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Speaker 1: Look ahead, imagine more, gain insight for your industry with

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Speaker 1: forward thinking advice from the professionals at Cone Resnick. Is

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Speaker 1: your business ready to break through? Find out more at

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Speaker 1: Cone resnick dot com. Slash Breakthrough. This week on the podcast,

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Speaker 1: I have an extra special guest. He's an old friend.

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Speaker 1: His name is Wes Gray, and he is not your

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Speaker 1: usual quant slash money manager. He is the founder and

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Speaker 1: CEO of Alpha architect Um, and he's also an unusual guy.

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Speaker 1: He uh comes out of uh University of Chicago in

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Speaker 1: an MBA PhD program and decides to take a little

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Speaker 1: time off in order to join the Marines, which he

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Speaker 1: did as a captain, went overseas in Iraq, where he

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Speaker 1: served as an information order officer embedded with the Iraqi Army,

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Speaker 1: and Um wrote a book about it, Colds Embedded and

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Speaker 1: Really a fascinating uh An unusual background discusses throughout his

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Speaker 1: career how Iraq and and the prosecution of war are

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Speaker 1: in some ways very similar to investing. Alpha architect is

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Speaker 1: a quantitative firm. Uh West crunches a lot of numbers.

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Speaker 1: He's a big believer in factor investing. He has long

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Speaker 1: since been a proponent of both momentum and value, which

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Speaker 1: is a somewhat unusual combination, but they are two of

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Speaker 1: the six main factors UH that are out there. I

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Speaker 1: thought the conversation was absolutely fascinating. If you are a

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Speaker 1: fan of quantitative investing, or if you enjoyed our previous

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Speaker 1: podcasts with people like Ammanual Derman or MEB Fabor or

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Speaker 1: any of the other quants we've spoken with, UH, you'll

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Speaker 1: really enjoy this. So, with no further ado, my conversation

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Speaker 1: with Wes Gray. This is Masters in Business with Barry

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Speaker 1: Ridholts on Bloomberg Radio. My special guest today is Dr

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Speaker 1: Wesley Gray. He is a former captain in the United

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Speaker 1: States Marine Corps. West graduated Magnicum Laudy from Morton. He

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Speaker 1: earned both his m b a. And PhD in finance

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Speaker 1: from the University of Chicago before becoming a professor of

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Speaker 1: finance at Drexel University. He currently runs the site Alpha Architect,

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Speaker 1: as well as running an asset management shop for high

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Speaker 1: net worth individuals. He is the author of three soon

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Speaker 1: to be four books on quantitative investing, as well as

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Speaker 1: numerous academic articles. Wes Gray, Welcome to Bloomberg. Very happy

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Speaker 1: to be here. So let's talk a little bit about

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Speaker 1: your background, because it's kind of unusual. Lots of people

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Speaker 1: take some time off between college and grad school. What

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Speaker 1: did you do between college and grad school? So what

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Speaker 1: I did is basically, right out of undergrad actually directly

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Speaker 1: enrolled in the University of Chicago paced program at ripe

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Speaker 1: old age of two, spent two years there getting hazed,

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Speaker 1: you know, fighting against Russian math champs to compete. And

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Speaker 1: then after two years in a PhD program, you you

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Speaker 1: get to your comps stage and I passed the comps

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Speaker 1: and I said, you know what, um twenty four, I'm

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Speaker 1: hating finance at the moment. I needed to do something

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Speaker 1: that I always wanted to do, and that was serve

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Speaker 1: in the military. So I asked for a special four

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Speaker 1: year sabbatical uh to basically serving the Marine Corps at

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Speaker 1: left for four years, which is probably first time that's

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Speaker 1: ever happened, I imagine in Chicago finance PhD program history,

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Speaker 1: and then came back and finished up. So let's not

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Speaker 1: skip over that middle part. Those four years were the

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Speaker 1: middle of the Iraq War. You were embedded with the

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Speaker 1: Iraqi Army as a captain or lieutenant. What was your rank.

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Speaker 1: When I was there as a lieutenant lieutenant, I called

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Speaker 1: you a first lieutenant. Yeah, well I got out as

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Speaker 1: a captain, but okay, I serving there as a first

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Speaker 1: lieutenant and your nickname amongst the Iraqis was Jamal. How

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Speaker 1: did that come about? Basically? I was the intel guy

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Speaker 1: in our our mid team military transition team, and so

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Speaker 1: the intel guy is supposed to know how to speak

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Speaker 1: the language, you know, how to influence the people. And

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Speaker 1: one of the things you learned about reading about Arab

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Speaker 1: culture is it's really important to learn the language and

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Speaker 1: hang out with the people in order to you know,

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Speaker 1: be able to better influence them. So I used to

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Speaker 1: hang out in what they call the swats Uh and

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Speaker 1: I was down there and they would always call me

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Speaker 1: lulas um gay because they can't say ours very well.

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Speaker 1: And I was like, you know what, guys, let's try

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Speaker 1: to find a language so instead of gay, instead of great.

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Speaker 1: You know, and it's usually not the greatest idea to

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Speaker 1: walk around with a bunch of Marines when when I

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Speaker 1: ras are calling you malasam gay, you just get some

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Speaker 1: ridicule subtimes um and they just couldn't say it, so

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Speaker 1: as like, can you guys, name me, and they literally

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Speaker 1: had like a naming party where there was probably fifty

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Speaker 1: Iraqis in the uh in this swaha it's maybe you know,

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Speaker 1: thousand square foot you know, cardboard building type thing, you

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Speaker 1: can think about it. And they came up with Jamal,

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Speaker 1: and then I was called Malasam Jamal, and uh, I

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Speaker 1: kind of like I actually that was my identity. Even

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Speaker 1: when I came back, I still felt like I was

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Speaker 1: Malasam Jamal. That's funny. So how did the Marines and

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Speaker 1: your your time in Iraq helped prepare you for a

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Speaker 1: career as a quant in in finance. I'd say the

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Speaker 1: biggest thing is just understanding that in all endeavors, humans

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Speaker 1: are involved. And when humans are involved in any sort

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Speaker 1: of decision making or activity where there's a lot of emotion,

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Speaker 1: stress and chaos, they do crazy things. There's certainly a

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Speaker 1: level of emotion involved there. And I think in the

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Speaker 1: military what you learn is it's all about standard operating procedures,

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Speaker 1: training to do things that seem you know, mundane and

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Speaker 1: dumb and checklist driven now, but when you get into

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Speaker 1: a chaotic situation, you think, God, you did that, so

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Speaker 1: you don't rely on your natural action you're rely on

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Speaker 1: your standard operating procedure. You know. Perfect example might be

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Speaker 1: I remember I was in the palm groves, an area

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Speaker 1: called Haditha, which is kind of you think out in

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Speaker 1: Alomar Province where a lot of the isis guys are

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Speaker 1: now and I was on Iraqi patrol and literally a

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Speaker 1: dude gets shot in the chest fifteen feet in front

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Speaker 1: of me. You know, natural action is hit the deck,

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Speaker 1: you know, go to the ground as fast as possible.

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Speaker 1: Another natural action, which you're not supposed to do, is

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Speaker 1: go run to the person who just got shot and

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Speaker 1: see what beat on him? And now that and they're

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Speaker 1: gonna go shoot me now, so what. But what you

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Speaker 1: train to is when there's a casualty, the first thing

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Speaker 1: you do is hit the deck, fine cover, figure out

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Speaker 1: where the other guys are, to make sure you secure

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Speaker 1: the area. The only way that you you have a

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Speaker 1: reaction to do that because you have stand operating procedure

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Speaker 1: and you're trained to that standard. Just like in financial markets,

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Speaker 1: I think a lot of time, like let's say there's

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Speaker 1: a fifty draw down in your portfolio, your gut reaction

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Speaker 1: is sell everything. But that's not what you should probably do.

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Speaker 1: So you need to have a process or something in

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Speaker 1: place before you hit chaos. So when you're actually in chaos,

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Speaker 1: you you know, you're act in a more rational, i'd

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Speaker 1: say logical way, And I think that you see a

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Speaker 1: lot of that between military and investing. You know, I

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Speaker 1: started on a trading desk. The head of the desk

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Speaker 1: was a former Marine jungle combat instructor. There was someone

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Speaker 1: else who was a former seal on the desk. Now,

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Speaker 1: what I always found fascinating wasn't just the standard operating

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Speaker 1: procedure for what to do. It was preparing emotionally for

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Speaker 1: the firefight. Like, how can an investor prepare emotionally for

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Speaker 1: those big draw downs? Yes, so I think it's just

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Speaker 1: like in the military. You try to train as close

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Speaker 1: as you can to fight and have ultimate faith and

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Speaker 1: confidence in the leadership and the decisions and the process

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Speaker 1: that you believe in. And when you have that, i'd

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Speaker 1: say belief in what you're doing, and you really put

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Speaker 1: a you know, good faith effort into working on that.

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Speaker 1: When you hit chaos, if you believe in your training,

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Speaker 1: you're more likely than not to stick with that process.

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Speaker 1: I'm Barry Ridhults. You're listening to Masters in Business on

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Speaker 1: Bloomberg Radio. My special guest today is West Gray. He

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Speaker 1: is a former captain in the Marines, served as an

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Speaker 1: in bed with the Iraqi Army on behalf of the

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Speaker 1: U S Marines. He runs a shop called Alpha Architect

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Speaker 1: and has written numerous books on quantitative investing. Let's talk

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Speaker 1: about a book of viewers that I really enjoyed quantitative value.

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Speaker 1: When we think of quantz and we think of value investors,

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Speaker 1: we really don't think of those as having a big overlap. Up.

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Speaker 1: Tell us how you came to the idea of value

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Speaker 1: that was quantitatively driven. Sure, so I had start out

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Speaker 1: with this being a total bible thumping Ben Graham intelligent

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Speaker 1: investor stockpicker did that for ten years my own personal money,

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Speaker 1: and thank god I had the opportunity to eat a

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Speaker 1: lot of humble pie along the way, and I was thinking,

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Speaker 1: you know what, this whole Warren Buffett Ben Graham idea

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Speaker 1: makes total sense to me. But after you get engaged

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Speaker 1: in the activity of stockpicking, you realize that you get

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Speaker 1: very emotionally involved. And even if you understand the biases

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Speaker 1: you've memorized. You know Kniman's book, even if you know it,

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Speaker 1: and you know how the biases influence you. You start

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Speaker 1: to realize you still can't control against the biases. So

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Speaker 1: I thought, hey, you know, fundamentally, value investing makes sense

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Speaker 1: by cheap stuff everyone hates. Great. The problem is hold

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Speaker 1: it for a long time, hold your nose when inevitably

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Speaker 1: it told the underperforms for potentially multi air stretches um.

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Speaker 1: But at the same time, how can we implement this

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Speaker 1: process in an objective discipline way such that I can

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Speaker 1: pull out monkey brain from making bad decisions, uh, you know,

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Speaker 1: from trying to be a stock picker, because I learned

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Speaker 1: my lessons basically on that. That's quite fascinating. So some

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Speaker 1: of the things you reference in the book. Obviously the

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Speaker 1: benefits of using a quant approach is you're taking out

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Speaker 1: the human elements. One of the things you reference in

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Speaker 1: the book is the importance of finding the highest quality stocks.

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Speaker 1: So first, what does it mean when we say a

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Speaker 1: stock is high quality? And then how do you screen

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Speaker 1: for those? Sure? So, so stepping back, it's really important

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Speaker 1: when we when we talk about quality in the context investing,

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Speaker 1: to understand given it's already cheap. So with value investing

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Speaker 1: the way we look at it, you have to be

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Speaker 1: buying the stress cheapest securities in the market. Only within

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Speaker 1: the cheap does quality start to help add value. So

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Speaker 1: if you just look at quality as a standalone, you know,

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Speaker 1: characteristic of a security, it's unclear that it adds any

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Speaker 1: quote unquote alpha or edge. It's all about looking at quality.

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Speaker 1: Given you're in the cheap stocks everyone hates. So the

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Speaker 1: step one is screened for an expensive stock. Step two

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Speaker 1: is within those cheap stocks. So how do you identify

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Speaker 1: what's quality and what's not amongst the cheap So, given

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Speaker 1: we're in the in the cheap bin, which are security,

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Speaker 1: obviously there's something going on and that's why they're cheap.

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Speaker 1: We have a table like the we call it the

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Speaker 1: quality table. There's two legs to it. There's understanding the

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Speaker 1: fundamental quality of the business and there's another thing called

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Speaker 1: current financial strength. So in assessing economic mode, we try

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Speaker 1: to objectively ascertain is this company a good business? How

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Speaker 1: do we do that? We look at things like long

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Speaker 1: term geometric means on return on assets, return on capital.

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Speaker 1: We look at long term free cash flow generation, profit

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Speaker 1: margin dynamics, like if you have fifty percent margin year

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Speaker 1: and year out, that's probably good business and we want

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Speaker 1: to quantify the quality of this business to essentially generate

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Speaker 1: returns hopefully an excess of their cost of capital. But

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Speaker 1: that's not enough. That's leg one because we're dealing with

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Speaker 1: cheap stocks that have issues. So we can one ascertain

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Speaker 1: that there historically have some indication of being a good business.

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Speaker 1: But then current financial strength is now at ten point

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Speaker 1: checklist where we want to make sure are you going

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Speaker 1: to survive the next few years? I e. Are you

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Speaker 1: making money? Are you're paying down debt? Are your repurchasing stock?

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Speaker 1: Is your current ratio is improving? Uh, it's literally like

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Speaker 1: a pre flight checklist. So are you a quality business

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Speaker 1: organically and do you have the current financial stature to

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Speaker 1: live for the next few years? So eventually hopefully you

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Speaker 1: can get revalued up to not be a value stock

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Speaker 1: anymore and hopefully be a growth stock in the future.

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Speaker 1: So is it safe to say that companies with strong

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Speaker 1: balance sheets have stocks that outperform? Or is that overstating it?

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Speaker 1: I think it is. I think cheap stocks with strong

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Speaker 1: balance sheets on a risk adjusted basis and from a

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Speaker 1: you know, betting standpoint, or better than cheap stocks with

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Speaker 1: bad balance sheets independently. No, because there's a few reasons

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Speaker 1: why everyone knows Google is great, Facebook's great, Procter and

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Speaker 1: Gambles great, So what's the edge? And then secondly, it's

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Speaker 1: also easy to buy those names for someone to recommend them.

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Speaker 1: So it's emotionally. Emotionally or are you referring to the

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Speaker 1: principal agency issue the principal agent problem? And also just emotionally,

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Speaker 1: it's easy to own high quality securities. But when you

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Speaker 1: look at it objectively from like an evidence based standpoint,

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Speaker 1: just as an independent analysis to I, we think quality

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Speaker 1: is not that valuable and it doesn't make any sense

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Speaker 1: it would have edge were cheapness. Everyone hates these things.

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Speaker 1: They're hard to own, like it's crazy, They're hard to hold.

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Speaker 1: There's a lot of pain involved and unfortunately, you know,

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Speaker 1: just like in the Marine Corps, no pain, no gain.

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Speaker 1: You know that that BAC holds and financial markets unfortunately

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Speaker 1: as well. So let's talk about stocks that can cause

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Speaker 1: permanent loss of capital. There's a chapter in the book

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Speaker 1: where you discuss that how do you avoid these stocks?

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Speaker 1: What do you look for to avoid owning names that

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Speaker 1: are going to go down and never come up? The

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Speaker 1: classic value trap, the value trap. Yeah, you catch the

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Speaker 1: falling knife, as they called on the way down. So, uh,

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Speaker 1: three of them are basically there's there's two or three

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Speaker 1: ways you can think about permanent loss of capital, and

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Speaker 1: these are One would be like a fraud or manipulation.

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Speaker 1: So if it comes out that the business you thought

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Speaker 1: that was making a billion dollars a year is actually

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Speaker 1: making zero, that's gonna be a bad news for equity holders.

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Speaker 1: I would guess, Yeah, same thing with manipulation, like oh

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Speaker 1: we thought we had this, now we have this other thing.

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Speaker 1: And then the other one that's that's obviously is financial

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Speaker 1: distress or bankruptcy. You can own the best business in

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Speaker 1: the world, but if you're an equity holder and this

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Speaker 1: firm is in distress, the debt holders might end up

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Speaker 1: owning that great company, not you as the stockholders. So

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Speaker 1: so by the time that news comes out, it's too late.

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Speaker 1: What can investors do to avoid owning those names? What

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Speaker 1: signs should they be looking for? Sure? So, so we

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Speaker 1: do is we leverage a lot of uh, I guess

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Speaker 1: you call them technologies in academic literature where people have

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Speaker 1: built up statistical constructs to try to predict who's most

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Speaker 1: likely or red flagged as being a manipulator, fraud ster,

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Speaker 1: or potentially going to be in a financial distress situation,

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Speaker 1: and we just at the outset say hey, if you're

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Speaker 1: extreme red flagging on any of these sort of things,

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Speaker 1: you're not in our You're not even gonna be in

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Speaker 1: our potential. Just remo. We're removing, yeah, because we don't

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Speaker 1: want to buy your falling knife situation. I'm Barry Hults.

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Speaker 1: You're listening to Masters in Business on Bloomberg Radio. My

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Speaker 1: special guest today is Wes League Gray. He is a

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Speaker 1: retired captain in the U. S. Marine Corps, an m

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Speaker 1: b A and PhD out of the University of Chicago.

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Speaker 1: He now runs Alpha Architect, which is a unique quantitative

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Speaker 1: asset management firm. And the first book he wrote was

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Speaker 1: called Embedded, which is something that you pretty much pens

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Speaker 1: right after getting out of the Marine Corps and after

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Speaker 1: spending was it four years in Iraq? Is that about right?

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Speaker 1: It was four years in the service I did uh.

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Speaker 1: I was there for a standard Marine seven months deployment

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Speaker 1: in a place called Haditha which down el Ombar Province there.

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Speaker 1: So what motivated you to sit down and write a

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Speaker 1: book when you get back that had nothing to do

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Speaker 1: with finance. That was strictly about your time with the Marines.

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Speaker 1: When it was is you know, I remember before the

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Speaker 1: Iraq War, had Colin Pale show us that little white

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Speaker 1: you know bottle that you're all gonna die, and I

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Speaker 1: was like, you know, this is kind of maybe a

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Speaker 1: survive of a war. This is a pretty important thing.

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Speaker 1: I'm a buyer, I'm a believer. And then you know,

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Speaker 1: so when in a Marine Corps, not really for that reason.

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Speaker 1: I just want to do my service. But when I

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Speaker 1: was I thought, hey, this is a mission that makes sense.

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Speaker 1: You know, it's a win win for America and hopefully

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Speaker 1: for the Rockies what have you. But then after actually

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Speaker 1: living and being embedded with the people, I started to

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Speaker 1: realize that, you know, culture matters, and we're we're in

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Speaker 1: a in this war now, we're really taking on a

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Speaker 1: fifty two year commitment because we're gonna try to change

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Speaker 1: culture and not easy to do. Not easy to do.

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Speaker 1: And I would argue it's very, very time intensive and costly,

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Speaker 1: and that's fine as a decision, but let's weigh that

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Speaker 1: against the potential benefits um and that book just really

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Speaker 1: opened my eyes to understanding. I would say just Arab

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Speaker 1: culture in general, and how the way they think about

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Speaker 1: the world is just so much different than us. And

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Speaker 1: then the idea that we can impose, you know, our

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Speaker 1: ideas and how we think about the world on them,

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Speaker 1: it just doesn't work. And I have an analogy here.

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Speaker 1: It's like, you know, it's a fish trying to tell

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Speaker 1: me how to breed it underwater, Like I understand I

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Speaker 1: need gills and understand you need to get oxygen, but

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Speaker 1: it doesn't work for me. Like it's just we all

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Speaker 1: understand each other kind of, but we just it's not

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Speaker 1: gonna work. Um. And that that was the biggest insight

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Speaker 1: when I had to share it, because it changed my

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Speaker 1: mind about the whole thing one eighty about why are

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Speaker 1: we here? And is this really a positive MPV project

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Speaker 1: for us? So so you can't really just walk into

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Speaker 1: a country with a completely different set of mores and

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Speaker 1: cultures and say here's how you do it. That's not

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Speaker 1: gonna fly, no, no, yeah, yeah exactly. It seems obviously

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Speaker 1: trivial after the fact, but yeah, but beforehand, you know,

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Speaker 1: that's the classic hindsight bias. It's easy to say these things.

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Speaker 1: Acts in In early two thousand three, a handful of

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Speaker 1: people were warning about that. Everybody remembers the big Eric

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Speaker 1: san Seki, the Army general, warning about you're not gonna

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Speaker 1: do this with a hundred thousand troops. You need a

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Speaker 1: half a million troops. It's more than just hearts and minds.

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Speaker 1: It's really a long process. Nobody wants to hear that

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Speaker 1: before you go in. Yeah, the biggest insight I got action.

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Speaker 1: And also it's a lot of the things I cite

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Speaker 1: and embedded. It is just my conversations with the actual

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Speaker 1: Rocky people about why they thought we were so weird

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Speaker 1: and crazy and the things that we did say that

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Speaker 1: was that the readers, these Americans are crazy. Um. They

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Speaker 1: try to explain to me their perspective, and a perfect

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Speaker 1: one is okay. So you guys want to go bring

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Speaker 1: democracy and freedom to the Rocky people, and you've done that.

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Speaker 1: But here's the problem. When you let a country of

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Speaker 1: cage lions totally free out of their cage, you don't

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Speaker 1: give them freedom and Rocky to give them anarchy because

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Speaker 1: you guys in America have a lot of implicit structures,

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Speaker 1: either legal, culturally or trust. Like we're tribal here, guys

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Speaker 1: like like we don't have a lot of that kind

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Speaker 1: of ether in your culture there that it's in stitutionalized

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Speaker 1: here there exactly. In fact, you wrote, the tribe matters

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Speaker 1: much more than the state. There, you got it. So

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Speaker 1: so the idea that you can bring us freedom and

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Speaker 1: democracy and that's a great thing, and you're helping us, No,

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Speaker 1: you're giving us anarchy. And everyone has a house with

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Speaker 1: one ak in thirty round seven six to mag And

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Speaker 1: guess what if there's not enough police, if I don't

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Speaker 1: like my neighbor, I'm gonna go shoot him because that's freedom.

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Speaker 1: And you guys don't do that in America. You're not

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Speaker 1: really that free. You're still constrained by civil laws and

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Speaker 1: and all these other things. And the idea that when

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Speaker 1: you give us freedom, you somehow are gonna help us out, No,

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Speaker 1: you're you're you're destroying all law and order in anything

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Speaker 1: that resembled a society here. So so let's bring this

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Speaker 1: back to finance. So what did you learn from the

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Speaker 1: experience there that you were able to bring to the

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Speaker 1: world of finance. You know, I think it's a lot

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Speaker 1: of times like coming from a you know, PhD. University

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Speaker 1: of Chicago, everyone's rational. This is how the markets work,

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Speaker 1: and yeah, they're probably right, but that fails to consider humans.

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Speaker 1: And there's humans operate in the economy, not agents, rational agents.

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Speaker 1: So I think just like when when we go to

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Speaker 1: a situation like Irock on paper, Yeah, go bring him freedom, democracy,

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Speaker 1: and they will become like America and everyone will have

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Speaker 1: a you know, a pick, white picket fence and three kids.

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Speaker 1: But then you start realizing, wait a second, there's cultural

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Speaker 1: issues here. There's human elements. Same thing in finance. Yeah,

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Speaker 1: you should go buy cheap stocks and do it, Warren

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Speaker 1: Buffett does. Why doesn't everyone do that? Well, because there's

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Speaker 1: humans involving finance, and it's really really hard. It's really

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Speaker 1: really hard, and we always need to consider the behavioral

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Speaker 1: human element of decision making. I'm Barry rid Hilts. You're

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Speaker 1: listening to Master's in Business on Bloomberg Radio. My special

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Speaker 1: guest today is West Gray. He runs the quantitative asset

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Speaker 1: management firm Alpha Architect. Let's talk a little bit about

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Speaker 1: quants on Wall Street. So, first question, what do people

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Speaker 1: misunderstand about quants and their models in the world of finance. Sure,

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Speaker 1: so I probably can't speak on behalf of all quants

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Speaker 1: because like every walks of life. There's a lot of

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Speaker 1: varieties within that segment. In one corner when it when

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Speaker 1: you talk about a quant you think about the physics

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Speaker 1: PhD who's never read a finance book ever. He's data mining,

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Speaker 1: building crazy models and C plus plus and do whatever

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Speaker 1: they do. That that's not the type of quant analysis

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Speaker 1: that we bring to the table. We're we're essentially economists

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Speaker 1: that are trying to think about how the machine works,

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Speaker 1: and we just leverage quantitative analysis and tools that basically

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Speaker 1: allow us to conduct what we consider like scientific method

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Speaker 1: as best we can. So we have competing hypotheses about

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Speaker 1: how the world works. We grab data, we test these

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Speaker 1: competing hypotheses, and we're always trying to get better evidence

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Speaker 1: space investing. It's not just let's data mind, because we've

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Speaker 1: got better computers and more physics PhDs like we're we're

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Speaker 1: basically fundamental investors that use quantitative tools to help our

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Speaker 1: process and how we think about things in the world.

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Speaker 1: So from your perspective, then models are really never finished.

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Speaker 1: You're constantly testing them and seeing how can I make

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Speaker 1: this better? Where can it be improved, or what may

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Speaker 1: have changed in the market. That means that this model

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Speaker 1: is no longer delivering any sort of advantage or edge

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Speaker 1: that it might have been previously. Sure, there's an element

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Speaker 1: of that, and then but the other element is is

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Speaker 1: understanding that when you start going down the model creep situation,

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Speaker 1: it's it's like the old game where the kids, like

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Speaker 1: the little girl first says, hey, you know, the princess

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Speaker 1: kissed the fraud and by the end of the circle,

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Speaker 1: it's like, you know, Spider Man beat up he Man.

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Speaker 1: So it's a total different story. And it's all because

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Speaker 1: you have small little changes where you end up in

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Speaker 1: a total object place you wanted to end up in

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Speaker 1: the first place. So when when we build models, and

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Speaker 1: when we think about it, it's very very time and

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Speaker 1: ten set of an R and D intenses up front

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Speaker 1: to build the simplest, most robust model we can Simpilicity

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Speaker 1: beats complexity definitely, because we want to look for the

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Speaker 1: what is the real signal here, not the noise, and

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Speaker 1: let's just focus on that signal. And what we've found

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Speaker 1: is that in financial markets, frankly, nothing's changed. Human behavior

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Speaker 1: is pretty constant, and incentives, specifically like this principal agent

429
00:24:28,520 --> 00:24:32,720
Speaker 1: delegating asset management problem, those are two constants, and they

430
00:24:32,840 --> 00:24:35,240
Speaker 1: derive a lot of predictions about what works and what

431
00:24:35,359 --> 00:24:38,879
Speaker 1: doesn't work. And we keep coming back to the same themes.

432
00:24:39,200 --> 00:24:43,560
Speaker 1: Value by cheap stuff, momentum by relatively strong stuff, and

433
00:24:43,600 --> 00:24:47,600
Speaker 1: trend being good trends and everything we look at at

434
00:24:47,640 --> 00:24:51,080
Speaker 1: having memorized, like most of these databases at this point,

435
00:24:51,440 --> 00:24:56,840
Speaker 1: it's it's those three simple muscle limits usually drive all

436
00:24:56,920 --> 00:25:00,760
Speaker 1: other perturbation of anomaly or fact or whatever the heck.

437
00:25:00,760 --> 00:25:04,160
Speaker 1: Super looking, So, how do you have momentum and trends

438
00:25:04,920 --> 00:25:07,200
Speaker 1: as the same group, because normally when you're saying by

439
00:25:07,280 --> 00:25:11,960
Speaker 1: trends you're buying strong stuff going up, but value you're

440
00:25:12,000 --> 00:25:15,320
Speaker 1: buying weak stuff that everybody hates. Yeah, So so really

441
00:25:15,320 --> 00:25:18,480
Speaker 1: the way we look at value and momentum in particular,

442
00:25:19,000 --> 00:25:21,639
Speaker 1: is there really two sides of the same behavioral coins.

443
00:25:21,640 --> 00:25:25,120
Speaker 1: So if you look at value, one of the arguments

444
00:25:25,160 --> 00:25:28,280
Speaker 1: for why it outperforms is obviously it could be more risky,

445
00:25:28,280 --> 00:25:31,119
Speaker 1: and we can't discount that. That's surely one component. But

446
00:25:31,200 --> 00:25:33,919
Speaker 1: there is a mispricing component, we think, and that's what

447
00:25:34,040 --> 00:25:37,400
Speaker 1: is that an inefficiency? It is, but it's it's hard

448
00:25:37,440 --> 00:25:40,639
Speaker 1: to arbitrage, which we can discuss. But what values driven

449
00:25:40,680 --> 00:25:43,240
Speaker 1: by we think, and by we I mean, like the

450
00:25:43,280 --> 00:25:48,080
Speaker 1: academic research community, is an overreaction to bad news. Essentially,

451
00:25:48,080 --> 00:25:52,120
Speaker 1: they throw the baby out at the bathwater. On average momentum,

452
00:25:52,160 --> 00:25:54,879
Speaker 1: it turns out is there's two competing theories, Like we're

453
00:25:54,880 --> 00:25:58,080
Speaker 1: talking about relative strength momentum, which is the classic kind

454
00:25:58,080 --> 00:26:03,600
Speaker 1: of stock selection momentum academics discuss, and that the proponse

455
00:26:03,680 --> 00:26:07,200
Speaker 1: of the evidence is that it's an under reaction to

456
00:26:07,440 --> 00:26:12,439
Speaker 1: positive news, so values and overrea to bad news. The

457
00:26:12,680 --> 00:26:15,879
Speaker 1: evidence in general seems to suggest that momentum is more

458
00:26:15,880 --> 00:26:19,800
Speaker 1: of an underreaction to positive news that's being signaled in

459
00:26:19,960 --> 00:26:22,880
Speaker 1: the price. But because people are overconfident in their own

460
00:26:22,880 --> 00:26:26,480
Speaker 1: information set, even though the price keeps telling them yeah,

461
00:26:26,520 --> 00:26:29,000
Speaker 1: and there's disposition effects. You know, you're supposed to let

462
00:26:29,000 --> 00:26:30,879
Speaker 1: your winners ride and cut your newsers short. What do

463
00:26:30,960 --> 00:26:33,280
Speaker 1: people do the opposite? So there's a lot of kind

464
00:26:33,280 --> 00:26:36,720
Speaker 1: of organic, you know, fake supply that comes on the

465
00:26:36,760 --> 00:26:40,520
Speaker 1: market for high momentum stocks, and they're only because they're

466
00:26:40,520 --> 00:26:43,560
Speaker 1: a winner. People are hey, hit the bed. Nobody. I

467
00:26:43,720 --> 00:26:45,760
Speaker 1: when I started, I used to hear this all the time,

468
00:26:45,760 --> 00:26:48,320
Speaker 1: and it turns out to be terrible advice. Nobody ever

469
00:26:48,440 --> 00:26:50,919
Speaker 1: went broke taking a profit. Yeah, exactly, And that's the

470
00:26:50,960 --> 00:26:54,639
Speaker 1: worst just supply for for a momentum. Yeah, it just

471
00:26:54,680 --> 00:26:57,639
Speaker 1: puts supply into the market when maybe the fundamental should

472
00:26:57,640 --> 00:27:00,439
Speaker 1: be the stocks should be worth a hunted and starts

473
00:27:00,440 --> 00:27:02,359
Speaker 1: at eighty, but it can only go to ninety because

474
00:27:02,359 --> 00:27:04,439
Speaker 1: as it starts moving, and who wants to be the

475
00:27:04,520 --> 00:27:07,520
Speaker 1: last guy owning it on the highest peak? Fear of

476
00:27:07,520 --> 00:27:09,760
Speaker 1: looking stupid? Yeah, fair looking stupid. So I love the

477
00:27:09,800 --> 00:27:13,560
Speaker 1: symmetry of overreaction on the value side undreaction on the

478
00:27:13,560 --> 00:27:15,960
Speaker 1: momentum side. Let me throw a little bit of a

479
00:27:16,000 --> 00:27:19,320
Speaker 1: curve ball again. What I learned early in the career,

480
00:27:19,359 --> 00:27:21,399
Speaker 1: which may or may not be true, is hey, you

481
00:27:21,440 --> 00:27:24,399
Speaker 1: know managers, when you look at the big institutions, hedge funds,

482
00:27:24,480 --> 00:27:29,639
Speaker 1: mutual funds, endowments, they have their favorite names, and especially

483
00:27:29,680 --> 00:27:31,440
Speaker 1: if it's a fund that has a lot of four

484
00:27:31,640 --> 00:27:36,719
Speaker 1: one K or that sort of inflow, there's only so

485
00:27:36,720 --> 00:27:39,200
Speaker 1: many names they're gonna buy in. As fresh money comes

486
00:27:39,200 --> 00:27:41,720
Speaker 1: in over the transom every week, they put it to

487
00:27:41,800 --> 00:27:43,840
Speaker 1: work in the same names, and that's why you see

488
00:27:43,880 --> 00:27:48,199
Speaker 1: some form of of persistency of price action. Is that

489
00:27:48,280 --> 00:27:50,760
Speaker 1: a fair description of momentum or is that just a

490
00:27:50,840 --> 00:27:54,000
Speaker 1: narrative that I think that that's basically like the fund

491
00:27:54,080 --> 00:27:57,720
Speaker 1: flows arguments. And there's actually a new paper that I

492
00:27:58,200 --> 00:28:00,840
Speaker 1: can't remember. It's some new like germ of finance papers,

493
00:28:00,880 --> 00:28:04,280
Speaker 1: a theory paper this trying to explain the value and

494
00:28:04,359 --> 00:28:08,639
Speaker 1: momentum effect via fun flows. Were like one fund is

495
00:28:08,680 --> 00:28:11,639
Speaker 1: like losing because they own like the you know, the

496
00:28:11,720 --> 00:28:14,160
Speaker 1: value stocks, so they're getting out of there. Then other

497
00:28:14,240 --> 00:28:16,879
Speaker 1: funds they're they're winning, they own the winner stocks, and

498
00:28:16,880 --> 00:28:19,479
Speaker 1: then you know, because they're winning, they get more fun flows,

499
00:28:19,480 --> 00:28:22,359
Speaker 1: and then those keep moving and eventually, like the value

500
00:28:22,400 --> 00:28:25,600
Speaker 1: stocks get too cheap, they may in revert. Momentum stocks

501
00:28:25,640 --> 00:28:28,399
Speaker 1: unless you keep staying in the high momentum eventually crash

502
00:28:28,440 --> 00:28:31,119
Speaker 1: and burn. And there's all these theories about trying to

503
00:28:31,480 --> 00:28:35,760
Speaker 1: explain value momentum, not via behavioral like overreaction to bad

504
00:28:35,800 --> 00:28:38,400
Speaker 1: news unreaction to good news theory, but through like a

505
00:28:38,440 --> 00:28:41,640
Speaker 1: fun flows argument. There could be something to it. I think,

506
00:28:41,680 --> 00:28:45,000
Speaker 1: I think all no one really knows exactly how and

507
00:28:45,040 --> 00:28:47,840
Speaker 1: while this works, but it's all about what is the

508
00:28:47,880 --> 00:28:51,520
Speaker 1: proponance of the evidence kind of tilt you towards because

509
00:28:51,720 --> 00:28:54,840
Speaker 1: God only knows what really explains value, So you really

510
00:28:54,840 --> 00:28:56,680
Speaker 1: don't need to know why it works. You just need

511
00:28:56,760 --> 00:28:58,840
Speaker 1: to know this works. This doesn't stay with what works

512
00:28:58,840 --> 00:29:01,680
Speaker 1: avoid what doesn't to some extent. And you know, as

513
00:29:01,760 --> 00:29:03,880
Speaker 1: this has a great quote about like we all knew

514
00:29:04,160 --> 00:29:07,000
Speaker 1: the world was flat before, or it wasn't flat before

515
00:29:07,040 --> 00:29:10,600
Speaker 1: we could explain exactly, you know, why it was. Some

516
00:29:10,640 --> 00:29:13,880
Speaker 1: of us still held out, Yeah, exactly, and value something.

517
00:29:13,880 --> 00:29:16,320
Speaker 1: I think that's way more understood because it's more intuitive.

518
00:29:16,680 --> 00:29:20,800
Speaker 1: Um by cheap stuff everyone hates, you get kind of distress. Premium,

519
00:29:20,840 --> 00:29:24,360
Speaker 1: you know, careers, premium were momentum. You know this. We

520
00:29:24,400 --> 00:29:26,720
Speaker 1: just wrote a whole book dedicated trying to understand this.

521
00:29:27,080 --> 00:29:29,840
Speaker 1: You know, there seems to be this underaction to the

522
00:29:29,920 --> 00:29:33,240
Speaker 1: good news. But there's another thing when I started reading about,

523
00:29:33,280 --> 00:29:37,280
Speaker 1: like what Soros talks about with with reflexivity, at some level,

524
00:29:37,480 --> 00:29:42,000
Speaker 1: price action itself can actually influence fundamentals. And here would

525
00:29:42,000 --> 00:29:44,200
Speaker 1: be an example. Let's say we're out in the valley,

526
00:29:44,200 --> 00:29:47,880
Speaker 1: like Silicon Valley. We have Google, who's got great price

527
00:29:47,920 --> 00:29:50,840
Speaker 1: action linked in who just dropped the hunter you know

528
00:29:50,960 --> 00:29:54,200
Speaker 1: fifty until recently here, But so what do you think

529
00:29:54,240 --> 00:29:57,040
Speaker 1: when most of your comp and it's all human capital.

530
00:29:57,080 --> 00:30:03,000
Speaker 1: Business is tied to your stock price Linkedins, so their

531
00:30:03,160 --> 00:30:08,400
Speaker 1: price movement momentum fundamentally is changing their fundamentals. And if

532
00:30:08,640 --> 00:30:12,800
Speaker 1: marketplace can't anticipate kind of the second derivative or nonlinear change,

533
00:30:13,200 --> 00:30:17,200
Speaker 1: they'll always kind of underappreciate the benefit of good prices

534
00:30:17,200 --> 00:30:19,560
Speaker 1: because you also get lower cost of capital on the street.

535
00:30:19,760 --> 00:30:22,560
Speaker 1: If I'm a high flying stock, every banker in the

536
00:30:22,600 --> 00:30:24,360
Speaker 1: world is going to help me go sell that over

537
00:30:24,400 --> 00:30:27,239
Speaker 1: priced stock to fund acquisitions and what have you. If

538
00:30:27,280 --> 00:30:30,040
Speaker 1: I'm a total Loserville stock, you know, I gotta pay

539
00:30:30,080 --> 00:30:32,920
Speaker 1: cash like LinkedIn yeah now, and now I gotta like

540
00:30:32,960 --> 00:30:35,600
Speaker 1: pay real market cost of capital. And you're at a

541
00:30:35,600 --> 00:30:38,640
Speaker 1: competitive disadvantage compared to this company that can you know,

542
00:30:39,040 --> 00:30:43,040
Speaker 1: check out overvalued stock to do acquisition until Microsoft comes

543
00:30:43,040 --> 00:30:45,680
Speaker 1: along advise you at a nice fat premium. So there's

544
00:30:45,840 --> 00:30:49,960
Speaker 1: there's momentums complex. You mentioned momentum and you mentioned Cliff Assness.

545
00:30:50,920 --> 00:30:54,840
Speaker 1: Am I correct in saying both you and Cliff had

546
00:30:54,920 --> 00:31:00,400
Speaker 1: Eugene Fama as your thesis h advisors at Chicago? Is

547
00:31:00,440 --> 00:31:03,680
Speaker 1: that right? We have more similar than that, even he

548
00:31:03,760 --> 00:31:07,640
Speaker 1: was also a working undergrad. So unfortunately both of your

549
00:31:08,000 --> 00:31:12,040
Speaker 1: your dissertations were on momentum to the guy who essentially

550
00:31:12,160 --> 00:31:15,840
Speaker 1: invented the efficient market hypothesis. That's right. So so we

551
00:31:16,040 --> 00:31:19,280
Speaker 1: apparently like a lot of pain and english and fighting

552
00:31:19,360 --> 00:31:22,280
Speaker 1: uphill when we probably don't have to. Maybe that's a

553
00:31:22,320 --> 00:31:26,120
Speaker 1: shared characteristics of Cliff and I is what it seems.

554
00:31:26,680 --> 00:31:28,280
Speaker 1: You guys have put out a few e t F

555
00:31:28,440 --> 00:31:30,440
Speaker 1: You've worked and advised on other e t f s.

556
00:31:30,800 --> 00:31:35,680
Speaker 1: How has the exchange traded fund shift changed the game

557
00:31:35,720 --> 00:31:39,040
Speaker 1: in terms of cost and execution? I think it's it's

558
00:31:39,120 --> 00:31:44,640
Speaker 1: revolutionized access to retail I would say more typical investors.

559
00:31:44,640 --> 00:31:47,440
Speaker 1: In the old days, you could always get clean, process

560
00:31:47,520 --> 00:31:51,440
Speaker 1: driven factor exposures as institutional investor, but you never could

561
00:31:51,440 --> 00:31:54,480
Speaker 1: do it as a retail investor with tax efficiency and

562
00:31:54,560 --> 00:31:57,600
Speaker 1: reasonable fees. And now the world is your oyster. You

563
00:31:57,600 --> 00:32:01,200
Speaker 1: can go on your you know, Schwab account by you

564
00:32:01,240 --> 00:32:04,719
Speaker 1: know a really great factor exposure for low costs with

565
00:32:04,760 --> 00:32:09,600
Speaker 1: tax efficiency and full transparency. And I think that's revolutionizing

566
00:32:09,640 --> 00:32:12,200
Speaker 1: the asset manager business as we speak. So, if people

567
00:32:12,240 --> 00:32:16,040
Speaker 1: want to read more about your writings and your research,

568
00:32:16,040 --> 00:32:18,320
Speaker 1: where's the best place for them to find you? Best

569
00:32:18,320 --> 00:32:21,440
Speaker 1: places just go to ALF architect dot com and sign

570
00:32:21,480 --> 00:32:24,720
Speaker 1: up for the blog, and that's that's how we communicate

571
00:32:24,760 --> 00:32:28,640
Speaker 1: to our audience. We have been speaking with Captain Wesley Gray,

572
00:32:28,760 --> 00:32:33,360
Speaker 1: formerly of the U. S. Marine Corps, now with Alpha Architect.

573
00:32:33,680 --> 00:32:36,360
Speaker 1: If you've enjoyed this conversation, be sure and hang out

574
00:32:36,400 --> 00:32:39,160
Speaker 1: for our podcast where we keep the tape rolling and

575
00:32:39,200 --> 00:32:43,640
Speaker 1: continue chatting about all things quantitative. Be sure and follow

576
00:32:43,720 --> 00:32:47,440
Speaker 1: my daily column on Bloomberg dot com or follow me

577
00:32:47,520 --> 00:32:51,400
Speaker 1: on Twitter at rit Halts. I'm Barry rit Halts. You're

578
00:32:51,480 --> 00:32:59,520
Speaker 1: listening to Masters in Business on Bloomberg Radio. Are you

579
00:32:59,600 --> 00:33:02,640
Speaker 1: looking to take your business to the next level? The accounting,

580
00:33:02,680 --> 00:33:06,120
Speaker 1: tax and advisory professionals from Cone Resnick can guide you.

581
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Speaker 1: Cone Resnick delivers industry expertise and forward thinking perspective that

582
00:33:11,240 --> 00:33:16,280
Speaker 1: can help turn business possibilities into business opportunities. Look ahead,

583
00:33:16,680 --> 00:33:20,800
Speaker 1: gain insight, imagine more. Is your business ready to break through?

584
00:33:21,280 --> 00:33:25,280
Speaker 1: Learn more at Cone Resnick dot com Slash Breakthrough, Cone

585
00:33:25,280 --> 00:33:30,200
Speaker 1: Resnick Accounting, Tax Advisory. West, thanks so much for being

586
00:33:30,240 --> 00:33:33,880
Speaker 1: so generous with your time. UM, so there's so much

587
00:33:33,880 --> 00:33:38,560
Speaker 1: stuff to go over. We blew through so many questions. UM,

588
00:33:38,600 --> 00:33:43,160
Speaker 1: but I really enjoy you, know West, I know West

589
00:33:43,240 --> 00:33:45,960
Speaker 1: for a good couple of years. I've followed Alpha Architect

590
00:33:46,480 --> 00:33:50,760
Speaker 1: for a while and everybody in my shop loves reading

591
00:33:50,840 --> 00:33:55,040
Speaker 1: his work. Uh. He is another one of the collection

592
00:33:55,080 --> 00:33:58,800
Speaker 1: of people who are really and I think you made

593
00:33:58,840 --> 00:34:03,360
Speaker 1: this clear during the the radio portion. He is evidence

594
00:34:03,440 --> 00:34:08,160
Speaker 1: based and data driven. So much of of finance is

595
00:34:08,239 --> 00:34:13,160
Speaker 1: filled with myths and heuristics and and shorthand rules of

596
00:34:13,239 --> 00:34:16,279
Speaker 1: thumb that turned out not to be true. Looking at

597
00:34:16,280 --> 00:34:21,680
Speaker 1: the actual data um really makes a really makes a

598
00:34:21,719 --> 00:34:25,200
Speaker 1: big difference. So let's let's go over a few questions

599
00:34:25,239 --> 00:34:28,840
Speaker 1: we we didn't get to, including a quote of yours

600
00:34:28,840 --> 00:34:31,320
Speaker 1: that I that I really like. And I don't remember

601
00:34:31,320 --> 00:34:36,759
Speaker 1: which book this was, but you said sustainable Alpha requires

602
00:34:36,840 --> 00:34:42,880
Speaker 1: sustainable clients. What does that mean? Sure? So I've always

603
00:34:42,920 --> 00:34:46,320
Speaker 1: been puzzled with this question of we find this factor

604
00:34:46,920 --> 00:34:50,959
Speaker 1: it generates the access for terms. Why is this there?

605
00:34:51,080 --> 00:34:54,400
Speaker 1: And why will it continue because you know? Sorry? And

606
00:34:54,719 --> 00:34:59,360
Speaker 1: why why hasn't everybody found this and stayed with it

607
00:34:59,400 --> 00:35:02,879
Speaker 1: if it's generally exactly and you have open secrets called

608
00:35:02,960 --> 00:35:06,040
Speaker 1: value momentum value as the strategy has been around for

609
00:35:06,080 --> 00:35:09,680
Speaker 1: a hundred years. Momentum was talked about like also two

610
00:35:09,800 --> 00:35:12,400
Speaker 1: hundred years ago, so it's not like these are secrets,

611
00:35:12,480 --> 00:35:15,960
Speaker 1: and yet they continue to work. So I needed to

612
00:35:16,040 --> 00:35:20,200
Speaker 1: intellectualize how is this possible? And what I started thinking

613
00:35:20,200 --> 00:35:23,080
Speaker 1: about is is I started thinking about behavioral finance and

614
00:35:23,360 --> 00:35:26,279
Speaker 1: the two real building blocks of it, which are one

615
00:35:26,520 --> 00:35:32,920
Speaker 1: understanding human behavior and to understanding institutional incentives to arbitrage

616
00:35:33,200 --> 00:35:39,080
Speaker 1: bad behavior. So most factors exist typically because there's some

617
00:35:39,160 --> 00:35:43,160
Speaker 1: sort of expectation are on behalf of investors that creates

618
00:35:43,239 --> 00:35:46,719
Speaker 1: a dislocation from fundamental prices, so that that would be

619
00:35:46,760 --> 00:35:51,040
Speaker 1: either the something like that, because you've got to have

620
00:35:51,440 --> 00:35:55,239
Speaker 1: someone can't be a perfectly rational buyer and seller, because

621
00:35:55,239 --> 00:35:57,920
Speaker 1: then prices would never deviate from their fundamental value in

622
00:35:57,960 --> 00:36:02,240
Speaker 1: efficient market, ipocess would hold. But clearly there's overwhelming evidence

623
00:36:02,280 --> 00:36:06,280
Speaker 1: that that happens. But the question is wise does it sustain?

624
00:36:06,840 --> 00:36:08,440
Speaker 1: And so that's where we got to look at the

625
00:36:08,440 --> 00:36:12,200
Speaker 1: incentives of those who manage the capital and for easy

626
00:36:12,320 --> 00:36:14,680
Speaker 1: things that are easy to arbitrage, Like if we see

627
00:36:14,680 --> 00:36:17,960
Speaker 1: a twenty dollar bill on this table, well let's grab it.

628
00:36:18,239 --> 00:36:20,480
Speaker 1: What if we see a twenty dollar bill on the table,

629
00:36:20,520 --> 00:36:23,799
Speaker 1: but there's a grizzly bear over it, Like is that

630
00:36:24,000 --> 00:36:27,040
Speaker 1: rational that a twenty dollar bills there no, but the

631
00:36:27,120 --> 00:36:29,720
Speaker 1: problem is to pick up this twenty it's a grizzly

632
00:36:29,760 --> 00:36:34,600
Speaker 1: bear there. So sometimes it's it's not frictionless to arbitrage prices,

633
00:36:34,640 --> 00:36:37,840
Speaker 1: which is a cordline assumption of the Fisher market, I passes,

634
00:36:38,239 --> 00:36:42,200
Speaker 1: is that competition will always drive prices to fundamental because

635
00:36:42,200 --> 00:36:46,560
Speaker 1: it's assumed it's easy to arbitrage. But that is totally

636
00:36:46,600 --> 00:36:50,400
Speaker 1: not true. And I would say the biggest issue with

637
00:36:50,640 --> 00:36:54,640
Speaker 1: quote unquote arbitrage on things like value or momentum is

638
00:36:54,760 --> 00:36:58,800
Speaker 1: career risk because to do those strategies, they're really long

639
00:36:59,000 --> 00:37:02,960
Speaker 1: duration kind of expected winners, but in the short one

640
00:37:03,360 --> 00:37:08,080
Speaker 1: they can get destroyed relative to standard benchmarks. We were

641
00:37:08,160 --> 00:37:12,440
Speaker 1: discussing the pain trade. The pain trade exactly and pain

642
00:37:12,520 --> 00:37:17,000
Speaker 1: trades ironically are the exact trades you want to own

643
00:37:17,120 --> 00:37:19,960
Speaker 1: if you want to have a sustainable out of sample

644
00:37:20,440 --> 00:37:23,440
Speaker 1: chance at outperformance, because now there's you want to have

645
00:37:23,480 --> 00:37:26,680
Speaker 1: a credible reason why other people on the side of

646
00:37:26,680 --> 00:37:29,799
Speaker 1: this trade or not make a good decision over overreaction,

647
00:37:29,880 --> 00:37:32,359
Speaker 1: bad news, unreaction, good news, or what have you. Then,

648
00:37:32,400 --> 00:37:34,520
Speaker 1: on the other hand, we understand, well, what are the

649
00:37:34,560 --> 00:37:37,479
Speaker 1: other competitive players in the market doing and why aren't

650
00:37:37,520 --> 00:37:39,520
Speaker 1: they already doing this? And it's usually because they like

651
00:37:39,640 --> 00:37:42,680
Speaker 1: their jobs a lot more than they like actually take

652
00:37:42,760 --> 00:37:47,120
Speaker 1: advantage of anomalies. That that's the famous Kings quote. Better

653
00:37:47,200 --> 00:37:50,879
Speaker 1: to fail conventionally than succeed un convention exactly. And there's

654
00:37:50,960 --> 00:37:53,560
Speaker 1: tons of research about this. It all boils down what

655
00:37:53,600 --> 00:37:56,920
Speaker 1: they call the principal agent conflict. There's there's a classic

656
00:37:56,960 --> 00:38:00,120
Speaker 1: theory paper um under Cipher and rob Vision and in

657
00:38:00,239 --> 00:38:03,200
Speaker 1: general Finance ninety seven is called limits of arbitrage, and

658
00:38:03,239 --> 00:38:06,360
Speaker 1: they make this very simple point. We all know what works.

659
00:38:06,880 --> 00:38:10,040
Speaker 1: The problem is in the short run, it may not work,

660
00:38:10,320 --> 00:38:14,160
Speaker 1: especially relative to other stuff. And to the extent that

661
00:38:14,239 --> 00:38:18,440
Speaker 1: I can't credibly convince my investors that I'm not an idiot,

662
00:38:18,480 --> 00:38:20,960
Speaker 1: even though I just lost twenty points to the index

663
00:38:21,320 --> 00:38:24,000
Speaker 1: and they pull my capital, I'm actually not in a

664
00:38:24,080 --> 00:38:26,480
Speaker 1: position to take advantage of this, so I kind of

665
00:38:26,520 --> 00:38:30,440
Speaker 1: hold back. So the only way to really exploit true

666
00:38:30,719 --> 00:38:34,239
Speaker 1: active anomalies is you need to one have a process

667
00:38:34,360 --> 00:38:37,799
Speaker 1: that takes advantage of some bias problem. But then more

668
00:38:37,840 --> 00:38:41,759
Speaker 1: importantly is you need to couple the capital that's there

669
00:38:41,760 --> 00:38:45,000
Speaker 1: to exploit and make sure it has the same duration

670
00:38:45,160 --> 00:38:48,400
Speaker 1: as the anomaly it's trying to exploit, which is long term,

671
00:38:48,440 --> 00:38:51,040
Speaker 1: so long term duration on the capital, long time duration

672
00:38:51,080 --> 00:38:54,799
Speaker 1: on the anomaly, short term human behavior getting in the

673
00:38:54,800 --> 00:38:58,960
Speaker 1: way exactly. And its analogy is like the bank that

674
00:38:58,960 --> 00:39:02,880
Speaker 1: that we discussed earlier, where a bank lands long borrows

675
00:39:02,920 --> 00:39:06,160
Speaker 1: short great most of the time, but sometimes you have

676
00:39:06,200 --> 00:39:09,120
Speaker 1: a run on the bank. Same thing with value strategies,

677
00:39:09,520 --> 00:39:13,560
Speaker 1: long duration opportunity that more often than not gets coupled

678
00:39:13,560 --> 00:39:17,000
Speaker 1: with short duration capital. Sometimes there's a run on the bank.

679
00:39:17,120 --> 00:39:20,000
Speaker 1: And when that run on the bank occurs, the winner

680
00:39:20,040 --> 00:39:22,600
Speaker 1: in that trade ends up being the Warren buffets, the

681
00:39:22,600 --> 00:39:26,200
Speaker 1: guys that just hold onto these things like grim death

682
00:39:26,719 --> 00:39:29,520
Speaker 1: and will not sell. I have a friend who runs

683
00:39:29,600 --> 00:39:34,480
Speaker 1: a value hedge funds, if there's such a thing, and

684
00:39:34,560 --> 00:39:38,760
Speaker 1: he says he'll go through the pain trade for quarters

685
00:39:38,760 --> 00:39:41,200
Speaker 1: and years at a time, and he said he's been

686
00:39:41,239 --> 00:39:45,080
Speaker 1: doing it for forty years. He knows when the portfolio

687
00:39:45,160 --> 00:39:48,320
Speaker 1: is going to start out performing because usually just before

688
00:39:48,440 --> 00:39:51,640
Speaker 1: he starts getting all sorts of inquiries about redemption and

689
00:39:51,680 --> 00:39:54,800
Speaker 1: people have had enough, and it's usually at that moment

690
00:39:54,840 --> 00:39:58,160
Speaker 1: when when the wheel is turning definitely, we we we

691
00:39:58,320 --> 00:40:03,480
Speaker 1: know multiple multibillion dollar hedge for manasures with heavy value

692
00:40:03,520 --> 00:40:06,560
Speaker 1: focus that are literally out of business because of the

693
00:40:06,600 --> 00:40:09,680
Speaker 1: back half of two thousand fifteen because deep value just

694
00:40:09,920 --> 00:40:15,120
Speaker 1: got destroyed and redemptions just overwhelmed their ability to convince

695
00:40:15,120 --> 00:40:19,160
Speaker 1: the capital stage. So so let's talk about career risk,

696
00:40:19,280 --> 00:40:23,080
Speaker 1: and let's talk about running money in real time. You

697
00:40:23,160 --> 00:40:26,520
Speaker 1: run a model, you run multiple models, multiple ETFs, but

698
00:40:26,640 --> 00:40:30,399
Speaker 1: you run a model that essentially is two sleeves. One

699
00:40:30,520 --> 00:40:34,680
Speaker 1: is value and the other is is the momentum side.

700
00:40:35,320 --> 00:40:39,600
Speaker 1: And invariably one of those two sleeves. And by the way,

701
00:40:39,640 --> 00:40:41,399
Speaker 1: I've explained this to people and the like, so wait,

702
00:40:41,440 --> 00:40:44,480
Speaker 1: they first they screened for value and then they screen

703
00:40:44,560 --> 00:40:48,160
Speaker 1: for momentum. No, these are a dual model where there

704
00:40:48,200 --> 00:40:53,960
Speaker 1: is simultaneously offsetting value and momentum. Uh, two different screens

705
00:40:53,960 --> 00:40:58,759
Speaker 1: and two different pools of stocks. But invariably one of

706
00:40:58,800 --> 00:41:01,719
Speaker 1: those sleeves is getting She'll act usually when one is

707
00:41:01,760 --> 00:41:05,480
Speaker 1: doing well, the other is doing poorly. Number one, how

708
00:41:05,520 --> 00:41:08,680
Speaker 1: does that make money over the long haul? And Number two?

709
00:41:09,400 --> 00:41:12,440
Speaker 1: What happens in the real world with all but the

710
00:41:12,480 --> 00:41:15,680
Speaker 1: most savvy institutions or individuals who may have money in

711
00:41:15,719 --> 00:41:19,640
Speaker 1: a portfolio like that. Sure, So so the way um

712
00:41:19,800 --> 00:41:23,200
Speaker 1: that value momentum work in a combination, whereas you mentioned,

713
00:41:23,239 --> 00:41:27,800
Speaker 1: it's not about an integrated package. It's about pure value

714
00:41:28,040 --> 00:41:32,080
Speaker 1: focusing on that religion, and then pure momentum focused on

715
00:41:32,080 --> 00:41:35,480
Speaker 1: that religion, combining the two and they happen to have

716
00:41:35,640 --> 00:41:39,839
Speaker 1: this very great dynamic relationship where they're like Yin and yang.

717
00:41:39,840 --> 00:41:42,440
Speaker 1: When one is blown up, the other one on average

718
00:41:42,480 --> 00:41:45,560
Speaker 1: tends to be working. So you get amazing diversification benefits.

719
00:41:45,840 --> 00:41:48,520
Speaker 1: Whereas if you look at either of those strategies as

720
00:41:48,520 --> 00:41:51,279
Speaker 1: a standalone basis, you know you're gonna want to jump

721
00:41:51,320 --> 00:41:55,160
Speaker 1: off a bridge it's too volatile. But that combination basically

722
00:41:55,200 --> 00:41:59,040
Speaker 1: gives you more survivability. From like a human psychology standpoint,

723
00:41:59,440 --> 00:42:02,840
Speaker 1: pure value, how you im pure momentum combined ran in

724
00:42:02,880 --> 00:42:06,400
Speaker 1: a very active way, can still have opportunities to have

725
00:42:06,719 --> 00:42:10,919
Speaker 1: multi year underperformance, but it's more sustainable than just being

726
00:42:10,920 --> 00:42:13,719
Speaker 1: a pure value person or a pure momentum person where

727
00:42:14,080 --> 00:42:18,280
Speaker 1: you could go for five ten years in theory of underperforming,

728
00:42:18,400 --> 00:42:21,880
Speaker 1: and who can do that? Even I would have problems,

729
00:42:22,320 --> 00:42:24,880
Speaker 1: you know, sticking to the model probably and I'm like

730
00:42:25,040 --> 00:42:27,560
Speaker 1: a cold believer in this stuff. So so what do

731
00:42:27,600 --> 00:42:29,600
Speaker 1: you say to somebody who says, hey, I'm in this

732
00:42:29,680 --> 00:42:34,239
Speaker 1: portfolio for three years. I understand it intellectually, but you're

733
00:42:34,320 --> 00:42:37,800
Speaker 1: under performing the benchmarked by forty basis points for three years.

734
00:42:38,800 --> 00:42:41,960
Speaker 1: How do you communicate, Well, that's part of the model

735
00:42:42,040 --> 00:42:45,600
Speaker 1: that's not unexpected, and soon it will be out performing

736
00:42:45,760 --> 00:42:48,600
Speaker 1: and by a substantial by file undred basis points. How

737
00:42:48,640 --> 00:42:51,600
Speaker 1: do you communicate that? So, the way we communicated is

738
00:42:51,680 --> 00:42:54,040
Speaker 1: this is not for everyone, it's for we have a

739
00:42:54,160 --> 00:42:57,360
Speaker 1: very segmented component of the marketplace where we need to

740
00:42:57,440 --> 00:43:02,359
Speaker 1: identify long duration cap roll that's really sophisticated and has

741
00:43:02,480 --> 00:43:08,160
Speaker 1: minimal agency conflicts where their career doesn't really amiable consultants,

742
00:43:08,440 --> 00:43:11,680
Speaker 1: No consultants, no, it's it literally who wants to take

743
00:43:11,719 --> 00:43:14,359
Speaker 1: care of their money best, the guy who owns their

744
00:43:14,360 --> 00:43:17,520
Speaker 1: own money because they actually have horizon, they don't have careers,

745
00:43:17,640 --> 00:43:20,879
Speaker 1: not gonna fire themselves, and they just want to maximize

746
00:43:20,880 --> 00:43:24,480
Speaker 1: their best chance of long term expected compounding. That is

747
00:43:24,520 --> 00:43:28,560
Speaker 1: the segment that we talked to. That's a really specific,

748
00:43:28,760 --> 00:43:33,000
Speaker 1: very specific niche, and the reason we're so hyper focus

749
00:43:33,080 --> 00:43:36,400
Speaker 1: on that niche is going back to that sustainable, active

750
00:43:36,400 --> 00:43:39,960
Speaker 1: framework where you need a couple long duration arbitrage with

751
00:43:40,080 --> 00:43:43,239
Speaker 1: long duration capital in order for it to be a victory.

752
00:43:43,760 --> 00:43:47,319
Speaker 1: You that's the only way you can believably exploit these

753
00:43:47,360 --> 00:43:51,640
Speaker 1: anomalies is the capital. The source of capital, and the

754
00:43:51,840 --> 00:43:54,360
Speaker 1: education of that capital and its ability to stick to

755
00:43:54,360 --> 00:43:59,080
Speaker 1: the program is more important than the nuance of your model. Yeah, Like,

756
00:43:59,280 --> 00:44:02,560
Speaker 1: we can do a billion perturbations of buy cheap, they're

757
00:44:02,600 --> 00:44:05,400
Speaker 1: all gonna be nine correlated. Do we think ours is

758
00:44:05,440 --> 00:44:08,600
Speaker 1: marginally better than Joe blows down the street. Sure, but

759
00:44:09,239 --> 00:44:11,000
Speaker 1: you know if you stuck a gun to my head

760
00:44:11,160 --> 00:44:13,400
Speaker 1: and said which value molo do you want, I'd be like,

761
00:44:13,480 --> 00:44:16,080
Speaker 1: they're all good. That's not the hard part. The hard

762
00:44:16,120 --> 00:44:19,239
Speaker 1: part is making sure the money that's in it is

763
00:44:19,520 --> 00:44:23,239
Speaker 1: able to actually exploit it the duration of that. Yeah,

764
00:44:23,440 --> 00:44:25,880
Speaker 1: and so we that's why we have this saying, like

765
00:44:25,960 --> 00:44:29,160
Speaker 1: most products on the street, they're they're sold, not bought.

766
00:44:29,840 --> 00:44:32,520
Speaker 1: For our strategies, we say no, no, we have to

767
00:44:32,560 --> 00:44:36,040
Speaker 1: have our products be bought, not sold, because it's more

768
00:44:36,040 --> 00:44:41,160
Speaker 1: important that our clients and investors understand explicitly, maybe even

769
00:44:41,200 --> 00:44:44,160
Speaker 1: more than we even understand it, how and why this works.

770
00:44:44,480 --> 00:44:47,080
Speaker 1: Because it's not it's not about us being smarter than

771
00:44:47,080 --> 00:44:50,160
Speaker 1: the next guy. There's already hundred peach d guys around here.

772
00:44:50,440 --> 00:44:52,160
Speaker 1: They got higher i q s and I could ever

773
00:44:52,280 --> 00:44:55,520
Speaker 1: dream of. That's not our edge, our edges getting the

774
00:44:55,640 --> 00:45:00,520
Speaker 1: capital matched with a reasonable process that's good enough for

775
00:45:00,560 --> 00:45:05,319
Speaker 1: our you know, not brains, that's gonna be. That's the

776
00:45:05,320 --> 00:45:08,799
Speaker 1: buffet trade basically. So let's talk about your dissertation with

777
00:45:08,840 --> 00:45:12,399
Speaker 1: Eugene Fama. We we mentioned that he was your your advisor.

778
00:45:12,760 --> 00:45:15,600
Speaker 1: What's it like pitching momentum to the father of the

779
00:45:15,600 --> 00:45:19,239
Speaker 1: efficient market hypothesis? So Cliff did value and momentum to

780
00:45:19,360 --> 00:45:24,080
Speaker 1: the vastness. I actually pitched him on value exclusive. I

781
00:45:24,120 --> 00:45:27,000
Speaker 1: wasn't going to touch the momentum, pain trade and a

782
00:45:27,080 --> 00:45:31,560
Speaker 1: dissertation because I wasn't that a wild as Cliff was. Um.

783
00:45:31,600 --> 00:45:33,520
Speaker 1: But what I did is, you know, I don't I

784
00:45:33,560 --> 00:45:37,360
Speaker 1: has always been a stock picker. Reading Ben Graham, warm

785
00:45:37,480 --> 00:45:39,839
Speaker 1: off its stuffed, I was blue in the face. I

786
00:45:39,920 --> 00:45:43,320
Speaker 1: believed that that was the way of the world. Um.

787
00:45:43,360 --> 00:45:45,240
Speaker 1: And so obviously, you know, you have the most famous

788
00:45:45,280 --> 00:45:47,520
Speaker 1: guy in the world that says no, that's never gonna work.

789
00:45:48,120 --> 00:45:50,319
Speaker 1: Screw this guy. I'm gonna figure out how to like,

790
00:45:50,680 --> 00:45:53,040
Speaker 1: you know, let's see if we can an outsmart this guy.

791
00:45:53,080 --> 00:45:55,080
Speaker 1: So what I did is, um, I'm sure if we

792
00:45:55,080 --> 00:45:59,960
Speaker 1: were like Joe Greenblatt, a little little book, little yeah,

793
00:46:00,040 --> 00:46:03,040
Speaker 1: great book, great ideas. He has this organization called Value

794
00:46:03,040 --> 00:46:05,920
Speaker 1: Messrs Club UM, which is ah, it's basically like an

795
00:46:05,920 --> 00:46:08,960
Speaker 1: invite only group of all these hedge fund managers and

796
00:46:09,000 --> 00:46:12,520
Speaker 1: really smart kind of fundamental stock pickers UM. And you've

797
00:46:12,520 --> 00:46:14,279
Speaker 1: been doing it since two thousand. I was like, hey,

798
00:46:14,320 --> 00:46:17,160
Speaker 1: this is a really great data source where there's all

799
00:46:17,160 --> 00:46:20,200
Speaker 1: these like full scale stock pitches from the by side.

800
00:46:20,560 --> 00:46:23,160
Speaker 1: Let's look at how it's done over time's let me

801
00:46:23,200 --> 00:46:27,360
Speaker 1: guess they stunt the joint on. Well no, actually interesting enough.

802
00:46:27,520 --> 00:46:31,839
Speaker 1: Well it's kinda but in an indirect way. So when

803
00:46:31,840 --> 00:46:35,640
Speaker 1: you actually look at the performance of as a whole,

804
00:46:35,800 --> 00:46:38,760
Speaker 1: they're actually pretty good. Like these people had real value.

805
00:46:38,960 --> 00:46:41,480
Speaker 1: It's unclear that if you paid in their funds after

806
00:46:41,560 --> 00:46:46,319
Speaker 1: the but there's certainly evidence that these guys have some

807
00:46:46,440 --> 00:46:49,759
Speaker 1: skill and an especially when you get that segmented down

808
00:46:49,760 --> 00:46:54,640
Speaker 1: to like the small value, there's no doubt these this

809
00:46:54,719 --> 00:46:57,600
Speaker 1: group has a ton of skill. There's a shortage of information,

810
00:46:57,640 --> 00:47:00,319
Speaker 1: there's not a lot of coverage, there's more risk's whole bunch.

811
00:47:00,400 --> 00:47:02,640
Speaker 1: When you read there, when you read their thesis, a

812
00:47:02,680 --> 00:47:05,400
Speaker 1: lot of these guys are talking about long duration anomalies

813
00:47:05,440 --> 00:47:08,000
Speaker 1: and like, hey, the cell side is crazy because they're

814
00:47:08,040 --> 00:47:09,920
Speaker 1: trying to beat the So a lot of it made

815
00:47:09,920 --> 00:47:12,800
Speaker 1: intuitive sense, um, and it was all good. I literally

816
00:47:12,800 --> 00:47:15,680
Speaker 1: read every single one of these stock pitches catalog did.

817
00:47:16,000 --> 00:47:18,120
Speaker 1: I had them all database by, Like what did they

818
00:47:18,200 --> 00:47:20,640
Speaker 1: mentioned as to why they liked this idea? Would have

819
00:47:20,719 --> 00:47:26,319
Speaker 1: you one part of it? I had a theory papers well,

820
00:47:26,640 --> 00:47:30,680
Speaker 1: which was beyond this discussion. But um, right, this thing up.

821
00:47:30,760 --> 00:47:34,160
Speaker 1: It actually says that these value investors actually do have skill.

822
00:47:34,760 --> 00:47:38,000
Speaker 1: And you know the fisher marketypothsis. It just it seems

823
00:47:38,040 --> 00:47:40,400
Speaker 1: to be some slack in it, which is fine, um,

824
00:47:40,480 --> 00:47:42,040
Speaker 1: you know. So so I sent it off to him

825
00:47:42,040 --> 00:47:43,920
Speaker 1: and of course, I you know, the first team I

826
00:47:43,920 --> 00:47:47,800
Speaker 1: get is basically no, this is wronging a conclusions false. Um.

827
00:47:48,000 --> 00:47:50,000
Speaker 1: So I'm like, great, it just wastes the year of

828
00:47:50,000 --> 00:47:52,520
Speaker 1: my life and I'm totally scared. But you have to

829
00:47:52,719 --> 00:47:56,239
Speaker 1: you can he I'm told he's pretty open minded, very

830
00:47:56,239 --> 00:48:00,600
Speaker 1: openustness said, listen, I think you're wrong, Prove I'm I'm

831
00:48:00,600 --> 00:48:04,040
Speaker 1: not correct exactly so. And and this is my like,

832
00:48:04,080 --> 00:48:06,360
Speaker 1: oh my god, I'm dead moment. So of course I

833
00:48:06,480 --> 00:48:08,839
Speaker 1: run down. I'm like, you know, and everyone calls him

834
00:48:08,880 --> 00:48:12,080
Speaker 1: prof fam I'm sure like Clifaz's price, I would never

835
00:48:12,200 --> 00:48:14,840
Speaker 1: call him by his first team. Yeah he's so gane.

836
00:48:14,880 --> 00:48:17,640
Speaker 1: Let me tell you why. Yeah, he's just too He's

837
00:48:17,680 --> 00:48:20,600
Speaker 1: too steadily. Like I just feel like, you know, I

838
00:48:20,600 --> 00:48:22,880
Speaker 1: don't want so many people I have a lot of

839
00:48:23,400 --> 00:48:25,440
Speaker 1: I'm not a big E M H guy, although I

840
00:48:26,040 --> 00:48:30,080
Speaker 1: the weak version of it makes sense, but there are

841
00:48:30,080 --> 00:48:32,399
Speaker 1: so many people I have all this respect for who

842
00:48:32,520 --> 00:48:36,359
Speaker 1: just sing say the world about him? Yeah, I mean, yeah,

843
00:48:36,600 --> 00:48:38,840
Speaker 1: a little off track, but as just a human being.

844
00:48:39,360 --> 00:48:42,600
Speaker 1: You know, the guy grinds every day. He's super honest,

845
00:48:42,640 --> 00:48:46,160
Speaker 1: super humble, works his face off, Like I don't care

846
00:48:46,200 --> 00:48:49,480
Speaker 1: if he's bacon donuts. I like this dude. Um. He

847
00:48:49,640 --> 00:48:52,600
Speaker 1: happens to be a Nobel Prize winner and that's awesome,

848
00:48:53,000 --> 00:48:55,279
Speaker 1: but but it's more about a fundamental respect for just

849
00:48:55,960 --> 00:48:58,799
Speaker 1: working his whole process. Yeah, what he's all about, like

850
00:48:58,960 --> 00:49:01,600
Speaker 1: not even death act. He's a financial economists. I just

851
00:49:01,719 --> 00:49:04,239
Speaker 1: like his the way it carries himself. You know. That's

852
00:49:04,280 --> 00:49:07,520
Speaker 1: why I said the exact same thing about Charlie Ellis,

853
00:49:07,520 --> 00:49:10,279
Speaker 1: who was a guest on the show Who and I

854
00:49:10,360 --> 00:49:12,560
Speaker 1: and I after the show, we walked downtown. I spent

855
00:49:12,640 --> 00:49:15,239
Speaker 1: like an extra hours with him, and I came away

856
00:49:15,280 --> 00:49:17,799
Speaker 1: with like, this is the finest human being I've ever

857
00:49:17,840 --> 00:49:19,919
Speaker 1: met in my life. And I'm hearing the same sort

858
00:49:19,920 --> 00:49:22,399
Speaker 1: of thing from the same thing. Just good dude, Like

859
00:49:22,400 --> 00:49:24,080
Speaker 1: like if I was in the Marine Corps and I

860
00:49:24,120 --> 00:49:28,040
Speaker 1: could transplant him fifty years or I want to, like,

861
00:49:28,120 --> 00:49:30,880
Speaker 1: this guy is good to go it regardless of what

862
00:49:30,920 --> 00:49:33,560
Speaker 1: he knows about finance. But so back to that, I

863
00:49:33,640 --> 00:49:35,759
Speaker 1: ran down there and and it was the same thing.

864
00:49:35,760 --> 00:49:39,800
Speaker 1: Like his Cliff said, he's very very open minded empirical evidence,

865
00:49:39,840 --> 00:49:42,960
Speaker 1: scientific focus, like if you got the evidence, you run

866
00:49:43,000 --> 00:49:45,840
Speaker 1: the right robustant tests, like all good. Um, so go

867
00:49:45,920 --> 00:49:48,160
Speaker 1: down there. And you know, in my dissertation in the

868
00:49:48,320 --> 00:49:51,839
Speaker 1: abstract for this particular paper, you know, I made an

869
00:49:51,880 --> 00:49:55,759
Speaker 1: overstated claim. I said value investors beat the market. You know,

870
00:49:55,880 --> 00:50:00,920
Speaker 1: He's like, no, the sample value investors you analyze be

871
00:50:01,000 --> 00:50:03,279
Speaker 1: at the market. And so literally it was like that

872
00:50:03,400 --> 00:50:06,600
Speaker 1: two or three word difference that because semantics matter and

873
00:50:06,600 --> 00:50:09,200
Speaker 1: that kind of stuff, because one is an overstatement and

874
00:50:09,239 --> 00:50:12,200
Speaker 1: the other is within the sub slept set of value managers.

875
00:50:13,200 --> 00:50:17,040
Speaker 1: I analyzed, they clearly have some skill, but you can't

876
00:50:17,080 --> 00:50:21,239
Speaker 1: say that value the market. And I was like, he's

877
00:50:21,280 --> 00:50:24,720
Speaker 1: being very precise, very precise, which was a great lesson.

878
00:50:25,040 --> 00:50:27,920
Speaker 1: And then and to be more precise on that particular thing.

879
00:50:28,280 --> 00:50:30,719
Speaker 1: This is not really in the dissertation because it's this

880
00:50:30,760 --> 00:50:33,360
Speaker 1: is a little bit too practitioner focus, I would say.

881
00:50:33,360 --> 00:50:35,759
Speaker 1: But after the fact we said, wow, this is incredible.

882
00:50:35,800 --> 00:50:39,040
Speaker 1: You have all these people that spend all this time,

883
00:50:39,560 --> 00:50:43,360
Speaker 1: incredible effort in data collection information come up with a

884
00:50:43,440 --> 00:50:47,399
Speaker 1: thesis on the stock pitch. Um, I'm really curious, can

885
00:50:47,440 --> 00:50:51,600
Speaker 1: this be quanted out? Turns out that we looked at

886
00:50:51,640 --> 00:50:55,040
Speaker 1: like that quant value agorithm, which basically is is essentially

887
00:50:55,440 --> 00:50:58,239
Speaker 1: a computer version of what the Value Investors Club guys

888
00:50:58,280 --> 00:51:03,160
Speaker 1: do by cheap high quality firms with a ton of

889
00:51:03,200 --> 00:51:06,440
Speaker 1: analysis on like the quality component, but cheapness is is

890
00:51:06,480 --> 00:51:10,360
Speaker 1: a is a primary. Turns out that the correlation between

891
00:51:10,400 --> 00:51:15,200
Speaker 1: just buying like a superactive cheap high quality basket is

892
00:51:15,280 --> 00:51:19,560
Speaker 1: essentially the same and very very highly correlated with kind

893
00:51:19,560 --> 00:51:22,800
Speaker 1: of what quote unquote the alpha generation is from these

894
00:51:22,800 --> 00:51:25,440
Speaker 1: stock picker people. So you know it's you know, what

895
00:51:25,600 --> 00:51:28,319
Speaker 1: is alpha? What is beta? Who knows? Um? You know,

896
00:51:28,760 --> 00:51:31,160
Speaker 1: alpha is just intercept on a regression where if you

897
00:51:31,160 --> 00:51:33,720
Speaker 1: put enough factors in there, obviously alpha is always zero,

898
00:51:34,080 --> 00:51:37,120
Speaker 1: but to some extent of you know, super concentrated. Wait

899
00:51:37,120 --> 00:51:39,759
Speaker 1: when you say, obviously alpha is always zero, but is

900
00:51:39,800 --> 00:51:42,640
Speaker 1: it always zero? It is if you keep adding factors

901
00:51:42,680 --> 00:51:46,600
Speaker 1: that explain the variants. Because because alpha, so you risk adjusted.

902
00:51:46,840 --> 00:51:49,640
Speaker 1: You once you once you go through all those different dimensions,

903
00:51:50,480 --> 00:51:54,680
Speaker 1: since we're talking about Chicago, eventually you can rationalize where

904
00:51:54,719 --> 00:51:58,520
Speaker 1: all that alpha comes and eventually alpha becomes beta. Yeah, exactly,

905
00:51:58,520 --> 00:52:01,880
Speaker 1: because all it is Alpha is literally just when you

906
00:52:01,920 --> 00:52:05,760
Speaker 1: calculate this stuff formally, beta is the coefficient on the factor.

907
00:52:05,840 --> 00:52:08,200
Speaker 1: Alpha is just kind of the average intercept, the kind

908
00:52:08,200 --> 00:52:11,319
Speaker 1: of the extra you get that's unexplained for. So the

909
00:52:11,360 --> 00:52:15,240
Speaker 1: deviation that you're looking for, why it occurs? Yeah, after

910
00:52:15,360 --> 00:52:18,120
Speaker 1: controlling for all these other quote unquote risk factors. But

911
00:52:18,360 --> 00:52:21,399
Speaker 1: let's take momentum for example. Okay, let's say we think

912
00:52:21,480 --> 00:52:25,560
Speaker 1: momentum is alpha. If you run momentum and you control

913
00:52:25,680 --> 00:52:29,360
Speaker 1: for market size, value, blah blah blah, you're gonna have

914
00:52:29,440 --> 00:52:31,800
Speaker 1: a huge alpha. So what do you do to control

915
00:52:31,840 --> 00:52:34,719
Speaker 1: for the alpha momentum? Throw a momentum factor on there. Now,

916
00:52:34,760 --> 00:52:37,359
Speaker 1: what happens the momentum strategy they have no alpha. So

917
00:52:37,760 --> 00:52:40,520
Speaker 1: now is that because they don't work and they're not

918
00:52:40,640 --> 00:52:42,880
Speaker 1: miss price or is that just because you controlled for

919
00:52:42,960 --> 00:52:46,800
Speaker 1: the momentum factor to say that momentum doesn't work anymore. Well, no,

920
00:52:46,960 --> 00:52:50,360
Speaker 1: momentum still works and it's been embraced in the factor.

921
00:52:50,760 --> 00:52:53,640
Speaker 1: But that doesn't necessarily mean that that factor is a

922
00:52:53,680 --> 00:52:57,920
Speaker 1: true risk factor. What if the returns associated with it

923
00:52:58,000 --> 00:53:02,120
Speaker 1: are associated with miss pricing problem, not like fundamental risks,

924
00:53:02,200 --> 00:53:05,480
Speaker 1: like it co varies with your future consumption or whatever

925
00:53:06,000 --> 00:53:09,680
Speaker 1: you know, fancy you know macro or model that some

926
00:53:09,719 --> 00:53:11,960
Speaker 1: economists is coming up with. And so I think the

927
00:53:12,040 --> 00:53:15,400
Speaker 1: problem with that the idea of alpha's and beta's is

928
00:53:15,440 --> 00:53:20,000
Speaker 1: alpha is an intuitive concept, is excess return controlling for

929
00:53:20,080 --> 00:53:24,160
Speaker 1: a bunch of risks. But the mechanical construct, it's a

930
00:53:24,200 --> 00:53:28,080
Speaker 1: statistical item and it can be totally manipulated. Where obviously

931
00:53:28,120 --> 00:53:30,680
Speaker 1: all alpha can become beta because you just put the

932
00:53:30,719 --> 00:53:33,640
Speaker 1: alpha generator on the beta side and you can go

933
00:53:33,719 --> 00:53:36,200
Speaker 1: buy it. But just because it can be beta, that

934
00:53:36,239 --> 00:53:38,479
Speaker 1: doesn't mean it's not alpha doesn't mean it's not real

935
00:53:38,760 --> 00:53:40,920
Speaker 1: or at least for that subset, And it doesn't mean

936
00:53:40,920 --> 00:53:43,680
Speaker 1: it's It's not easy to explain, right, because momentum is

937
00:53:43,680 --> 00:53:46,800
Speaker 1: a great example. Momentum is underperformed as a long short

938
00:53:46,840 --> 00:53:50,040
Speaker 1: factor for arguably five to ten years. Everyone's like, oh,

939
00:53:50,080 --> 00:53:53,680
Speaker 1: it's dead. Yeah. One of my old bosses, Chris Gates,

940
00:53:53,680 --> 00:53:56,640
Speaker 1: he wrote the paper like the long World's longest back tests.

941
00:53:56,920 --> 00:54:00,360
Speaker 1: They get data back and he actually expecially says in

942
00:54:00,400 --> 00:54:04,880
Speaker 1: the abstract momentum factor has underperformed for tenure cycles like

943
00:54:05,040 --> 00:54:09,279
Speaker 1: seven times. So this is this underperformance recently a momentum Yeah,

944
00:54:09,320 --> 00:54:12,759
Speaker 1: it's not all that operational, it's just so so one

945
00:54:12,800 --> 00:54:15,200
Speaker 1: of the one of the things you mentioned before about

946
00:54:15,680 --> 00:54:18,400
Speaker 1: the two two issues you look at, which is the

947
00:54:18,440 --> 00:54:23,840
Speaker 1: behavioral side and and the principal agent side. So I

948
00:54:23,880 --> 00:54:27,839
Speaker 1: would imagine someone like you looks at the FED with

949
00:54:27,960 --> 00:54:30,439
Speaker 1: Quie and up and all that stuff and says, yeah,

950
00:54:30,440 --> 00:54:33,560
Speaker 1: we don't care about that. It's not. What matters is

951
00:54:33,560 --> 00:54:38,640
Speaker 1: is the behavioral and the agency issue, not all these externalities.

952
00:54:39,120 --> 00:54:42,880
Speaker 1: It's all about what is the signal? What is the noise?

953
00:54:43,880 --> 00:54:47,520
Speaker 1: The signal is the huge It just driven from the

954
00:54:47,600 --> 00:54:50,680
Speaker 1: humans evolved in the game and the dynamics and the

955
00:54:50,760 --> 00:54:52,640
Speaker 1: rules of the game they play and how that shapes

956
00:54:52,680 --> 00:54:56,319
Speaker 1: their own synips. That doesn't change no matter what. I

957
00:54:56,360 --> 00:54:59,680
Speaker 1: don't care about g DP what the FED says, because

958
00:54:59,680 --> 00:55:03,040
Speaker 1: it's relevant. Human behavior stay indo chain, stay in the

959
00:55:03,080 --> 00:55:06,239
Speaker 1: same in human incentives are stay in the same in

960
00:55:06,280 --> 00:55:09,640
Speaker 1: the institutional construct that we currently live in, which is

961
00:55:10,120 --> 00:55:13,920
Speaker 1: primarily driven by a lot of delegated asset management. That's

962
00:55:13,920 --> 00:55:16,919
Speaker 1: funny because as we're as we're recording this, the FET

963
00:55:17,040 --> 00:55:20,200
Speaker 1: is meeting and uh literally the news is coming out

964
00:55:20,280 --> 00:55:22,279
Speaker 1: the second and we won't even talk about it because

965
00:55:22,320 --> 00:55:26,320
Speaker 1: it's meaningless. Instead, let's in the last ten or fifteen

966
00:55:26,360 --> 00:55:29,279
Speaker 1: minutes I have you, let's get to some of my

967
00:55:29,440 --> 00:55:35,120
Speaker 1: favorite questions. Um, well, you mentioned Cliff ass Nests. Who

968
00:55:35,160 --> 00:55:38,879
Speaker 1: else were other quants that you you admired or who

969
00:55:38,880 --> 00:55:41,960
Speaker 1: were mentors of yours? Tell tell us the people who

970
00:55:42,040 --> 00:55:45,439
Speaker 1: who influenced your approach to invest in Sure, I'd say

971
00:55:45,520 --> 00:55:48,440
Speaker 1: the danser directly like the quants that I admire. Obviously,

972
00:55:48,640 --> 00:55:51,120
Speaker 1: Cliff as nous I like a lot. He does value momentum.

973
00:55:51,520 --> 00:55:54,839
Speaker 1: HRS a great firm. Uh, you know, booth at Ata

974
00:55:55,000 --> 00:55:58,360
Speaker 1: is great. They figured out how to capture small value premium.

975
00:55:58,640 --> 00:56:01,839
Speaker 1: And I think probably the most underrespected or under appreciated

976
00:56:01,920 --> 00:56:06,120
Speaker 1: quant is Jack Bogel at Vanguard because indexing is a

977
00:56:06,120 --> 00:56:10,359
Speaker 1: form of systematic quant investing. It's just your your systematically

978
00:56:10,480 --> 00:56:15,200
Speaker 1: buying these market capuited passive indices. And for all intents

979
00:56:15,239 --> 00:56:19,200
Speaker 1: and purposes, he is a quantitative, systematic investor, and clearly

980
00:56:19,280 --> 00:56:22,560
Speaker 1: that's in a world of good for society. And his

981
00:56:22,680 --> 00:56:25,920
Speaker 1: alpha is we recognize that the cost structure is the

982
00:56:25,960 --> 00:56:29,280
Speaker 1: most important element investing, and if we could do everything

983
00:56:29,280 --> 00:56:32,839
Speaker 1: we can to reduce the cost factor, that's gonna our

984
00:56:32,960 --> 00:56:36,160
Speaker 1: beta is everybody else's is actually a form of alpha

985
00:56:36,560 --> 00:56:39,880
Speaker 1: if only you've given enough time. Yeah, costs and taxes,

986
00:56:40,800 --> 00:56:43,719
Speaker 1: or if you can minimize those somehow, that that is

987
00:56:44,200 --> 00:56:47,680
Speaker 1: always the answer now and that even they talk about

988
00:56:47,719 --> 00:56:51,279
Speaker 1: like active active is only bad to the extent that

989
00:56:51,400 --> 00:56:54,600
Speaker 1: it's the cost of achieving it. The net benefit is

990
00:56:54,600 --> 00:56:56,920
Speaker 1: not positive, it's negative because it goes in taxes and

991
00:56:56,960 --> 00:57:01,120
Speaker 1: fees to some idiot people. People are surprised when I said,

992
00:57:01,160 --> 00:57:04,280
Speaker 1: you know, Vanguard has a trillion dollars in active funds

993
00:57:04,280 --> 00:57:07,200
Speaker 1: that like really has anybody written a paper or or

994
00:57:07,320 --> 00:57:09,480
Speaker 1: or a column, and I may have to if nobody

995
00:57:09,520 --> 00:57:13,839
Speaker 1: has Jack Bogel the quant. I don't know if anyone has.

996
00:57:13,920 --> 00:57:16,640
Speaker 1: But so now now you've forced me to do this,

997
00:57:16,720 --> 00:57:18,640
Speaker 1: that's what's gonna happen. I think he might be the

998
00:57:18,680 --> 00:57:22,160
Speaker 1: world's greatest quant, just that no one really appreciate it.

999
00:57:22,400 --> 00:57:24,680
Speaker 1: I'm gonna have to quote you in this and you've

1000
00:57:24,760 --> 00:57:27,040
Speaker 1: just given me an idea. Now I have to get

1001
00:57:27,080 --> 00:57:30,959
Speaker 1: this out before the podcast goes up, so uh, it'll

1002
00:57:31,000 --> 00:57:34,960
Speaker 1: it'll be pretty interesting. So you've mentioned Buffett, You've mentioned Graham.

1003
00:57:35,040 --> 00:57:41,480
Speaker 1: What other investors have influenced your approach? I would say, um,

1004
00:57:41,520 --> 00:57:45,280
Speaker 1: not much beyond that, Like Graham taught me about, you know,

1005
00:57:45,320 --> 00:57:50,520
Speaker 1: thinking about businesses or stocks is businesses. Buffett actually didn't

1006
00:57:50,560 --> 00:57:52,640
Speaker 1: add any thing onto that. But I just like his

1007
00:57:52,800 --> 00:57:56,080
Speaker 1: like transparent approach and the whole idea that integrity is

1008
00:57:56,120 --> 00:57:58,240
Speaker 1: everything and in the end that's what you live and

1009
00:57:58,320 --> 00:58:00,520
Speaker 1: die by. And he has that old what were you know?

1010
00:58:00,720 --> 00:58:03,680
Speaker 1: You know, integrity spends a lifetime to build, five minutes

1011
00:58:03,680 --> 00:58:06,320
Speaker 1: to destroy, which it has nothing to do with investing,

1012
00:58:06,600 --> 00:58:08,680
Speaker 1: but it has everything to do with investing. Well, it

1013
00:58:08,720 --> 00:58:12,240
Speaker 1: has everything to do with working in the investment field exact.

1014
00:58:12,280 --> 00:58:16,080
Speaker 1: It's always you know, my my favorite line is no

1015
00:58:16,160 --> 00:58:18,840
Speaker 1: one has a patience to get rich slowly, and the

1016
00:58:18,880 --> 00:58:22,240
Speaker 1: people who are in a hurry invariably run into trouble.

1017
00:58:22,320 --> 00:58:25,200
Speaker 1: You got it. It's amazing. Let's talk about books you

1018
00:58:25,200 --> 00:58:28,080
Speaker 1: mentioned one or two earlier. What are some of your

1019
00:58:28,520 --> 00:58:32,600
Speaker 1: and fiction, nonfiction, investing, whatever, what What are some of

1020
00:58:32,640 --> 00:58:36,680
Speaker 1: your favorite books? Yeah, so, unfortunately I'm not a one

1021
00:58:36,720 --> 00:58:39,760
Speaker 1: of my weaknesses is I'm very pragmatic and I just

1022
00:58:39,880 --> 00:58:43,120
Speaker 1: read stuff that helps me get better. So you're reading

1023
00:58:43,120 --> 00:58:45,320
Speaker 1: more academic papers, Yeah, I read. I read a lot

1024
00:58:45,360 --> 00:58:48,000
Speaker 1: of journals, four books. Some of the things that heavily

1025
00:58:48,040 --> 00:58:50,880
Speaker 1: influenced the way I've thought about things, and I know

1026
00:58:51,000 --> 00:58:53,360
Speaker 1: you know it very well, like Dan Kahneman's book The

1027
00:58:53,760 --> 00:58:57,800
Speaker 1: Fastest Epic. Another one is, you know Taylor sustained that

1028
00:58:57,880 --> 00:59:00,960
Speaker 1: Nudge book. The whole idea of like liberty Ryan paternalism,

1029
00:59:01,080 --> 00:59:03,000
Speaker 1: I thought made a ton of sense because I used

1030
00:59:03,000 --> 00:59:05,360
Speaker 1: to be a libertarian. I was like, wait a secondaris

1031
00:59:05,440 --> 00:59:08,280
Speaker 1: humans involved and they make bad decisions. You have to

1032
00:59:08,320 --> 00:59:12,560
Speaker 1: have some bumpers up otherwise that someone just someone just

1033
00:59:12,720 --> 00:59:17,840
Speaker 1: ran maybe with Samantha b at the Libertarian convention, and

1034
00:59:17,960 --> 00:59:21,240
Speaker 1: one of the guys got booed for saying, I believe

1035
00:59:21,280 --> 00:59:25,560
Speaker 1: that we should have um people, the states should mandate

1036
00:59:26,120 --> 00:59:28,360
Speaker 1: tests for driving. We don't just give anyone a car.

1037
00:59:28,680 --> 00:59:31,480
Speaker 1: And they were booed by the Libertarians, and it's like, oh,

1038
00:59:31,520 --> 00:59:34,000
Speaker 1: so you guys don't understand humans at all. Yeah, yeah,

1039
00:59:34,200 --> 00:59:37,000
Speaker 1: and that's my big I mean, I'm a I'm gonna

1040
00:59:37,000 --> 00:59:40,280
Speaker 1: be a Gary Johnson voter. He was the one who

1041
00:59:40,360 --> 00:59:42,640
Speaker 1: was booed when he said, yes, you should. He's a

1042
00:59:42,680 --> 00:59:47,000
Speaker 1: pragmatic hematic libertarian. That's a subset of the part. And

1043
00:59:47,200 --> 00:59:50,200
Speaker 1: guess what, none of these political folks appealed to the

1044
00:59:50,240 --> 00:59:54,680
Speaker 1: pragmatic part. You always get extremes because that's what sells well.

1045
00:59:55,000 --> 00:59:58,439
Speaker 1: Was but yeah, give me one more book, the other one,

1046
00:59:58,760 --> 01:00:02,000
Speaker 1: a whole bunch of them. Chardini's books on like the

1047
01:00:02,040 --> 01:00:06,320
Speaker 1: science of persuadion, influence, influence, fifty scientific ways to say yes,

1048
01:00:06,440 --> 01:00:09,240
Speaker 1: like after re and that guy's stuff. It just made

1049
01:00:09,240 --> 01:00:13,640
Speaker 1: me rethink the whole world of of like human thinking

1050
01:00:13,680 --> 01:00:18,040
Speaker 1: and decision making from the perspective of like a marketing person,

1051
01:00:18,200 --> 01:00:21,720
Speaker 1: and how you get influence and bombarded every day in

1052
01:00:21,800 --> 01:00:24,680
Speaker 1: subconscious ways to do things you may or may not

1053
01:00:24,800 --> 01:00:26,960
Speaker 1: want to do. But it's very important, I think, to

1054
01:00:27,000 --> 01:00:30,760
Speaker 1: be aware of this influenced tactics out there, so one

1055
01:00:30,800 --> 01:00:33,160
Speaker 1: you can defend against it, and then too, you can

1056
01:00:33,240 --> 01:00:35,600
Speaker 1: use it to your advantage, you know, in a sensible,

1057
01:00:35,640 --> 01:00:40,000
Speaker 1: you know, high integrity way. I'm gonna out myself embarrassingly.

1058
01:00:40,360 --> 01:00:42,280
Speaker 1: I've had that book on my bookshelf for years. I

1059
01:00:42,320 --> 01:00:46,800
Speaker 1: still haven't read it. Unlivable. You're not the first want

1060
01:00:46,840 --> 01:00:48,520
Speaker 1: to say that. All right, we're down to our last

1061
01:00:48,600 --> 01:00:53,479
Speaker 1: few favorite questions. So if somebody, if a millennial's coming

1062
01:00:53,480 --> 01:00:56,960
Speaker 1: to you and says, I'm beginning my career in finance,

1063
01:00:57,480 --> 01:01:00,320
Speaker 1: what sort of uh, what sort of advice would you

1064
01:01:00,320 --> 01:01:04,400
Speaker 1: give them? So back to our discussion about manual labor,

1065
01:01:04,880 --> 01:01:09,280
Speaker 1: I would say, first, get mentally tough. So do sports.

1066
01:01:09,440 --> 01:01:13,240
Speaker 1: Do things that are painful that allow you to be tough.

1067
01:01:13,640 --> 01:01:17,120
Speaker 1: Adapt because we're in the world where it's gonna change,

1068
01:01:17,120 --> 01:01:19,560
Speaker 1: it's gonna be tough, it's gonna be adapting, and you're

1069
01:01:19,600 --> 01:01:22,840
Speaker 1: competing not with Americans, you're competing with the globe now.

1070
01:01:23,120 --> 01:01:24,800
Speaker 1: So you know, we have a lot of you know,

1071
01:01:24,840 --> 01:01:28,880
Speaker 1: my old students are Chinese guys, and these guys grind,

1072
01:01:29,320 --> 01:01:33,920
Speaker 1: they work harder, faster, stronger, and that's who you're competing

1073
01:01:33,960 --> 01:01:38,080
Speaker 1: with out there. So unless you're you gotta rate rise occasion.

1074
01:01:38,400 --> 01:01:40,560
Speaker 1: I hear, I hear a lot of marine corps. Yeah,

1075
01:01:40,600 --> 01:01:43,440
Speaker 1: so I would say, just get mentally tough, don't It

1076
01:01:43,480 --> 01:01:45,920
Speaker 1: doesn't even matter what you learn. Get mentally tough and

1077
01:01:45,960 --> 01:01:48,040
Speaker 1: know how to adapt and overcome. And then the other

1078
01:01:48,120 --> 01:01:50,760
Speaker 1: thing I said here I just write down my notes

1079
01:01:50,920 --> 01:01:53,480
Speaker 1: is you know, I become a either a robot salesman

1080
01:01:53,840 --> 01:01:56,760
Speaker 1: or a robot manufacturer because I feel like in the

1081
01:01:56,880 --> 01:02:00,360
Speaker 1: very near future robots are taken over and so you

1082
01:02:00,440 --> 01:02:02,600
Speaker 1: might as well adapt and train to the future and

1083
01:02:02,640 --> 01:02:05,680
Speaker 1: not you know, be a basket weaver guy anymore because

1084
01:02:05,680 --> 01:02:09,080
Speaker 1: it's not gonna pay um. And our final question, what

1085
01:02:09,280 --> 01:02:12,320
Speaker 1: is it that you know about investing today that you

1086
01:02:12,400 --> 01:02:16,360
Speaker 1: wish you knew fifteen years ago? Well, I wrote down

1087
01:02:16,480 --> 01:02:19,440
Speaker 1: the Big Three, which have been uh, you know, endowed

1088
01:02:19,520 --> 01:02:21,480
Speaker 1: upon me by a lot of our investors who are

1089
01:02:21,520 --> 01:02:24,320
Speaker 1: all insanely rich. And I'm like, wow, that's pretty cool.

1090
01:02:24,320 --> 01:02:25,960
Speaker 1: How how do you guys do that? And there's literally

1091
01:02:26,040 --> 01:02:28,760
Speaker 1: three themes that come out of every single one of

1092
01:02:28,800 --> 01:02:33,320
Speaker 1: these stories. Minimize tax burdens, defer to for to for

1093
01:02:34,080 --> 01:02:38,400
Speaker 1: have horizon, and live below your means. So always be humble,

1094
01:02:38,960 --> 01:02:41,760
Speaker 1: you know, never rise to the level of what you

1095
01:02:41,760 --> 01:02:45,120
Speaker 1: can afford. Just you know, live within your means and

1096
01:02:45,200 --> 01:02:48,160
Speaker 1: enjoy your life with what you got. Um and and

1097
01:02:48,240 --> 01:02:50,280
Speaker 1: those are the three things and you'll be all right.

1098
01:02:50,520 --> 01:02:53,840
Speaker 1: West Gray, thank you so much for for doing this this.

1099
01:02:53,840 --> 01:02:57,600
Speaker 1: This has just been absolutely fascinating. We have been speaking

1100
01:02:57,880 --> 01:03:01,160
Speaker 1: with Captain Wesley Gray, formally of the U. S. Marine

1101
01:03:01,160 --> 01:03:06,120
Speaker 1: Corps now with Alpha Architect. I would be remiss if

1102
01:03:06,120 --> 01:03:09,880
Speaker 1: I did not think our producer Charlie Vhmer, my booker

1103
01:03:10,600 --> 01:03:14,280
Speaker 1: Taylor Riggs, and Mike bat Nick, my head of research,

1104
01:03:14,320 --> 01:03:18,760
Speaker 1: our recording engineer Jennie. If you have enjoyed this conversation,

1105
01:03:18,800 --> 01:03:20,560
Speaker 1: be sure and look up an Inch or Down an

1106
01:03:20,600 --> 01:03:23,560
Speaker 1: Inch on Apple iTunes and you will see any of

1107
01:03:23,600 --> 01:03:28,200
Speaker 1: the nineties six other such podcasts that we've had. Uh,

1108
01:03:28,440 --> 01:03:31,680
Speaker 1: be sure and check out the list of upcoming guests,

1109
01:03:31,800 --> 01:03:36,760
Speaker 1: which is really quite astonishing. I'm Barry rit Halts. You're

1110
01:03:36,800 --> 01:03:45,920
Speaker 1: listening to Masters in Business on Bloomberg Radio look Ahead

1111
01:03:46,280 --> 01:03:50,000
Speaker 1: Imagine more gain insight for your industry with forward thinking

1112
01:03:50,000 --> 01:03:53,960
Speaker 1: advice from the professionals at Cone Resnick. Is your business

1113
01:03:53,960 --> 01:03:57,160
Speaker 1: ready to break through? Find out more at Cone Resnick

1114
01:03:57,240 --> 01:03:59,040
Speaker 1: dot com Slash Breakthrough