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Speaker 1: M. This is Mesters in Business with very Results on

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Speaker 1: Bloomberg Radio. This week on the podcast, I have an

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Speaker 1: extra special guest. BoA's Weinstein is the founder of SABA Capital,

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Speaker 1: of five billion dollar hedge fund that specializes in some

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Speaker 1: really interesting types of trading um credit to fault swaps,

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Speaker 1: tale protection, volatility trading UH. SABA is one of the

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Speaker 1: five largest investors globally in spacts, but not in the

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Speaker 1: way you think they've done really well with it despite

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Speaker 1: all of the troubles that spacts have seen. Previously, he

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Speaker 1: was co head of global credit trading at Deutsche Bank,

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Speaker 1: and ultimately he and Deutsche spun out SABA along with

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Speaker 1: his whole team as a standalone funds man. I don't

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Speaker 1: even know where to begin. This was just an absolutely

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Speaker 1: fascinating conversation. Not only is he a quant with some

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Speaker 1: real insight into capital market structures and valuation and miss pricings,

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Speaker 1: but he's put together an amazing track record, uh, not

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Speaker 1: just in terms of his trading, but his consistent ability

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Speaker 1: to find parts of the markets that are completely miss

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Speaker 1: priced because people fundamentally misunderstand what's going on there. Really

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Speaker 1: just a fascinating guy, an amazing conversation with no further Ado,

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Speaker 1: my conversation with BoA's Weinstein of Sabba Capital, Hi, Barry,

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Speaker 1: it's great to be here. And am I pronouncing your

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Speaker 1: first name correctly Boas? Depends where you're from in these parts,

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Speaker 1: that would work, and it's really a typical Israeli name

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Speaker 1: and it would be Boas alright. So so let's start

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Speaker 1: with um your background, beginning with you started to play

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Speaker 1: chess when you were five and eventually became pretty highly ranked.

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Speaker 1: How did you get into chess and and how long

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Speaker 1: did it take to become a ranked player here in

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Speaker 1: the US? Sure, so I had those parents that would

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Speaker 1: drive us on weekends. I have a sister actually been

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Speaker 1: been on Bloomberg many times, uh Elana. But we my

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Speaker 1: parents would take us to Saturday morning workshops to learn

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Speaker 1: about model rocketry or chess or what have you. But

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Speaker 1: I didn't actually playing tournaments to always thirteen. I got

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Speaker 1: to junior high school and I was interested in the game.

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Speaker 1: And there was a kid a year above me, and

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Speaker 1: I saw that he was ranked in the top fifteen

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Speaker 1: the United States, and I thought that's amazing. How do

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Speaker 1: I how do I get there? And so how long

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Speaker 1: did it take you from when you started playing in

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Speaker 1: tournaments to becoming ranked. So I became really obsessed with it.

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Speaker 1: And so in three years I went from a beginner

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Speaker 1: to number two in the country for age fifteen sixteen. Wow,

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Speaker 1: that's pretty impressive. And that's thousands and thousands of hours. Uh, yeah,

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Speaker 1: at least. And and so from chess you moved to

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Speaker 1: poker and black jack, which seems more of a fit

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Speaker 1: with with finance. What led you from poker and black

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Speaker 1: jack to credit it and derivatives? I knew I wanted

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Speaker 1: to be on Wall Street well before I knew how

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Speaker 1: to play poker. In fact, I didn't really learn poker

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Speaker 1: until I was in my mid twenties. Black Jack I

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Speaker 1: learned a bit earlier. Maybe we'll get there, But Wall

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Speaker 1: Street was always something I was interested in. My parents

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Speaker 1: would listen to watch Wall Street Week with Lewis Ruckiser.

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Speaker 1: I can tell you the postcode for Owens Mills, Maryland.

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Speaker 1: It's two one one one seven, because that's they would

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Speaker 1: always do that right in the middle of the show.

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Speaker 1: And uh. And so I was able to parlay that

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Speaker 1: interest into getting an after school job when I was

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Speaker 1: a high school student in New York City, at Merrill

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Speaker 1: Lynch and then uh summer internships at Coleman Sacks, which

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Speaker 1: were really among the most fun times in my career

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Speaker 1: on Wall Street. Well, we'll talk a little bit about

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Speaker 1: Goldman In a bit, Um, you mentioned black jack. I

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Speaker 1: understand you got pretty good at black jack, eventually getting

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Speaker 1: kicked out of the Blaggio as a card counter to

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Speaker 1: tell us about that. So it's they're very polite. It's

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Speaker 1: a you know, it's it's kicked out as more of

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Speaker 1: the nineteen sixties. Um. But you know ed Thorpe is

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Speaker 1: a is a hero and beat the dealer and a

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Speaker 1: man for all markets. Also is I think a fantastic book. Um.

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Speaker 1: And So I learned how to count cards when I

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Speaker 1: was a summer intern on the risk guard desk at

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Speaker 1: Goldman from the partner in charge, Frank Brozen's almost Marone,

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Speaker 1: some of these legendary hedge fund managers, UM and UH

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Speaker 1: and I got pretty good at it, and UM and

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Speaker 1: I went and was sent over to London when I

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Speaker 1: graduated college with Merlynch, and I found that the games

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Speaker 1: in London had a weakness that the games in the

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Speaker 1: US didn't. They had a certain side bed that was

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Speaker 1: very crackable, and I had to kind of figure it out.

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Speaker 1: There was no internet, you know, to look up everything

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Speaker 1: back then, and I became quite a skilled card counter.

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Speaker 1: Uh that's really that's really quite fascinating. So so from

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Speaker 1: counting cards, how do you end up at Deutsche Bach? Uh?

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Speaker 1: So the people at Marylynch that I first worked with

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Speaker 1: out of college had moved really in mass to Deutsche

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Speaker 1: um Edson Mitchell legendary Mary Lynch, head of global markets,

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Speaker 1: wanted to recreate that at Deutsche Bank without having the

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Speaker 1: deep institutional capital markets relationships, and so he really wanted

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Speaker 1: to build up trading quickly, and credit derivatives was a

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Speaker 1: new market, and he had someone named Aunt Jane, who

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Speaker 1: has really been an amazing mentor to me. Um poor

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Speaker 1: huge amount of resources into making Deutsche if if not

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Speaker 1: the best, the top two year and in year out.

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Speaker 1: And at Deutsche Bank you become the youngest person to

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Speaker 1: be a managing director. Tell us about that path? Yeah,

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Speaker 1: so I think, um, it's either youngest, your second youngest.

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Speaker 1: Let me let me not overstep it. But still I

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Speaker 1: was twenty seven and usually it's not until you're in

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Speaker 1: your thirties, and I have to say there's so many

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Speaker 1: aspects to one's career that have to do with luck

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Speaker 1: and timing that have to go along with skill. Almost

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Speaker 1: all the time, sometimes you can even avoid the skill

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Speaker 1: part just be ultra lucky. At my My luck was

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Speaker 1: that UM, this market creditortives basically started when I started,

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Speaker 1: and even a year or two after, and I was

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Speaker 1: waiting for it. It It was like I was waiting for

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Speaker 1: it to be created, because I was never going to

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Speaker 1: be the credit investor that can read through the tent

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Speaker 1: k and and do the deep uh you know, fun

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Speaker 1: fundamental work and accounting work that was going to I

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Speaker 1: was not going to make my mark in credit that way.

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Speaker 1: I needed something more quantitative, more tactical, and creditor. It

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Speaker 1: of started really in ninety seven and UM and so

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Speaker 1: there was no one, there were no adults to learn from.

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Speaker 1: I got to I got to UM learn learn from experience,

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Speaker 1: and and ninety eight with Russia defaulting and LTCM blowing up,

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Speaker 1: gave an incredible path to that those lessons, and so

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Speaker 1: Deutsche Bank kept giving me more and more responsibilities UM

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Speaker 1: and so each year they promoted me and I and

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Speaker 1: I think another bit of luck was not just being

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Speaker 1: at a place that wanted to expand in this new area.

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Speaker 1: But also Goldman Sachs had hired away my boss, an

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Speaker 1: amazing guy, Ron Tannemora, and I think Deutsche was a

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Speaker 1: little afraid that that I might move over to Goldman,

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Speaker 1: and so, you know, earlier than than one would have expected,

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Speaker 1: they made me an empty So so good timing, right place,

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Speaker 1: right time, plus the right set of skills in in

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Speaker 1: derivatives trading before we moved to spinning out SABA from

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Speaker 1: Deutsche Bank. I have to follow up your conversation about

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Speaker 1: being an intern at Goldman Sachs. You kind of worked

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Speaker 1: with a murderers row there and you said it was

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Speaker 1: the most fun you ever had. Tell us about your

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Speaker 1: time at Goldman, Who did you work for and what

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Speaker 1: do they have you doing? Sure, so, look, anyone who

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Speaker 1: comes to Wall Street needs to read Liars Poker doesn't

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Speaker 1: matter we're talking now, ten years ago or fifty years

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Speaker 1: from now. And um there was a minor character in

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Speaker 1: that book, David DeLucia, who Goldman hired from Solomon to

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Speaker 1: set up the junk bond desk, and he had a

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Speaker 1: incredible love of chess. He actually has the world's greatest

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Speaker 1: going to say something that's not gonna sound so great.

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Speaker 1: World's greatest chess book collection. Um um. Hopefully no one's

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Speaker 1: gasping at that. But he has, you know, fifteen century

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Speaker 1: books and and the busts of the hand of the

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Speaker 1: world champion from the eighteenth century, and so he was

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Speaker 1: obsessed with chess. I had met him at a at

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Speaker 1: a chess club, and I came to Goldman Sachs to

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Speaker 1: interview for a summer internship. And I had a very

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Speaker 1: perfunctory meeting with the HR person. They they even met me,

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Speaker 1: I think only because my sister was working in private

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Speaker 1: client services then, so they as I have this twenty

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Speaker 1: five minute meeting, the woman says, thanks for coming your

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Speaker 1: college freshman, why don't you come back in three years

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Speaker 1: and shows me to the door, and I said, okay,

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Speaker 1: can I use the men's room? And on my way out,

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Speaker 1: I went into the men's room and who's standing washing

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Speaker 1: his hands at the sink is David de Lucia. He says,

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Speaker 1: what are you doing here? Come on back, and that

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Speaker 1: began five rounds, five interviews per round, and finally, after

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Speaker 1: twenty five interviews, he calls me back and he says,

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Speaker 1: we tried to do everything we could. There's no program

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Speaker 1: for you. There's a there's a program called s c

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Speaker 1: o UH to give minorities a chance to come to

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Speaker 1: Wall Street. There's a program for sons and daughters. We

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Speaker 1: just couldn't fit you in. And I said it's you know,

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Speaker 1: one thing is never give up. So I said to him,

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Speaker 1: it's really too bad. You have a program for sons

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Speaker 1: and daughters but not brothers of sisters. And he said,

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Speaker 1: let me try that one. And he and he came

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Speaker 1: back and I had another two sets of meetings and

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Speaker 1: they they they jammed me in with the Summer NBA.

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Speaker 1: So I'm a college freshman and I'm there with the

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Speaker 1: the HBS and Wharton n B as UH during doing

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Speaker 1: training and all sorts of you know things, and and

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Speaker 1: the desk I was assigned to. His desk was we

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Speaker 1: had a three by two rows, so six seats. He

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Speaker 1: was directly facing me and it was a murderers row.

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Speaker 1: Um on my on my left was Bill Troy. It

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Speaker 1: was really an amazing mentor to me. He was a

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Speaker 1: co founder of a fund called um Gray Wolf Capital.

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Speaker 1: Next to him was Jim Zelter, who's one of the

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Speaker 1: heads of Apollo Um. And then on the other side

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Speaker 1: Jonathan Coleach, the founder of Redwood. And then last but

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Speaker 1: not least, a guy who was named David Tepper. But

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Speaker 1: he was not the David Tepper we all know and

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Speaker 1: love now larger than life. He was. He was a

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Speaker 1: distressed analyst that was working for for a group. He

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Speaker 1: wasn't this. I can't even imagine him, you know, the

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Speaker 1: way he was then versa now he's He's an incredible superstar,

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Speaker 1: one of the greatest investors of all time. And I

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Speaker 1: got to work with the five of them every day

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Speaker 1: for you know, for months. And what sort of work

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Speaker 1: did they give you? Because I've read that Tepper used

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Speaker 1: to bust your chops a little bit, a lot, not

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Speaker 1: not a little bit. So he would say, what are

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Speaker 1: we paying you for? You're here to play chess with DeLucia.

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Speaker 1: That's why Goldman saxes paying you as if it was

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Speaker 1: any of his business. So what did he do? He

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Speaker 1: didn't teach me much about the market that I learned

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Speaker 1: from some of the other guys on the desk. But

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Speaker 1: I would have to get broker quotes in the morning, Um, Murphy,

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Speaker 1: Duryer or Garband. I'd write down where all the bond

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Speaker 1: prices were. And I barely knew anything at the time,

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Speaker 1: but what he would do ring the course of the day.

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Speaker 1: I remember this was Wall Street in the early nineties. Um,

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Speaker 1: they would make bets. So he would yell over at

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Speaker 1: Jim's alter, how many how many synagogues do you think

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Speaker 1: there are in Montana? And and Zelter would say not

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Speaker 1: more than three. And he would say, I'm I'm gonna

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Speaker 1: buy three bo as, go to the library and figure

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Speaker 1: it out. And this was this is pre internet. So

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Speaker 1: you want to know how many synagogues are in Montana,

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Speaker 1: It's gonna be a lot of work. And so I

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Speaker 1: would settle that bed I would settle were interest rates

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Speaker 1: every negative they were briefly during World War Two. I

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Speaker 1: would settle, you know, bets of all kinds. And in

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Speaker 1: the meantime I would also learn a lot through outmosis

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Speaker 1: and by asking questions. So it was just a marvelous experience.

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Speaker 1: And if I have a million stories about it, so

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Speaker 1: we'll see what we have time for. So so the

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Speaker 1: Solomon Brothers version of gambling was liars poker, played with

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Speaker 1: dollar bills at Goldman It was a trivia contest for

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Speaker 1: random unknown facts. You know, traders like Tibet and and

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Speaker 1: some of the obscure bets need to be settled. And

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Speaker 1: there was no internet, so you a final word. They

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Speaker 1: trusted you to say what what Boa says, that's what goes.

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Speaker 1: I uh, I don't even remember if I had to

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Speaker 1: show evidence or not, but I was. I was asked

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Speaker 1: to do all sorts of things, and along the way,

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Speaker 1: I asked dozens of questions a day. And I think

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Speaker 1: that's really important for anyone who is going to have

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Speaker 1: an internship on Wall Street is that there are things

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Speaker 1: you can do to annoy the people around you, but

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Speaker 1: one of them is not asking too many decent questions

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Speaker 1: about markets. That's that's the only way you're going to

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Speaker 1: get to where you want to be, and actually, I

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Speaker 1: think it will impress the people around you. So let's

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Speaker 1: talk a little bit about your time trading at Deutsche

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Speaker 1: Bank before the Great Financial Crisis. You allegedly made profits

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Speaker 1: in forty out of forty four quarters. How did you

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Speaker 1: manage to be so consistent? I think there are a

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Speaker 1: lot of investors who, if you look at how they

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Speaker 1: did in that time frame. So let's say the late

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Speaker 1: nineties to the Lehman Brothers. The markets really were a

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Speaker 1: lot easier than they and laws compare editive. There were

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Speaker 1: thousands of fewer hedge funds, and we were we were

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Speaker 1: relatively consistent because there also was a lot of edge

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Speaker 1: in creditoratives. Creditoratives being synthetic bonds or insurance contracts. You

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Speaker 1: can refer to them any number of ways, but how

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Speaker 1: to think about, how to price them, miss pricings, in

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Speaker 1: credit dioratives against equity ritives. Some of those things were really,

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Speaker 1: again not well understood, and I think Deutsche allowing me

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Speaker 1: to trade those relationships, trading out of the money puts

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Speaker 1: on a stock compared to hedging them with a bond,

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Speaker 1: which is not as crazy as it sounds, is something

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Speaker 1: that I think gave us a big leg leg up

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Speaker 1: and an ability to look across markets and find relative value.

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Speaker 1: And so we were we were consistent. We were particularly

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Speaker 1: profitable when markets were volatile up until Lehman Brothers, which

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Speaker 1: is where we had two of our four down quarters.

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Speaker 1: That's volatility large, so you're looking for medium load of

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Speaker 1: medium amount of volatility. Once it spikes to very high levels,

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Speaker 1: suddenly all the correlations start to fail or why does

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Speaker 1: that degree of volatility affect trading. Oh, it was really

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Speaker 1: so specific to Lehman failing as a counterparty. So because

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Speaker 1: I was inside of a bank, if you were um

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Speaker 1: whether it's interest rate swaps or credit swaps, you were

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Speaker 1: part of a daisy chain where you buy protection on

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Speaker 1: General Electric or IBM from Morgan Stanley, who buys it

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Speaker 1: from Lehman. And these hundreds of thousands of swaps would

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Speaker 1: remain on the books. So even if you bought and

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Speaker 1: sold something, instead of being out of the trade, you

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Speaker 1: would have two swaps on. And so when Lehman Brothers failed,

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Speaker 1: we had enormous exposure to them as a counterparty, just

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Speaker 1: like all the other desks at Deutsche Bank. So that

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Speaker 1: made it more challenging than being at a hedge fund.

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Speaker 1: But the more volatility for our strategy is really the better,

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Speaker 1: and we saw that and we've seen it again this year.

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Speaker 1: But Lehman Brothers was very specific because if you couldn't

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Speaker 1: trust not just Lehman to pay you, anybody, Mary Lynch,

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Speaker 1: you know, and and Goldman, Sax and Morgan Stanley were

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Speaker 1: trading like you nearly bankrupt identities trading at credit spreads

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Speaker 1: that were a thousand basis points are higher. So so

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Speaker 1: that was very specific, and I think the market has

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Speaker 1: done a great job to reduce counterparty risk in the

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Speaker 1: intervening fifteen years. So let's talk a little bit about

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Speaker 1: the strategies that SABA employees. One of your funds is

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Speaker 1: a closed end funds arbitrage where companies are either trading

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Speaker 1: at a substantial discount or premium to nav to net

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Speaker 1: asset value. Tell us a little bit about trading closed

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Speaker 1: end funds. Yeah, this is an amazing space. It's one

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Speaker 1: where the product has been around a hundred years. Berkshire

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Speaker 1: Hathaway in a sense is a closed end fund, and

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Speaker 1: Warren Buffett in particular has talked to me and showed

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Speaker 1: me how enamored he was with them right before he

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Speaker 1: took Benjamin Graham's class. So we're going back to nineteen

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Speaker 1: fifty where he had two thirds of his holdings in

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Speaker 1: closed end funds. Why why are they interesting? Because you

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Speaker 1: get to buy a dollar of assets for less than

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Speaker 1: a dollar, and there are ways to turn it back

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Speaker 1: into a dollar. So the there's five hundred of them

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Speaker 1: on the New York Stock Exchange. The most venerable managers

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Speaker 1: all have tons of them, whether it's black Rock or

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Speaker 1: black Stone or Pimpco, UM and Templeton, and they um

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Speaker 1: sometimes because they're not cared for, because the fees are high,

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Speaker 1: because the manager is not thinking about the investor, they

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Speaker 1: can slip into trading for a discounts to any v

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Speaker 1: So objective dollar bassets valued properly in the same way

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Speaker 1: that ETFs mutual funds are valued. You can buy a

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Speaker 1: dollar for eight five cents, and if you accumulate enough

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Speaker 1: of it, and if you take on an institutional approach

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Speaker 1: to reading the documents, understanding the rules as a shareholder,

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Speaker 1: your rights to UM to vote for a board of

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Speaker 1: trustees and UH or or overthrow the board if they're

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Speaker 1: not doing the right thing for investors UM. If you

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Speaker 1: buy up enough of the shares UM, you have a

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Speaker 1: chance to to make change. And UH we only started

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Speaker 1: doing that when they started to go to deep discounts.

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Speaker 1: Some these barry had been at discounts seven eight, nine years.

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Speaker 1: They never had a day where they were not at

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Speaker 1: a discount. And we've been able in dozens of cases

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Speaker 1: two for thousands and thousands of investors, tens of thousands,

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Speaker 1: to get the discount to UM converge back to ny VING.

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Speaker 1: So so let's talk about that approach. When I think

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Speaker 1: of activist campaigns, I think of investors like Carl Icon

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Speaker 1: or Dan Loebe or or uh Bill Ackman. How is

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Speaker 1: your approach similar or different to their sort of activist

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Speaker 1: investing campaigns. Right, So, they're finding a company where they

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Speaker 1: can make change, and that change maybe on average, is

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Speaker 1: quite valuable, but you can debate it. And certainly there

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Speaker 1: are examples where the impact of the activist was terrible

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Speaker 1: me in some cases even led to the bankruptcy of

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Speaker 1: the of the company. Enclosed end funds. It's totally different

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Speaker 1: because the medicine, the plan for how to get the

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Speaker 1: fund trading to ny V works every single time. And

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Speaker 1: all I'll tell you why, because we're not trying to

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Speaker 1: remake J. C. Penny in the image of Apple Computer,

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Speaker 1: which might or might not work. Or you know, we

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Speaker 1: could pick some that were fantastic successes um general growth

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Speaker 1: to follow on with one of Akman's amazing longs um

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Speaker 1: on the close end funt side, if the manager we're

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Speaker 1: just thinking about the investor, they could literally press a

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Speaker 1: button turn it into an e t F, which they

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Speaker 1: also those same managers. Black Rock is selling e t

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Speaker 1: s by the cartload. If they changed their closed end

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Speaker 1: fund into an open ended fund, because it didn't give

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Speaker 1: investors an exit at n a V for five six,

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Speaker 1: seven years, it would immediately go to n a V,

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Speaker 1: just like all e t f s are arbitrage double

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Speaker 1: if they're trading different than any of V. So they

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Speaker 1: could change it to an open ended fund, they could

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Speaker 1: tender for shares at no discount. They could liquidate the

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Speaker 1: fund and offer investors the chance to go into almost

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Speaker 1: the exact same products, whether it's New York communities or

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Speaker 1: or junk loans, or UM or energy equities MLPs UM.

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Speaker 1: There's five hundred closed in funds and there's thousands of

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Speaker 1: mutual funds and thousands of e t fs, So the

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Speaker 1: ability to go from eighty four to a hundred, you're

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Speaker 1: talking about return, and maybe it's the recapture of a

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Speaker 1: loss that the investor, of course UM, if they knew enough,

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Speaker 1: would want it every time. And the only thing standing

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Speaker 1: in your way is the manager that feels like they

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Speaker 1: have some god given right for that capital to be

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Speaker 1: permanent capital. And if they tender for shares, that means

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Speaker 1: less au M and less fees for them, and so

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Speaker 1: there's a huge um. There's really a huge problem where

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Speaker 1: the managers putting their own interests and the board is

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Speaker 1: putting the manager's interests ahead of the shareholders. And that's

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Speaker 1: where we come in. So why can't closed n funds

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Speaker 1: be arbitrage the same way E t f s can? So?

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Speaker 1: E t s have a mechanism where you can create

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Speaker 1: new shares if or redeem old chairs and so if

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Speaker 1: if it's ever trading below, you could buy it and

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Speaker 1: then redeem it, if it's trading above, you could sell

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Speaker 1: it and then create it and always at any V.

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Speaker 1: So there's that mechanism that tether is E t f

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Speaker 1: s two N A V closed end funds. It's like

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Speaker 1: a stock. You know, you may think IBM is worth

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Speaker 1: two to share, but you've got to find somebody to

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Speaker 1: sell to. You can't call our monk New York and

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Speaker 1: ask IBM to give you the two d bucks. So

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Speaker 1: so the things can trade at a big discount for

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Speaker 1: very very long time, and even at a big premium,

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Speaker 1: and so um. But there's a very simple fix, which

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Speaker 1: is they don't have to figure out some new fangled

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Speaker 1: way to run the company. They just need to offer

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Speaker 1: liquidity like a mutual fund or an e t F

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Speaker 1: that would get it back to ny V. And so

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Speaker 1: we've basically won all of the challenges we've had because

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Speaker 1: we're on the side of right. We get letters from

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Speaker 1: octogenarian saying I was in this fund for fifteen years.

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Speaker 1: I never thought I would see the light of day

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Speaker 1: to get out near n a V And um, we're

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Speaker 1: not doing it for them, but but at the same time,

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Speaker 1: we're doing it for our investors. It is a great

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Speaker 1: joy to be able to in certain market environments pick

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Speaker 1: through the closed in fund space and find literally dollars

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Speaker 1: trading for a two cents that you can pick up

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Speaker 1: the two cents and turn it back into a dollar.

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Speaker 1: And that's true even today. So markets are efficient, they're

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Speaker 1: just not that efficient. Well, yeah, there's you need someone

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Speaker 1: to come along and say I'm gonna change that. And

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Speaker 1: the closed in fund space really was lacking an institutional

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Speaker 1: manager to do that in size because institutions are also

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Speaker 1: that are an activists are also beholden to those same managers.

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Speaker 1: They need black rocks votes when they're an activist, so

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Speaker 1: they so they might say I'm not going to upset

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Speaker 1: the Apple card and annoy black Rock to the benefit

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Speaker 1: of thousands of investors and our investors if I need

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Speaker 1: to come to black Rock on my regular way, activism

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Speaker 1: when they're a big shareholder, so you have a little

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Speaker 1: bit of you know, people don't necessarily want to fight

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Speaker 1: UM the big asset managers, but we UM, We're very

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Speaker 1: happy to. We're not We're not activists in any other place.

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Speaker 1: And this is one of the best ARBs uh that

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Speaker 1: that you can find. And there's only one entity that suffers.

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Speaker 1: It's the asset manager that goes from managing seven trillion

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Speaker 1: to managing six point nine nine trillion. Thousands of investors

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Speaker 1: get to make gains that they would never otherwise get

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Speaker 1: really really interesting. Let's talk about one of the most

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Speaker 1: popular investment vehicles out there, SPACs special purpose acquisition companies.

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Speaker 1: SABA has about five and a half billion dollars in

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Speaker 1: that space. Is that right? That sounds like a lot

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Speaker 1: of money. You're the fifth largest SPACK holder along with

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Speaker 1: peers like Citadel, Millennium d E share. Your approach is

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Speaker 1: different than how retail investors look at SPACs. Tell us

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Speaker 1: a little bit about what you guys do. Yeah, SPACs

431
00:22:36,440 --> 00:22:39,639
Speaker 1: are this amazing thing in that it's all over the

432
00:22:39,680 --> 00:22:44,440
Speaker 1: press whenever there's an acquisition. It's also critiqued, sometimes maligned

433
00:22:44,480 --> 00:22:47,880
Speaker 1: for being a product that that ought not to exist.

434
00:22:48,080 --> 00:22:51,959
Speaker 1: Um uh, in the in the number of offerings that exist.

435
00:22:52,040 --> 00:22:55,439
Speaker 1: So so in the last year there's generally been a

436
00:22:55,520 --> 00:22:59,560
Speaker 1: negative ting tinge to the to the coverage about SPACs,

437
00:23:00,280 --> 00:23:04,000
Speaker 1: and they've performed poorly. They've performed poorly when they do SPAC.

438
00:23:04,119 --> 00:23:07,720
Speaker 1: So what's important to understand with spacts is the life

439
00:23:07,760 --> 00:23:11,920
Speaker 1: cycle that they start by being extraordinarily safe. And by

440
00:23:11,960 --> 00:23:14,240
Speaker 1: that I mean when the I p O happens, the

441
00:23:14,280 --> 00:23:17,960
Speaker 1: money is taken into trust, the manager doesn't touch it,

442
00:23:18,040 --> 00:23:21,600
Speaker 1: and the trust must buy us T bills. So from

443
00:23:21,600 --> 00:23:24,840
Speaker 1: time zero to the day that they are converting into

444
00:23:24,920 --> 00:23:28,040
Speaker 1: the company that they're taking public, you have the risk

445
00:23:28,080 --> 00:23:30,520
Speaker 1: of T bills, but you have some mark to market

446
00:23:30,640 --> 00:23:33,600
Speaker 1: risk as sentiment goes up and down. That sometimes that

447
00:23:33,680 --> 00:23:35,760
Speaker 1: ten dollars that you pay for at I p O.

448
00:23:36,200 --> 00:23:39,639
Speaker 1: You know, back in the heady days of let's say Ark,

449
00:23:39,680 --> 00:23:42,040
Speaker 1: when arquestrating at a hundred and fifty and flying cars

450
00:23:42,320 --> 00:23:46,960
Speaker 1: were you know, we're exciting people's imaginations. Um even before

451
00:23:46,960 --> 00:23:49,800
Speaker 1: the spack manager would find someone that ten dollars are

452
00:23:49,840 --> 00:23:53,159
Speaker 1: traded eleven or twelve or even higher. UM Today you

453
00:23:53,200 --> 00:23:55,440
Speaker 1: can find and for the last year, you can find

454
00:23:55,720 --> 00:23:59,439
Speaker 1: many billions offered at a discount. Instead of ten dollars

455
00:23:59,480 --> 00:24:03,080
Speaker 1: you get to pay is something like and UM one

456
00:24:03,160 --> 00:24:06,879
Speaker 1: year later or even ten months later that for certain

457
00:24:07,160 --> 00:24:09,840
Speaker 1: will be worth ten dollars. So on top of that

458
00:24:09,920 --> 00:24:12,359
Speaker 1: you also get the yield that is in T bills,

459
00:24:12,359 --> 00:24:15,399
Speaker 1: which right now is another hundred forty basis points. And

460
00:24:15,440 --> 00:24:18,480
Speaker 1: so you could put together something where if you screened

461
00:24:18,600 --> 00:24:22,000
Speaker 1: for SPACs and you look for high quality managers, you

462
00:24:22,040 --> 00:24:25,200
Speaker 1: can still find a four and a half percent return,

463
00:24:25,280 --> 00:24:27,880
Speaker 1: which is a certain return. But on top of that,

464
00:24:27,960 --> 00:24:30,679
Speaker 1: in case they find a company to buy and the

465
00:24:30,720 --> 00:24:33,400
Speaker 1: market gets very excited about it, whether it's electric vehicles

466
00:24:33,760 --> 00:24:36,640
Speaker 1: or media companies or whatever it may be. UM, you

467
00:24:36,720 --> 00:24:39,120
Speaker 1: are a stockholder and you don't have to take only

468
00:24:39,119 --> 00:24:41,720
Speaker 1: ten dollars back. That goes to fifteen or to the moon.

469
00:24:41,840 --> 00:24:44,120
Speaker 1: That's that's your profit. And so I I really look

470
00:24:44,119 --> 00:24:48,359
Speaker 1: at spacts like an incredibly valuable product in these times

471
00:24:48,359 --> 00:24:51,639
Speaker 1: were worried about inflation, because it's a guaranteed return in

472
00:24:51,680 --> 00:24:55,840
Speaker 1: the fours plus an equity option for free and um,

473
00:24:55,880 --> 00:24:57,960
Speaker 1: it's really hard to find something this safe in the

474
00:24:58,040 --> 00:25:01,439
Speaker 1: history of specs back a before you know the environment

475
00:25:01,480 --> 00:25:03,960
Speaker 1: today where they're actually quite a bit safer. Not one

476
00:25:04,000 --> 00:25:07,080
Speaker 1: time in history could you not get back trust value.

477
00:25:07,119 --> 00:25:09,320
Speaker 1: You always have trust value to look to, and trust

478
00:25:09,400 --> 00:25:12,719
Speaker 1: value is us T bills. What happens if the announcement

479
00:25:12,760 --> 00:25:16,760
Speaker 1: comes out of the acquisition and the public doesn't like it,

480
00:25:16,960 --> 00:25:19,600
Speaker 1: and the spact trades at a discount, there is a

481
00:25:19,640 --> 00:25:22,760
Speaker 1: subsequent vote about that eventually. Isn't that there's a vote

482
00:25:22,920 --> 00:25:26,520
Speaker 1: You can vote for the spack to to do the

483
00:25:26,560 --> 00:25:30,320
Speaker 1: deal or against. But that is even a separable question

484
00:25:30,400 --> 00:25:32,480
Speaker 1: from can you vote to get your money back? So

485
00:25:32,520 --> 00:25:34,800
Speaker 1: you could say, I've support the deal, but give me

486
00:25:34,840 --> 00:25:37,400
Speaker 1: my trust value back, which should be your ten dollars,

487
00:25:37,480 --> 00:25:39,879
Speaker 1: let's say, plus the the yield that you made on

488
00:25:39,960 --> 00:25:43,040
Speaker 1: the T bills, so you always have the ability to

489
00:25:43,119 --> 00:25:45,640
Speaker 1: get your money back. And so then as an investor,

490
00:25:45,680 --> 00:25:48,560
Speaker 1: I have to think about, well, how the market is

491
00:25:48,560 --> 00:25:50,760
Speaker 1: not just driven by the way things ought to be,

492
00:25:50,880 --> 00:25:53,159
Speaker 1: even though it's T bills. If there's six hundred of

493
00:25:53,200 --> 00:25:56,120
Speaker 1: these running around trying to find companies to buy. There

494
00:25:56,119 --> 00:25:58,680
Speaker 1: could be a period where because of losses, one is

495
00:25:58,720 --> 00:26:01,600
Speaker 1: suffering in their portfolio. You you might dump your SPACs

496
00:26:01,640 --> 00:26:03,560
Speaker 1: and put pressure on that market. It's I have to

497
00:26:03,600 --> 00:26:06,440
Speaker 1: think about how cheap get spacts get, even if they're

498
00:26:06,480 --> 00:26:09,960
Speaker 1: basically the safest investment I know of T bills in

499
00:26:09,960 --> 00:26:14,000
Speaker 1: a box UM and UM with a ten, ten month,

500
00:26:14,040 --> 00:26:16,480
Speaker 1: eleven month average life. You know you're gonna get your

501
00:26:16,480 --> 00:26:18,199
Speaker 1: money back, but in the meantime you have to be

502
00:26:18,240 --> 00:26:20,639
Speaker 1: ready for some mark to market pain. Let's talk about

503
00:26:20,680 --> 00:26:24,159
Speaker 1: tail hedging and crash protection funds. How do you find

504
00:26:24,359 --> 00:26:29,359
Speaker 1: efficient tail protection and what's the difference between paid for

505
00:26:29,480 --> 00:26:35,399
Speaker 1: tail protection with a zero carry and more expensive tail protection. Yeah,

506
00:26:35,560 --> 00:26:40,120
Speaker 1: so I've been running tail protection funds since two thousand nine,

507
00:26:40,680 --> 00:26:44,480
Speaker 1: and um so I've seen many hundreds of investors and

508
00:26:44,560 --> 00:26:46,520
Speaker 1: heard from them. How are they thinking about it? How

509
00:26:46,600 --> 00:26:48,480
Speaker 1: much premium do they want to spend? Do they look

510
00:26:48,520 --> 00:26:50,800
Speaker 1: at it as an insurance policy where you know, just

511
00:26:50,840 --> 00:26:53,359
Speaker 1: because your car doesn't get stolen or house doesn't go

512
00:26:53,400 --> 00:26:56,080
Speaker 1: on fire, you're you're not thinking that something bad happened.

513
00:26:56,040 --> 00:26:58,480
Speaker 1: You bought a policy and you spent it and its

514
00:26:58,520 --> 00:27:01,600
Speaker 1: portfolio insurance and then their investors that say, well, look,

515
00:27:01,720 --> 00:27:03,119
Speaker 1: I don't have a budget for that. I have to

516
00:27:03,160 --> 00:27:05,120
Speaker 1: keep up with the joneses, I have to make my

517
00:27:05,440 --> 00:27:08,640
Speaker 1: expected return. So is there a way that since I'm

518
00:27:08,680 --> 00:27:10,480
Speaker 1: not going to do the first one can is there

519
00:27:10,480 --> 00:27:12,639
Speaker 1: a way that you can find something that will have

520
00:27:13,080 --> 00:27:17,240
Speaker 1: very low um negative carry or burn or bleed some

521
00:27:17,280 --> 00:27:19,760
Speaker 1: people call it and um and so in the credit

522
00:27:19,840 --> 00:27:22,240
Speaker 1: or of market, in the last two or three years,

523
00:27:22,240 --> 00:27:25,359
Speaker 1: there has been, in my view, way to have your

524
00:27:25,400 --> 00:27:27,080
Speaker 1: cake and eat it too, to have a very low

525
00:27:27,119 --> 00:27:32,399
Speaker 1: cost or no cost portfolio of tail protection and still

526
00:27:32,440 --> 00:27:36,600
Speaker 1: benefit and so in um, you know, this strategy was

527
00:27:37,080 --> 00:27:40,720
Speaker 1: incredibly profitable even though it didn't have the negative carry

528
00:27:40,800 --> 00:27:44,760
Speaker 1: that one assumes they need to get a big payout.

529
00:27:45,160 --> 00:27:48,000
Speaker 1: So that sounds a bit like a free free lunch.

530
00:27:48,560 --> 00:27:52,320
Speaker 1: How do you get tail protection with with no cost

531
00:27:52,320 --> 00:27:55,760
Speaker 1: to carry? What risks are you assuming in order to

532
00:27:56,480 --> 00:28:01,040
Speaker 1: execute that? Uh So, there there's an there's no free

533
00:28:01,119 --> 00:28:06,560
Speaker 1: lunch anywhere, not even at Bloomberg. Uh So, um, I'm

534
00:28:06,560 --> 00:28:09,600
Speaker 1: getting free lunch. At least we got that going for

535
00:28:09,840 --> 00:28:12,160
Speaker 1: So that's the only free lunch on Wall Street. Well,

536
00:28:12,440 --> 00:28:15,919
Speaker 1: so the free lunch is not free. You are you

537
00:28:15,960 --> 00:28:18,320
Speaker 1: are making a bet. But what I see now and

538
00:28:18,480 --> 00:28:21,040
Speaker 1: for the last few years in the credit space is

539
00:28:21,040 --> 00:28:26,399
Speaker 1: that there is not enough differentiation between safe companies and

540
00:28:26,560 --> 00:28:29,080
Speaker 1: less safe or safe and dangerous. And by that I

541
00:28:29,119 --> 00:28:33,000
Speaker 1: mean if you look at the credit spreads of fifty

542
00:28:33,000 --> 00:28:35,919
Speaker 1: different companies rated triple B or single A, some of

543
00:28:35,960 --> 00:28:39,480
Speaker 1: them are ultra safe. They go by the names of McDonald's, IBM, E,

544
00:28:39,560 --> 00:28:44,520
Speaker 1: T and T, you know, Verizon, Um, Disney and But

545
00:28:44,600 --> 00:28:48,920
Speaker 1: the thing is that banks, federal express banks make loans

546
00:28:48,960 --> 00:28:52,040
Speaker 1: to these companies when Disney, when when IBM, but Red

547
00:28:52,040 --> 00:28:55,840
Speaker 1: Hat or Philip Morris, Bud Jewel and so banks have exposures,

548
00:28:56,080 --> 00:28:58,360
Speaker 1: and that when they go out and buy CDs, they

549
00:28:58,360 --> 00:29:01,680
Speaker 1: are not They are not brilliant hedgehow manager saying what's

550
00:29:01,720 --> 00:29:05,000
Speaker 1: the next en round? Like Jim Chainos. They're saying, what's

551
00:29:05,000 --> 00:29:07,120
Speaker 1: in my book, and I need to hedge it. And

552
00:29:07,160 --> 00:29:11,280
Speaker 1: so the CDs spread on some of the best companies

553
00:29:11,320 --> 00:29:14,080
Speaker 1: in the world market caps between a hundred and three

554
00:29:14,160 --> 00:29:18,040
Speaker 1: hundred billion dollars um, trade at very similar levels. Because

555
00:29:18,040 --> 00:29:20,880
Speaker 1: of that upward pressure pushing up the spread to names

556
00:29:20,920 --> 00:29:23,160
Speaker 1: that they're the banks are not pushing up higher, and

557
00:29:23,200 --> 00:29:25,400
Speaker 1: so you can set up a portfolio where you go

558
00:29:25,560 --> 00:29:28,320
Speaker 1: long risk to the IBM s of the world and

559
00:29:28,400 --> 00:29:32,200
Speaker 1: take that carry and buy protection on companies that are

560
00:29:32,200 --> 00:29:34,000
Speaker 1: not as safe. And so, just to use the example

561
00:29:34,000 --> 00:29:38,760
Speaker 1: of I was amazed coming into the COVID environment where

562
00:29:39,160 --> 00:29:42,920
Speaker 1: McDonald's had the same credit spread as a double B

563
00:29:43,120 --> 00:29:48,600
Speaker 1: rated online travel company called Saber, and Saber double B

564
00:29:48,840 --> 00:29:52,040
Speaker 1: was trading at twenty five basis points and McDonald's trading

565
00:29:53,200 --> 00:29:55,280
Speaker 1: but if you pay twenty five enough times, it can

566
00:29:55,280 --> 00:29:57,920
Speaker 1: add up. So we we put on these trades. You know,

567
00:29:58,040 --> 00:30:00,480
Speaker 1: imagine a book of thirty or forty names. You're you're

568
00:30:00,520 --> 00:30:04,000
Speaker 1: selling the McDonald's and buying the Saber exactly. And and

569
00:30:04,240 --> 00:30:07,120
Speaker 1: of course Saber was negatively affected by COVID, but even

570
00:30:07,160 --> 00:30:10,120
Speaker 1: today Saber trades at five hundred and guess where McDonald's

571
00:30:10,120 --> 00:30:14,680
Speaker 1: trains back at. And so there is a free lunch,

572
00:30:15,160 --> 00:30:17,360
Speaker 1: so to speak, that I didn't see until two thousand,

573
00:30:17,400 --> 00:30:20,240
Speaker 1: nineteen or twenty, which is that credit when it got

574
00:30:20,360 --> 00:30:23,520
Speaker 1: ultra tight because people were so confident that the FED

575
00:30:23,560 --> 00:30:26,160
Speaker 1: had the markets back, and the FED did extraordinary things,

576
00:30:26,360 --> 00:30:29,440
Speaker 1: you know, since two thousand and eight that credit spreads

577
00:30:29,640 --> 00:30:33,440
Speaker 1: were too clumped together and one could pick through the portfolio,

578
00:30:33,760 --> 00:30:35,720
Speaker 1: find the names that would be good tail hedges and

579
00:30:35,760 --> 00:30:38,600
Speaker 1: the names that would be bad ones, and set up

580
00:30:38,640 --> 00:30:41,920
Speaker 1: that trade and it it's worked in better than I thought,

581
00:30:41,920 --> 00:30:45,040
Speaker 1: and it's working again in so to put some numbers

582
00:30:45,080 --> 00:30:48,480
Speaker 1: on that, I recall reading the first couple of months

583
00:30:48,520 --> 00:30:52,960
Speaker 1: of that fun was up like to start the year,

584
00:30:53,000 --> 00:30:55,960
Speaker 1: you gave a little bit back, but not a whole lot.

585
00:30:56,000 --> 00:30:59,040
Speaker 1: I think you finished the year up some crazy number

586
00:30:59,120 --> 00:31:01,760
Speaker 1: like that. So we we have different funds, and not

587
00:31:01,800 --> 00:31:04,560
Speaker 1: to speak about any any in particular. Those numbers are

588
00:31:04,720 --> 00:31:09,040
Speaker 1: are in the frame correct, So so pretty close to

589
00:31:09,400 --> 00:31:11,880
Speaker 1: a zero carry, pretty close to a free launch. You

590
00:31:11,920 --> 00:31:14,160
Speaker 1: are assuming some risk, but it sounds like not a

591
00:31:14,160 --> 00:31:16,840
Speaker 1: lot of risk. Well, you know, I'm agnostic as to

592
00:31:17,040 --> 00:31:20,400
Speaker 1: which which strategy is right. It's really up to the individual.

593
00:31:20,440 --> 00:31:23,440
Speaker 1: If you say, well, should everyone have insurance? Should we

594
00:31:23,440 --> 00:31:26,320
Speaker 1: walk around with uh? You know, insurance? Sometimes we're mandated.

595
00:31:26,480 --> 00:31:29,160
Speaker 1: You want to get a car, you need insurance. In portfolios,

596
00:31:29,920 --> 00:31:33,840
Speaker 1: you get this problem where people don't necessarily think they

597
00:31:33,880 --> 00:31:35,959
Speaker 1: have a budget for it. If there and if they

598
00:31:36,000 --> 00:31:39,480
Speaker 1: have that constraint, I think paid for tell protection is

599
00:31:39,480 --> 00:31:42,520
Speaker 1: a whole lot better than not having anything because look

600
00:31:42,560 --> 00:31:44,240
Speaker 1: at what's going on now in the market, and I've

601
00:31:44,280 --> 00:31:47,280
Speaker 1: been seeing for the last year, whether it's from state pensions.

602
00:31:47,280 --> 00:31:50,040
Speaker 1: We just got one on board last month. UM and

603
00:31:50,360 --> 00:31:55,160
Speaker 1: university endowments. Incredible desire for strategies that will pay off

604
00:31:55,280 --> 00:32:00,360
Speaker 1: when there's volatility. Quite quite interesting. Last question about about

605
00:32:00,400 --> 00:32:05,480
Speaker 1: SABA Capital Hedge Fund. Where did the name SABA come from? Uh? So,

606
00:32:05,520 --> 00:32:08,200
Speaker 1: I was at I was at Deutscha, and there were

607
00:32:08,200 --> 00:32:11,160
Speaker 1: a lot of Deutsche prop groups and I wanted to

608
00:32:11,160 --> 00:32:13,720
Speaker 1: to brand it. And so I was trying to think,

609
00:32:14,040 --> 00:32:16,960
Speaker 1: what's easy to say, easy to spell, and hasn't been

610
00:32:16,960 --> 00:32:20,800
Speaker 1: taken and there wasn't really much much left. And Saba

611
00:32:20,880 --> 00:32:25,080
Speaker 1: means grandfather in Hebrew. My mother was raised in Israel

612
00:32:25,120 --> 00:32:29,520
Speaker 1: after the Holocaust, and her father, my Saba, saved the family,

613
00:32:29,800 --> 00:32:32,440
Speaker 1: saved her, you know, and and saved a lot of

614
00:32:32,600 --> 00:32:36,280
Speaker 1: innocent people of Um hid them. So I really felt,

615
00:32:36,360 --> 00:32:40,880
Speaker 1: as a kid, an incredible debt to to him, and

616
00:32:40,920 --> 00:32:43,120
Speaker 1: I wanted to honor him by by calling it that.

617
00:32:43,160 --> 00:32:44,880
Speaker 1: So we named it that at Deutsche was called SABA

618
00:32:44,920 --> 00:32:47,680
Speaker 1: Principal Strategies, And when we lifted the team out in

619
00:32:47,800 --> 00:32:50,760
Speaker 1: oh nine, we we kept the name. So it's Saba capital.

620
00:32:50,840 --> 00:32:54,479
Speaker 1: And if I recall reading correctly, your your grandfather built

621
00:32:54,920 --> 00:32:57,560
Speaker 1: a double wall of false wall and on in order

622
00:32:57,560 --> 00:33:01,040
Speaker 1: to hide people from the Nazis that are looking for

623
00:33:01,240 --> 00:33:04,120
Speaker 1: people's children. Is that right? Yeah, So he was a

624
00:33:04,160 --> 00:33:07,040
Speaker 1: carpenter and um, he had a hardware store after the

625
00:33:07,080 --> 00:33:10,760
Speaker 1: war in Israel. He didn't have um any wealth of

626
00:33:10,840 --> 00:33:13,320
Speaker 1: significance to speak of, but he was he had a

627
00:33:13,360 --> 00:33:16,200
Speaker 1: lot of vision. And there was a moment. My mother

628
00:33:16,280 --> 00:33:18,720
Speaker 1: was born in July forty one in the war saw Ghetto,

629
00:33:19,040 --> 00:33:23,240
Speaker 1: and sometime around forty two he realized he needed to

630
00:33:23,240 --> 00:33:25,520
Speaker 1: get her out of there, and he got fake papers

631
00:33:26,040 --> 00:33:29,840
Speaker 1: that showed he was a gentile with his wife and um,

632
00:33:29,880 --> 00:33:33,160
Speaker 1: and my mother was hidden on a farm, and so um,

633
00:33:33,240 --> 00:33:35,240
Speaker 1: yes he's he was a real hero. And I actually,

634
00:33:35,600 --> 00:33:39,000
Speaker 1: just a month or two ago, got to take my

635
00:33:39,040 --> 00:33:43,440
Speaker 1: eldest daughter to Yad Vashem in Israel and and explained

636
00:33:43,440 --> 00:33:46,760
Speaker 1: to her a bit about the history, really really intriguing stuff.

637
00:33:47,320 --> 00:33:49,280
Speaker 1: So so it made a lot of sense to spin

638
00:33:49,320 --> 00:33:52,920
Speaker 1: out and be a free standing fund instead of being

639
00:33:53,000 --> 00:33:57,040
Speaker 1: part of a larger bank and all of the baggage

640
00:33:57,040 --> 00:33:59,240
Speaker 1: that comes with that. Yeah, I I I love my

641
00:33:59,280 --> 00:34:01,320
Speaker 1: time at Deutsche In. But I had taken on enough

642
00:34:01,360 --> 00:34:05,480
Speaker 1: responsibility that when my boss left and UH left the

643
00:34:05,480 --> 00:34:07,600
Speaker 1: bank and he's actually now the head of the vision

644
00:34:07,600 --> 00:34:09,640
Speaker 1: fund at soft Bank, I had to make a choice.

645
00:34:09,640 --> 00:34:12,000
Speaker 1: Am I going to be a manager or an investor?

646
00:34:12,400 --> 00:34:14,760
Speaker 1: And I chose investor. And that was in late oh seven,

647
00:34:14,800 --> 00:34:17,719
Speaker 1: and the spinout happened early or nine. And along the

648
00:34:17,760 --> 00:34:21,480
Speaker 1: way came Lehman Brothers, which was, you know, just a

649
00:34:21,520 --> 00:34:24,239
Speaker 1: mind blowing experience. I was at the New York Fed

650
00:34:24,480 --> 00:34:27,120
Speaker 1: the weekend Lehman failed, and you know, we lost quite

651
00:34:27,120 --> 00:34:28,919
Speaker 1: a bit of money in a eight like like most

652
00:34:28,920 --> 00:34:33,280
Speaker 1: desks are all desks, but um, but incredible, incredible experience

653
00:34:33,320 --> 00:34:35,600
Speaker 1: and lessons to well, what were you doing with the

654
00:34:35,600 --> 00:34:40,120
Speaker 1: New York Fed UH that weekend? It looks it's gonna

655
00:34:40,160 --> 00:34:43,440
Speaker 1: sound so silly, like they call us in um and

656
00:34:43,480 --> 00:34:47,400
Speaker 1: they wanted us to game out on the weekend. Um.

657
00:34:47,440 --> 00:34:51,400
Speaker 1: If Lehman was closed for business on Monday, if it

658
00:34:51,440 --> 00:34:55,200
Speaker 1: was done, UM, could you on Sunday, the day before,

659
00:34:55,280 --> 00:34:58,319
Speaker 1: could you unwind all sorts of trades contingent on them

660
00:34:58,320 --> 00:35:01,920
Speaker 1: not being there? Like, let's let's do a pre mortem.

661
00:35:01,960 --> 00:35:05,040
Speaker 1: What can we do to reduce the amount of counterparty exposure,

662
00:35:05,320 --> 00:35:07,239
Speaker 1: and it was really like dectures in the Titanic. I

663
00:35:07,239 --> 00:35:11,520
Speaker 1: think Deutsche Bank had hundreds of thousands of swaps facing Lehman,

664
00:35:12,000 --> 00:35:14,200
Speaker 1: and it was like we were able to that week

665
00:35:14,280 --> 00:35:17,120
Speaker 1: and unwind maybe a dozen of them. Really, And that's

666
00:35:17,160 --> 00:35:20,360
Speaker 1: before we start talking about one step removed, where you

667
00:35:20,400 --> 00:35:22,719
Speaker 1: have counterparties who then threw it off to Lehman on

668
00:35:22,760 --> 00:35:25,279
Speaker 1: top of it, or were you including that in that list? No,

669
00:35:25,520 --> 00:35:28,719
Speaker 1: just direct exposure was hundreds of thousands of rates, fcs

670
00:35:28,800 --> 00:35:31,560
Speaker 1: and credit swaps. I was in charge of credit, so

671
00:35:31,640 --> 00:35:34,080
Speaker 1: we were there. I was in a room of you know,

672
00:35:34,160 --> 00:35:36,600
Speaker 1: all the major banks sent their head of credit, and

673
00:35:36,760 --> 00:35:39,320
Speaker 1: there were other rooms had head of you know, mortgages

674
00:35:39,400 --> 00:35:42,640
Speaker 1: had CEO. But um I got in on a Saturday

675
00:35:42,680 --> 00:35:45,719
Speaker 1: at at one pm and I left maybe Sunday at

676
00:35:45,719 --> 00:35:49,560
Speaker 1: five am. So I've heard people complain that the FED

677
00:35:49,640 --> 00:35:53,680
Speaker 1: made a terrible mistake not rescuing Lehman. But no matter

678
00:35:53,719 --> 00:35:56,720
Speaker 1: how I've looked at Lehman Brothers, hold aside the fact

679
00:35:56,719 --> 00:36:00,480
Speaker 1: that they were technically insolvent, it sounds like it was

680
00:36:00,560 --> 00:36:03,799
Speaker 1: all but impossible for Lehman to be rescued. There was

681
00:36:03,920 --> 00:36:08,080
Speaker 1: just far too much risk, far too much exposure for everybody,

682
00:36:08,120 --> 00:36:11,120
Speaker 1: and it was really sort of a mercy killing, you know.

683
00:36:11,320 --> 00:36:14,759
Speaker 1: I think if the FED knew what was going to

684
00:36:14,800 --> 00:36:17,200
Speaker 1: happen in just the intervening days with A. I. G.

685
00:36:17,400 --> 00:36:19,319
Speaker 1: And the others, I think they would have rescued it.

686
00:36:19,400 --> 00:36:22,200
Speaker 1: The price tag would have been a drop in the

687
00:36:22,239 --> 00:36:25,640
Speaker 1: bucket compared to um what they eventually had to do

688
00:36:25,719 --> 00:36:28,799
Speaker 1: with all the different programs and everything that came after it.

689
00:36:28,920 --> 00:36:32,880
Speaker 1: So so I think that there was a moral imperative

690
00:36:32,920 --> 00:36:38,439
Speaker 1: they thought to not rewarding uh greed and treating risk

691
00:36:38,560 --> 00:36:42,040
Speaker 1: like it's always gonna get bailed out. But we learned

692
00:36:42,040 --> 00:36:44,000
Speaker 1: that the FED couldn't see in front of their nose,

693
00:36:44,080 --> 00:36:46,640
Speaker 1: because only days later we have Fannie and Freddie any

694
00:36:46,680 --> 00:36:49,560
Speaker 1: I G that needed massive bailouts, and so Barry. I

695
00:36:49,560 --> 00:36:51,520
Speaker 1: don't know the price tag, but whatever it was, I

696
00:36:51,520 --> 00:36:54,080
Speaker 1: think it was a tiny drop compared to the damage.

697
00:36:54,800 --> 00:36:57,600
Speaker 1: You know. I always thought a lot of people don't

698
00:36:57,640 --> 00:37:02,279
Speaker 1: remember that buff It made an offer to Fold to

699
00:37:02,360 --> 00:37:05,800
Speaker 1: bail out Lehman, and Fold rejected him, and ultimately Buffet

700
00:37:05,840 --> 00:37:08,319
Speaker 1: ended up taking a small piece of goldman Um. But

701
00:37:08,400 --> 00:37:12,239
Speaker 1: I always imagined that the conversation with Bernanke, and the

702
00:37:12,320 --> 00:37:16,799
Speaker 1: desk was, wait, he turned down Buffett's money, how can

703
00:37:16,840 --> 00:37:20,560
Speaker 1: we give money to this yachts if he turned down

704
00:37:20,560 --> 00:37:23,600
Speaker 1: Berkshire hath Away And I always felt that was the

705
00:37:23,640 --> 00:37:26,600
Speaker 1: moral hazard, that you an opportunity to save the firm

706
00:37:26,960 --> 00:37:30,319
Speaker 1: you refused, Sorry, we can't help you. Yeah, so they

707
00:37:30,400 --> 00:37:32,719
Speaker 1: did take money, if I'm not mistaken, from a Korean bank,

708
00:37:32,920 --> 00:37:36,120
Speaker 1: and I think it was just Buffet's terms were worse

709
00:37:36,160 --> 00:37:38,120
Speaker 1: than the Korean bank. But of course you're right, they

710
00:37:38,120 --> 00:37:41,040
Speaker 1: should have taken it from from both, because once in

711
00:37:41,080 --> 00:37:44,360
Speaker 1: a financial institution with such massive leverage starts to unravel,

712
00:37:44,760 --> 00:37:47,239
Speaker 1: it's uh, it's self fulfilling, it has its own the

713
00:37:47,320 --> 00:37:50,239
Speaker 1: decline has its own gravity. And you take it from

714
00:37:50,280 --> 00:37:53,239
Speaker 1: the Korean bank, and you take it from Buffett and

715
00:37:53,440 --> 00:37:56,040
Speaker 1: uh and you uh, you know, you count your blessings

716
00:37:56,080 --> 00:37:57,960
Speaker 1: that you didn't go under. This would have been after

717
00:37:58,000 --> 00:38:02,880
Speaker 1: he already rescued Solomon Brother. It's the financial sector. Goodhouse

718
00:38:02,960 --> 00:38:06,560
Speaker 1: king being seal of approval. Lehman might have might have

719
00:38:06,600 --> 00:38:09,239
Speaker 1: survived if he took the money from Buffett. Who knows. Yeah,

720
00:38:09,280 --> 00:38:12,040
Speaker 1: I don't think they had such large losses that couldn't

721
00:38:12,040 --> 00:38:14,400
Speaker 1: you couldn't put umpty empty back together again. But so

722
00:38:14,400 --> 00:38:17,879
Speaker 1: so you know, I was already h planning the hedge

723
00:38:17,920 --> 00:38:20,960
Speaker 1: fund from well before that. And so when I left

724
00:38:21,000 --> 00:38:24,200
Speaker 1: Deutsche Bank in February, around February, middle of February O nine.

725
00:38:24,480 --> 00:38:27,279
Speaker 1: By April one, O nine's only six weeks later, I

726
00:38:27,320 --> 00:38:29,080
Speaker 1: was already up and running with the fund that I

727
00:38:29,160 --> 00:38:33,400
Speaker 1: had been prepping. Uh Saba has had some spectacular trades.

728
00:38:33,960 --> 00:38:36,880
Speaker 1: Let's let's talk about some of your most successful ones.

729
00:38:37,200 --> 00:38:41,840
Speaker 1: I mentioned earlier. The Tail fund practically doubled in um

730
00:38:42,680 --> 00:38:45,520
Speaker 1: The fund itself was up thirty three percent in that year.

731
00:38:46,600 --> 00:38:51,000
Speaker 1: How does having one of your strategies up a hundred

732
00:38:51,040 --> 00:38:54,680
Speaker 1: percent affect how you think about trading? Do you just

733
00:38:54,960 --> 00:38:59,160
Speaker 1: leave it and and not interfere or are those sort

734
00:38:59,160 --> 00:39:03,200
Speaker 1: of returns do do the mean reversion light start flashing

735
00:39:03,239 --> 00:39:07,319
Speaker 1: and encourage you to start paring back a bit? Right?

736
00:39:07,440 --> 00:39:11,000
Speaker 1: So specifically in the tail fund, since investors in that

737
00:39:11,080 --> 00:39:12,920
Speaker 1: fund or using it for a purpose, or using it

738
00:39:12,960 --> 00:39:14,520
Speaker 1: for a hedge I don't want to be the one

739
00:39:14,560 --> 00:39:17,839
Speaker 1: to say, hey, the loads are in, let's let's take

740
00:39:17,840 --> 00:39:20,840
Speaker 1: it off. And you know, people's crystal balls are I

741
00:39:20,840 --> 00:39:23,680
Speaker 1: think always cloudy if if not worse. But in those

742
00:39:23,800 --> 00:39:26,600
Speaker 1: environments it's especially hard to see. I would say when

743
00:39:26,640 --> 00:39:29,160
Speaker 1: we talk about two, this is another one of those

744
00:39:29,160 --> 00:39:32,680
Speaker 1: hards to see environments. So I'm not generally tweaking that

745
00:39:32,880 --> 00:39:35,799
Speaker 1: too much. In our flagship fund where tail doesn't have

746
00:39:35,840 --> 00:39:37,799
Speaker 1: to be the biggest part or you know, and we

747
00:39:37,840 --> 00:39:41,839
Speaker 1: had very similar returns. Um we did find in that

748
00:39:41,960 --> 00:39:45,640
Speaker 1: environment incredible miss pricings, and so we were able to

749
00:39:45,719 --> 00:39:48,440
Speaker 1: monetize some of the tail protection and invest in the

750
00:39:48,440 --> 00:39:52,680
Speaker 1: then you know, most miss priced things, which was relationships

751
00:39:52,719 --> 00:39:56,960
Speaker 1: between the credit rutives and the bonds or various et fs. Basically,

752
00:39:56,960 --> 00:40:02,160
Speaker 1: the bond market broke, and Uh, there was an incredible

753
00:40:02,160 --> 00:40:05,000
Speaker 1: opportunity to do things that I didn't even think I'd

754
00:40:05,040 --> 00:40:08,719
Speaker 1: ever see again after a wait, really really intriguing. Let's

755
00:40:08,800 --> 00:40:13,000
Speaker 1: let's talk a little bit about Bruno excel a k A.

756
00:40:13,160 --> 00:40:16,960
Speaker 1: The London whale Uh, that trade lost over two billion

757
00:40:16,960 --> 00:40:20,360
Speaker 1: dollars for JP Morgan. You were on the other side

758
00:40:20,360 --> 00:40:23,239
Speaker 1: of that trade and ostensibly picked up some of that,

759
00:40:23,520 --> 00:40:26,080
Speaker 1: not all, but some of that two billion. Tell us

760
00:40:26,080 --> 00:40:29,200
Speaker 1: a little bit about the London whale trade, which I

761
00:40:29,320 --> 00:40:34,480
Speaker 1: recall reading you discussing at a conference before everything went

762
00:40:34,520 --> 00:40:36,920
Speaker 1: to hell, tell us about that, yes, and and the

763
00:40:36,960 --> 00:40:40,200
Speaker 1: eventual price tag what they had started the estimated too.

764
00:40:40,200 --> 00:40:42,719
Speaker 1: I think they acknowledged some number like six point six

765
00:40:42,719 --> 00:40:45,560
Speaker 1: billion ended up being even a lot worse. So I

766
00:40:45,680 --> 00:40:49,879
Speaker 1: am I noticed, being that we're looking very closely at

767
00:40:50,400 --> 00:40:54,080
Speaker 1: miss pricings in derivatives, I noticed that an older series

768
00:40:54,719 --> 00:40:56,920
Speaker 1: of the index, the creditor at of index, by the way,

769
00:40:56,920 --> 00:40:59,680
Speaker 1: I should say, is the most liquid product in fixed income,

770
00:41:00,200 --> 00:41:03,600
Speaker 1: certainly in credit. The the investment grade one trades about

771
00:41:03,640 --> 00:41:07,040
Speaker 1: fifty billion a day. It has basically zero bid offer cost.

772
00:41:07,080 --> 00:41:10,040
Speaker 1: You can get in and out very cleanly with in billions,

773
00:41:10,040 --> 00:41:12,680
Speaker 1: and that's why firms like Bridgewater and a q R

774
00:41:12,800 --> 00:41:16,560
Speaker 1: use it in enormous quantities. Back then, I noticed that

775
00:41:16,640 --> 00:41:20,200
Speaker 1: an older series one that was not current anymore, retained

776
00:41:20,320 --> 00:41:23,759
Speaker 1: having a lot of interest, and that interest all came

777
00:41:23,840 --> 00:41:27,320
Speaker 1: from one counterparty, according to market sources, and one counterparty

778
00:41:27,400 --> 00:41:29,839
Speaker 1: was kind of driving the interest in it. And one

779
00:41:29,880 --> 00:41:33,360
Speaker 1: thing that I noticed was that um it was priced

780
00:41:33,680 --> 00:41:35,640
Speaker 1: very differently than the others. So if you have just

781
00:41:35,719 --> 00:41:38,120
Speaker 1: imagine the SMP five hundred and it has an at

782
00:41:38,120 --> 00:41:40,759
Speaker 1: asset value of one, well it's gonna trade right at

783
00:41:40,760 --> 00:41:42,680
Speaker 1: one or someone's gonna arbitrage it. Now, if you have

784
00:41:42,719 --> 00:41:45,440
Speaker 1: the older series before they change three or four names.

785
00:41:45,920 --> 00:41:49,239
Speaker 1: If if the current series at one and the older

786
00:41:49,280 --> 00:41:52,480
Speaker 1: series that you know, point nine or something, that's that's

787
00:41:52,520 --> 00:41:56,759
Speaker 1: really strange that that you have this kind of difference, UM,

788
00:41:56,800 --> 00:41:59,040
Speaker 1: where the some of the parts is not the same

789
00:41:59,080 --> 00:42:00,880
Speaker 1: as the whole. And I and I noticed that it

790
00:42:00,920 --> 00:42:03,640
Speaker 1: was it was too low. You're able to buy credit

791
00:42:03,640 --> 00:42:07,920
Speaker 1: protection for too low a number comparing the pieces to

792
00:42:07,960 --> 00:42:10,919
Speaker 1: the whole. And I wanted to understand why. And through

793
00:42:10,920 --> 00:42:14,200
Speaker 1: a lot of work we started to see some strange patterns.

794
00:42:14,520 --> 00:42:17,680
Speaker 1: We knew that it was a trader in London that

795
00:42:17,840 --> 00:42:21,880
Speaker 1: had by all accounts of this there was it was

796
00:42:21,920 --> 00:42:26,880
Speaker 1: basically everybody against one and UM and we noticed patterns

797
00:42:26,880 --> 00:42:30,040
Speaker 1: where in the final days of a week, or particularly

798
00:42:30,080 --> 00:42:32,360
Speaker 1: the final days of a month, there would be unusual

799
00:42:32,400 --> 00:42:36,200
Speaker 1: trading which smelled like someone trying to mark market. You know,

800
00:42:36,239 --> 00:42:38,759
Speaker 1: I'm not saying that's what they did, but that's what

801
00:42:38,880 --> 00:42:41,759
Speaker 1: the data showed that there was something going on. And

802
00:42:41,800 --> 00:42:44,239
Speaker 1: so we took the other side. And as you said,

803
00:42:44,600 --> 00:42:47,279
Speaker 1: I went to speak at a conference for boys and

804
00:42:47,520 --> 00:42:50,160
Speaker 1: boys girls Harbor. I think the charity was called and

805
00:42:50,200 --> 00:42:53,080
Speaker 1: I wanted to come up with something accessible. I want

806
00:42:53,120 --> 00:42:55,840
Speaker 1: to talk about an index, not some weird single company.

807
00:42:56,239 --> 00:42:58,279
Speaker 1: I go to present and it's at JP Morgan. The

808
00:42:58,320 --> 00:43:01,439
Speaker 1: conference is held at JP Morgan, and I talked about

809
00:43:01,480 --> 00:43:03,359
Speaker 1: and I say, you know, you have this trader that's

810
00:43:03,360 --> 00:43:05,960
Speaker 1: really uh taking on everybody and and it's and we

811
00:43:06,000 --> 00:43:07,840
Speaker 1: can all do the same math, and why why is

812
00:43:07,880 --> 00:43:10,880
Speaker 1: it trading there? And uh. It took about six months

813
00:43:11,640 --> 00:43:14,840
Speaker 1: but eventually cost the bank six billion dollars. And so

814
00:43:15,040 --> 00:43:18,160
Speaker 1: despite you know Jamie Diamond highly regarded as one of

815
00:43:18,200 --> 00:43:20,960
Speaker 1: the great bank CEOs of all time, the idea that

816
00:43:21,000 --> 00:43:24,120
Speaker 1: the bank could have lost that much on, by the way,

817
00:43:24,160 --> 00:43:26,920
Speaker 1: a notional quantity. So that's the lost six billion, a

818
00:43:27,000 --> 00:43:31,239
Speaker 1: quantity probably three to four hundred billion, uh and out

819
00:43:31,239 --> 00:43:34,120
Speaker 1: of some London desk taking risk to us credit. It

820
00:43:34,160 --> 00:43:36,480
Speaker 1: really is mind blowing. And so when it all ended,

821
00:43:37,160 --> 00:43:39,440
Speaker 1: someone from JP Morgan came over to our office and

822
00:43:39,480 --> 00:43:42,360
Speaker 1: we were one of the larger people on the other side,

823
00:43:42,360 --> 00:43:44,600
Speaker 1: but as you said, we were not nearly their size.

824
00:43:45,040 --> 00:43:47,319
Speaker 1: UM came over with a piece of paper and said,

825
00:43:47,320 --> 00:43:49,840
Speaker 1: write down your number for letting us out. Of this trade,

826
00:43:50,400 --> 00:43:52,120
Speaker 1: and if you do, we're going to have an extra

827
00:43:52,160 --> 00:43:55,359
Speaker 1: great relationship from now on. Uh. I wrote the number

828
00:43:55,400 --> 00:43:58,279
Speaker 1: down we traded. It was we traded fifteen billion and

829
00:43:58,840 --> 00:44:01,960
Speaker 1: one one trade. That was the size we had. And um,

830
00:44:03,239 --> 00:44:07,000
Speaker 1: we have a good relationship with JP Morgan. I would

831
00:44:07,040 --> 00:44:09,120
Speaker 1: imagine you would after being on the other side of

832
00:44:09,120 --> 00:44:12,480
Speaker 1: that trade. Did they do that with all of their counterparties?

833
00:44:12,880 --> 00:44:15,960
Speaker 1: I think so? Um, Look, we weren't. It was nothing personal.

834
00:44:16,000 --> 00:44:18,560
Speaker 1: It's just someone's again like closed in fund, someone selling

835
00:44:18,560 --> 00:44:22,600
Speaker 1: a dollar for seventy five cents, and and it's that's

836
00:44:22,640 --> 00:44:26,560
Speaker 1: that's our bread and butter, and especially the the spacks.

837
00:44:26,600 --> 00:44:28,319
Speaker 1: It's it's a little easier because you know you're gonna

838
00:44:28,320 --> 00:44:31,239
Speaker 1: get any v back, But this one's tougher because you know,

839
00:44:31,280 --> 00:44:34,160
Speaker 1: we're tiny compared to JP Morgan and UH and so

840
00:44:34,360 --> 00:44:37,200
Speaker 1: we were one of four or five counterparties that were

841
00:44:37,280 --> 00:44:39,560
Speaker 1: quite large in the trade. We made a few hundred

842
00:44:39,560 --> 00:44:43,560
Speaker 1: million dollars from it. But um, but it was more

843
00:44:43,800 --> 00:44:47,440
Speaker 1: the detective work to find it than the than the

844
00:44:47,480 --> 00:44:50,680
Speaker 1: actual game that I think is is what stays with me. Huh,

845
00:44:50,840 --> 00:44:53,680
Speaker 1: really really quite fascinating. Let's talk a little bit about

846
00:44:53,680 --> 00:44:57,000
Speaker 1: ever Grand, which has become a bit of a debacle

847
00:44:57,360 --> 00:44:59,600
Speaker 1: over in China, tell us a little bit about your

848
00:44:59,600 --> 00:45:02,879
Speaker 1: involved in that. So I thought, Barry, we were gonna

849
00:45:02,880 --> 00:45:05,120
Speaker 1: only talk about my greatest trades, and now you're mentioning

850
00:45:05,680 --> 00:45:07,680
Speaker 1: a giant loss maker. So let's do it. Not well,

851
00:45:08,000 --> 00:45:11,120
Speaker 1: this is this is a great trade, just not a

852
00:45:11,120 --> 00:45:15,960
Speaker 1: positive one. Um No, it's only fair. So Evergrands stuck

853
00:45:16,000 --> 00:45:20,000
Speaker 1: out to us as really interesting because we run a

854
00:45:20,040 --> 00:45:24,480
Speaker 1: screen that says, show me the credit spread of a company,

855
00:45:24,920 --> 00:45:27,000
Speaker 1: what the you know, with the spread over treasuries or

856
00:45:27,040 --> 00:45:31,520
Speaker 1: library or sofur is, and and chart that against the

857
00:45:31,560 --> 00:45:34,440
Speaker 1: market cap of the company. So how big it is

858
00:45:34,520 --> 00:45:37,480
Speaker 1: and how volatile the stock is the you know, if

859
00:45:37,480 --> 00:45:39,560
Speaker 1: you look at the equity options. So if you look

860
00:45:39,600 --> 00:45:42,360
Speaker 1: for companies that have a credit spread like Evergrand of

861
00:45:42,440 --> 00:45:45,000
Speaker 1: over a thousand basis points, it did. It had that

862
00:45:45,040 --> 00:45:47,239
Speaker 1: credit spread when it was totally healthy, when it had

863
00:45:47,280 --> 00:45:50,080
Speaker 1: a market cap of forty billion dollars and holdings in

864
00:45:50,520 --> 00:45:53,840
Speaker 1: various entities that are not even in the real estate space,

865
00:45:53,920 --> 00:45:57,520
Speaker 1: like of like electric cars. You know, on top of

866
00:45:57,600 --> 00:46:01,520
Speaker 1: the being the behemoth in the needs property market, you

867
00:46:01,520 --> 00:46:03,680
Speaker 1: you have forty billion of equity, but you have a

868
00:46:03,680 --> 00:46:06,480
Speaker 1: credit spread of eleven d basis point that's basically unheard of,

869
00:46:06,800 --> 00:46:09,840
Speaker 1: and you have equity options that are trading at a

870
00:46:09,840 --> 00:46:12,320
Speaker 1: pretty attractive level. If you wanted to buy that bond,

871
00:46:12,640 --> 00:46:14,920
Speaker 1: you have eleven hundred basis points. And if you go

872
00:46:14,960 --> 00:46:17,399
Speaker 1: and spend that eleven hundred and equity puts, you can

873
00:46:17,440 --> 00:46:20,359
Speaker 1: hedge yourself quite a bit on the all the way

874
00:46:20,400 --> 00:46:24,000
Speaker 1: down from far down to you know, near zero. So

875
00:46:24,000 --> 00:46:26,760
Speaker 1: so why didn't that trade work out? So we didn't

876
00:46:26,760 --> 00:46:29,879
Speaker 1: hedge ourselves down to near zero? We we you know,

877
00:46:30,280 --> 00:46:32,839
Speaker 1: we thought that the We didn't think the company the

878
00:46:32,880 --> 00:46:36,600
Speaker 1: company was going to blow up, and we also um

879
00:46:36,800 --> 00:46:38,799
Speaker 1: thought that there would be decent recovery value and there

880
00:46:38,840 --> 00:46:41,240
Speaker 1: may still be by the way, but um, the way

881
00:46:41,280 --> 00:46:45,359
Speaker 1: everything went south so quickly. Um, we ended up having

882
00:46:45,360 --> 00:46:47,719
Speaker 1: not enough hedge on and it was it was a

883
00:46:47,760 --> 00:46:51,000
Speaker 1: loss making trade. But I would say even just it,

884
00:46:51,440 --> 00:46:55,120
Speaker 1: these kinds of screens can help identify things that become problems,

885
00:46:55,160 --> 00:46:57,400
Speaker 1: and we've we've seen that in a number of cases

886
00:46:57,440 --> 00:47:01,680
Speaker 1: where you know, the markets today Barry should be more

887
00:47:01,680 --> 00:47:05,120
Speaker 1: connected when you think about the passage of time and technology.

888
00:47:05,200 --> 00:47:08,239
Speaker 1: But when I was at Deutsche Bank, the credit and

889
00:47:08,280 --> 00:47:11,319
Speaker 1: equity departments were on different floors and they spoke to

890
00:47:11,320 --> 00:47:13,440
Speaker 1: each other, but you had this segmentation, and you assume

891
00:47:13,480 --> 00:47:16,960
Speaker 1: over time things will get more and more connected. But

892
00:47:17,120 --> 00:47:21,040
Speaker 1: it requires different disciplines, different mandates, and so sometimes you

893
00:47:21,080 --> 00:47:22,759
Speaker 1: can get a very high credit spread and a low

894
00:47:22,800 --> 00:47:25,000
Speaker 1: equity of vol or a very low credit spread and

895
00:47:25,000 --> 00:47:26,880
Speaker 1: a very high equity of vault, and that might point

896
00:47:26,920 --> 00:47:30,719
Speaker 1: to UM something that that can lead to, whether it's

897
00:47:30,800 --> 00:47:33,640
Speaker 1: us doing the r V or someone saying I see

898
00:47:33,640 --> 00:47:35,759
Speaker 1: a short here, I see along here, And so I

899
00:47:35,840 --> 00:47:39,759
Speaker 1: really do love UM looking across markets for clues. And

900
00:47:40,160 --> 00:47:42,719
Speaker 1: the reason I asked you about ever grand is I

901
00:47:42,760 --> 00:47:45,839
Speaker 1: began my career on a trading desk, and anybody who

902
00:47:45,880 --> 00:47:48,840
Speaker 1: only talked about the winners and never talked about their losers,

903
00:47:49,280 --> 00:47:51,319
Speaker 1: I know they were full crap, and I can pay

904
00:47:51,320 --> 00:47:56,680
Speaker 1: any attention. But people who are really UM skilled and

905
00:47:56,760 --> 00:48:00,080
Speaker 1: polished traders, their losses are a badge of honor and

906
00:48:00,120 --> 00:48:02,080
Speaker 1: they treat it that way. And so that's why I

907
00:48:02,080 --> 00:48:05,160
Speaker 1: had to ask you about that. Following the London whale,

908
00:48:05,520 --> 00:48:07,719
Speaker 1: let's talk about a couple of other things you do

909
00:48:07,800 --> 00:48:12,960
Speaker 1: that I think are really really interesting. You mentioned closed

910
00:48:13,120 --> 00:48:17,279
Speaker 1: and funds. Uh and some mispricings in that space in

911
00:48:17,360 --> 00:48:19,880
Speaker 1: my prep for this, and and you might have referenced

912
00:48:19,880 --> 00:48:22,960
Speaker 1: this to me. Um Bill Ackman was a Deutsche banklin

913
00:48:23,080 --> 00:48:25,600
Speaker 1: for a long time. He has some closed and funds,

914
00:48:26,080 --> 00:48:29,800
Speaker 1: some of which run at a pretty substantial discount to

915
00:48:29,880 --> 00:48:32,400
Speaker 1: n A V. Tell us a little bit about trading

916
00:48:32,440 --> 00:48:36,320
Speaker 1: with Acman. Sure, so I I met Acman and oh

917
00:48:36,520 --> 00:48:39,600
Speaker 1: two and Uh I went to go see him after

918
00:48:39,680 --> 00:48:42,799
Speaker 1: we had done some trades in NB I A the

919
00:48:42,840 --> 00:48:49,279
Speaker 1: bond insure and UH defunct bond insure. Basically, Uh, so

920
00:48:49,560 --> 00:48:52,360
Speaker 1: I went to his office and uh there were boxes

921
00:48:52,440 --> 00:48:55,160
Speaker 1: piles to the ceiling. They were full. They were with

922
00:48:55,200 --> 00:48:57,920
Speaker 1: offer show of the work he had done on n

923
00:48:57,960 --> 00:49:01,279
Speaker 1: B I A. And so I saw first hand how

924
00:49:01,360 --> 00:49:05,840
Speaker 1: he understood that UM aside from and looking at investing

925
00:49:05,880 --> 00:49:08,239
Speaker 1: that h you know, is this an attractive stock god

926
00:49:08,239 --> 00:49:11,160
Speaker 1: to go up twenty or thirty percent? He also understands

927
00:49:11,239 --> 00:49:14,640
Speaker 1: when there's potentially ways to make fifty times your money

928
00:49:14,760 --> 00:49:17,560
Speaker 1: or twenty times your money, like he did in n BIA.

929
00:49:17,680 --> 00:49:20,719
Speaker 1: And he's done in general growth and coupang and you know,

930
00:49:20,760 --> 00:49:24,360
Speaker 1: things like that his closed end fund because it happened

931
00:49:24,400 --> 00:49:26,400
Speaker 1: to have launched at a time where he hit a

932
00:49:26,480 --> 00:49:29,880
Speaker 1: draw down. As all investors you know, great and not

933
00:49:29,960 --> 00:49:33,320
Speaker 1: so great do. UM. His closed end fund has stayed

934
00:49:33,360 --> 00:49:35,479
Speaker 1: at a very large discount. So I talked to before

935
00:49:35,480 --> 00:49:37,640
Speaker 1: about buying stuff at eight eight five cents in the dollar.

936
00:49:37,840 --> 00:49:40,480
Speaker 1: Bill Ackman's fund trading at about sixty eight cents in

937
00:49:40,520 --> 00:49:44,160
Speaker 1: the dollar. But that's not something that we as activists

938
00:49:44,200 --> 00:49:47,640
Speaker 1: can can take on because he's already set the rules

939
00:49:47,680 --> 00:49:49,520
Speaker 1: so that he has the majority of the voting rights.

940
00:49:49,640 --> 00:49:51,680
Speaker 1: So there wouldn't be a way too for the activist

941
00:49:51,960 --> 00:49:55,799
Speaker 1: to have an activist UM couldn't force a result on him. Yeah.

942
00:49:55,880 --> 00:49:57,799
Speaker 1: But at the same time, you know, he has, to

943
00:49:57,920 --> 00:50:01,160
Speaker 1: his credit, bought back a lot of the stock and UM.

944
00:50:01,200 --> 00:50:03,640
Speaker 1: And he's also UM uh you know, done quite well

945
00:50:03,680 --> 00:50:06,480
Speaker 1: over the last few years. Uh leave leave aside. Uh

946
00:50:06,520 --> 00:50:09,040
Speaker 1: you know a recent trade that he exited. UM. But

947
00:50:09,120 --> 00:50:13,160
Speaker 1: he's he's been an amazing investor. UM. He's really, in

948
00:50:13,239 --> 00:50:17,920
Speaker 1: my view, amazing for understanding asymmetry because I've seen whether

949
00:50:17,960 --> 00:50:21,480
Speaker 1: it's Enron with UM. You know, the incredible work Jim

950
00:50:21,560 --> 00:50:24,400
Speaker 1: Chainos did to UM to find Enron. If you go

951
00:50:24,440 --> 00:50:25,879
Speaker 1: in short of stock and you make it a three

952
00:50:25,880 --> 00:50:28,200
Speaker 1: percent position and it goes to zero. Okay, you made

953
00:50:28,200 --> 00:50:32,200
Speaker 1: three percent, but credit derivatives if you bought protection and

954
00:50:32,320 --> 00:50:34,720
Speaker 1: end run and you you only have to pay one percent.

955
00:50:34,800 --> 00:50:36,960
Speaker 1: Even after ken Lay was out, it only cost one

956
00:50:37,000 --> 00:50:39,719
Speaker 1: percent a year for five years. A year later it's

957
00:50:39,760 --> 00:50:42,479
Speaker 1: gone and you you turned one point of premium into

958
00:50:42,480 --> 00:50:45,360
Speaker 1: about ninety five points. You made ninety five times your money.

959
00:50:45,400 --> 00:50:48,520
Speaker 1: That kind of payoff profile is a different skill set

960
00:50:48,560 --> 00:50:51,279
Speaker 1: than the skill set of analyzing companies. And I see

961
00:50:51,320 --> 00:50:54,640
Speaker 1: examples where people get things right, whether it's Enron or Lehman,

962
00:50:54,960 --> 00:50:58,239
Speaker 1: but they but it didn't change, it didn't change their

963
00:50:58,320 --> 00:51:00,399
Speaker 1: the outcome for their fund that year. And I think

964
00:51:00,400 --> 00:51:03,200
Speaker 1: Acman a number of times has shown he really gets

965
00:51:03,239 --> 00:51:05,960
Speaker 1: a symmetry. Now his clothes End fund is is at

966
00:51:05,960 --> 00:51:08,120
Speaker 1: a very big discount, and if one we're looking for

967
00:51:08,160 --> 00:51:11,239
Speaker 1: a top quality manager to be able to buy in

968
00:51:11,560 --> 00:51:15,920
Speaker 1: at that discount, I think um is really compelling. But

969
00:51:16,080 --> 00:51:18,000
Speaker 1: there's nothing we as activists can do to our the

970
00:51:18,040 --> 00:51:22,759
Speaker 1: discount really interesting. So I mentioned earlier your tail funds. Uh,

971
00:51:22,800 --> 00:51:26,680
Speaker 1: there are some pretty famous people who run similar or

972
00:51:26,719 --> 00:51:29,439
Speaker 1: I guess not so similar tail funds. Let's talk about

973
00:51:29,560 --> 00:51:35,280
Speaker 1: now seemed teleb and spitz Nagels funds um Int Integral Integral.

974
00:51:35,320 --> 00:51:37,879
Speaker 1: I don't remember the name of the fund. How does

975
00:51:38,120 --> 00:51:42,919
Speaker 1: their approach differ or is similar to your approach? Yeah?

976
00:51:42,960 --> 00:51:48,880
Speaker 1: So universe universe But uh so, look I'm here. You

977
00:51:48,880 --> 00:51:51,080
Speaker 1: want to have good stories, you want to hear here

978
00:51:51,120 --> 00:51:56,040
Speaker 1: the so I I've never I've never been at first

979
00:51:56,040 --> 00:51:57,480
Speaker 1: of all, let me say before I say nerve been

980
00:51:57,520 --> 00:52:01,279
Speaker 1: a fan of that seemed to his I Q is

981
00:52:01,360 --> 00:52:05,440
Speaker 1: twice as high as mine. Brilliant, brilliant, the smartest guy

982
00:52:05,520 --> 00:52:08,239
Speaker 1: in the world, just ask him. Okay, and but he

983
00:52:08,360 --> 00:52:09,719
Speaker 1: but he happens to be but he happens to be

984
00:52:09,760 --> 00:52:13,360
Speaker 1: super smart. Um, I don't smart. But anyway, but you

985
00:52:13,360 --> 00:52:15,839
Speaker 1: know I had I had a couple of experiences from

986
00:52:15,840 --> 00:52:17,960
Speaker 1: afar or from clothes. I'll share with you so we

987
00:52:18,000 --> 00:52:20,800
Speaker 1: can have a little fun. And so I'm at Deutsche

988
00:52:20,800 --> 00:52:22,839
Speaker 1: Bank and I'm still a pretty young guyme speaking at

989
00:52:22,840 --> 00:52:25,560
Speaker 1: a conference that we're having in Barcelona. And he's the

990
00:52:25,640 --> 00:52:29,000
Speaker 1: lunch speaker. Okay, I'm the Deutsche whatever speaker, and he's

991
00:52:29,040 --> 00:52:33,319
Speaker 1: the entertainment for lunch. And and so we've been all

992
00:52:33,400 --> 00:52:36,600
Speaker 1: given in our in our satchels, his book Fooled by Randomness,

993
00:52:36,600 --> 00:52:39,719
Speaker 1: which is a legendar, it's a crisis. I had not

994
00:52:39,800 --> 00:52:42,520
Speaker 1: read it, so so there he's showing up. I'm sitting

995
00:52:42,520 --> 00:52:45,919
Speaker 1: with them at some cocktails and um, and I read

996
00:52:45,920 --> 00:52:49,120
Speaker 1: the flap Jacket. And Peter Bernstein, who was one of

997
00:52:49,120 --> 00:52:51,680
Speaker 1: my has written one of the great books about about

998
00:52:51,800 --> 00:52:54,880
Speaker 1: risk and finance, Against the Gods. I mean when I

999
00:52:54,920 --> 00:52:57,480
Speaker 1: just say those words and I want to reread it

1000
00:52:57,480 --> 00:53:02,080
Speaker 1: when I got out. Absolutely so, Teleb somehow has gotten

1001
00:53:02,320 --> 00:53:05,840
Speaker 1: Bernstein to say the most wonderful things about Fooled by Randomness?

1002
00:53:06,360 --> 00:53:07,880
Speaker 1: And so what am I going to say to Toleb?

1003
00:53:07,920 --> 00:53:09,600
Speaker 1: I don't know him. He sits down and I say,

1004
00:53:09,760 --> 00:53:12,239
Speaker 1: you know, I haven't read your book. But but Peter

1005
00:53:12,280 --> 00:53:14,759
Speaker 1: Bernstein on the five Jacket, he said, you know, he

1006
00:53:14,800 --> 00:53:16,560
Speaker 1: said something that was so strong, and I really loved

1007
00:53:16,560 --> 00:53:19,520
Speaker 1: Against the Gods. Now there's a range of answers that

1008
00:53:19,560 --> 00:53:23,240
Speaker 1: one can say, thank you appreciated. I hope you enjoyed

1009
00:53:23,239 --> 00:53:25,839
Speaker 1: the book. Can do you have any others? Barry? Because

1010
00:53:25,840 --> 00:53:28,040
Speaker 1: I'll tell you what's not in the range. How dare

1011
00:53:28,080 --> 00:53:31,279
Speaker 1: you not read my book? Okay, that's that's in the range,

1012
00:53:31,280 --> 00:53:33,040
Speaker 1: But it's not the range. When someone says that to

1013
00:53:33,080 --> 00:53:35,960
Speaker 1: another person at that venue, and I'm from Deutscha and

1014
00:53:36,040 --> 00:53:39,839
Speaker 1: common decency, he says, Peter Bernstein is not a very

1015
00:53:39,840 --> 00:53:43,400
Speaker 1: intelligent man, which by the way, could not be further

1016
00:53:43,480 --> 00:53:46,359
Speaker 1: from the truth even if it were true. So so

1017
00:53:46,520 --> 00:53:50,200
Speaker 1: that the the the hubrist, the arrogance, the so so anyway,

1018
00:53:50,400 --> 00:53:53,239
Speaker 1: so look fleds fast forward the number of years. I'm

1019
00:53:53,280 --> 00:53:56,080
Speaker 1: now at a different Japing Morgan conference, not talking about

1020
00:53:56,120 --> 00:53:59,080
Speaker 1: the London Well, they've had me back and I'm speaking,

1021
00:53:59,120 --> 00:54:00,760
Speaker 1: and I get off the stage, and now they're introducing

1022
00:54:00,800 --> 00:54:03,480
Speaker 1: to Seem to Live and instead of you know, with me,

1023
00:54:03,560 --> 00:54:06,040
Speaker 1: they're like, okay, he played chess, he's Deutsche Bank whatever.

1024
00:54:06,200 --> 00:54:09,360
Speaker 1: With to Leb, they say he speaks twenty six languages,

1025
00:54:09,400 --> 00:54:11,680
Speaker 1: and they say a fifty other things, and he's given

1026
00:54:11,680 --> 00:54:13,799
Speaker 1: it to them, and he speaks twenty six languages. Every

1027
00:54:13,840 --> 00:54:15,360
Speaker 1: put your hands together. When he Seemed to Leb, he

1028
00:54:15,400 --> 00:54:17,920
Speaker 1: gets up and he says, I have to make a correction.

1029
00:54:18,040 --> 00:54:21,600
Speaker 1: I speak twenty seven languages. But he's not kidding. He's

1030
00:54:21,719 --> 00:54:24,400
Speaker 1: he needs to make that correction, and so I I

1031
00:54:24,560 --> 00:54:26,279
Speaker 1: he's brilliant, But you know, I have to tell these

1032
00:54:26,320 --> 00:54:30,520
Speaker 1: two stories because we gotta keep it interesting. On to Universa.

1033
00:54:30,880 --> 00:54:33,840
Speaker 1: They have said to Bloomberg effect, to Eric Schatzker in

1034
00:54:33,880 --> 00:54:36,839
Speaker 1: too many other places, that they made four thousand, one

1035
00:54:37,200 --> 00:54:42,560
Speaker 1: d and forty four percent in thousand. Okay, but is

1036
00:54:42,640 --> 00:54:46,600
Speaker 1: that that's a trade annualized, that's not their total return

1037
00:54:47,239 --> 00:54:51,319
Speaker 1: for the year. They can't possibly be talking about those numbers. Well,

1038
00:54:51,440 --> 00:54:54,120
Speaker 1: so that's a thing. If I'm talking fahrenheit and all

1039
00:54:54,120 --> 00:54:56,160
Speaker 1: of a sudden, you want to talk forget Celsie's, you

1040
00:54:56,200 --> 00:54:58,080
Speaker 1: want to talk Vin, you want to talk Kelvin, you

1041
00:54:58,160 --> 00:55:01,479
Speaker 1: gotta say Kelvin. So there, because you end up having

1042
00:55:01,640 --> 00:55:04,759
Speaker 1: false expectations and reporting you know by the you know,

1043
00:55:04,880 --> 00:55:08,400
Speaker 1: innocent journalists. But they were not saying annualized. What they

1044
00:55:08,440 --> 00:55:13,000
Speaker 1: are saying is we spend premium as we go. So

1045
00:55:13,560 --> 00:55:15,600
Speaker 1: we spend let's say it's twenty basis points a month,

1046
00:55:15,719 --> 00:55:19,000
Speaker 1: so point to twelve months, will every three months, will

1047
00:55:19,040 --> 00:55:21,600
Speaker 1: spend sixty basis points, will spend two point four percent

1048
00:55:21,680 --> 00:55:26,520
Speaker 1: a year. And on that that you know batch of protection.

1049
00:55:26,600 --> 00:55:29,480
Speaker 1: We we paid twenty cents on we got back forty

1050
00:55:29,560 --> 00:55:32,080
Speaker 1: times or money. We got eight points, So twenty cents

1051
00:55:32,200 --> 00:55:35,880
Speaker 1: went to eight points. Now the batch beforehand, and the

1052
00:55:35,920 --> 00:55:38,960
Speaker 1: batch before that and before that that expired worthless. Did

1053
00:55:39,040 --> 00:55:40,759
Speaker 1: you see them say they lost a hundred percent? The

1054
00:55:40,840 --> 00:55:43,680
Speaker 1: lost er h percent. So we have investors to say, well,

1055
00:55:43,680 --> 00:55:45,520
Speaker 1: how do you make four thousand percent? I mean, my

1056
00:55:45,640 --> 00:55:48,360
Speaker 1: god like people make forty our legends. So if you

1057
00:55:48,520 --> 00:55:52,200
Speaker 1: run around not just miss quoted about four thousand, but

1058
00:55:52,239 --> 00:55:55,200
Speaker 1: affirmatively talking about it, I think you're doing the investment

1059
00:55:55,239 --> 00:55:57,920
Speaker 1: space at disservice to talk about returns like that. When

1060
00:55:57,960 --> 00:55:59,800
Speaker 1: we talk about our returns and in the way that

1061
00:56:00,000 --> 00:56:02,239
Speaker 1: we've talked about them, it's all the exact same way

1062
00:56:02,320 --> 00:56:04,600
Speaker 1: that we know returns to be, which is return on

1063
00:56:04,719 --> 00:56:07,800
Speaker 1: assets UM, not return on the return you made on

1064
00:56:07,880 --> 00:56:10,000
Speaker 1: the a U M, not return on an options trade

1065
00:56:10,040 --> 00:56:12,080
Speaker 1: you did UM. And so I did it for fun.

1066
00:56:12,440 --> 00:56:15,320
Speaker 1: I looked under their framework of what the return was

1067
00:56:15,480 --> 00:56:18,640
Speaker 1: for us. It was not four thousand percent, but because

1068
00:56:18,719 --> 00:56:20,759
Speaker 1: we had very little negative carry, just like we were

1069
00:56:20,800 --> 00:56:24,320
Speaker 1: talking about before, it was actually twelve I remember. But

1070
00:56:24,400 --> 00:56:27,319
Speaker 1: it's a gobbledea economy. Sure the SEC would bless those

1071
00:56:27,360 --> 00:56:30,520
Speaker 1: sort of numbers in a public document. They'd be thrilled.

1072
00:56:30,680 --> 00:56:33,279
Speaker 1: I can't speak to that, but we you know, for

1073
00:56:34,040 --> 00:56:37,320
Speaker 1: we it's a silly way to boast about your returns,

1074
00:56:37,880 --> 00:56:41,520
Speaker 1: I think so. So, so let's talk about another big brain.

1075
00:56:42,160 --> 00:56:46,560
Speaker 1: Nobody bust my chops better than Cliff Assens. I love

1076
00:56:46,719 --> 00:56:50,240
Speaker 1: mixing it up with him on Twitter. Um, not because

1077
00:56:50,280 --> 00:56:53,200
Speaker 1: I expect to win, but if I could survive fifteen

1078
00:56:53,280 --> 00:56:56,279
Speaker 1: rounds with him, that that's a victory. That's more than

1079
00:56:56,320 --> 00:56:58,800
Speaker 1: a part of victory. It's like, all right, I defended

1080
00:56:58,880 --> 00:57:01,440
Speaker 1: my position. We just ad greed, but at least he

1081
00:57:01,520 --> 00:57:04,080
Speaker 1: didn't say, you're an idiot, go away. And I love Cliff.

1082
00:57:04,120 --> 00:57:07,680
Speaker 1: I find him to be endlessly amusing. Sometimes he and

1083
00:57:07,800 --> 00:57:11,560
Speaker 1: to Leb get into these bizarre fights. Tell us a

1084
00:57:11,600 --> 00:57:14,640
Speaker 1: little bit about what you've seen with Asthnes and to

1085
00:57:14,800 --> 00:57:18,280
Speaker 1: Leb doing battle. Yeah, so you picked another guy who's

1086
00:57:18,280 --> 00:57:20,480
Speaker 1: twice as smart as me, but he handles it with

1087
00:57:20,560 --> 00:57:22,600
Speaker 1: grace and humility. How how bright he is, and he's

1088
00:57:22,840 --> 00:57:25,400
Speaker 1: and he sounds like a vaudeville comedian. He's one of

1089
00:57:25,480 --> 00:57:28,280
Speaker 1: my favorite people to listen to. So so he wrote

1090
00:57:28,320 --> 00:57:32,360
Speaker 1: a paper that tail protection is is not additive to portfolios,

1091
00:57:32,400 --> 00:57:36,280
Speaker 1: and that caused to Leb to really critique not only

1092
00:57:36,880 --> 00:57:39,120
Speaker 1: the paper but also a QRS returns. And they got

1093
00:57:39,160 --> 00:57:42,120
Speaker 1: into a big Twitter spat, which Cliff seems to seems

1094
00:57:42,120 --> 00:57:43,600
Speaker 1: to do every now and again. And I was reading

1095
00:57:43,640 --> 00:57:46,280
Speaker 1: it really as an outsider looking in, but as being

1096
00:57:46,400 --> 00:57:49,160
Speaker 1: an expert in some of this, and I feel like, um,

1097
00:57:50,120 --> 00:57:53,360
Speaker 1: some of the some of the praise that teleb was

1098
00:57:53,400 --> 00:57:57,200
Speaker 1: giving himself was you can't just look at what this

1099
00:57:57,520 --> 00:58:00,240
Speaker 1: two percent that we invested out of your hundreds sense

1100
00:58:00,520 --> 00:58:04,120
Speaker 1: you took two and bought the tele protection did He says, well,

1101
00:58:04,160 --> 00:58:05,920
Speaker 1: what did it allow you to do with your sixty

1102
00:58:06,000 --> 00:58:10,280
Speaker 1: forty plan? Instead of being sixty forty equities bonds? You

1103
00:58:10,320 --> 00:58:14,080
Speaker 1: could go ninety eight or ninety seven equities and two

1104
00:58:14,160 --> 00:58:16,880
Speaker 1: percent me. And because of me, you've got to have

1105
00:58:16,960 --> 00:58:21,080
Speaker 1: all these stocks that beat bonds, you know, mercilessly until uh,

1106
00:58:21,280 --> 00:58:23,680
Speaker 1: you know, for for quite a long time with the SMP.

1107
00:58:23,800 --> 00:58:27,040
Speaker 1: And he picked the smpino less and so so when

1108
00:58:27,080 --> 00:58:29,920
Speaker 1: he was comparing the apples to apples, he was taking

1109
00:58:29,960 --> 00:58:34,080
Speaker 1: the gains that his tail protection allowed by adding on

1110
00:58:34,200 --> 00:58:37,720
Speaker 1: top of it the gains of SMP over over treasuries.

1111
00:58:37,760 --> 00:58:40,400
Speaker 1: But he has the benefit of seeing that this was

1112
00:58:40,440 --> 00:58:42,920
Speaker 1: a world or SMP app into have beaten treasuries. What

1113
00:58:43,080 --> 00:58:45,479
Speaker 1: if SMP had done worse than treasuries that wouldn't be true,

1114
00:58:45,680 --> 00:58:48,000
Speaker 1: which which they did for long periods of time over

1115
00:58:48,040 --> 00:58:50,120
Speaker 1: the past forty years. Yeah. So it's a little bit

1116
00:58:50,160 --> 00:58:53,520
Speaker 1: like like why when people have that intuitive understanding of

1117
00:58:53,600 --> 00:58:56,840
Speaker 1: why the Monty Hall problem works, why does that behind

1118
00:58:56,880 --> 00:58:59,200
Speaker 1: the door there's a prize, behind one door, there's a

1119
00:58:59,280 --> 00:59:02,360
Speaker 1: lion the and the the guy shows you, the host

1120
00:59:02,400 --> 00:59:04,480
Speaker 1: shows you the empty door, do you make the switch?

1121
00:59:04,720 --> 00:59:07,400
Speaker 1: It's because the host already knows that there's nothing behind

1122
00:59:07,480 --> 00:59:10,240
Speaker 1: that door, and so you already know that anything you

1123
00:59:10,320 --> 00:59:12,680
Speaker 1: can say that allowed you to have more SMP risk

1124
00:59:12,760 --> 00:59:16,400
Speaker 1: into the biggest SMP rally after the fact, you know.

1125
00:59:16,560 --> 00:59:19,920
Speaker 1: So I think, um, uh, maybe I kind of am

1126
00:59:19,960 --> 00:59:22,920
Speaker 1: in between because I think if Cliff is saying that

1127
00:59:23,000 --> 00:59:24,840
Speaker 1: tail production is not worth it, well I beg to

1128
00:59:24,920 --> 00:59:27,080
Speaker 1: differ there. But um, but they had Yeah, you're right,

1129
00:59:27,120 --> 00:59:29,360
Speaker 1: they had quite a quite a big spat something that

1130
00:59:29,760 --> 00:59:33,320
Speaker 1: I I've thus far, um you know, managed to avoid

1131
00:59:33,560 --> 00:59:36,480
Speaker 1: uh in my my career. Yet you're inserting yourself right

1132
00:59:36,520 --> 00:59:37,960
Speaker 1: into the middle of it. Well, you know, I came

1133
00:59:38,000 --> 00:59:39,680
Speaker 1: on your show and I wanted to make it interesting.

1134
00:59:39,760 --> 00:59:42,160
Speaker 1: So yeah, I appreciate that. I really appreciate that. So,

1135
00:59:42,480 --> 00:59:46,440
Speaker 1: so you've mentioned certain phrases which are really books that

1136
00:59:46,560 --> 00:59:49,960
Speaker 1: Tolb has written. We've talked offline. We've talked about the

1137
00:59:50,080 --> 00:59:55,240
Speaker 1: fragility of certain institutions, certain sectors, um and and certain

1138
00:59:55,320 --> 00:59:59,560
Speaker 1: investment strategies, as well as the advantages of skin in

1139
00:59:59,600 --> 01:00:02,520
Speaker 1: the game. These are two really big concepts that to

1140
01:00:02,640 --> 01:00:06,280
Speaker 1: Leb has champions. Tell us a little bit about both

1141
01:00:06,360 --> 01:00:09,919
Speaker 1: of those issues relative to the world of investment. Yeah,

1142
01:00:10,120 --> 01:00:13,959
Speaker 1: so look, um, I think that skin in the game

1143
01:00:14,440 --> 01:00:17,840
Speaker 1: so the head fund manager having enough exposure so that

1144
01:00:18,120 --> 01:00:19,920
Speaker 1: if the fund is going to do very poorly, and

1145
01:00:20,000 --> 01:00:22,320
Speaker 1: we've seen a number of funds this year even you

1146
01:00:22,360 --> 01:00:24,600
Speaker 1: know news breaking today about a fund that is down

1147
01:00:25,600 --> 01:00:28,480
Speaker 1: this year. That the you want, um not from a

1148
01:00:28,520 --> 01:00:31,480
Speaker 1: shot and Freud perspective, but just from a equity, equity

1149
01:00:31,520 --> 01:00:35,240
Speaker 1: and fairness perspective. You want the manager to have a

1150
01:00:35,320 --> 01:00:37,320
Speaker 1: lot of money invested in their funds so that they're

1151
01:00:37,360 --> 01:00:39,920
Speaker 1: treating that fund like they with their own personal net

1152
01:00:39,960 --> 01:00:43,160
Speaker 1: worth and not literally and and I am no one

1153
01:00:43,240 --> 01:00:46,120
Speaker 1: forced me to do it, but I've had effectively all

1154
01:00:46,200 --> 01:00:49,360
Speaker 1: of my net worth, uh that is in investments in

1155
01:00:49,560 --> 01:00:51,880
Speaker 1: SAVA funds because I want to eat my own cooking.

1156
01:00:52,240 --> 01:00:53,520
Speaker 1: I want to have skin in the game. I think

1157
01:00:53,560 --> 01:00:55,720
Speaker 1: it sets the right example. And also, you know, it's

1158
01:00:55,720 --> 01:00:57,520
Speaker 1: not so bad to be able to invest without fees

1159
01:00:57,880 --> 01:01:00,040
Speaker 1: in a fund which at the moment my my my

1160
01:01:00,080 --> 01:01:02,040
Speaker 1: own fund is the only one that is not charging

1161
01:01:02,080 --> 01:01:04,520
Speaker 1: me fees. So um. So I've and I have a

1162
01:01:04,640 --> 01:01:08,560
Speaker 1: number of different strategies. So I've really put skin in

1163
01:01:08,600 --> 01:01:11,160
Speaker 1: the game into practice by having something in the upper

1164
01:01:11,240 --> 01:01:13,920
Speaker 1: ninety percent of of my of my network now. But

1165
01:01:14,000 --> 01:01:17,440
Speaker 1: there have been times where I see venture tech and

1166
01:01:17,520 --> 01:01:19,800
Speaker 1: all sorts of growth stocks going up a lot, which

1167
01:01:19,840 --> 01:01:21,360
Speaker 1: is not my expertise, and I wonder it should I

1168
01:01:21,400 --> 01:01:23,880
Speaker 1: diversify And so I'm having these thoughts right now Verry,

1169
01:01:24,000 --> 01:01:27,320
Speaker 1: like should I into this giant swoon um, you know,

1170
01:01:27,400 --> 01:01:30,680
Speaker 1: diversify a bid into things with other managers or index

1171
01:01:30,760 --> 01:01:34,360
Speaker 1: funds that I don't have any personal domain expertise like tech.

1172
01:01:34,720 --> 01:01:38,480
Speaker 1: But um, thus far um. I've really ate my own cooking.

1173
01:01:38,560 --> 01:01:41,040
Speaker 1: And the last few years it tasted very good. There

1174
01:01:41,080 --> 01:01:43,560
Speaker 1: have been years where it didn't. Uh. And I think

1175
01:01:44,000 --> 01:01:46,600
Speaker 1: to the second point about fragility, you do see a

1176
01:01:46,640 --> 01:01:49,960
Speaker 1: lot of funds that go through periods where they're amazing,

1177
01:01:50,400 --> 01:01:52,360
Speaker 1: and then they'll hit a bump, and if the bump

1178
01:01:52,520 --> 01:01:54,040
Speaker 1: lasts more than a year or year and a half,

1179
01:01:54,360 --> 01:01:57,040
Speaker 1: sometimes they're just done. And without mentioning any names, there

1180
01:01:57,080 --> 01:01:59,840
Speaker 1: are long list of funds that were more than ten

1181
01:02:00,000 --> 01:02:03,120
Speaker 1: Allien had some kind of style drift issue or some

1182
01:02:03,720 --> 01:02:06,560
Speaker 1: whatever issue and UM, and they're over in a year.

1183
01:02:06,600 --> 01:02:09,440
Speaker 1: And I think, UM, it is a fragile business. We're

1184
01:02:09,440 --> 01:02:11,200
Speaker 1: seeing a fund now trying to figure out what to do.

1185
01:02:11,440 --> 01:02:13,400
Speaker 1: Should it launch a new fund, should it shut down

1186
01:02:13,400 --> 01:02:15,800
Speaker 1: the old one after a long success and then and

1187
01:02:15,840 --> 01:02:19,440
Speaker 1: then a failure? And I think that UM. Having been

1188
01:02:19,520 --> 01:02:23,120
Speaker 1: through draw downs myself, I went through a period from

1189
01:02:23,200 --> 01:02:26,120
Speaker 1: the time Mario Drag said trust me, it's enough, and

1190
01:02:26,160 --> 01:02:29,280
Speaker 1: I should have trusted him. So from that period of

1191
01:02:29,320 --> 01:02:33,680
Speaker 1: let's say June two twelve to maybe June two, I couldn't,

1192
01:02:34,120 --> 01:02:36,880
Speaker 1: you know, I couldn't get anything right and UM. And

1193
01:02:36,960 --> 01:02:38,520
Speaker 1: to be able to come through that and out the

1194
01:02:38,600 --> 01:02:41,680
Speaker 1: other side, UM and not succumbed to the to the

1195
01:02:42,360 --> 01:02:45,400
Speaker 1: fragility problem with hedge funds is actually something I'm more

1196
01:02:45,440 --> 01:02:47,360
Speaker 1: proud of than the than the good years we've had.

1197
01:02:47,400 --> 01:02:49,520
Speaker 1: And I can maybe even if you like, tell you

1198
01:02:49,560 --> 01:02:52,960
Speaker 1: a bit about why I think we survived. Sure, go ahead,

1199
01:02:53,000 --> 01:02:55,640
Speaker 1: Why why do you think you survived? I think the

1200
01:02:55,760 --> 01:02:57,560
Speaker 1: first thing is you have to love what you're doing.

1201
01:02:57,840 --> 01:03:00,200
Speaker 1: And I think back to that three year drawing own,

1202
01:03:00,600 --> 01:03:02,800
Speaker 1: and it was not severe. The losses were not severe

1203
01:03:02,920 --> 01:03:05,480
Speaker 1: per year. It just took a long time. UM, I

1204
01:03:05,720 --> 01:03:08,040
Speaker 1: loved even then coming into work. I love the markets.

1205
01:03:08,240 --> 01:03:12,880
Speaker 1: I'm a just you're junkie. It's the greatest puzzle. It's

1206
01:03:13,040 --> 01:03:16,000
Speaker 1: it's it's it's a game, but it's important. It's it's

1207
01:03:16,120 --> 01:03:19,400
Speaker 1: it's people's financial future. And um, I love it. I

1208
01:03:19,520 --> 01:03:22,680
Speaker 1: love it, and it it made it it's it's especially

1209
01:03:22,760 --> 01:03:25,120
Speaker 1: fun when you're winning. But it made it very tolerable

1210
01:03:25,200 --> 01:03:26,640
Speaker 1: even when I when I was in and I have

1211
01:03:27,000 --> 01:03:29,680
Speaker 1: a great competitive drive to um to not give up.

1212
01:03:29,920 --> 01:03:32,320
Speaker 1: And maybe some of that is the fortitude even just

1213
01:03:32,480 --> 01:03:35,520
Speaker 1: from thinking about my grandfather and so forth. UM. And

1214
01:03:35,640 --> 01:03:39,200
Speaker 1: then and then secondly, you have to be so thankful

1215
01:03:39,320 --> 01:03:40,840
Speaker 1: for where you are that you you could be in

1216
01:03:40,880 --> 01:03:45,200
Speaker 1: an industry that has this type of compensation that when

1217
01:03:45,320 --> 01:03:48,720
Speaker 1: times are tough, you need to actually um dig into

1218
01:03:48,760 --> 01:03:50,960
Speaker 1: your pocket and and fund the business a little bit.

1219
01:03:50,960 --> 01:03:52,920
Speaker 1: And I think there's some managers when the going got

1220
01:03:53,000 --> 01:03:55,600
Speaker 1: rough and they didn't have bonuses to pay people. They

1221
01:03:56,080 --> 01:03:59,480
Speaker 1: you know, it folded and when in our draw downs,

1222
01:03:59,680 --> 01:04:01,320
Speaker 1: we went through some periods where I was willing to

1223
01:04:01,400 --> 01:04:04,200
Speaker 1: invest back into the firm, earn nothing in those years

1224
01:04:04,240 --> 01:04:07,440
Speaker 1: for myself, but knowing that, UM, I have all the

1225
01:04:07,520 --> 01:04:10,520
Speaker 1: upside of things turned around, and I think it's surprising

1226
01:04:10,600 --> 01:04:14,840
Speaker 1: to me that more institutions don't make that investment, even

1227
01:04:14,880 --> 01:04:18,240
Speaker 1: if it doesn't look amazing in that exact moment, but

1228
01:04:18,400 --> 01:04:21,560
Speaker 1: they there's a lot of enterprise value that is there

1229
01:04:21,640 --> 01:04:25,000
Speaker 1: for that turnaround. And UM, and so uh, you know

1230
01:04:25,120 --> 01:04:28,760
Speaker 1: that's my antidote to fragility is actually UM to invest

1231
01:04:29,160 --> 01:04:32,800
Speaker 1: and those draw downs, I'm going to assume we're fairly modest.

1232
01:04:33,480 --> 01:04:35,640
Speaker 1: You weren't cut in half and trying to think about

1233
01:04:35,680 --> 01:04:38,120
Speaker 1: how do I get back over that high water mark.

1234
01:04:38,200 --> 01:04:41,200
Speaker 1: I'm assuming you had faith in the process and said

1235
01:04:42,120 --> 01:04:44,240
Speaker 1: the environment is changing and we just have to ride

1236
01:04:44,280 --> 01:04:49,880
Speaker 1: this out. Yeah, three three percent, six percent nine survival. Yeah.

1237
01:04:50,080 --> 01:04:52,720
Speaker 1: And also, um, the other thing is in my world,

1238
01:04:52,880 --> 01:04:55,280
Speaker 1: so the credit market could not be more different than

1239
01:04:55,320 --> 01:04:58,240
Speaker 1: the equity market in a way that people I think

1240
01:04:58,240 --> 01:05:00,560
Speaker 1: don't appreciate. So let me tell you so if I'm

1241
01:05:00,640 --> 01:05:03,840
Speaker 1: short and credit spreads are going tighter and tighter. So

1242
01:05:03,960 --> 01:05:06,120
Speaker 1: now let's say the spread on hy yold is to

1243
01:05:06,240 --> 01:05:08,840
Speaker 1: an a half percent or three, there is a boundary

1244
01:05:08,880 --> 01:05:10,960
Speaker 1: condition where it's not going to go below x. There's

1245
01:05:10,960 --> 01:05:13,880
Speaker 1: still gonna be a couple of faults. Whereas if you're

1246
01:05:13,920 --> 01:05:17,160
Speaker 1: short of stock and I think game stop, the stock doubles,

1247
01:05:17,240 --> 01:05:20,040
Speaker 1: you have to recognize your risk more than doubled, or

1248
01:05:20,040 --> 01:05:22,200
Speaker 1: at least doubled, because now you have twice the market value.

1249
01:05:22,360 --> 01:05:24,120
Speaker 1: And the more it goes up, the bigger position is.

1250
01:05:24,560 --> 01:05:28,120
Speaker 1: The more credit protection, the more shorting bonds, let's say,

1251
01:05:28,160 --> 01:05:30,600
Speaker 1: goes against you, the smaller your exposure is. And so

1252
01:05:31,000 --> 01:05:34,400
Speaker 1: one of the things about credit is it's a it's

1253
01:05:34,400 --> 01:05:38,280
Speaker 1: an accordion. There's a boundary um and and in those

1254
01:05:38,360 --> 01:05:41,960
Speaker 1: moments where owning volatility and owning protection was not um

1255
01:05:42,520 --> 01:05:44,880
Speaker 1: the best thing to have, credit spreads were ultra low

1256
01:05:44,960 --> 01:05:46,919
Speaker 1: and really you just couldn't lose much more. And maybe

1257
01:05:46,960 --> 01:05:49,080
Speaker 1: that's part of where the confidence came from. So so

1258
01:05:49,280 --> 01:05:53,440
Speaker 1: let's talk about you mentioned equity. Let's talk about another

1259
01:05:53,600 --> 01:05:59,600
Speaker 1: fund that did spectacularly well in but seems to have stumbled.

1260
01:05:59,640 --> 01:06:04,080
Speaker 1: And there's no clear path to recovery right now ARC.

1261
01:06:04,520 --> 01:06:06,040
Speaker 1: And and by the way, I'm not part of the

1262
01:06:06,120 --> 01:06:10,080
Speaker 1: Schaudenfreud crew who don't like her. I think she's really

1263
01:06:10,160 --> 01:06:14,680
Speaker 1: interesting and innovative and has the um, you know, conviction

1264
01:06:14,760 --> 01:06:18,600
Speaker 1: and confidence in her beliefs. In she was the top

1265
01:06:18,640 --> 01:06:21,440
Speaker 1: performing fund I think a hundred and sixties something that

1266
01:06:21,560 --> 01:06:24,160
Speaker 1: no one was even close. Number two was like fifty

1267
01:06:24,240 --> 01:06:29,160
Speaker 1: percentage points under her. But since the fun peaked, it's

1268
01:06:29,200 --> 01:06:32,840
Speaker 1: been almost straight down. She sold off. I think she's

1269
01:06:32,960 --> 01:06:37,400
Speaker 1: excess of sixty down, maybe even sent down, and filled

1270
01:06:37,520 --> 01:06:41,720
Speaker 1: with things like tele aduc and Netflix and um Tesla.

1271
01:06:41,840 --> 01:06:44,000
Speaker 1: A lot of the big winners became big win losers.

1272
01:06:44,000 --> 01:06:47,160
Speaker 1: I don't remember she's in Netflix, but certainly Tesla tell

1273
01:06:47,320 --> 01:06:52,560
Speaker 1: doc um the bitcoin five hundred thousand, call the fifty

1274
01:06:52,640 --> 01:06:56,040
Speaker 1: percent a year for the next five year call. Uh.

1275
01:06:56,760 --> 01:06:59,440
Speaker 1: She seems to have lost her way. What are your

1276
01:06:59,520 --> 01:07:03,439
Speaker 1: thoughts of about that sort of self confidence heading into

1277
01:07:04,200 --> 01:07:08,280
Speaker 1: what's been a reopening buzz all. Yeah, So we're actually

1278
01:07:08,480 --> 01:07:12,200
Speaker 1: tracking ARC quite closely because the ARC portfolio is not

1279
01:07:12,400 --> 01:07:16,880
Speaker 1: altogether different than the list of companies that SPACs are requiring.

1280
01:07:16,880 --> 01:07:22,160
Speaker 1: They're all future innovative unprofitable tech companies, I think flying

1281
01:07:22,240 --> 01:07:27,640
Speaker 1: cars and UM. And so we've we've seen what happened

1282
01:07:27,680 --> 01:07:30,720
Speaker 1: to ARC. And one thing we like about about SPACs

1283
01:07:30,800 --> 01:07:32,440
Speaker 1: is that all the deals that will be struck here

1284
01:07:33,320 --> 01:07:35,480
Speaker 1: from now on are gonna be struck at the current market,

1285
01:07:35,520 --> 01:07:38,120
Speaker 1: whereas in in ARC you're really hoping for it to

1286
01:07:38,160 --> 01:07:41,720
Speaker 1: return to the glory days of of the past. UM.

1287
01:07:42,120 --> 01:07:43,960
Speaker 1: But I think there are some good deals that can

1288
01:07:44,000 --> 01:07:46,680
Speaker 1: be made in this more difficult environment. And so those

1289
01:07:46,720 --> 01:07:49,560
Speaker 1: warrants you own in a spack or struck at the market,

1290
01:07:49,560 --> 01:07:51,000
Speaker 1: they're not out of the money. If you think about

1291
01:07:51,000 --> 01:07:53,720
Speaker 1: if you had along dated option on on ARC, that's

1292
01:07:53,920 --> 01:07:55,640
Speaker 1: very far out of the money. Now. Now, as far

1293
01:07:55,720 --> 01:08:00,960
Speaker 1: as her confidence, I do witness you know, if someone's

1294
01:08:01,000 --> 01:08:06,000
Speaker 1: down that much, this is a humbling market. And it's

1295
01:08:06,040 --> 01:08:08,280
Speaker 1: not particular to Cathy would but I think I've seen

1296
01:08:08,320 --> 01:08:11,240
Speaker 1: a number of cases where people are way too confident

1297
01:08:11,280 --> 01:08:13,240
Speaker 1: about the future, and if they were up fifty would

1298
01:08:13,240 --> 01:08:16,200
Speaker 1: be one thing. If you're down, probably there's there's an

1299
01:08:16,240 --> 01:08:18,400
Speaker 1: extra dose of humility. So one thing I thought was

1300
01:08:18,479 --> 01:08:24,280
Speaker 1: kind of uh telling, there was in February she um spoke,

1301
01:08:24,360 --> 01:08:27,840
Speaker 1: I don't remember which which program was on and said, um,

1302
01:08:28,560 --> 01:08:30,639
Speaker 1: some of those calls that you mentioned very about bitcoin,

1303
01:08:31,479 --> 01:08:34,880
Speaker 1: uh and make a year. And by the way, you know,

1304
01:08:35,000 --> 01:08:37,400
Speaker 1: great claim should be backed by a great evidence, such

1305
01:08:37,439 --> 01:08:39,559
Speaker 1: Carl Sagan. So I didn't. I didn't see the evidence.

1306
01:08:39,640 --> 01:08:42,840
Speaker 1: But but but she said also that something that really

1307
01:08:43,000 --> 01:08:44,599
Speaker 1: kind of it's a pet peeve of mine. She said,

1308
01:08:44,920 --> 01:08:47,040
Speaker 1: the lows for ARC were in January, and this is

1309
01:08:47,080 --> 01:08:50,479
Speaker 1: in February. I guess what happened within two days? Another

1310
01:08:50,600 --> 01:08:53,000
Speaker 1: leg down. So you know, you want to say something

1311
01:08:53,040 --> 01:08:55,479
Speaker 1: about what will happen in five years. We were not

1312
01:08:55,560 --> 01:08:58,160
Speaker 1: going to remember in five years whether you're right or wrong,

1313
01:08:58,200 --> 01:09:00,080
Speaker 1: but we're gonna remember when the thing you said and

1314
01:09:00,240 --> 01:09:02,639
Speaker 1: happen happens the next day. And I saw it also

1315
01:09:02,640 --> 01:09:05,400
Speaker 1: a few weeks ago one of the big banks said

1316
01:09:06,200 --> 01:09:08,880
Speaker 1: oil will not be lower than a hundred for the

1317
01:09:09,000 --> 01:09:11,080
Speaker 1: remainder of the decade. We we don't want to beat

1318
01:09:11,200 --> 01:09:13,360
Speaker 1: up on JP Morgan because they were on the other side,

1319
01:09:13,439 --> 01:09:16,400
Speaker 1: but I saw that hundred dollar in oil trade. Um,

1320
01:09:16,520 --> 01:09:18,680
Speaker 1: you'll never see below hundred. What did it take three

1321
01:09:18,760 --> 01:09:20,720
Speaker 1: days to break below hundred? I actually think that one

1322
01:09:20,800 --> 01:09:22,800
Speaker 1: was the next day tree day in true day. So

1323
01:09:23,040 --> 01:09:24,760
Speaker 1: so you know, don't say what's not gonna happen for

1324
01:09:24,800 --> 01:09:27,040
Speaker 1: three thousand days or whatever, and and and get it

1325
01:09:27,120 --> 01:09:29,280
Speaker 1: wrong the next day. There should be a Murphy's Laws.

1326
01:09:29,280 --> 01:09:31,800
Speaker 1: There should be some someone should name the what that

1327
01:09:31,960 --> 01:09:33,840
Speaker 1: law is, where if you say it, you're damning yourself.

1328
01:09:33,920 --> 01:09:37,680
Speaker 1: So so I see way too much hubris over confidence,

1329
01:09:37,720 --> 01:09:40,679
Speaker 1: even in the face of giant losses. And it really

1330
01:09:41,280 --> 01:09:44,320
Speaker 1: it kind of drives me crazy because when I get asked, well,

1331
01:09:44,360 --> 01:09:46,760
Speaker 1: what does your crystal ball tell you? I say, first

1332
01:09:46,800 --> 01:09:50,040
Speaker 1: of all, this is the wrong time, you know, it's foggy.

1333
01:09:50,240 --> 01:09:53,760
Speaker 1: It should be like, like people get so used to

1334
01:09:54,680 --> 01:09:57,360
Speaker 1: recency bias. What's been true for the last month, what's

1335
01:09:57,360 --> 01:10:00,479
Speaker 1: been true for the last three years? Extrapolating for a yeah,

1336
01:10:00,520 --> 01:10:02,000
Speaker 1: and we're now in the world. Maybe you're supposed to

1337
01:10:02,000 --> 01:10:04,360
Speaker 1: look at charts in the nineteen seventies and uh, you

1338
01:10:04,439 --> 01:10:07,200
Speaker 1: know we're talking given more inflation is and we should

1339
01:10:07,200 --> 01:10:10,559
Speaker 1: all be super humble because prediction is a very hard business.

1340
01:10:10,800 --> 01:10:13,200
Speaker 1: And I think the problem is that people who predict

1341
01:10:13,240 --> 01:10:16,320
Speaker 1: the loudest, you know, get the most attention. And and

1342
01:10:17,040 --> 01:10:20,160
Speaker 1: it's um uh, boy, is a tough sledding right now.

1343
01:10:20,240 --> 01:10:22,840
Speaker 1: This market is so challenging. So so there are two

1344
01:10:22,960 --> 01:10:27,080
Speaker 1: other um post pandemic issues I wanted to talk to

1345
01:10:27,160 --> 01:10:31,759
Speaker 1: you about. One is the meme stocks um game stop

1346
01:10:31,920 --> 01:10:35,719
Speaker 1: amc Robin Hood. Uh, tell us a little bit about

1347
01:10:36,120 --> 01:10:39,200
Speaker 1: what you were thinking with those? Were you trading those?

1348
01:10:39,240 --> 01:10:42,880
Speaker 1: Were you on either side of that trade? And were

1349
01:10:43,000 --> 01:10:45,880
Speaker 1: these just people board at home or or what's going

1350
01:10:45,920 --> 01:10:49,240
Speaker 1: on with this? I think there's a lot. There's a

1351
01:10:49,280 --> 01:10:53,400
Speaker 1: lot to the story. Um. And Uh, you know, we've

1352
01:10:53,439 --> 01:10:56,599
Speaker 1: seen cases where somebody's too short and they didn't realize

1353
01:10:56,680 --> 01:10:59,040
Speaker 1: being too short can create its own problem, and that

1354
01:10:59,080 --> 01:11:02,479
Speaker 1: could be the entire your investment thesis is is if

1355
01:11:02,520 --> 01:11:03,960
Speaker 1: we push it up high enough, they have to be

1356
01:11:04,160 --> 01:11:07,040
Speaker 1: be squeezed out and um, and it more more becomes

1357
01:11:07,080 --> 01:11:10,880
Speaker 1: a supply demand thing. Um. But but I also see

1358
01:11:11,560 --> 01:11:14,200
Speaker 1: that in one right around the time that people are

1359
01:11:14,200 --> 01:11:17,200
Speaker 1: getting stimulus checks and you know, the the rise of

1360
01:11:17,760 --> 01:11:19,560
Speaker 1: and you see n f t s taking off and

1361
01:11:19,640 --> 01:11:23,479
Speaker 1: crypto taking off even another leg higher, that there's basically

1362
01:11:23,600 --> 01:11:28,800
Speaker 1: been a degradation in the importance of what something ought

1363
01:11:28,840 --> 01:11:31,040
Speaker 1: to be worth, what the value ought to be, and

1364
01:11:31,160 --> 01:11:34,760
Speaker 1: the price of something is much more determined by the

1365
01:11:34,880 --> 01:11:38,080
Speaker 1: physics of it. The puh, the push and the pull

1366
01:11:38,160 --> 01:11:41,639
Speaker 1: and and and not about economic models, more about physical models.

1367
01:11:41,720 --> 01:11:44,880
Speaker 1: And so so you see the combination of people buying

1368
01:11:44,880 --> 01:11:46,840
Speaker 1: out of the money call options, whether it's with their

1369
01:11:46,840 --> 01:11:49,840
Speaker 1: stimulus checks or their net worth, and it working. And

1370
01:11:49,960 --> 01:11:51,960
Speaker 1: I saw you in the heart of game stuff. So

1371
01:11:52,040 --> 01:11:55,360
Speaker 1: we were basically uninvolved. But I couldn't resist Barry when

1372
01:11:55,439 --> 01:11:57,600
Speaker 1: like maybe game stop was three fifty, I was. I

1373
01:11:57,680 --> 01:12:00,720
Speaker 1: was actually using to fine h a brush because I

1374
01:12:00,760 --> 01:12:02,320
Speaker 1: knew if I lost money and this would be embarrassing.

1375
01:12:02,400 --> 01:12:04,400
Speaker 1: So I was I did it too small and and

1376
01:12:04,760 --> 01:12:06,800
Speaker 1: waited for too too good a level and didn't get

1377
01:12:07,280 --> 01:12:09,400
Speaker 1: any kind of reasonable size. But there was a day

1378
01:12:09,479 --> 01:12:11,880
Speaker 1: where like the game stop was near the highs were

1379
01:12:12,040 --> 01:12:14,360
Speaker 1: a call for three weeks a hundred percent out of

1380
01:12:14,360 --> 01:12:16,439
Speaker 1: the money, like game stops at three eight. But the

1381
01:12:16,479 --> 01:12:19,840
Speaker 1: eight hundred call is that such an astronomical number that

1382
01:12:19,920 --> 01:12:22,360
Speaker 1: it costs like a hundred and fifty points or something,

1383
01:12:22,439 --> 01:12:25,320
Speaker 1: And the vall literally broke people's computers. They couldn't they

1384
01:12:25,320 --> 01:12:27,439
Speaker 1: couldn't do pn L that night because it was the

1385
01:12:27,520 --> 01:12:30,760
Speaker 1: vault was some four digit number. And so I don't

1386
01:12:30,800 --> 01:12:34,360
Speaker 1: think those investors are sophisticated on on equity options. But

1387
01:12:34,520 --> 01:12:36,400
Speaker 1: but for many of them it worked, and it was

1388
01:12:36,760 --> 01:12:39,920
Speaker 1: it was a you know, it was an incredible moment.

1389
01:12:40,000 --> 01:12:43,759
Speaker 1: But it reminds me that that love of call options

1390
01:12:43,840 --> 01:12:47,280
Speaker 1: started last the summer before um soft Bank set up

1391
01:12:47,280 --> 01:12:49,760
Speaker 1: an entity to trade short term call options on the

1392
01:12:49,800 --> 01:12:53,320
Speaker 1: tech names they liked, and the sellers of these options,

1393
01:12:53,360 --> 01:12:56,160
Speaker 1: as sellers of all, whether it's puts or calls, you know,

1394
01:12:56,240 --> 01:12:59,320
Speaker 1: basically blew up during COVID short vall funds that had

1395
01:12:59,720 --> 01:13:02,720
Speaker 1: done incredibly well when there was no volume, not surprisingly

1396
01:13:03,080 --> 01:13:05,240
Speaker 1: blew up. And so you didn't have the supply, you

1397
01:13:05,360 --> 01:13:08,160
Speaker 1: had the demand. And so I see today um. You know,

1398
01:13:08,320 --> 01:13:09,719
Speaker 1: n f T s are kind of like an option.

1399
01:13:09,760 --> 01:13:12,519
Speaker 1: They have an asymmetric payout that people are in love

1400
01:13:12,560 --> 01:13:15,800
Speaker 1: with option like payouts and um and as a consequence,

1401
01:13:16,280 --> 01:13:19,680
Speaker 1: volt is elevated even in the nine times even last year.

1402
01:13:19,840 --> 01:13:21,800
Speaker 1: You know, Barry, you've been. You probably know way more

1403
01:13:21,800 --> 01:13:24,160
Speaker 1: about the VIX and the history of it than I do.

1404
01:13:24,600 --> 01:13:27,160
Speaker 1: But the VIX never really went below twenty last year

1405
01:13:27,200 --> 01:13:28,799
Speaker 1: for more than a day or two. Even in tranquil

1406
01:13:28,880 --> 01:13:31,560
Speaker 1: times go back five years earlier, twenty was like a

1407
01:13:32,040 --> 01:13:34,080
Speaker 1: read alert. You know, all we're in a we're in

1408
01:13:34,120 --> 01:13:36,719
Speaker 1: a correction or a bear market, but we've been between

1409
01:13:36,760 --> 01:13:40,639
Speaker 1: twenty and forty since COVID, and I think these volatile

1410
01:13:40,680 --> 01:13:43,960
Speaker 1: times are going to stay with us. One last question

1411
01:13:44,080 --> 01:13:47,479
Speaker 1: before we get to our favorite question, which is you

1412
01:13:47,720 --> 01:13:51,880
Speaker 1: hired Stephanie Rule at Deutsche Bank and she tells me

1413
01:13:52,080 --> 01:13:55,559
Speaker 1: that you had a business as a New York City

1414
01:13:55,680 --> 01:13:59,759
Speaker 1: dog walker. So you have to tell us about hiring

1415
01:14:00,640 --> 01:14:03,400
Speaker 1: and dog walker? What the hell is that, Barry? This

1416
01:14:03,560 --> 01:14:05,559
Speaker 1: is this is low. You've really gotte low. I'm trying

1417
01:14:05,560 --> 01:14:09,000
Speaker 1: to go high and uh, you gotta Okay. So I

1418
01:14:09,160 --> 01:14:12,720
Speaker 1: was thirteen. My parents wouldn't let me watch TV and

1419
01:14:12,880 --> 01:14:15,640
Speaker 1: the Sony Watchman had come out, and uh, black and

1420
01:14:15,680 --> 01:14:17,920
Speaker 1: white TV about two by two, and this is the

1421
01:14:18,040 --> 01:14:20,360
Speaker 1: nineteen eighties, and so I thought if I had some money,

1422
01:14:20,360 --> 01:14:22,800
Speaker 1: I could buy one for a hundred dollars. And um,

1423
01:14:23,120 --> 01:14:24,760
Speaker 1: So I used to walk dogs. I grew up on

1424
01:14:24,760 --> 01:14:27,439
Speaker 1: the Upper West Side, uh, which was not the safe

1425
01:14:27,479 --> 01:14:29,600
Speaker 1: place it is today back then in the in the

1426
01:14:29,640 --> 01:14:32,200
Speaker 1: late eighties. And um, and I tell my kids that

1427
01:14:32,920 --> 01:14:36,200
Speaker 1: in one instance I had one of those extended Alisha's.

1428
01:14:36,439 --> 01:14:39,240
Speaker 1: The dog ran ahead, ran into the elevator, elevator closed,

1429
01:14:39,880 --> 01:14:41,599
Speaker 1: and it started going up and I'm holding this big

1430
01:14:41,680 --> 01:14:44,439
Speaker 1: plastic thing that I can't even get rid of, and

1431
01:14:44,920 --> 01:14:47,519
Speaker 1: it gets pulled from my hand, and it seemed like

1432
01:14:47,880 --> 01:14:50,519
Speaker 1: way too many seconds. It's up in the corner of

1433
01:14:50,600 --> 01:14:53,080
Speaker 1: the elevator door, and I'm thinking the dog is dead

1434
01:14:53,120 --> 01:14:55,920
Speaker 1: because the elevator went up and came down, you know,

1435
01:14:56,240 --> 01:14:58,760
Speaker 1: bouncing around. But it was totally okay. So my my

1436
01:14:58,880 --> 01:15:01,960
Speaker 1: dog like career was literally the almost uh ended in

1437
01:15:02,120 --> 01:15:05,479
Speaker 1: in one in one cut. Um. But I um, when

1438
01:15:05,479 --> 01:15:07,560
Speaker 1: I when I was a kid, I did that. But

1439
01:15:07,760 --> 01:15:10,160
Speaker 1: two years later I was working as a summer intern

1440
01:15:10,560 --> 01:15:13,240
Speaker 1: and after school at Marylynch, so um. Stephanie really got

1441
01:15:13,280 --> 01:15:16,519
Speaker 1: me with that one. She is basically one of the

1442
01:15:16,560 --> 01:15:19,120
Speaker 1: best things that ever happened to me. At Deutsche Banks,

1443
01:15:19,200 --> 01:15:21,360
Speaker 1: I knew a credit sueez. She was so good as

1444
01:15:21,400 --> 01:15:25,120
Speaker 1: my salesperson that I would forego that benefit to have

1445
01:15:25,320 --> 01:15:28,040
Speaker 1: her at the bank, and I helped bring her in. Huh.

1446
01:15:28,200 --> 01:15:30,240
Speaker 1: That's that's really interesting. All right, Let's jump to our

1447
01:15:30,280 --> 01:15:33,840
Speaker 1: favorite questions that we ask all of our guests, starting

1448
01:15:34,000 --> 01:15:36,800
Speaker 1: with tell us what you've been streaming these days on

1449
01:15:36,920 --> 01:15:40,960
Speaker 1: your two by two sony uh TV man? Whatever that was?

1450
01:15:41,040 --> 01:15:43,879
Speaker 1: I remember that was like a Dick Tracy watch almost.

1451
01:15:44,360 --> 01:15:47,000
Speaker 1: Um what are you watching on Netflix or Amazon Prime

1452
01:15:47,120 --> 01:15:51,360
Speaker 1: or whatever? Sure, so um uh, I definitely watched my

1453
01:15:51,439 --> 01:15:53,519
Speaker 1: favorite bit of TV. I'm doing with one eye, so

1454
01:15:53,800 --> 01:15:57,000
Speaker 1: i'm you know, the other I'm I'm at least when

1455
01:15:57,000 --> 01:15:59,920
Speaker 1: my kids are asleep. I'm definitely following the markets at

1456
01:16:00,000 --> 01:16:02,519
Speaker 1: you're closest here. But I just finished the first six

1457
01:16:02,600 --> 01:16:05,360
Speaker 1: episodes of Slow Horses with Gary Old. I just started

1458
01:16:05,439 --> 01:16:08,040
Speaker 1: that this week. I have to tell you there are

1459
01:16:08,120 --> 01:16:11,400
Speaker 1: so many lines of his that are just so quotable,

1460
01:16:11,520 --> 01:16:14,280
Speaker 1: and they're they're just there. I think the writing is

1461
01:16:14,320 --> 01:16:17,639
Speaker 1: brilliant and m and the show I'd give it an

1462
01:16:17,680 --> 01:16:20,040
Speaker 1: a minus, but his lines are in a plus. Um.

1463
01:16:20,160 --> 01:16:22,360
Speaker 1: So that that's what I finished. I'm about to start

1464
01:16:22,400 --> 01:16:25,960
Speaker 1: season two of Tehran and my wife is from Tehran,

1465
01:16:26,280 --> 01:16:29,040
Speaker 1: and in season one, right in the heart of COVID

1466
01:16:29,160 --> 01:16:33,600
Speaker 1: before Apple started uh streaming it, um, it was a

1467
01:16:34,240 --> 01:16:38,519
Speaker 1: an Israeli show in Farsi and sometimes in Hebrew and

1468
01:16:38,720 --> 01:16:41,679
Speaker 1: so um so my COVID memory is my in laws

1469
01:16:42,439 --> 01:16:45,320
Speaker 1: and my wife doing simultaneous translation for me. Because there

1470
01:16:45,360 --> 01:16:48,839
Speaker 1: were no English subtitles. I certainly couldn't understand the Farsi

1471
01:16:49,240 --> 01:16:51,559
Speaker 1: and so we that was a really nice family activity.

1472
01:16:51,760 --> 01:16:53,840
Speaker 1: And I thought that was really a great show. Huh.

1473
01:16:54,200 --> 01:16:58,720
Speaker 1: Have you watched another Israeli show, Fouda? I have. I've

1474
01:16:58,760 --> 01:17:02,040
Speaker 1: actually met the cast. I think it is very good.

1475
01:17:02,240 --> 01:17:04,960
Speaker 1: I've seen all those shows. Um, I can't watch it

1476
01:17:05,040 --> 01:17:06,800
Speaker 1: before you go to bed because you just like so

1477
01:17:07,040 --> 01:17:10,800
Speaker 1: stressed out. It's the it's the most suspenseful, exciting thing

1478
01:17:10,880 --> 01:17:14,720
Speaker 1: on TV. Yeah, yeah, really interesting. Tell us about some

1479
01:17:14,840 --> 01:17:18,240
Speaker 1: of your mentors who helped shape your career. So my

1480
01:17:18,360 --> 01:17:21,360
Speaker 1: start is because a woman who went to Hunter Elementary

1481
01:17:21,400 --> 01:17:24,240
Speaker 1: School as a kid put up an ad at Hunter

1482
01:17:24,360 --> 01:17:27,080
Speaker 1: and it's Dyvesant where I went looking for someone to

1483
01:17:27,120 --> 01:17:29,920
Speaker 1: come in after school and help her arrange meetings and

1484
01:17:30,120 --> 01:17:33,479
Speaker 1: put you know, cards in uh in folders and listen

1485
01:17:34,000 --> 01:17:37,200
Speaker 1: to uh read stock research in my spare time. So

1486
01:17:37,280 --> 01:17:40,000
Speaker 1: that was Jeanine Crane. I'm still close with her to

1487
01:17:40,120 --> 01:17:42,720
Speaker 1: this day. She was a high net worth broker at

1488
01:17:42,760 --> 01:17:45,600
Speaker 1: Meryl and I worked there from fifteen to seventeen. And

1489
01:17:45,680 --> 01:17:49,280
Speaker 1: then the great David DeLucia from a Wars poker who

1490
01:17:49,680 --> 01:17:52,360
Speaker 1: ran the junk bond desk at Goldman, the chess player

1491
01:17:52,479 --> 01:17:55,400
Speaker 1: who gave me my start at Goldman was an incredible

1492
01:17:55,439 --> 01:17:58,639
Speaker 1: mentor to me. But you know, Barry, I I think

1493
01:17:58,720 --> 01:18:00,800
Speaker 1: the importance of having some that you can ask those

1494
01:18:00,880 --> 01:18:03,160
Speaker 1: questions too, and why did this happen? And what do

1495
01:18:03,240 --> 01:18:05,280
Speaker 1: you think? And why did you sell this? Are so

1496
01:18:05,439 --> 01:18:07,639
Speaker 1: crucial when you're young. But when I got into credit

1497
01:18:07,720 --> 01:18:11,720
Speaker 1: ord of January night i joined Deutsche, I'm still only

1498
01:18:13,560 --> 01:18:16,960
Speaker 1: years old, and um there's no one to really learn

1499
01:18:17,000 --> 01:18:19,320
Speaker 1: about credit orders from because it's the things brand new.

1500
01:18:19,800 --> 01:18:22,840
Speaker 1: And my my two bosses actually left the bank six

1501
01:18:22,880 --> 01:18:25,280
Speaker 1: months after I started. So I really was alone in

1502
01:18:25,320 --> 01:18:28,760
Speaker 1: the wilderness during LTCM in Russia and it was it

1503
01:18:28,920 --> 01:18:31,200
Speaker 1: was a it was an incredible experience. I was the

1504
01:18:31,200 --> 01:18:33,519
Speaker 1: most junior person on the desk and the most senior

1505
01:18:33,560 --> 01:18:35,840
Speaker 1: because it became a group of one and they let

1506
01:18:35,920 --> 01:18:40,280
Speaker 1: me in hire some people and the rest is history. Interesting.

1507
01:18:40,720 --> 01:18:43,639
Speaker 1: Let's talk about books. What are some of your favorites

1508
01:18:43,680 --> 01:18:46,640
Speaker 1: and what are you reading right now? Uh? Well, so

1509
01:18:46,800 --> 01:18:49,320
Speaker 1: I'm gonna read I'm about to reread Against the Gods.

1510
01:18:49,360 --> 01:18:53,479
Speaker 1: Now that we had this awesome conversation about Peter Bernstein, Um,

1511
01:18:54,040 --> 01:18:57,960
Speaker 1: I'm not that into reading the latest book. Um, so

1512
01:18:59,080 --> 01:19:01,479
Speaker 1: I've gone back and read some books that I should

1513
01:19:01,479 --> 01:19:04,439
Speaker 1: have read before. So this uh, the last few months,

1514
01:19:04,520 --> 01:19:08,719
Speaker 1: I read The Powerbroker by Caro and um just feeling

1515
01:19:08,720 --> 01:19:11,960
Speaker 1: a little bit uh interested in my own personal history

1516
01:19:12,520 --> 01:19:16,760
Speaker 1: um and this trip to Yad Vashem. Quite recently I

1517
01:19:16,880 --> 01:19:20,000
Speaker 1: reread Man Search for Meaning by Victor Frankel. UM. But

1518
01:19:20,080 --> 01:19:22,080
Speaker 1: a few years ago a book that is kind of

1519
01:19:22,120 --> 01:19:25,400
Speaker 1: one of those books like that that people in our

1520
01:19:25,439 --> 01:19:29,839
Speaker 1: community read about different topics about whether it's finance related

1521
01:19:29,960 --> 01:19:35,120
Speaker 1: or or skill versus uh, nurture nature. Uh. There's a

1522
01:19:35,160 --> 01:19:38,280
Speaker 1: book called Range by David Epstein that I thought had

1523
01:19:38,400 --> 01:19:41,719
Speaker 1: some really interesting chapters that I was unfamiliar with. Whether

1524
01:19:41,800 --> 01:19:44,920
Speaker 1: it's the spatial disaster is a little familiar with, or

1525
01:19:45,680 --> 01:19:48,960
Speaker 1: violinists of the eighteenth century. It's it's really a tourtive force. Um.

1526
01:19:49,120 --> 01:19:51,479
Speaker 1: You can get the basic ideas from it pretty quickly.

1527
01:19:51,560 --> 01:19:55,320
Speaker 1: But I quite enjoyed it. Huh. Really interesting. You mentioned

1528
01:19:55,439 --> 01:19:58,880
Speaker 1: Liars Poker before. I just reread it for the first

1529
01:19:58,960 --> 01:20:02,160
Speaker 1: time in like thirty years when I had Michael Lewis

1530
01:20:02,280 --> 01:20:06,040
Speaker 1: on recently, and it's surprising how well it holds up

1531
01:20:06,120 --> 01:20:08,800
Speaker 1: over time. And there's a book I'm gonna recommend to you,

1532
01:20:08,840 --> 01:20:11,839
Speaker 1: because I get a sense of your likes and dislikes.

1533
01:20:12,120 --> 01:20:16,280
Speaker 1: Have you ever read godal escher Bach. It seems like

1534
01:20:16,400 --> 01:20:18,479
Speaker 1: that's right up your alley. So I tried to read

1535
01:20:18,520 --> 01:20:20,760
Speaker 1: it as a college student, and I kept trying because

1536
01:20:20,800 --> 01:20:23,200
Speaker 1: I knew this, well, this is a book that's people

1537
01:20:23,240 --> 01:20:26,120
Speaker 1: who think, you know that they can understand complicated things

1538
01:20:26,160 --> 01:20:28,439
Speaker 1: should read and I am. I loved parts of it.

1539
01:20:28,720 --> 01:20:31,920
Speaker 1: I'm I need to need to give it another look

1540
01:20:31,960 --> 01:20:34,959
Speaker 1: because it's been thirty years. I literally had the same experience.

1541
01:20:35,040 --> 01:20:37,120
Speaker 1: I fought through it in college and said, I got

1542
01:20:37,240 --> 01:20:40,000
Speaker 1: to reread it, and it's on my list to reread

1543
01:20:40,320 --> 01:20:43,840
Speaker 1: same same exact things. Um. Last two questions, what sort

1544
01:20:43,840 --> 01:20:46,639
Speaker 1: of advice would you give to a recent college grad

1545
01:20:46,680 --> 01:20:50,840
Speaker 1: who was interested in a career? Uh in finance. You know,

1546
01:20:51,120 --> 01:20:55,200
Speaker 1: I had people over the years very frequently at Deutscha

1547
01:20:55,280 --> 01:20:58,280
Speaker 1: asked me. Let's say they were summer intern that wanted

1548
01:20:58,320 --> 01:20:59,760
Speaker 1: to get a full time job, or as a person

1549
01:20:59,840 --> 01:21:03,000
Speaker 1: in operations that wanted to get a trading job. And

1550
01:21:03,040 --> 01:21:04,720
Speaker 1: they'd say, at the end of the summer or at

1551
01:21:04,760 --> 01:21:06,200
Speaker 1: the at the end of some period, how do I

1552
01:21:06,240 --> 01:21:09,280
Speaker 1: get a job on the trading desk? And I would sometimes,

1553
01:21:09,400 --> 01:21:12,880
Speaker 1: and we we were pretty good about actually giving those opportunities.

1554
01:21:13,439 --> 01:21:16,880
Speaker 1: I'd say to the person who didn't deserve it, let's say, well,

1555
01:21:17,000 --> 01:21:19,400
Speaker 1: you know, we have this seven thirty meeting where all

1556
01:21:19,479 --> 01:21:21,639
Speaker 1: the traders go over their top positions and the salesforce

1557
01:21:21,720 --> 01:21:24,880
Speaker 1: asked questions, why haven't I seen you in those meetings? Oh?

1558
01:21:25,160 --> 01:21:27,920
Speaker 1: I you know, I didn't my job starts at date,

1559
01:21:28,040 --> 01:21:30,000
Speaker 1: or that's I didn't know I could go to those meetings,

1560
01:21:30,320 --> 01:21:32,600
Speaker 1: you know. And there's decisions like that, like should you

1561
01:21:32,680 --> 01:21:34,679
Speaker 1: go to that meeting or should you read the week's

1562
01:21:34,760 --> 01:21:37,480
Speaker 1: research and ask a question, even if you work in operations,

1563
01:21:37,680 --> 01:21:40,360
Speaker 1: or even if you're a summer intern and a reasonable

1564
01:21:40,400 --> 01:21:42,760
Speaker 1: person on the other end will should look at that

1565
01:21:43,000 --> 01:21:46,400
Speaker 1: with loving eyes. And I feel like some people want it,

1566
01:21:46,640 --> 01:21:48,519
Speaker 1: but they don't do the things they need to do

1567
01:21:48,680 --> 01:21:51,799
Speaker 1: to deserve it. And if it's if it's about business,

1568
01:21:52,240 --> 01:21:54,880
Speaker 1: there's almost nothing that would be too aggressive for someone

1569
01:21:54,920 --> 01:21:57,120
Speaker 1: to do, like showing up at a meeting they weren't

1570
01:21:57,120 --> 01:21:59,080
Speaker 1: invited to that fifty people are in. It's not a

1571
01:21:59,160 --> 01:22:01,560
Speaker 1: secret meeting. And I think young people who want to

1572
01:22:01,600 --> 01:22:04,679
Speaker 1: get ahead, um, who want to be doing something different,

1573
01:22:05,160 --> 01:22:09,320
Speaker 1: need to uh do those things and our final question,

1574
01:22:09,760 --> 01:22:12,160
Speaker 1: what do you know about the world of investing today

1575
01:22:12,280 --> 01:22:15,840
Speaker 1: you wish you knew back when you were first getting

1576
01:22:15,880 --> 01:22:20,519
Speaker 1: started as an investor. I mean, this is an amazing

1577
01:22:20,600 --> 01:22:24,320
Speaker 1: question as an investor that has to think about when

1578
01:22:24,520 --> 01:22:27,599
Speaker 1: is it cheap enough? How what's the discount one needs

1579
01:22:27,680 --> 01:22:29,640
Speaker 1: on a spack or on a closed in fund, or

1580
01:22:29,800 --> 01:22:33,040
Speaker 1: the mispricing between a credit and an equity to put

1581
01:22:33,120 --> 01:22:37,599
Speaker 1: on a trade. I think that, um, if I could

1582
01:22:37,640 --> 01:22:41,439
Speaker 1: go back, I would tell myself that my imagination for

1583
01:22:41,600 --> 01:22:44,880
Speaker 1: how crazy things could get is not enough. You know,

1584
01:22:44,920 --> 01:22:47,120
Speaker 1: if you think about, like if you took the government

1585
01:22:47,160 --> 01:22:50,280
Speaker 1: bond traders of pre O eight and sent them to

1586
01:22:50,360 --> 01:22:52,400
Speaker 1: the moon and left them there for years, and brought

1587
01:22:52,439 --> 01:22:54,840
Speaker 1: them back and tell them that interest rates, oh you're back,

1588
01:22:55,160 --> 01:22:58,639
Speaker 1: you know, here's your you know, uh, here's your newspaper.

1589
01:22:58,680 --> 01:23:00,760
Speaker 1: Interest rates are negative. I think to them would think

1590
01:23:00,840 --> 01:23:02,680
Speaker 1: like you're playing a prank on them. We have we

1591
01:23:02,760 --> 01:23:05,120
Speaker 1: have Swiss rates negative to fifty years, like it's not

1592
01:23:05,240 --> 01:23:07,920
Speaker 1: just a three month bond, like fifty thirty years negative

1593
01:23:07,960 --> 01:23:11,360
Speaker 1: and and so so I think the market never will

1594
01:23:11,400 --> 01:23:17,080
Speaker 1: cease to surprise and people who get tracked into recency

1595
01:23:17,160 --> 01:23:19,439
Speaker 1: bias and this is the way things are, and this

1596
01:23:19,520 --> 01:23:21,960
Speaker 1: is the way they'll be. They're not imaginative enough about

1597
01:23:22,000 --> 01:23:25,040
Speaker 1: what can happen, and it's it's those extraordinary things that

1598
01:23:25,160 --> 01:23:29,000
Speaker 1: happened where the real amazing payouts are. You know, maybe

1599
01:23:29,040 --> 01:23:31,840
Speaker 1: an example now something that hasn't worked instead is there

1600
01:23:31,840 --> 01:23:34,439
Speaker 1: are probably some currency pegs that people assume are going

1601
01:23:34,479 --> 01:23:36,960
Speaker 1: to be there forever and you know, you just have

1602
01:23:37,080 --> 01:23:39,120
Speaker 1: to be right one time in a hundred years and

1603
01:23:39,160 --> 01:23:41,200
Speaker 1: you're gonna get paid back five dred times or a

1604
01:23:41,280 --> 01:23:45,080
Speaker 1: hundred times and things. I think, Uh, with what's happened

1605
01:23:45,120 --> 01:23:47,960
Speaker 1: now with with Ukraine and Russia and COVID and China

1606
01:23:48,040 --> 01:23:50,720
Speaker 1: and inflation, I think we're in a world where the

1607
01:23:50,800 --> 01:23:54,920
Speaker 1: impossible can be possible and we should think creatively about

1608
01:23:55,479 --> 01:23:57,960
Speaker 1: um a range of outcomes instead of what's the central

1609
01:23:58,320 --> 01:24:00,760
Speaker 1: what's the central theory? Thank you o As for being

1610
01:24:00,840 --> 01:24:03,439
Speaker 1: so generous with your time. We have been speaking with

1611
01:24:03,560 --> 01:24:08,520
Speaker 1: BoA's Weinstein, founder of Saba Capital. If you enjoy this conversation,

1612
01:24:08,600 --> 01:24:10,760
Speaker 1: we'll be sure and check out any of the four

1613
01:24:10,840 --> 01:24:13,759
Speaker 1: hundred previous ones we've done over the past eight years.

1614
01:24:14,280 --> 01:24:17,920
Speaker 1: You can find those at iTunes, Spotify, wherever you find

1615
01:24:17,960 --> 01:24:21,760
Speaker 1: your favorite podcasts. We love your comments, feedback and suggestions

1616
01:24:21,920 --> 01:24:25,479
Speaker 1: right to us at might be podcast at Bloomberg dot net.

1617
01:24:26,000 --> 01:24:28,360
Speaker 1: Follow me on Twitter at rid Halts. Check out my

1618
01:24:28,479 --> 01:24:32,000
Speaker 1: daily reads at Dholts dot com. I would be remiss

1619
01:24:32,040 --> 01:24:33,960
Speaker 1: if I did not thank the correct team that helps

1620
01:24:34,040 --> 01:24:38,280
Speaker 1: put these conversations together each week. Mohammed Ramaui is my

1621
01:24:38,400 --> 01:24:42,639
Speaker 1: audio engineer. Sean Russo is my head of research. Paris

1622
01:24:42,720 --> 01:24:47,400
Speaker 1: Wald is our producer. Batika val Brund is our project manager.

1623
01:24:48,040 --> 01:24:51,679
Speaker 1: I'm Barry Results. You've been listening to Master's in Business

1624
01:24:52,160 --> 01:24:53,280
Speaker 1: on Bloomberg Radia