,120
Speaker 2: afraid to fail, not being afraid to try things, iterate

498
00:27:12,280 --> 00:27:16,120
Speaker 2: and take this doesn't work, let's go with that. How

499
00:27:16,200 --> 00:27:19,720
Speaker 2: different is that experience on the West Coast than what

500
00:27:19,760 --> 00:27:21,600
Speaker 2: you experienced on Wall Street?

501
00:27:22,160 --> 00:27:23,200
Speaker 4: Yeah, I mean.

502
00:27:25,280 --> 00:27:29,520
Speaker 3: Definitely. In Silicon Valley failure is okay.

503
00:27:29,560 --> 00:27:32,600
Speaker 4: They have a saying if you're going to fail, fail fast, right,

504
00:27:33,960 --> 00:27:36,600
Speaker 4: whereas I feel like on Wall Street is like, you

505
00:27:36,640 --> 00:27:38,719
Speaker 4: don't want to fail fast, Like that's called a blow up.

506
00:27:39,320 --> 00:27:39,600
Speaker 3: Right.

507
00:27:40,880 --> 00:27:43,800
Speaker 4: So there are some parts, given the industry that we're in,

508
00:27:43,840 --> 00:27:47,320
Speaker 4: we have to ignore some of the aspects of it.

509
00:27:48,240 --> 00:27:50,479
Speaker 4: I think everything that we did, I wouldn't say was

510
00:27:50,880 --> 00:27:54,000
Speaker 4: ultimate failure, maybe not the success that we wanted, because

511
00:27:54,119 --> 00:27:57,040
Speaker 4: we wanted to make sure everything built were strong in foundation.

512
00:27:57,680 --> 00:27:57,840
Speaker 2: Right.

513
00:27:57,920 --> 00:28:00,920
Speaker 4: It would like last stand test the time, no matter

514
00:28:00,960 --> 00:28:05,200
Speaker 4: what happened. Maybe not wildly successful, but then that that's

515
00:28:05,200 --> 00:28:07,800
Speaker 4: how you pivot. So it's not necessarily failure per se,

516
00:28:07,880 --> 00:28:10,600
Speaker 4: but not the success you're looking for them pivot and

517
00:28:10,640 --> 00:28:12,520
Speaker 4: try to find other ways to deliver and how to

518
00:28:12,560 --> 00:28:13,600
Speaker 4: solve the problem better.

519
00:28:14,520 --> 00:28:15,840
Speaker 3: But I still think that.

520
00:28:15,840 --> 00:28:20,840
Speaker 4: The idea of not being afraid of failure and that

521
00:28:20,960 --> 00:28:24,439
Speaker 4: grit and the ability to you know, pick yourself up.

522
00:28:24,480 --> 00:28:27,480
Speaker 4: It's that attitude that, like, you know, this is not

523
00:28:27,600 --> 00:28:31,280
Speaker 4: the end. Failure is just the the mother of success,

524
00:28:31,320 --> 00:28:35,119
Speaker 4: and you just have to keep learning from those mistakes

525
00:28:35,119 --> 00:28:37,119
Speaker 4: because everything is a learning process. I can't tell you

526
00:28:37,160 --> 00:28:39,760
Speaker 4: one person that I know that's successful that has not failed.

527
00:28:40,320 --> 00:28:42,640
Speaker 2: No, that makes perfect sense. You know, you you don't

528
00:28:42,680 --> 00:28:45,240
Speaker 2: know what's going to work, and you don't know what's

529
00:28:45,280 --> 00:28:48,840
Speaker 2: not gonna work until you try. And if you know

530
00:28:48,920 --> 00:28:53,920
Speaker 2: the there's a story about Hey, if you're not failing occasionally,

531
00:28:53,960 --> 00:28:57,280
Speaker 2: then you're just not taking enough risk to say the

532
00:28:57,360 --> 00:28:59,880
Speaker 2: very least. All right, So so let's talk a little

533
00:28:59,920 --> 00:29:04,160
Speaker 2: bit about how this developed. You come out of Y

534
00:29:04,280 --> 00:29:09,480
Speaker 2: Combinator sometime in twenty fifteen. When did you first start

535
00:29:09,520 --> 00:29:11,640
Speaker 2: taking client assets client money?

536
00:29:12,600 --> 00:29:14,800
Speaker 3: Well, NYC, we were taking client assets.

537
00:29:14,840 --> 00:29:18,800
Speaker 4: I think we launched our first mutual fund in twenty sixteen.

538
00:29:18,840 --> 00:29:21,840
Speaker 4: It was the first buffer fund of its kind.

539
00:29:22,920 --> 00:29:24,400
Speaker 3: And then so.

540
00:29:24,480 --> 00:29:27,800
Speaker 2: Wait, let's stay with mutual funds, which have their own

541
00:29:28,480 --> 00:29:33,920
Speaker 2: complications with capital gains tax. Given what you do primarily

542
00:29:33,960 --> 00:29:37,880
Speaker 2: with derivatives and options in order to create that buffer,

543
00:29:38,320 --> 00:29:40,640
Speaker 2: how does that play out in a mutual fund wrapper?

544
00:29:41,240 --> 00:29:46,240
Speaker 4: Yeah, there are obviously challenges that may not be as

545
00:29:47,160 --> 00:29:50,560
Speaker 4: let's say, the same as like an ETF that you know.

546
00:29:50,600 --> 00:29:52,960
Speaker 4: In twenty nineteen they introduced the in kind This is

547
00:29:52,960 --> 00:29:56,560
Speaker 4: also another example of the partnership with Cibo.

548
00:29:57,000 --> 00:29:59,920
Speaker 2: It's been around for real estate for forever. It seems

549
00:30:00,080 --> 00:30:02,360
Speaker 2: that's right, and it just took Wall Street a while

550
00:30:02,400 --> 00:30:06,280
Speaker 2: to catch up to that explain what in clount incline

551
00:30:06,360 --> 00:30:09,160
Speaker 2: creation and redemption looks like, what it means to you.

552
00:30:09,560 --> 00:30:13,000
Speaker 4: So in mutual funds there's a challenge in some cases

553
00:30:14,080 --> 00:30:18,960
Speaker 4: that if there's a redemption, you would sell your securities,

554
00:30:18,960 --> 00:30:23,960
Speaker 4: which could have the potential to realize gains. In ETFs

555
00:30:24,400 --> 00:30:28,360
Speaker 4: not just unique to these ETFs or all ETFs, they

556
00:30:28,840 --> 00:30:30,560
Speaker 4: have the ability to let's say.

557
00:30:30,360 --> 00:30:31,160
Speaker 3: In kind security.

558
00:30:31,200 --> 00:30:33,200
Speaker 4: So when someone wants their money back, instead of giving

559
00:30:33,240 --> 00:30:37,040
Speaker 4: the market maker selling securities and giving them cash in

560
00:30:37,080 --> 00:30:41,080
Speaker 4: some cases, you can give them securities, thereby not potentially

561
00:30:41,120 --> 00:30:42,200
Speaker 4: realizing the gain.

562
00:30:42,040 --> 00:30:43,959
Speaker 3: For the shareholders.

563
00:30:44,000 --> 00:30:48,360
Speaker 4: So it has the potential for tax efficiency by having

564
00:30:48,440 --> 00:30:52,840
Speaker 4: inkin now. Prior to twenty nineteen. October twenty nineteen, that

565
00:30:53,000 --> 00:30:56,720
Speaker 4: was not we weren't able to do that with options

566
00:30:57,240 --> 00:31:00,680
Speaker 4: that was introduced in October twenty nineteen, we launched our

567
00:31:00,720 --> 00:31:05,040
Speaker 4: first buffer ETFs in November of twenty nineteen in partnership

568
00:31:05,360 --> 00:31:09,080
Speaker 4: with our partners at First Trust, and so that has

569
00:31:09,160 --> 00:31:12,320
Speaker 4: been one of the fastest growing areas, not just for

570
00:31:12,360 --> 00:31:15,360
Speaker 4: our firm, but as the ETF industry as a whole.

571
00:31:15,760 --> 00:31:18,880
Speaker 2: So let's talk a little bit about what a buffer

572
00:31:19,240 --> 00:31:22,600
Speaker 2: fund does, what are the advantages, what are you giving

573
00:31:22,680 --> 00:31:26,640
Speaker 2: up in order to obtain those advantages. What's the largest funds?

574
00:31:26,760 --> 00:31:29,920
Speaker 2: What's the largest ETF now at VEST.

575
00:31:30,320 --> 00:31:33,080
Speaker 4: So the largest buffer fund and the one at VES

576
00:31:33,280 --> 00:31:38,160
Speaker 4: is BUFR. And it's built Yeah, it's built on the

577
00:31:38,200 --> 00:31:44,000
Speaker 4: foundation that you know, the kind of fundamentals of the

578
00:31:44,040 --> 00:31:47,520
Speaker 4: strategy is the buffer strategy, which is, you know, let's

579
00:31:47,560 --> 00:31:50,880
Speaker 4: say you get SMP exposure for one year, the first

580
00:31:50,920 --> 00:31:54,080
Speaker 4: ten percent is protected. So as an example of strategy,

581
00:31:54,080 --> 00:31:56,200
Speaker 4: if SMP is down ten your flat for the year,

582
00:31:56,840 --> 00:31:58,520
Speaker 4: and then you get upside up to let's say a

583
00:31:58,560 --> 00:32:01,680
Speaker 4: predetermined cap. So let's say SMP is up fifteen, you're

584
00:32:01,720 --> 00:32:04,320
Speaker 4: up fifteen, but the most you can make is fifteen.

585
00:32:04,360 --> 00:32:08,280
Speaker 4: So if smps up sixteen, you're up fifteen, right, so

586
00:32:08,320 --> 00:32:09,640
Speaker 4: you're capped out at that face.

587
00:32:09,800 --> 00:32:13,440
Speaker 2: So years like twenty three and twenty four kind of unusual.

588
00:32:13,880 --> 00:32:17,000
Speaker 2: You don't usually see twenty five percent two years in

589
00:32:17,040 --> 00:32:20,440
Speaker 2: a row. But if you were in the fund in

590
00:32:20,480 --> 00:32:25,080
Speaker 2: twenty two, down twenty two percent means you're only down

591
00:32:25,080 --> 00:32:26,680
Speaker 2: twelve percent, that's right.

592
00:32:26,400 --> 00:32:26,800
Speaker 3: That's right.

593
00:32:26,920 --> 00:32:27,880
Speaker 2: So that's the trade off.

594
00:32:28,040 --> 00:32:30,680
Speaker 4: Yeah, And here's the thing is that most people don't

595
00:32:30,720 --> 00:32:33,600
Speaker 4: realize these strategies have the potential to outperform the market,

596
00:32:33,680 --> 00:32:36,760
Speaker 4: even if you're talking about you know, high double digit

597
00:32:37,080 --> 00:32:39,800
Speaker 4: equity returns. Because think about this, in twenty twenty two,

598
00:32:39,880 --> 00:32:42,520
Speaker 4: because of inflation, when interest rates went up, stocks and

599
00:32:42,560 --> 00:32:44,800
Speaker 4: bonds both went down at the same time. Right, you

600
00:32:44,880 --> 00:32:47,640
Speaker 4: could have mixed your stocks and bonds any way you wanted.

601
00:32:47,680 --> 00:32:51,200
Speaker 2: In twenty twenty two, sixty was negative exactly twenty.

602
00:32:51,040 --> 00:32:53,520
Speaker 4: And unless you were managing money forty years ago, you

603
00:32:53,600 --> 00:32:58,040
Speaker 4: had not experienced inflation, right, And you couldn't hide anywhere.

604
00:32:58,080 --> 00:33:01,040
Speaker 3: I mean, you were like Tom Brady.

605
00:33:00,800 --> 00:33:03,560
Speaker 4: Choosing between alimony and child support while taking your kids

606
00:33:03,680 --> 00:33:06,680
Speaker 4: jiu jitsu practice. Like the thing is, there was nowhere

607
00:33:06,720 --> 00:33:11,080
Speaker 4: to hide, right Whereas if you were hedging. And the

608
00:33:11,080 --> 00:33:13,400
Speaker 4: great thing about hedging is if you buy SMP and

609
00:33:13,400 --> 00:33:17,560
Speaker 4: you buy an SMP put, that put is perfectly negatively correlated.

610
00:33:18,880 --> 00:33:18,920
Speaker 2: It.

611
00:33:20,480 --> 00:33:24,520
Speaker 4: And so imagine if you had a strategy that did

612
00:33:24,560 --> 00:33:27,080
Speaker 4: not participate in the majority of the drawdowns in twenty

613
00:33:27,120 --> 00:33:30,240
Speaker 4: twenty two, that means you had more to invest to

614
00:33:30,280 --> 00:33:32,240
Speaker 4: take advantage of the games in twenty twenty three, twenty

615
00:33:32,280 --> 00:33:34,880
Speaker 4: twenty four, and twenty twenty five. This is the compounding

616
00:33:34,880 --> 00:33:38,520
Speaker 4: effect of winning without losing, right, It's the compounding effect

617
00:33:38,960 --> 00:33:41,960
Speaker 4: of playing offense and defense at the same time, because

618
00:33:42,000 --> 00:33:44,240
Speaker 4: the end of the day is a lot of times,

619
00:33:44,920 --> 00:33:47,320
Speaker 4: you know, these types of strategies are not the get

620
00:33:47,400 --> 00:33:50,200
Speaker 4: rich game. If you're twenty years old, probably not the

621
00:33:50,240 --> 00:33:54,040
Speaker 4: strategy for you. But you know, in our industry, a

622
00:33:54,080 --> 00:33:55,959
Speaker 4: lot of the people that have wealth, they're in the

623
00:33:56,000 --> 00:33:56,840
Speaker 4: stay rich game.

624
00:33:57,040 --> 00:33:57,280
Speaker 2: Right.

625
00:33:57,320 --> 00:33:59,640
Speaker 4: These types of strategies are in the stay riche game

626
00:33:59,640 --> 00:34:02,360
Speaker 4: because if if you have wealth, you just don't want

627
00:34:02,400 --> 00:34:05,640
Speaker 4: to be poor, right, So that's why that's the kind

628
00:34:05,680 --> 00:34:10,560
Speaker 4: of crux of protecting your equity exposure. And the idea

629
00:34:10,760 --> 00:34:14,759
Speaker 4: is the issue with hedging has always been that to

630
00:34:14,880 --> 00:34:17,040
Speaker 4: hedge with options and so on and so forth one

631
00:34:17,040 --> 00:34:20,120
Speaker 4: of the biggest and they had surveys on why you know,

632
00:34:20,880 --> 00:34:23,640
Speaker 4: investors and financial advisors don't hedge with options, and they

633
00:34:23,960 --> 00:34:29,279
Speaker 4: everybody said the same two things, compliance and scalability. You know,

634
00:34:29,320 --> 00:34:32,000
Speaker 4: the compliance burden associated with trading options and the scalability

635
00:34:32,000 --> 00:34:34,320
Speaker 4: because when you buy a fund, you buy a stock

636
00:34:34,520 --> 00:34:36,680
Speaker 4: you can put in your portfolio fallsey for thirty years.

637
00:34:36,719 --> 00:34:39,480
Speaker 4: Maybe you rebalance once a quarter. You buy an option

638
00:34:39,560 --> 00:34:41,440
Speaker 4: every thirty days sixty days from now you have to

639
00:34:41,440 --> 00:34:44,239
Speaker 4: trade it. By having it inside a fund, we can

640
00:34:44,280 --> 00:34:46,520
Speaker 4: trade that for you and so now you can ask

641
00:34:46,560 --> 00:34:49,120
Speaker 4: it out, Okay, rebalance once a quarter. It solves a

642
00:34:49,160 --> 00:34:52,239
Speaker 4: lot of those issues. And this is the thing that

643
00:34:52,320 --> 00:34:56,319
Speaker 4: I find very interesting is two things. Number one is

644
00:34:56,360 --> 00:34:58,480
Speaker 4: these strategies have been around for over thirty years. The

645
00:34:58,520 --> 00:35:01,520
Speaker 4: buffer structure note has been around for years. Buffer annuities,

646
00:35:01,520 --> 00:35:04,239
Speaker 4: I think were introduced in twenty ten. All we did

647
00:35:04,360 --> 00:35:07,360
Speaker 4: was cut the bank and insurance company out. Instead of

648
00:35:07,400 --> 00:35:10,520
Speaker 4: having the banker insurance company hedge themselves with options and

649
00:35:10,560 --> 00:35:12,920
Speaker 4: then issue you a policy or issue you a no,

650
00:35:13,360 --> 00:35:15,080
Speaker 4: we just said, why not just put the hedge in

651
00:35:15,120 --> 00:35:17,640
Speaker 4: a fund and now you own it. We cut the

652
00:35:17,680 --> 00:35:21,000
Speaker 4: middleman out of the middle. The other component is to

653
00:35:21,000 --> 00:35:25,000
Speaker 4: think about in business that I always look back. So

654
00:35:25,680 --> 00:35:28,360
Speaker 4: Richard Thayer, the professor at Universe Chicago won the Nobel

655
00:35:28,400 --> 00:35:29,960
Speaker 4: Prize for Behavioral finance.

656
00:35:30,040 --> 00:35:32,440
Speaker 2: Right essentially created the field.

657
00:35:32,560 --> 00:35:35,680
Speaker 4: Yeah, the nudge, And I believe one of the studies

658
00:35:36,080 --> 00:35:40,640
Speaker 4: by Cornell University had this study of I think they

659
00:35:40,680 --> 00:35:43,759
Speaker 4: had kids in the lunchline. They gave them free apples,

660
00:35:43,840 --> 00:35:45,319
Speaker 4: Like you get the end of that, you get a

661
00:35:45,320 --> 00:35:47,640
Speaker 4: free apple right by the way, the consumption was like

662
00:35:47,719 --> 00:35:49,719
Speaker 4: less than like, I don't know, twenty percent, Like it

663
00:35:49,760 --> 00:35:51,080
Speaker 4: was a very low consumption rate.

664
00:35:51,160 --> 00:35:52,000
Speaker 3: No one took the apple.

665
00:35:52,600 --> 00:35:55,319
Speaker 4: Then they cut the apples up and they put them

666
00:35:55,320 --> 00:35:58,240
Speaker 4: in little bags. By the way, the consumption went through

667
00:35:58,280 --> 00:36:01,120
Speaker 4: the roof. Why this was the nudge. This was the

668
00:36:01,160 --> 00:36:04,040
Speaker 4: idea that you make it simple, people will use it.

669
00:36:04,480 --> 00:36:08,400
Speaker 4: Think about options as apples, and then that we had

670
00:36:08,520 --> 00:36:11,600
Speaker 4: bag those apples to make it easier for the user

671
00:36:11,719 --> 00:36:15,400
Speaker 4: to consume them without the compliance and scalability burden to them.

672
00:36:15,440 --> 00:36:19,359
Speaker 4: Because theoretically any broker or any financial advisor out there

673
00:36:19,400 --> 00:36:22,919
Speaker 4: can actually trade those themselves. But that's like the same thing,

674
00:36:23,000 --> 00:36:24,920
Speaker 4: like every child could sit there and cut their own

675
00:36:25,000 --> 00:36:27,400
Speaker 4: slice their own apples, but they don't want to do that.

676
00:36:27,680 --> 00:36:30,080
Speaker 2: So let me ask you, because you've brought this up

677
00:36:30,120 --> 00:36:31,759
Speaker 2: a few times, and I want to hone in on

678
00:36:31,800 --> 00:36:38,440
Speaker 2: this is your target consumer, mom and pop mainStreet investors,

679
00:36:38,680 --> 00:36:43,960
Speaker 2: or you focused more on the advisor channel or brokerage

680
00:36:44,000 --> 00:36:46,240
Speaker 2: channel or all three some combination.

681
00:36:46,560 --> 00:36:50,600
Speaker 4: We are not that focused in the retail space mostly

682
00:36:51,719 --> 00:36:54,160
Speaker 4: and by the way, I would say one hundred percent

683
00:36:54,200 --> 00:36:59,600
Speaker 4: of our focus is in financial professionals really because those

684
00:36:59,640 --> 00:37:03,720
Speaker 4: are our partners. Those are the people that we stand

685
00:37:03,800 --> 00:37:06,200
Speaker 4: side by side with, we build products that those are

686
00:37:06,200 --> 00:37:10,480
Speaker 4: the people we're solving problems for them, which they're solving

687
00:37:10,520 --> 00:37:13,560
Speaker 4: problems for their clients. We stand side by side with

688
00:37:13,840 --> 00:37:18,120
Speaker 4: the financial professionals and manage, you know.

689
00:37:19,480 --> 00:37:22,080
Speaker 2: And once you bring them up to speed, it's it's

690
00:37:22,120 --> 00:37:25,879
Speaker 2: incumbent on them to find the clients that think are

691
00:37:25,880 --> 00:37:27,920
Speaker 2: the right fit for this, and they get to explain

692
00:37:28,000 --> 00:37:29,120
Speaker 2: that exactly.

693
00:37:29,120 --> 00:37:32,520
Speaker 4: Because every single client is different and unique. We make

694
00:37:33,040 --> 00:37:35,880
Speaker 4: products across and every client is different and how that

695
00:37:36,200 --> 00:37:36,880
Speaker 4: gets utilized.

696
00:37:36,880 --> 00:37:39,360
Speaker 3: We help the financial.

697
00:37:38,960 --> 00:37:43,280
Speaker 4: Advisor even you know, how to best build and achieve

698
00:37:43,360 --> 00:37:47,680
Speaker 4: their client's investment objectives. But as far as the end client,

699
00:37:47,719 --> 00:37:49,800
Speaker 4: that's typically not our customer.

700
00:37:50,280 --> 00:37:53,920
Speaker 2: So I mentioned sixty forty earlier. Does a buffer fund

701
00:37:54,200 --> 00:37:57,600
Speaker 2: act as a substitute for sixty forty in other words,

702
00:37:58,160 --> 00:38:01,920
Speaker 2: if you own whether it's sixty forty, seventy thirty, you

703
00:38:02,160 --> 00:38:05,160
Speaker 2: own bonds for income of which there has been a

704
00:38:05,160 --> 00:38:09,600
Speaker 2: lot over the past fifteen twenty years, but also as

705
00:38:09,640 --> 00:38:13,560
Speaker 2: a non correlated asset with equity other than eighty one

706
00:38:13,840 --> 00:38:18,800
Speaker 2: and twenty twenty two, does this and it offsets the

707
00:38:18,880 --> 00:38:23,920
Speaker 2: volatility and draw down's inequities. Do buffered funds behave similarly

708
00:38:23,960 --> 00:38:25,799
Speaker 2: to a sixty forty? Is that the thinking I.

709
00:38:25,760 --> 00:38:29,840
Speaker 4: Wouldn't say similarly. Let me give you a kind of

710
00:38:29,880 --> 00:38:33,120
Speaker 4: a how we think about it. So if you look

711
00:38:33,160 --> 00:38:36,160
Speaker 4: at let's say, a strategy of a ten percent buffer

712
00:38:36,200 --> 00:38:38,759
Speaker 4: on SMP, in fact, you know there are indexes out

713
00:38:38,800 --> 00:38:41,200
Speaker 4: there that track these. If you compare that to let's say,

714
00:38:43,400 --> 00:38:46,040
Speaker 4: like a black Rock sixty forty portfolio, actually notice that

715
00:38:46,040 --> 00:38:50,840
Speaker 4: the standard deviation is almost identical. Volatility is very similar

716
00:38:51,080 --> 00:38:53,520
Speaker 4: right over the long term, but the source of the

717
00:38:53,600 --> 00:38:55,080
Speaker 4: risk management is different.

718
00:38:55,400 --> 00:38:56,720
Speaker 3: Right you're actually hedging.

719
00:38:56,800 --> 00:39:00,960
Speaker 4: You're not hoping that the correlation between stocks and bonds,

720
00:39:01,000 --> 00:39:03,120
Speaker 4: the negative correlation is there that you know, when my

721
00:39:03,160 --> 00:39:05,480
Speaker 4: stocks go down, I hope my bonds go up kind

722
00:39:05,480 --> 00:39:06,520
Speaker 4: of situation, right.

723
00:39:06,400 --> 00:39:09,839
Speaker 2: Well, historically they do most of the time. Yeah, they

724
00:39:09,880 --> 00:39:13,000
Speaker 2: didn't in twenty twenty two, they didn't in nineteen eighty one, exactly,

725
00:39:13,040 --> 00:39:15,520
Speaker 2: you know, So it's every forty years or so we

726
00:39:15,560 --> 00:39:17,400
Speaker 2: seem to get this rork.

727
00:39:17,280 --> 00:39:21,120
Speaker 4: With inflation at you know, three percent. What happens if

728
00:39:21,160 --> 00:39:22,440
Speaker 4: inflation rears its head.

729
00:39:22,280 --> 00:39:26,240
Speaker 2: Again rising exactly, You'll end up with the same issue

730
00:39:26,680 --> 00:39:29,080
Speaker 2: the next time we see a serious exactly.

731
00:39:29,200 --> 00:39:32,560
Speaker 4: And this is why we say, why not diversify your

732
00:39:32,640 --> 00:39:36,360
Speaker 4: risk management and hedge. So if I have one hundred

733
00:39:36,360 --> 00:39:39,080
Speaker 4: dollars portfolio, and let's say I have sixty dollars in equity,

734
00:39:39,120 --> 00:39:41,120
Speaker 4: forty dollars in fixed income, and let's just say I

735
00:39:41,160 --> 00:39:44,280
Speaker 4: take ten bucks out, I put six, take six from equity,

736
00:39:44,280 --> 00:39:46,239
Speaker 4: four from fixed income, I put it into let's say

737
00:39:46,239 --> 00:39:49,120
Speaker 4: a ten percent buffer strategy in S and P. Perhaps

738
00:39:49,160 --> 00:39:52,200
Speaker 4: the standard deviation of the portfolio could be very, very similar.

739
00:39:52,400 --> 00:39:54,640
Speaker 4: But notice the source your risk management has changed. You've

740
00:39:54,680 --> 00:39:57,759
Speaker 4: introduced hedging as the source of your risk management, without

741
00:39:57,760 --> 00:40:03,600
Speaker 4: the compliance, without the trading scalability issues of options. You've

742
00:40:03,680 --> 00:40:07,320
Speaker 4: introduced hedging as the source of risk management if inflation

743
00:40:07,440 --> 00:40:10,840
Speaker 4: were toor rears its head. Because the thing is, this

744
00:40:10,920 --> 00:40:14,719
Speaker 4: is what everybody needs to ask themselves. If inflation were

745
00:40:14,760 --> 00:40:17,360
Speaker 4: to come back, right, which.

746
00:40:17,160 --> 00:40:19,399
Speaker 3: Is a very. It's not a very.

747
00:40:19,719 --> 00:40:23,200
Speaker 2: There's a non zero pity way above that.

748
00:40:23,280 --> 00:40:28,000
Speaker 4: Yeah, exactly what in your portfolio is going to save

749
00:40:28,120 --> 00:40:31,680
Speaker 4: you if twenty twenty two repeats itself. That's the question

750
00:40:31,719 --> 00:40:35,279
Speaker 4: everybody needs to ask. I always get the answer. Commodities,

751
00:40:35,760 --> 00:40:39,440
Speaker 4: great commodities. It's a timing trade, right, you can get

752
00:40:39,480 --> 00:40:42,760
Speaker 4: in it'll work. But when it's not inflationary, what happens

753
00:40:42,760 --> 00:40:43,480
Speaker 4: to that trade?

754
00:40:44,000 --> 00:40:45,680
Speaker 3: I mean, you point out.

755
00:40:45,480 --> 00:40:48,839
Speaker 2: That gold didn't do great in twenty one or twenty two.

756
00:40:49,360 --> 00:40:52,400
Speaker 2: It's only in the past few years where it's really

757
00:40:52,640 --> 00:40:53,520
Speaker 2: exploded higher.

758
00:40:53,600 --> 00:40:56,800
Speaker 4: That's right, That's right. So I'm not smart enough to

759
00:40:56,840 --> 00:40:59,279
Speaker 4: time that trade. And that's the great thing about these

760
00:40:59,280 --> 00:41:01,960
Speaker 4: types of solutions is you don't have to time the trade, right,

761
00:41:02,080 --> 00:41:05,719
Speaker 4: Like you're diversifying your risk management through just hedging. And

762
00:41:05,760 --> 00:41:09,560
Speaker 4: like I said repeated again, this is the Stayerage game, right,

763
00:41:09,600 --> 00:41:16,080
Speaker 4: how do we protect wealth, not like make exorbitant amounts

764
00:41:16,120 --> 00:41:20,640
Speaker 4: of it, but protect wealth and get a decent return

765
00:41:21,239 --> 00:41:22,600
Speaker 4: from people's wealth.

766
00:41:22,840 --> 00:41:26,080
Speaker 2: So buffer is ten percent hedged on the S and

767
00:41:26,080 --> 00:41:28,600
Speaker 2: P five hundred. Tell us about some of the other ETFs,

768
00:41:28,600 --> 00:41:29,359
Speaker 2: you guys, run.

769
00:41:29,400 --> 00:41:32,439
Speaker 4: So one of the kind of overall themes that we've

770
00:41:32,480 --> 00:41:34,839
Speaker 4: seen in the market is, you know, the two things

771
00:41:34,840 --> 00:41:37,960
Speaker 4: that really people are looking for is downside protection, but

772
00:41:38,000 --> 00:41:41,319
Speaker 4: the other one is income generation. As the boomers are

773
00:41:41,360 --> 00:41:45,279
Speaker 4: in retirement, the need for yield has really shown how

774
00:41:45,360 --> 00:41:47,279
Speaker 4: high it is. I mean, if you look at the

775
00:41:47,320 --> 00:41:49,600
Speaker 4: derivative income space, I think in twenty eighteen and the

776
00:41:49,680 --> 00:41:52,760
Speaker 4: morning Stars ranked fifty eighth last year is ranked ninth

777
00:41:53,160 --> 00:41:57,359
Speaker 4: and flows right. People are looking for income and as

778
00:41:57,440 --> 00:42:00,760
Speaker 4: volatility goes up, just like strategies like right cover calls

779
00:42:01,880 --> 00:42:07,080
Speaker 4: are extremely it's another way to derive yield by monetizing

780
00:42:07,160 --> 00:42:09,600
Speaker 4: volatility in different asset classes. You could do it in gold,

781
00:42:10,080 --> 00:42:11,600
Speaker 4: you can do it in bitcoin, you can do it

782
00:42:11,640 --> 00:42:14,480
Speaker 4: in equities, you can do it in fixed income. And

783
00:42:14,520 --> 00:42:17,080
Speaker 4: that's the thing is people were always thinking one dimensionally.

784
00:42:17,160 --> 00:42:21,759
Speaker 4: That like the innovation is always about thinking three dimensionally

785
00:42:21,800 --> 00:42:24,759
Speaker 4: when everybody else is thinking in two dimensions. Right, this

786
00:42:24,840 --> 00:42:28,720
Speaker 4: is why we have UH, you know, build strategies to

787
00:42:28,760 --> 00:42:32,600
Speaker 4: derive income from uh you know, not just equities, but

788
00:42:32,640 --> 00:42:36,399
Speaker 4: fixed income, but for from gold, from bitcoin, from any

789
00:42:36,440 --> 00:42:37,040
Speaker 4: asset class.

790
00:42:37,040 --> 00:42:39,080
Speaker 2: You can so give us a few ETFs that are

791
00:42:39,400 --> 00:42:40,880
Speaker 2: primarily income focused.

792
00:42:41,120 --> 00:42:41,319
Speaker 3: Yeah.

793
00:42:41,360 --> 00:42:45,200
Speaker 4: So one of our biggest ones is UH UH K

794
00:42:45,320 --> 00:42:49,560
Speaker 4: and G, which tracks the divin in aristaurrats our d

795
00:42:49,719 --> 00:42:54,279
Speaker 4: v I which tracks the uh divin in achievers. These

796
00:42:54,320 --> 00:42:55,600
Speaker 4: all provide uh.

797
00:42:55,600 --> 00:42:57,040
Speaker 3: You know, attractive level yield. I think.

798
00:42:57,400 --> 00:43:04,000
Speaker 2: So diven in aristocrats tend to be high dividends, low price.

799
00:43:04,080 --> 00:43:06,879
Speaker 2: They tend not to be high PE companies, so they're

800
00:43:06,880 --> 00:43:08,200
Speaker 2: fairly stable. Is that? Is that?

801
00:43:08,520 --> 00:43:10,960
Speaker 4: So the companies that have grown their dividend is created

802
00:43:10,960 --> 00:43:12,680
Speaker 4: by S and P back in two thousand and five,

803
00:43:12,680 --> 00:43:15,520
Speaker 4: companies have grown. They're diven in for twenty five consecutive years.

804
00:43:15,520 --> 00:43:15,960
Speaker 2: Wow.

805
00:43:16,480 --> 00:43:19,600
Speaker 4: And these are diven and growers. They're not diven in payers.

806
00:43:19,680 --> 00:43:22,239
Speaker 4: So they typically I believe, you know, yield less than

807
00:43:22,280 --> 00:43:25,560
Speaker 4: two percent. But they've grown. They're diven in for twenty

808
00:43:25,600 --> 00:43:27,520
Speaker 4: five consecutive years. So for a company to grow, they're

809
00:43:27,520 --> 00:43:29,040
Speaker 4: diven in for twenty five consecutive years.

810
00:43:29,160 --> 00:43:30,280
Speaker 2: That's a stable business.

811
00:43:30,360 --> 00:43:33,520
Speaker 4: Yes, And it has to cash flow. It's not a

812
00:43:33,680 --> 00:43:37,719
Speaker 4: pe play right for all intents and purposes. It is

813
00:43:38,120 --> 00:43:40,680
Speaker 4: companies that have to have strong notes. And the other

814
00:43:40,840 --> 00:43:43,640
Speaker 4: thing that people miss is good corporate governance because who

815
00:43:43,680 --> 00:43:47,359
Speaker 4: makes dividend policy The board for board to never cut

816
00:43:47,400 --> 00:43:50,239
Speaker 4: a dividend for twenty five years. It actually was a

817
00:43:50,239 --> 00:43:52,240
Speaker 4: filter for good corporate governors.

818
00:43:51,800 --> 00:43:54,880
Speaker 2: Now and that stock symbol is that ETF.

819
00:43:54,440 --> 00:43:59,440
Speaker 4: Symbol is KNG k NG, Yeah, and you.

820
00:43:59,320 --> 00:44:03,880
Speaker 2: Guys generate additional income on that with recover call writing.

821
00:44:03,920 --> 00:44:04,279
Speaker 3: That's right.

822
00:44:04,440 --> 00:44:06,400
Speaker 2: So if it's a two percent yield, what do you

823
00:44:06,520 --> 00:44:07,640
Speaker 2: actually so.

824
00:44:08,680 --> 00:44:13,120
Speaker 3: Our distribution yields probably in the past year over eight percent.

825
00:44:13,640 --> 00:44:14,920
Speaker 2: Really that's a big number.

826
00:44:14,960 --> 00:44:15,520
Speaker 3: And we're on.

827
00:44:15,440 --> 00:44:19,320
Speaker 4: Average, I believe, covering around twenty percent of every single name.

828
00:44:19,560 --> 00:44:21,600
Speaker 4: So you know, if I have one hundred shares of Walmart,

829
00:44:21,640 --> 00:44:23,359
Speaker 4: I'm writing in at the money call and let's say

830
00:44:23,360 --> 00:44:27,120
Speaker 4: twenty of those shares as an example to achieve that

831
00:44:27,200 --> 00:44:30,960
Speaker 4: target income. So one of the things that core beliefs

832
00:44:30,960 --> 00:44:34,200
Speaker 4: that we have when writing cover calls is like one

833
00:44:34,239 --> 00:44:35,000
Speaker 4: of the biggest.

834
00:44:34,719 --> 00:44:37,160
Speaker 3: Drivers is stock selection. You pick the stocks you get

835
00:44:37,200 --> 00:44:38,200
Speaker 3: good results. Right.

836
00:44:38,680 --> 00:44:41,359
Speaker 4: While you know the aristocrats they don't have the high

837
00:44:41,360 --> 00:44:44,759
Speaker 4: flying mag seven names, right, but definitely as you look

838
00:44:44,800 --> 00:44:47,520
Speaker 4: forward into the windshield, these are really going to be

839
00:44:47,560 --> 00:44:49,719
Speaker 4: the names as the market bronze out right, Like I

840
00:44:49,760 --> 00:44:52,080
Speaker 4: really do think in the next year, you're really looking

841
00:44:52,120 --> 00:44:54,800
Speaker 4: at kind of a Barbell approach where you yeah.

842
00:44:54,600 --> 00:44:55,839
Speaker 3: You have the NVIDIAs in the.

843
00:44:57,440 --> 00:45:01,759
Speaker 4: In the high hyper scalers portfolio, but you really need

844
00:45:01,800 --> 00:45:04,800
Speaker 4: to have the strong staples that cash flow.

845
00:45:06,040 --> 00:45:08,440
Speaker 2: What are some of the names in KNG.

846
00:45:08,640 --> 00:45:12,200
Speaker 4: What you got like Chevron, Walmart, like you're really blue

847
00:45:12,280 --> 00:45:14,120
Speaker 4: chip names that are there.

848
00:45:14,360 --> 00:45:15,640
Speaker 3: I mean, look at Chevron.

849
00:45:15,680 --> 00:45:17,719
Speaker 4: They they have the potential to be, you know, one

850
00:45:17,760 --> 00:45:21,879
Speaker 4: of the beneficiaries of oil in Venezuela right like they were,

851
00:45:21,960 --> 00:45:27,240
Speaker 4: they were there before. And these are the cash flowing

852
00:45:27,280 --> 00:45:30,520
Speaker 4: like crime like companies that like, like I said, grown,

853
00:45:30,520 --> 00:45:32,160
Speaker 4: they're giving for twenty five second years.

854
00:45:32,160 --> 00:45:34,319
Speaker 3: These are strong, strong names that are out there.

855
00:45:34,520 --> 00:45:36,600
Speaker 2: You do you do anything with fixed income on the

856
00:45:36,680 --> 00:45:37,680
Speaker 2: yield side as well?

857
00:45:37,800 --> 00:45:38,200
Speaker 3: Yeah, so.

858
00:45:39,719 --> 00:45:44,839
Speaker 4: We have cover calls on high yield tracking HyG gives

859
00:45:44,840 --> 00:45:48,120
Speaker 4: you also a I believe a double digit distribution yield

860
00:45:49,000 --> 00:45:51,920
Speaker 4: only covering about you know, twenty to twenty five percent

861
00:45:51,960 --> 00:45:53,960
Speaker 4: of the portfolio, so you're still getting over you know,

862
00:45:54,080 --> 00:45:55,480
Speaker 4: on a weekly basis seventy And.

863
00:45:55,520 --> 00:45:59,680
Speaker 2: What's that symbol h y T I heidi mm hmm.

864
00:46:00,080 --> 00:46:01,799
Speaker 4: Yeah.

865
00:46:00,680 --> 00:46:04,239
Speaker 2: And what about do you do anything on the commodity So.

866
00:46:04,560 --> 00:46:09,160
Speaker 4: We have gold IGLD, so you know, biggest not on

867
00:46:09,239 --> 00:46:10,480
Speaker 4: goal has been a hunk of metal.

868
00:46:10,480 --> 00:46:12,000
Speaker 3: Since your portfolio doesn't do anything.

869
00:46:12,040 --> 00:46:16,359
Speaker 4: Now you can monetize the volatility and have you know, potentially.

870
00:46:16,160 --> 00:46:20,040
Speaker 2: Same process covered coal writ in exactly. So this is

871
00:46:20,080 --> 00:46:23,560
Speaker 2: why CBOW is to partner with you. Guys. How does

872
00:46:23,600 --> 00:46:28,360
Speaker 2: that relationship help you manage all of this option writing,

873
00:46:28,400 --> 00:46:30,360
Speaker 2: all this all active.

874
00:46:30,560 --> 00:46:33,719
Speaker 4: That's a great question. So let's take eye Gold as

875
00:46:33,719 --> 00:46:39,080
Speaker 4: an example. Right, prior to that fund, GLD options stop

876
00:46:39,120 --> 00:46:41,680
Speaker 4: trading at four o'clock. By the way, this is one

877
00:46:41,719 --> 00:46:44,640
Speaker 4: of the reasons why CEBO partner with us is how

878
00:46:44,640 --> 00:46:47,160
Speaker 4: do we solve certain issues in the option market for

879
00:46:47,320 --> 00:46:53,359
Speaker 4: the construction of funds? Right if options stop trading at

880
00:46:53,360 --> 00:46:55,279
Speaker 4: four o'clock and I need to know the clothes, I

881
00:46:55,360 --> 00:46:57,520
Speaker 4: can't create an ETF on that.

882
00:46:57,520 --> 00:46:57,960
Speaker 3: That's right.

883
00:46:58,120 --> 00:47:00,919
Speaker 4: S and P options, SPI options they trade, they close

884
00:47:00,960 --> 00:47:05,800
Speaker 4: at four fifteen. Today, GLD options stop trading at four fifteen.

885
00:47:06,560 --> 00:47:08,520
Speaker 4: By the way, that's a really cool statement to say

886
00:47:08,520 --> 00:47:13,480
Speaker 4: that the entire street trades GLD options that extra fifteen

887
00:47:13,480 --> 00:47:15,560
Speaker 4: minutes because we wanted that.

888
00:47:15,560 --> 00:47:17,920
Speaker 2: That's great, but that was you have you have to

889
00:47:17,920 --> 00:47:20,640
Speaker 2: take the closing price at four and then use it

890
00:47:20,719 --> 00:47:22,400
Speaker 2: for and we need that, they need.

891
00:47:22,120 --> 00:47:23,759
Speaker 4: That we need that option market to be open that

892
00:47:23,800 --> 00:47:26,760
Speaker 4: extra fifteen minutes. And by the way, that that those

893
00:47:27,000 --> 00:47:31,120
Speaker 4: products by for trust invests are the reason why we

894
00:47:31,200 --> 00:47:33,319
Speaker 4: have an extra fifteen minutes to trade GLD option. So

895
00:47:33,320 --> 00:47:35,640
Speaker 4: if you're you're late and you're trading at four or five,

896
00:47:37,360 --> 00:47:37,879
Speaker 4: that's us.

897
00:47:38,440 --> 00:47:42,000
Speaker 2: And option trading is so much more complicated, so much

898
00:47:42,000 --> 00:47:45,720
Speaker 2: more difficult. Like you, I started on an equity desk,

899
00:47:45,880 --> 00:47:48,640
Speaker 2: but have always been a little bit of an option

900
00:47:48,880 --> 00:47:53,520
Speaker 2: junkie because it's so fascinating and most people use don't

901
00:47:53,600 --> 00:47:58,760
Speaker 2: use options correctly. They're just making like a lottery ticket bet,

902
00:47:58,800 --> 00:48:02,200
Speaker 2: which tends not to be smart. You guys are using

903
00:48:02,239 --> 00:48:06,440
Speaker 2: options for a very specific purpose to achieve what you

904
00:48:06,560 --> 00:48:09,279
Speaker 2: describe as a defined outcome.

905
00:48:09,200 --> 00:48:11,120
Speaker 3: Solve a problem.

906
00:48:11,160 --> 00:48:15,440
Speaker 2: Solving a problem. Really interesting. Yeah, coming up, we continue

907
00:48:15,480 --> 00:48:19,280
Speaker 2: our conversation with Jeff Chang, co founder and president a VEST.

908
00:48:19,640 --> 00:48:23,319
Speaker 2: I'm Barry Ridults. You're listening to Masters in Business on

909
00:48:23,400 --> 00:48:39,640
Speaker 2: Bloomberg Radio. I'm Barry Redults. You're listening to Masters in

910
00:48:39,680 --> 00:48:43,120
Speaker 2: Business on Bloomberg Radio. My extra special guest this week

911
00:48:43,400 --> 00:48:47,000
Speaker 2: is Jeff Chang. He's president and co founder a VEST,

912
00:48:47,280 --> 00:48:54,040
Speaker 2: the firm specializes in outcome oriented investing via primarily ETFs.

913
00:48:54,040 --> 00:48:58,440
Speaker 2: Then run over fifty billion dollars in assets. Before I

914
00:48:58,480 --> 00:49:01,360
Speaker 2: get to my favorite questions, I want to ask any

915
00:49:01,640 --> 00:49:05,800
Speaker 2: So we've covered stocks, bonds, commodities. You mentioned crypto. What

916
00:49:06,200 --> 00:49:10,520
Speaker 2: are you doing in terms of crypto and generating additional

917
00:49:11,640 --> 00:49:15,200
Speaker 2: defined outcome results using derivatives.

918
00:49:15,480 --> 00:49:21,640
Speaker 4: Yeah, so we have a strategy also target income almost

919
00:49:21,680 --> 00:49:24,279
Speaker 4: I believe about a eighteen nineteen percent yield and you're

920
00:49:24,280 --> 00:49:29,640
Speaker 4: still only covering about twenty percent. So that strategy tracks bitcoin,

921
00:49:29,800 --> 00:49:32,040
Speaker 4: so you can get on a weekly basis, let's say

922
00:49:32,200 --> 00:49:34,120
Speaker 4: you know, seventy eighty percent of the upside and bitcoin

923
00:49:34,160 --> 00:49:38,640
Speaker 4: and then you know really high almost twenty percent yield

924
00:49:38,680 --> 00:49:41,560
Speaker 4: by monetizing the volatility. It's the same thing because like

925
00:49:41,680 --> 00:49:44,440
Speaker 4: just like gold, some of the knock is is that

926
00:49:44,480 --> 00:49:46,799
Speaker 4: it just sits in my portfolio, doesn't do anything, and

927
00:49:46,840 --> 00:49:47,920
Speaker 4: the value.

928
00:49:47,880 --> 00:49:50,160
Speaker 2: Well, no one can say that about bitcoin. It's always

929
00:49:50,200 --> 00:49:52,120
Speaker 2: doing something going up and down.

930
00:49:52,160 --> 00:49:52,680
Speaker 3: Yeah, exactly.

931
00:49:52,719 --> 00:49:54,640
Speaker 2: And what's the ETF symbol.

932
00:49:54,400 --> 00:49:55,960
Speaker 3: For the ibit.

933
00:49:58,000 --> 00:50:02,400
Speaker 4: I'm sorry not that's black, right, yeah, yeah, DFII, that's.

934
00:50:02,320 --> 00:50:09,640
Speaker 2: Right, DFI. And so that's options. How much of the upside,

935
00:50:09,680 --> 00:50:12,000
Speaker 2: how much of the downside, do you get and give

936
00:50:12,080 --> 00:50:13,280
Speaker 2: up or is it just geared?

937
00:50:13,440 --> 00:50:16,880
Speaker 4: We're just writing cover calls on to target you know,

938
00:50:16,920 --> 00:50:19,399
Speaker 4: a specific yield, Like I said, I think anywhere from

939
00:50:19,520 --> 00:50:22,200
Speaker 4: recovering every week about twenty to twenty five percent and

940
00:50:22,360 --> 00:50:26,000
Speaker 4: at the mind how every week every week, every Friday.

941
00:50:26,040 --> 00:50:26,440
Speaker 2: Yeah.

942
00:50:26,560 --> 00:50:29,200
Speaker 3: The reason why we like weeklies.

943
00:50:30,440 --> 00:50:33,840
Speaker 4: Is that when you sell a call, you want the

944
00:50:33,840 --> 00:50:36,120
Speaker 4: premium to go to zero, right, that's right, and that

945
00:50:37,320 --> 00:50:40,440
Speaker 4: decay accelerates in that last week if you're selling a

946
00:50:40,520 --> 00:50:42,520
Speaker 4: monthly options, so if you like do it four times

947
00:50:42,960 --> 00:50:45,680
Speaker 4: a month, you have the potential to generate more yield

948
00:50:46,000 --> 00:50:48,520
Speaker 4: because you're always capturing that extra decay. It's like it's

949
00:50:48,560 --> 00:50:50,600
Speaker 4: like football tickets, right, Like you ever go on step

950
00:50:50,640 --> 00:50:53,719
Speaker 4: up like game times at one o'clock and you go

951
00:50:53,760 --> 00:50:55,680
Speaker 4: on stop up at twelve, the ticket starts to drop

952
00:50:55,800 --> 00:50:59,279
Speaker 4: like rock. Imagine if you kept tracking that and you

953
00:50:59,280 --> 00:51:03,480
Speaker 4: you made money off that drop, right, and everything.

954
00:51:03,239 --> 00:51:04,200
Speaker 3: Kind of follows that.

955
00:51:04,440 --> 00:51:07,920
Speaker 4: In fact, there's actually only one thing that doesn't follow that,

956
00:51:08,000 --> 00:51:11,279
Speaker 4: you know what that is go on Giants tickets, they

957
00:51:11,320 --> 00:51:12,920
Speaker 4: decay before the season starts.

958
00:51:14,280 --> 00:51:17,000
Speaker 2: Well as a guy used to be in New Jersey

959
00:51:17,120 --> 00:51:17,840
Speaker 2: for sure.

960
00:51:18,880 --> 00:51:21,440
Speaker 4: Or jets, tickets. Actually both of those are anominally there.

961
00:51:21,560 --> 00:51:25,040
Speaker 2: So really so in other words, bad assets don't generate

962
00:51:25,080 --> 00:51:29,520
Speaker 2: good option that that's pretty reasonable. How often do things

963
00:51:29,560 --> 00:51:33,240
Speaker 2: get called away? That's obviously the risk when you're writing calls.

964
00:51:34,719 --> 00:51:37,960
Speaker 2: How do you manage around that? How frequently is that

965
00:51:38,120 --> 00:51:39,240
Speaker 2: built into your models?

966
00:51:39,320 --> 00:51:43,440
Speaker 4: I mean, that can happen pretty frequently. But here's the deal, Like,

967
00:51:43,760 --> 00:51:46,279
Speaker 4: think about this, and this is just a concept of

968
00:51:48,680 --> 00:51:51,520
Speaker 4: let's say I collect a two dollar premium and the

969
00:51:51,640 --> 00:51:56,000
Speaker 4: stock goes up one dollar. You're good, Yeah I made

970
00:51:56,040 --> 00:51:57,960
Speaker 4: a dollar, but it's still got called away, but I

971
00:51:58,000 --> 00:52:00,200
Speaker 4: still made a dollar. I just buy the stock back

972
00:52:00,280 --> 00:52:03,279
Speaker 4: or however way I deal with the assignment, depending on

973
00:52:03,600 --> 00:52:04,640
Speaker 4: the strategy.

974
00:52:05,080 --> 00:52:06,840
Speaker 3: So the idea is, as long as the stock.

975
00:52:06,640 --> 00:52:08,719
Speaker 4: Doesn't go above the premium, if I'm writing out the

976
00:52:08,800 --> 00:52:10,640
Speaker 4: money or what I've actually.

977
00:52:10,480 --> 00:52:14,160
Speaker 2: Gives you a buffer to repurchase the stock, not at

978
00:52:14,160 --> 00:52:15,080
Speaker 2: a loss exactly.

979
00:52:15,120 --> 00:52:17,840
Speaker 4: And this comes into what we call about the implied

980
00:52:17,920 --> 00:52:24,080
Speaker 4: versus realized premium, meaning options. If I look historically of

981
00:52:24,120 --> 00:52:26,480
Speaker 4: a particular asset, whether it be a stock or a

982
00:52:26,480 --> 00:52:30,759
Speaker 4: commodity or whatever, and it historically moves X, I'm not

983
00:52:30,800 --> 00:52:35,560
Speaker 4: going to sell the premium at that number to be plus, right,

984
00:52:35,800 --> 00:52:38,840
Speaker 4: just like when you sell car insurance, Like if my

985
00:52:39,000 --> 00:52:41,480
Speaker 4: expected loss is one thousand dollars, I'm not going to

986
00:52:41,520 --> 00:52:43,399
Speaker 4: sell the premium. If for a thousand, I'm gonna sell

987
00:52:43,400 --> 00:52:45,440
Speaker 4: it for twelve hundred dollars to make two hundred, right,

988
00:52:45,480 --> 00:52:46,600
Speaker 4: that extra a little bit.

989
00:52:47,120 --> 00:52:48,520
Speaker 3: So in options, they have.

990
00:52:48,520 --> 00:52:51,640
Speaker 4: What's called the implied versus realized premium, And so that's

991
00:52:51,680 --> 00:52:56,120
Speaker 4: really kind of where you're trying to capture, is the

992
00:52:56,160 --> 00:52:59,280
Speaker 4: implied volatility versus what the realized volatility, And you're hoping

993
00:52:59,280 --> 00:53:01,640
Speaker 4: that the implied will be greater than the realize. I mean,

994
00:53:01,680 --> 00:53:04,080
Speaker 4: that's the hope and option, especially when you're selling them,

995
00:53:04,200 --> 00:53:06,440
Speaker 4: all right, I think there's a stat that, like, you know,

996
00:53:06,480 --> 00:53:09,799
Speaker 4: sixty percent or seventy percent of the time, the person

997
00:53:09,920 --> 00:53:12,440
Speaker 4: selling the option wins the trade, right right.

998
00:53:12,360 --> 00:53:15,120
Speaker 2: Most you know, old option traders don't die, They just

999
00:53:15,200 --> 00:53:18,880
Speaker 2: expire worthless. Yeah, is the exactly that's joke. But you know,

1000
00:53:18,920 --> 00:53:21,520
Speaker 2: if you're a writer of options, you're making a very

1001
00:53:21,520 --> 00:53:24,799
Speaker 2: specific bet, and if you're a purchase of options, you're

1002
00:53:24,840 --> 00:53:25,839
Speaker 2: making a very different bet.

1003
00:53:25,960 --> 00:53:27,040
Speaker 3: Yeah, yeah, I mean you see this.

1004
00:53:28,000 --> 00:53:29,880
Speaker 4: Uh, you know, in some cases the buying options is

1005
00:53:30,640 --> 00:53:33,840
Speaker 4: like you said it can you know, even warm Buffet

1006
00:53:33,920 --> 00:53:35,560
Speaker 4: said there could be weapons of mass destruction.

1007
00:53:35,640 --> 00:53:37,600
Speaker 3: I mean you can see these zero day options that.

1008
00:53:37,520 --> 00:53:39,560
Speaker 2: People are buying, and that's become crazy.

1009
00:53:39,560 --> 00:53:42,439
Speaker 4: I mean those are like scratch off lottery tickets, right,

1010
00:53:42,480 --> 00:53:43,160
Speaker 4: who's buying them?

1011
00:53:43,160 --> 00:53:43,560
Speaker 3: I don't know.

1012
00:53:43,640 --> 00:53:46,000
Speaker 4: The kid and his mom basement pop and his pimples

1013
00:53:46,000 --> 00:53:46,960
Speaker 4: eat many sandwiches.

1014
00:53:47,000 --> 00:53:50,359
Speaker 2: I'm at one point in time, I imagine that there

1015
00:53:50,400 --> 00:53:53,960
Speaker 2: were market makers that had a hedge that, for reasons

1016
00:53:54,080 --> 00:53:58,120
Speaker 2: that were complicated, they were stuck with overnight positions like

1017
00:53:58,200 --> 00:54:02,920
Speaker 2: I almost understand that. But the day traders playing with

1018
00:54:02,960 --> 00:54:08,680
Speaker 2: these this is fan duels and draftking, pure speculative nonsense.

1019
00:54:08,760 --> 00:54:09,440
Speaker 3: Yeah, exactly.

1020
00:54:09,480 --> 00:54:12,320
Speaker 4: So that's why we don't have anything in that space,

1021
00:54:12,440 --> 00:54:16,360
Speaker 4: but it is something to look at from AFAR.

1022
00:54:17,160 --> 00:54:21,319
Speaker 2: Really fascinating stuff. Last question before I jump to my

1023
00:54:22,080 --> 00:54:28,279
Speaker 2: favorite questions. So you're constantly thinking about how do we

1024
00:54:28,360 --> 00:54:30,920
Speaker 2: hedge this position, how do we create a buffer, how

1025
00:54:30,920 --> 00:54:35,600
Speaker 2: do we define a specific outcome for clients? What do

1026
00:54:35,640 --> 00:54:39,759
Speaker 2: you think the average investor isn't thinking about relative to

1027
00:54:39,800 --> 00:54:42,920
Speaker 2: that approach, but perhaps should be. What do you think

1028
00:54:43,000 --> 00:54:45,879
Speaker 2: most people are kind of missing or not paying enough

1029
00:54:45,880 --> 00:54:49,520
Speaker 2: attention to and it could be a geography, it could

1030
00:54:49,560 --> 00:54:53,200
Speaker 2: be a policy whatever, but you're obviously thinking about a

1031
00:54:53,239 --> 00:54:58,040
Speaker 2: lot of things differently than the typical index purchaser. What

1032
00:54:58,080 --> 00:54:58,640
Speaker 2: are we missing?

1033
00:54:59,640 --> 00:55:03,360
Speaker 4: Yeah, I think, you know, while we've had a tremendous

1034
00:55:03,400 --> 00:55:06,200
Speaker 4: amount of growth in kind of the option space of

1035
00:55:06,239 --> 00:55:10,160
Speaker 4: downside protection and the income generation part, I think a

1036
00:55:10,200 --> 00:55:11,279
Speaker 4: lot of the market.

1037
00:55:11,000 --> 00:55:11,759
Speaker 2: Is still.

1038
00:55:13,080 --> 00:55:16,640
Speaker 4: I think thinking two dimensionally in the stocks and bonds, right, Like,

1039
00:55:17,760 --> 00:55:22,200
Speaker 4: instead of just diversifying across, think about you can still diversify,

1040
00:55:22,280 --> 00:55:24,719
Speaker 4: but think about other ways to shape your return, right

1041
00:55:24,880 --> 00:55:28,520
Speaker 4: or thinking about income generation out of the equity portfolio,

1042
00:55:28,560 --> 00:55:31,160
Speaker 4: think about income generation or boosting yield and your fixed

1043
00:55:31,160 --> 00:55:35,359
Speaker 4: income part of it, and then also thinking about risk

1044
00:55:35,360 --> 00:55:40,319
Speaker 4: management beyond diversification. While there is a lot of good

1045
00:55:40,360 --> 00:55:43,600
Speaker 4: part of the financial professional space that is picking up

1046
00:55:43,640 --> 00:55:46,000
Speaker 4: on this, I still don't think like we're just tip

1047
00:55:46,000 --> 00:55:47,400
Speaker 4: of the iceberg at this point.

1048
00:55:47,640 --> 00:55:47,839
Speaker 2: Right.

1049
00:55:48,239 --> 00:55:51,880
Speaker 4: That's on one one standpoint I think people are still missing.

1050
00:55:52,640 --> 00:55:57,960
Speaker 4: The second I think is that I think one of

1051
00:55:58,000 --> 00:56:00,520
Speaker 4: the biggest drivers of the market today, no one would

1052
00:56:00,560 --> 00:56:03,600
Speaker 4: discree a is AI right. However, that's not the part

1053
00:56:03,600 --> 00:56:08,600
Speaker 4: that people are missing that you know, haven't been through

1054
00:56:08,680 --> 00:56:10,759
Speaker 4: the two thousands. I really feel like this is like

1055
00:56:10,840 --> 00:56:13,680
Speaker 4: nineteen ninety nine, two thousand. Like, think about the stocks

1056
00:56:13,719 --> 00:56:14,960
Speaker 4: that were big then, right.

1057
00:56:14,920 --> 00:56:18,880
Speaker 2: Like you had Juniper Networks, Metromedia five right.

1058
00:56:19,080 --> 00:56:22,759
Speaker 4: Like I remember you guys remember price Line Global Crossing.

1059
00:56:22,880 --> 00:56:26,000
Speaker 2: Yeah, you know a lot of these companies have been

1060
00:56:26,280 --> 00:56:30,840
Speaker 2: either absorbed into other companies and still Priceline Expedia, there's

1061
00:56:30,880 --> 00:56:33,680
Speaker 2: a through line there. How is pets dot Com not

1062
00:56:33,840 --> 00:56:36,840
Speaker 2: chewy today? So some of them were just a little

1063
00:56:36,880 --> 00:56:37,880
Speaker 2: early exactly.

1064
00:56:38,040 --> 00:56:39,720
Speaker 3: So let me ask you who won that trade?

1065
00:56:39,719 --> 00:56:45,040
Speaker 4: Facebook, Google, Amazon, Amazon, Apple, Microsoft. A lot of those

1066
00:56:45,120 --> 00:56:49,520
Speaker 4: companies were private or startups then Google, Right, think about that,

1067
00:56:50,000 --> 00:56:52,239
Speaker 4: and I think that's the same, like history doesn't repeat

1068
00:56:52,239 --> 00:56:55,239
Speaker 4: itself at rhymes. I actually think a lot of the

1069
00:56:55,760 --> 00:57:00,920
Speaker 4: kind of the hugely successful companies from AI in startup mode.

1070
00:57:00,920 --> 00:57:04,400
Speaker 4: They're at y Comedy or the ninety of the uh

1071
00:57:06,080 --> 00:57:08,719
Speaker 4: almost eighty ninety percent of the companies at YC are

1072
00:57:08,880 --> 00:57:12,799
Speaker 4: AI driven. They have I've seen an article recently. Their

1073
00:57:13,000 --> 00:57:16,560
Speaker 4: month over month average for the batch is double digits,

1074
00:57:16,600 --> 00:57:20,760
Speaker 4: meaning their revenue is growing over ten percent month month

1075
00:57:20,800 --> 00:57:24,439
Speaker 4: to month or in some cases week over weeks.

1076
00:57:24,520 --> 00:57:28,080
Speaker 2: That's unbelievable. And I said to someone the other day,

1077
00:57:28,480 --> 00:57:32,400
Speaker 2: someone said, who's gonna dethrone and Video? And I said,

1078
00:57:32,440 --> 00:57:35,760
Speaker 2: the founder of that company hasn't graduated high school yet.

1079
00:57:35,920 --> 00:57:39,400
Speaker 2: But he's common or she's coming, he's not. It's not impossible.

1080
00:57:39,400 --> 00:57:42,440
Speaker 2: All right, Let's let's jump to our favorite questions that

1081
00:57:42,480 --> 00:57:45,360
Speaker 2: we ask all of our guests, starting with who are

1082
00:57:45,400 --> 00:57:48,520
Speaker 2: your mentors who helped shape your career?

1083
00:57:49,680 --> 00:57:50,920
Speaker 3: Oh, that's a great question.

1084
00:57:52,200 --> 00:57:57,400
Speaker 4: I would actually uh have to say my brother really yes,

1085
00:57:59,360 --> 00:58:02,360
Speaker 4: and in what way? I have an older brother, he's

1086
00:58:02,360 --> 00:58:06,560
Speaker 4: four years older than me. He's the overachiever. I'm the

1087
00:58:06,640 --> 00:58:11,600
Speaker 4: underachiever of the uh so, uh my brother I remember

1088
00:58:11,640 --> 00:58:14,280
Speaker 4: growing up he was like the uh he was good

1089
00:58:14,280 --> 00:58:16,160
Speaker 4: at math and science. I would literally show up the

1090
00:58:16,160 --> 00:58:18,120
Speaker 4: class and they'd be like, Oh, you're Bill Chain's brother.

1091
00:58:18,160 --> 00:58:19,880
Speaker 3: You must be smart by the way. You know what

1092
00:58:19,880 --> 00:58:20,440
Speaker 3: that does to you.

1093
00:58:20,480 --> 00:58:22,680
Speaker 4: It's like a lot of pressure, a lot of pressure.

1094
00:58:23,640 --> 00:58:27,480
Speaker 4: So he went on. He worked at Apple and then

1095
00:58:28,560 --> 00:58:32,400
Speaker 4: was at Tesla. I think he was chief architect of

1096
00:58:32,440 --> 00:58:39,440
Speaker 4: the dojo dojo price Folks that aren't familiar with dojo,

1097
00:58:39,560 --> 00:58:42,360
Speaker 4: it's the AI system at Tesla that coded the self

1098
00:58:42,440 --> 00:58:47,720
Speaker 4: driving right. He recently, and in fact, Bloomberg wrote an

1099
00:58:47,800 --> 00:58:52,840
Speaker 4: article about his firm, Density Ai that I think they

1100
00:58:52,880 --> 00:58:56,040
Speaker 4: are one of the first companies to really, uh kind

1101
00:58:56,080 --> 00:58:59,800
Speaker 4: of take on because the dojo I think system is

1102
00:58:59,880 --> 00:59:02,880
Speaker 4: one of the one of the more efficient ways that

1103
00:59:02,960 --> 00:59:04,680
Speaker 4: can take on in video for the chips. So that's

1104
00:59:04,680 --> 00:59:06,760
Speaker 4: why it's funny that you said, like, Hey, the person

1105
00:59:06,760 --> 00:59:08,360
Speaker 4: that's going to de thrown a video it may may

1106
00:59:08,400 --> 00:59:09,640
Speaker 4: not may still be in high school.

1107
00:59:09,680 --> 00:59:12,160
Speaker 3: I was like, yeah, he might just be four years old, right.

1108
00:59:13,720 --> 00:59:16,960
Speaker 2: Or he can be deep into the process already. Yeah.

1109
00:59:17,000 --> 00:59:22,400
Speaker 4: So, uh, they recently, like I said, like, Bloomberg just

1110
00:59:22,400 --> 00:59:26,120
Speaker 4: wrote an article about them on dense Ai and he

1111
00:59:26,120 --> 00:59:28,760
Speaker 4: he has been extremely Like a lot of times people

1112
00:59:28,760 --> 00:59:31,840
Speaker 4: ask like, hey, did you work that hard because your

1113
00:59:31,840 --> 00:59:34,920
Speaker 4: parents were, you know, like tire your parents. No. Actually

1114
00:59:34,960 --> 00:59:37,040
Speaker 4: I was just chasing my brother the whole time. It

1115
00:59:37,120 --> 00:59:40,800
Speaker 4: was definitely a different dynamic and uh, yeah, I couldn't

1116
00:59:40,840 --> 00:59:41,680
Speaker 4: be more proud of him.

1117
00:59:41,960 --> 00:59:42,080
Speaker 2: Uh.

1118
00:59:42,360 --> 00:59:44,800
Speaker 4: And a lot of times people are like, hey, what

1119
00:59:44,800 --> 00:59:49,080
Speaker 4: what tea are the chains drinking? Because we're but we

1120
00:59:49,120 --> 00:59:52,880
Speaker 4: get along great. While we're competitive, we we support each other.

1121
00:59:52,960 --> 00:59:53,680
Speaker 3: But he's been.

1122
00:59:53,840 --> 00:59:56,280
Speaker 2: You're in different fields, so the competition exactly.

1123
00:59:56,320 --> 01:00:00,720
Speaker 3: He's engineering. I'm in financial yeah, yeah.

1124
01:00:00,560 --> 01:00:03,880
Speaker 2: Exactly, so similar, similar background. Let's talk about books. What

1125
01:00:03,920 --> 01:00:05,640
Speaker 2: are some of your favorites. What are you reading right now? Oh?

1126
01:00:05,680 --> 01:00:08,520
Speaker 3: I said Liar's Poker, a very inflacable one.

1127
01:00:08,600 --> 01:00:12,960
Speaker 2: Yeah, just had its thirtieth anniversary. I think last year.

1128
01:00:13,040 --> 01:00:16,640
Speaker 4: I like, I thought was really good for me was

1129
01:00:16,680 --> 01:00:19,920
Speaker 4: the book Influenced by Robert Childonie Fantastic.

1130
01:00:20,000 --> 01:00:23,240
Speaker 3: It was a great book. Kind of along with that,

1131
01:00:23,360 --> 01:00:24,840
Speaker 3: how to win friends and influence people.

1132
01:00:24,960 --> 01:00:28,160
Speaker 4: I think those are great. I actually in financed. One

1133
01:00:28,160 --> 01:00:31,760
Speaker 4: of my first ones was The Intelligent Investor by Ben Grant.

1134
01:00:31,800 --> 01:00:34,320
Speaker 3: Yeah, Ben Graham. Those are kind of cornerstones.

1135
01:00:34,480 --> 01:00:38,560
Speaker 2: Yeah, that's a great list. I know you are on

1136
01:00:38,680 --> 01:00:42,280
Speaker 2: planes a lot when you're not reading. What are you streaming?

1137
01:00:42,320 --> 01:00:45,920
Speaker 2: What's keeping you entertained on these long cross country flights,

1138
01:00:46,320 --> 01:00:48,160
Speaker 2: either podcasts or Netflix or whatever.

1139
01:00:48,600 --> 01:00:54,400
Speaker 4: I do listen to podcasts a masters in business. However,

1140
01:00:55,440 --> 01:00:58,880
Speaker 4: there's a new thing that I've been doing. Actually it's

1141
01:00:58,920 --> 01:01:03,440
Speaker 4: not a book, all right, and it'll probably be hit

1142
01:01:03,480 --> 01:01:06,919
Speaker 4: everybody differently on on what I'm doing here. Okay, And

1143
01:01:07,440 --> 01:01:10,439
Speaker 4: I could tell you I got this from a good

1144
01:01:10,480 --> 01:01:13,920
Speaker 4: friend of mine and he's going to kill me for

1145
01:01:13,960 --> 01:01:14,520
Speaker 4: saying this, So.

1146
01:01:16,600 --> 01:01:17,000
Speaker 3: I'm good.

1147
01:01:17,360 --> 01:01:19,280
Speaker 4: A friend of mine and his name Matt Bellamy, he's

1148
01:01:19,280 --> 01:01:22,360
Speaker 4: the lead singer in the Muse and he actually taught

1149
01:01:22,400 --> 01:01:24,240
Speaker 4: me this, so I can't take credit for this. We

1150
01:01:24,320 --> 01:01:27,400
Speaker 4: go into chat EBT and he actually sent me the prompt,

1151
01:01:27,560 --> 01:01:30,880
Speaker 4: and we prompt chat GBT, tell me in the last

1152
01:01:30,880 --> 01:01:35,280
Speaker 4: two weeks, what you have learned that is beyond human

1153
01:01:35,320 --> 01:01:37,040
Speaker 4: comprehension something.

1154
01:01:36,840 --> 01:01:37,640
Speaker 3: Along those lines.

1155
01:01:37,760 --> 01:01:40,040
Speaker 4: How fascinating And by the way it spits out all

1156
01:01:40,120 --> 01:01:42,920
Speaker 4: this stuff because if you think about it humans, like

1157
01:01:42,960 --> 01:01:45,640
Speaker 4: we as a human you could get a PhD in

1158
01:01:45,640 --> 01:01:49,360
Speaker 4: biology you get a PhD. And astrophysicists you get PhD

1159
01:01:49,400 --> 01:01:52,000
Speaker 4: in chemistry, but like you're the expert in their field.

1160
01:01:52,000 --> 01:01:55,440
Speaker 4: But think about this that like chat GBT passed the

1161
01:01:55,480 --> 01:01:57,520
Speaker 4: Bar exam and like, I don't know, like a couple

1162
01:01:57,480 --> 01:02:00,560
Speaker 4: of weeks, right, So it's becoming experts and everything, and

1163
01:02:00,560 --> 01:02:03,120
Speaker 4: then it's combining all of those things together. So how

1164
01:02:03,160 --> 01:02:06,080
Speaker 4: many like PhDs and chemistry, astrophysics do you have that

1165
01:02:06,200 --> 01:02:08,400
Speaker 4: I have like the expert and everything, And then what

1166
01:02:08,520 --> 01:02:11,680
Speaker 4: comes out like you tend to learn so many things

1167
01:02:11,720 --> 01:02:14,720
Speaker 4: that like by the way it turns into this rabbit hole.

1168
01:02:15,040 --> 01:02:17,640
Speaker 4: And I noticed that my prompt actually because I always

1169
01:02:17,640 --> 01:02:19,240
Speaker 4: tell it to me, like explain it to me, Like

1170
01:02:19,280 --> 01:02:23,000
Speaker 4: I'm sixteen, so I've been driving into this other thing.

1171
01:02:23,040 --> 01:02:27,040
Speaker 4: Of Uh, it's been teaching me about quantum entanglement.

1172
01:02:27,320 --> 01:02:28,160
Speaker 3: Are you familiar with this?

1173
01:02:28,440 --> 01:02:32,800
Speaker 2: Of course, like we wasn't familiar with spooky action at

1174
01:02:32,800 --> 01:02:35,600
Speaker 2: a distance. I mean they teach that in middle school.

1175
01:02:35,720 --> 01:02:36,400
Speaker 3: Yeah, exactly.

1176
01:02:36,440 --> 01:02:41,120
Speaker 4: So the quantum entanglement that you have two protons that

1177
01:02:41,360 --> 01:02:44,560
Speaker 4: you know, if you do want to X, why we'll

1178
01:02:44,560 --> 01:02:46,560
Speaker 4: do the same. It's just like having two dice. If

1179
01:02:46,840 --> 01:02:49,040
Speaker 4: dice on Earth. By the way, they've proven this, like

1180
01:02:49,120 --> 01:02:51,880
Speaker 4: if you roll the dice on Earth it rolls a six,

1181
01:02:51,880 --> 01:02:53,960
Speaker 4: it will definitely roll six, and it's not bound by

1182
01:02:53,960 --> 01:02:56,760
Speaker 4: space and time, so basically it could be light years away.

1183
01:02:56,800 --> 01:02:58,600
Speaker 3: You roll that dice, it rolls an eight. This one

1184
01:02:58,640 --> 01:02:59,800
Speaker 3: on Earth is going to roll in eight.

1185
01:03:00,120 --> 01:03:03,160
Speaker 4: And so then they sort of combine that with is

1186
01:03:03,200 --> 01:03:08,360
Speaker 4: that part of human consciousness that is your consciousness? Quantum

1187
01:03:08,520 --> 01:03:10,880
Speaker 4: entangled is what makes you you?

1188
01:03:11,200 --> 01:03:12,920
Speaker 3: By the way, this type of thinking.

1189
01:03:13,200 --> 01:03:15,840
Speaker 2: There's a related topic and I haven't run this through

1190
01:03:15,920 --> 01:03:20,360
Speaker 2: chat GBT, but I should, which is the concept of

1191
01:03:20,480 --> 01:03:26,720
Speaker 2: emergence intelligence emergence as the natural outcome of the universe.

1192
01:03:26,760 --> 01:03:30,120
Speaker 2: Why does the universe exist if not to create a

1193
01:03:30,280 --> 01:03:36,760
Speaker 2: conscience intelligence? Although the flip side of that is life

1194
01:03:36,800 --> 01:03:40,960
Speaker 2: is fairly common throughout the universe hydrogen, carbon, oxygen, nitrogen,

1195
01:03:41,400 --> 01:03:45,880
Speaker 2: but advanced technological life so far at least, appears to

1196
01:03:45,920 --> 01:03:51,360
Speaker 2: be exceedingly rare. So that's the counterbalance of emergence totally.

1197
01:03:52,120 --> 01:03:54,240
Speaker 4: And then the other thing that I found recently that

1198
01:03:54,240 --> 01:03:57,480
Speaker 4: people can dig into I think this is fascinating, is

1199
01:03:57,560 --> 01:04:03,760
Speaker 4: that your head experiences time different than your feet from

1200
01:04:03,800 --> 01:04:05,840
Speaker 4: the proximity of Gravity's.

1201
01:04:05,520 --> 01:04:09,880
Speaker 2: Well, certainly we have to adjust GPS because for the

1202
01:04:09,960 --> 01:04:13,720
Speaker 2: relative relative the GPS persons, which Einstein turned out to

1203
01:04:13,720 --> 01:04:16,600
Speaker 2: be right about exactly so. But the difference between your

1204
01:04:16,680 --> 01:04:20,600
Speaker 2: head and feet, oh yes, is so tiny unless you're

1205
01:04:20,640 --> 01:04:25,240
Speaker 2: falling into a black hole. And then spaghetification is the problem. Yeah.

1206
01:04:25,280 --> 01:04:28,400
Speaker 4: So then you take quantum entanglement uh huh, And you

1207
01:04:28,480 --> 01:04:31,000
Speaker 4: then say, okay, if I have a proton here and

1208
01:04:31,240 --> 01:04:34,960
Speaker 4: a proton elsewhere, and the light in the how that

1209
01:04:35,040 --> 01:04:41,320
Speaker 4: proton experiences time through entanglement versus how time bends with gravity.

1210
01:04:42,000 --> 01:04:43,960
Speaker 3: By the way, all of this just.

1211
01:04:44,040 --> 01:04:47,920
Speaker 4: Keeps going deeper and deeper and deeper into And then

1212
01:04:48,120 --> 01:04:50,400
Speaker 4: the thing is that I keep telling it to explain

1213
01:04:50,440 --> 01:04:53,440
Speaker 4: it to me like I'm sixteen. Now my entire prompt

1214
01:04:53,440 --> 01:04:56,120
Speaker 4: explains everything. I will explain it to you as if

1215
01:04:56,160 --> 01:04:57,200
Speaker 4: you're sixteen years old.

1216
01:04:57,240 --> 01:05:01,920
Speaker 2: So the issue I occasionally run in with perplexity or

1217
01:05:02,080 --> 01:05:08,880
Speaker 2: chat ept is it tends to conform its output to you. Yes,

1218
01:05:09,120 --> 01:05:11,160
Speaker 2: And sometimes I'll ask a question. It's like, no, I

1219
01:05:11,240 --> 01:05:14,320
Speaker 2: want a list of ten podcast questions. I just tell

1220
01:05:14,320 --> 01:05:18,000
Speaker 2: me about Jeff Chang and what led to VEST. Don't

1221
01:05:18,000 --> 01:05:20,640
Speaker 2: give me a podcast. I have my own questions.

1222
01:05:20,640 --> 01:05:23,120
Speaker 4: That's why I use multiple rock every right. That way

1223
01:05:23,120 --> 01:05:25,680
Speaker 4: I get a whole plethora. And then what ends up

1224
01:05:25,680 --> 01:05:28,760
Speaker 4: happening is you get all this new stuff and then

1225
01:05:28,800 --> 01:05:31,280
Speaker 4: you dig deep into whatever topic. And I found that

1226
01:05:31,360 --> 01:05:36,320
Speaker 4: so fascinating because I just it's curiosity.

1227
01:05:36,400 --> 01:05:40,000
Speaker 2: It's like if you're interested in these sorts of things exacsolutely,

1228
01:05:41,320 --> 01:05:44,520
Speaker 2: but you have to be on guard for the occasional hallucination.

1229
01:05:44,720 --> 01:05:50,160
Speaker 2: And every now and then I find myself leaving AI

1230
01:05:50,360 --> 01:05:53,320
Speaker 2: to go to just traditional search and say, hey, show

1231
01:05:53,360 --> 01:05:56,560
Speaker 2: me a source for this. Is this I don't think

1232
01:05:56,920 --> 01:06:00,360
Speaker 2: before AI. I don't think people were skeptical enough about

1233
01:06:00,880 --> 01:06:04,320
Speaker 2: the sources of what they consumed with AI. You really

1234
01:06:04,360 --> 01:06:07,320
Speaker 2: have to know what is real and what is fake.

1235
01:06:07,840 --> 01:06:11,240
Speaker 2: People miss that, all Right, our final two questions, what

1236
01:06:11,320 --> 01:06:13,920
Speaker 2: sort of advice would you give to a recent college

1237
01:06:13,960 --> 01:06:20,720
Speaker 2: grad interested in a career in asset management or or

1238
01:06:20,760 --> 01:06:22,280
Speaker 2: ETFs specifically?

1239
01:06:22,920 --> 01:06:24,880
Speaker 4: Yeah, I think at recent college grad, I think similar

1240
01:06:24,960 --> 01:06:27,960
Speaker 4: to kind of bringing in full circle same thing, like

1241
01:06:28,480 --> 01:06:32,200
Speaker 4: develop the skills that you know you're not beholden to anybody,

1242
01:06:32,640 --> 01:06:37,920
Speaker 4: right whatever that is, whether you're in college or out

1243
01:06:37,920 --> 01:06:41,200
Speaker 4: of college, Like develop those skills that you can actually

1244
01:06:41,200 --> 01:06:45,120
Speaker 4: that they're portable one or the other, and then not

1245
01:06:45,200 --> 01:06:51,160
Speaker 4: be afraid of failure, take chances. Now, this is not

1246
01:06:51,200 --> 01:06:54,800
Speaker 4: for everybody, I would say, you know, meaning not everybody

1247
01:06:54,840 --> 01:06:57,720
Speaker 4: is going to be a founder. Not everybody's going to

1248
01:06:57,720 --> 01:06:59,720
Speaker 4: be an entrepreneur, which I, by the way, I find

1249
01:07:00,040 --> 01:07:03,960
Speaker 4: as two different people. Founder has the creativity, an entrepreneur

1250
01:07:04,040 --> 01:07:07,240
Speaker 4: has the grit and influence. A founder has to have

1251
01:07:07,280 --> 01:07:10,440
Speaker 4: the creativity because you're actually introducing a whole new industry

1252
01:07:10,520 --> 01:07:13,880
Speaker 4: or a whole new thing that somebody else has not

1253
01:07:14,120 --> 01:07:14,680
Speaker 4: seen yet.

1254
01:07:14,800 --> 01:07:17,320
Speaker 3: Right, But that's the thing.

1255
01:07:17,520 --> 01:07:21,000
Speaker 4: And then also keep your eye out for painful problems

1256
01:07:21,400 --> 01:07:24,840
Speaker 4: that you have the skill set to solve. So obtain

1257
01:07:24,920 --> 01:07:27,919
Speaker 4: those skill sets and then have your eyes out, eyes

1258
01:07:27,960 --> 01:07:31,040
Speaker 4: peeled throughout life, write them down, look for pain points,

1259
01:07:31,120 --> 01:07:33,840
Speaker 4: look for pain points, look for problems. And then the

1260
01:07:33,880 --> 01:07:35,960
Speaker 4: second the last thing is just a person thing is

1261
01:07:36,200 --> 01:07:41,000
Speaker 4: don't take yourself too seriously, right, have fun with life.

1262
01:07:41,160 --> 01:07:44,320
Speaker 4: And I think that that is because otherwise all this

1263
01:07:44,360 --> 01:07:46,440
Speaker 4: stuff can create massive amounts of burnout.

1264
01:07:46,600 --> 01:07:49,320
Speaker 2: And our final question, what do you know about the

1265
01:07:49,320 --> 01:07:54,240
Speaker 2: world of buffered funds? Investing ETFs today might have been

1266
01:07:54,280 --> 01:07:57,800
Speaker 2: healthful fifteen twenty years ago when you were first getting started?

1267
01:07:59,520 --> 01:08:01,880
Speaker 3: How hard it would have been? Right?

1268
01:08:02,000 --> 01:08:05,640
Speaker 2: Like? Literally would that have discouraged you from launching?

1269
01:08:05,720 --> 01:08:07,880
Speaker 4: Yeah? Well, I think that was actually the superpower, Right

1270
01:08:07,920 --> 01:08:09,600
Speaker 4: Like when you climb a mountain and you don't know

1271
01:08:09,640 --> 01:08:12,160
Speaker 4: how high it is, and if there's a cloud base,

1272
01:08:13,040 --> 01:08:16,360
Speaker 4: if you saw it and a clearer view, it probably

1273
01:08:16,400 --> 01:08:18,599
Speaker 4: wouldn't be If you told me to quit my job

1274
01:08:18,600 --> 01:08:20,519
Speaker 4: and I wouldn't get paid for four plus years, I

1275
01:08:20,560 --> 01:08:23,080
Speaker 4: probably wouldn't have done that, huh. But then it's like

1276
01:08:23,160 --> 01:08:26,519
Speaker 4: always success is always around the corner, at least you

1277
01:08:26,640 --> 01:08:30,160
Speaker 4: dream of it, right, everybody sees what you are now.

1278
01:08:30,320 --> 01:08:34,320
Speaker 4: They don't see the pain where you're constantly just waiting

1279
01:08:34,320 --> 01:08:36,360
Speaker 4: for that cloud to clear on the next part of

1280
01:08:36,360 --> 01:08:38,760
Speaker 4: the mountain. Because I could tell you this that like

1281
01:08:38,840 --> 01:08:40,759
Speaker 4: if you saw how.

1282
01:08:40,600 --> 01:08:43,360
Speaker 3: Big the mountain is, it would be nobody would.

1283
01:08:43,160 --> 01:08:46,320
Speaker 2: Do it really really interesting. Thank you Jeff for being

1284
01:08:46,400 --> 01:08:49,360
Speaker 2: so generous with your time. We have been speaking with

1285
01:08:49,439 --> 01:08:53,600
Speaker 2: Jeff Chang, co founder and president of vest. If you

1286
01:08:53,760 --> 01:08:56,559
Speaker 2: enjoy this conversation, well check out any of the six

1287
01:08:56,680 --> 01:09:00,000
Speaker 2: hundred we've done over the past twelve years. You can

1288
01:09:00,000 --> 01:09:03,799
Speaker 2: I find those at iTunes and Spotify, YouTube, Bloomberg, wherever

1289
01:09:03,880 --> 01:09:07,360
Speaker 2: you get your favorite podcasts. I would be remiss if

1290
01:09:07,360 --> 01:09:09,519
Speaker 2: I didn't thank the product staff that helps with these

1291
01:09:09,520 --> 01:09:15,040
Speaker 2: conversations together each week. Alexis Norriega is my video producer.

1292
01:09:15,160 --> 01:09:20,560
Speaker 2: Sean Russo is my researcher. Anna Luke is my podcast producer.

1293
01:09:21,040 --> 01:09:24,960
Speaker 2: I'm Barry Ritoltz. You've been listening to Masters in Business

1294
01:09:25,439 --> 01:09:26,639
Speaker 2: on Bloomberg Radio.