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Speaker 1: This is Masters in Business with Barry Ridholts on Boomberg Radio.

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Speaker 1: This weekend on the podcast, I have an extra special guest,

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Speaker 1: and this was a master class in what is going

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Speaker 1: on in the alternative space. Alana Weinstein is uniquely situated

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Speaker 1: to understand hedge funds, venture capital, private equity, the demands

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Speaker 1: of scaling a billion dollar firm into a forty billion

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Speaker 1: dollar firm, Who is moving around from firm to firm,

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Speaker 1: Who are the most talented people in the space, What

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Speaker 1: is going on without flows from hedge funds and why.

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Speaker 1: I don't know how to describe this except to say

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Speaker 1: this is absolutely an incredible discussion from a person uniquely

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Speaker 1: situated in a one off vantage point to understand exactly

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Speaker 1: what's taking place in this space. So, with no further ado,

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Speaker 1: my conversation with Alana Weinstein. This is Masters in Business

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Speaker 1: with Barry Ridholts on Bloomberg Radio. My special guest this

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Speaker 1: week is Alana Weinstein. She is the founder and CEO

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Speaker 1: of the I d W Group, a leading boutique for

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Speaker 1: hedge funds, private equity, and family offices in search of

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Speaker 1: top investment talent. Previously, she worked at such August firms

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Speaker 1: as Goldman Stacks and the Boston Consulting Group. She got

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Speaker 1: her undergraduate degree from the University of Pennsylvania and her

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Speaker 1: MBA from Harvard Elana Weinstein, Welcome to Bloomberg Radio. And

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Speaker 1: I add that because I've seen you on Bloomberg TV

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Speaker 1: many times, but I don't recall ever hearing you on

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Speaker 1: Bloomberg Radio. This is my first time, Barry, So, you've

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Speaker 1: been in the asset management industry for more than two decades.

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Speaker 1: How did you end up on the recruiting side. The

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Speaker 1: short answer is I was really young and I was

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Speaker 1: still trying to figure or out what I wanted to

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Speaker 1: be when I grew up. Literally, Um, I had gone

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Speaker 1: to HBS after a year at Goldman, So I literally

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Speaker 1: went from penn from my dorm room to my parents home,

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Speaker 1: worked a Goldman for a year, uh and then UH

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Speaker 1: and then went to HBS. And just to go back

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Speaker 1: and answer your question, I ended up going to the

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Speaker 1: Boston Consulting Group really because I felt I needed to

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Speaker 1: get a post m b A to my m b A.

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Speaker 1: I wanted to figure out, um, what path I wanted

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Speaker 1: to take, what sorts of problems I wanted to solve,

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Speaker 1: what industries were interesting to me, and um and this

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Speaker 1: is in the I was in my late twenties, this

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Speaker 1: is in the mid nineties, so the dot com because

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Speaker 1: that's of course what we called it back then, and

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Speaker 1: the dot com bubble was just bubbling. And within a

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Speaker 1: year and a half, my entire class of MBAs at BCG,

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Speaker 1: the class I entered with, was gonzo. I was literally

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Speaker 1: they'd all gone to California to seek their you know,

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Speaker 1: start the next whatever. Give me a big fat slug

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Speaker 1: of stock options and a stock that just goes up

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Speaker 1: ten percent a day, and and everybody jumped at it

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Speaker 1: and done right. And you can imagine how that ended

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Speaker 1: for most of them. It depends on if they knew

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Speaker 1: when to hit the bit or not. If they were

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Speaker 1: smart and and took off some risk, not too bad

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Speaker 1: the people who didn't, so they had gone to try

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Speaker 1: to start dot com companies. And um, I that wasn't

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Speaker 1: my gig. I wasn't I realized I didn't. Really, I

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Speaker 1: had learned a lot of BCG. I didn't want to

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Speaker 1: be a management consultant um as a as a career path,

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Speaker 1: and I still was figuring out what do I want

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Speaker 1: to do? And before I committed to UM any particular pathway.

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Speaker 1: I figured I would jump into another milieu where I

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Speaker 1: could learn again more about companies and functions and just

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Speaker 1: figure out where I wanted to commit to. And so

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Speaker 1: I joined a large recruiting firm, thinking that would give

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Speaker 1: me a purview. And as it turned out, I was

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Speaker 1: really good at it, and I fell into quickly joined

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Speaker 1: their financial services practice, and uh, that's how That's how

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Speaker 1: I ended up in recruiting, and so you end up

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Speaker 1: focusing a little further along in your career on head funds,

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Speaker 1: private equity, family offices. So what happened was UM after

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Speaker 1: about a year or two, there the dot com bubble burst,

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Speaker 1: and there this is this big search firm I was at.

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Speaker 1: Their financial services practice was really focused more on investment, banking, equities,

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Speaker 1: traditional asset management, sort of what i'll call older school businesses,

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Speaker 1: compared to what I really fell into and started to

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Speaker 1: focus on, which was back in the late nineties early

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Speaker 1: two thousands. As you'll remember, these were the this is

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Speaker 1: what was fueling the cell side. This is where the

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Speaker 1: action was. It was the prop groups, and it was

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Speaker 1: it was these new, first of their kind type financial products.

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Speaker 1: It was called so it was credit correlation. Asset swaps

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Speaker 1: wasn't even called credit derivatives back then, highly structured first

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Speaker 1: of their kind derivativesy types of transactions. That's what we

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Speaker 1: were focused on for the cell side clients that I

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Speaker 1: was working with, and that's where the juice was. And

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Speaker 1: all of a sudden, I developed my own business which

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Speaker 1: was on fire within this big firm, and it just

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Speaker 1: became obvious after a few years to me um to

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Speaker 1: really try to do this on my own, given um

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Speaker 1: I was acting effectively independently within a larger construct which

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Speaker 1: was having issues at the time. So let's talk also

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Speaker 1: about the timing. As you were explained that, I began

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Speaker 1: to think about the timing. If we go back years,

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Speaker 1: what were there two hundred four hundred hedge funds Today

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Speaker 1: there's eleven thousand. Your timing into that ramp up could

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Speaker 1: not perfect Barry, right, I planned it perfectly, right. I mean,

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Speaker 1: so so all these and Goldman sachs Is is infamous

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Speaker 1: for saying to a group of traders who they smell

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Speaker 1: might be itching to head out, Hey, why don't you

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Speaker 1: guys go set up a hedge fun We'll get you capital,

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Speaker 1: will will prime broker for you, and we'll steer some

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Speaker 1: potential clients to you. And that's how they built an

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Speaker 1: immense prime brokerage business. How much was the Goldman Sacks

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Speaker 1: connection helpful or as you was an analyst, it had nothing.

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Speaker 1: I was literally just understand I started a Goldman in

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Speaker 1: the middle of my senior year of PEN. I mean

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Speaker 1: because I just was. I don't know, I was stupid.

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Speaker 1: I was like working. I just I got through all

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Speaker 1: my classes. I didn't have I didn't have enough fun

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Speaker 1: in college. At the bottom line, I'm making up for it,

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Speaker 1: trying to make up for lost time now. But I

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Speaker 1: was finished with my classes. I started middle of my

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Speaker 1: senior year and I was out within literally a year

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Speaker 1: to HBS. So think about it. I was I hadn't

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Speaker 1: even graduated from college. So this was it was. That

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Speaker 1: was not what UM really what really jump started my business.

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Speaker 1: It what it was. However, UM, you are correct in

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Speaker 1: signaling the cell side um as as a driver of

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Speaker 1: hedge fund talent, because back then it was the prop

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Speaker 1: groups that were the precursors to hedge funds. It was

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Speaker 1: it was these you know again, high octane um and

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Speaker 1: these were the guys who got paid the most on

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Speaker 1: the cell side at the time, and I even still

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Speaker 1: felt like they weren't capturing as much of their p

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Speaker 1: m L as they wanted. Well, you know it, within

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Speaker 1: a cell side context, they were doing as well as

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Speaker 1: they possibly could. Back then, you could be a superstar

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Speaker 1: prop trader and earning forty million bucks a year, which

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Speaker 1: which doesn't happen anymore. You could be earning more certainly

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Speaker 1: than the CEO. But their buddies were leaving UM, many

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Speaker 1: of whom were Goldman partners or just were um just

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Speaker 1: like again, high octane prop traders from Credit Sweez, from

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Speaker 1: Deutsche Bank, from Morgan Stanley, from JP Morgan, and they

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Speaker 1: were setting up shop. And remember back then you could

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Speaker 1: start with fifty and scale to a billion very quickly.

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Speaker 1: And so and all of a sudden, there's no headwinds

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Speaker 1: from any other part in the bank. There's no cap

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Speaker 1: at all in terms of how you get paid. You

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Speaker 1: can do whatever you want. And if you're an entrepreneurial

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Speaker 1: person who is a great investment professional and that's your

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Speaker 1: passion and that's what you want to do, why be

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Speaker 1: part of a bank. There was no headwind to getting

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Speaker 1: into this business and scaling if you could produce the goods,

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Speaker 1: and back then you could do that a lot more easily,

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Speaker 1: quite quite fascinating. Let's let's talk a little bit a

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Speaker 1: lot about how your business works. Do hedge funds and

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Speaker 1: family offices come to you looking for slots to fill?

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Speaker 1: Are the traders and fund managers reaching out to you? What?

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Speaker 1: What does the structure like? So, UM, let me back

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Speaker 1: up and tell you, which I'm actually quite proud of.

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Speaker 1: We've been in business for almost seventeen years, seventeen this February.

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Speaker 1: Most of our clients we've been working with practically, if

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Speaker 1: not since the beginning beginning, certainly within the first few

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Speaker 1: years of inception of I DW. So what that means

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Speaker 1: is we're UM, we really know their business, We've helped

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Speaker 1: them build their business. And yes they are coming to

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Speaker 1: us UM for specific assignments, whether it's and the common

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Speaker 1: thread being they are all uh senior people who can

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Speaker 1: move the needle, whether it's a someone to do VI,

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Speaker 1: a t M t PM for equities UM, someone to

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Speaker 1: run an emerging markets business, someone to build and run distress.

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Speaker 1: But at the same time, and this goes back perhaps

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Speaker 1: to my BCG background, UM, I really are our role

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Speaker 1: my firm's role is to also be an advisor to

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Speaker 1: them as well as to the market. So it's I'll

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Speaker 1: give you two assignments we're working on today. A in

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Speaker 1: the genesis of it UM each each one UM is

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Speaker 1: arguably for one of the biggest and most sophisticated hedge

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Speaker 1: funds in the world. One UM, I started talking with

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Speaker 1: the founder at the end of the summer about a

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Speaker 1: new business he wants to build. He runs a forty

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Speaker 1: billion dollar hedge funds, super successful, and he wants to

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Speaker 1: create something wholly other than what he does today. So

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Speaker 1: we're helping him find somebody who could oversee that and

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Speaker 1: build that. That's that's a very sophisticated person who's not

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Speaker 1: This isn't someone looking for a job. This is somebody

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Speaker 1: who has actually had great success with what they've done

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Speaker 1: in the past, and this is kind of an interesting

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Speaker 1: maybe chapter two UM and and as successful as they've been,

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Speaker 1: it's an opportunity for even greater wealth creation. The second

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Speaker 1: example I'll give you is another UM client that is

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Speaker 1: almost as big UM and again, these are two of

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Speaker 1: the most successful hedge funds in the world. Very forward

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Speaker 1: thinking guys. Uh, this is al we've worked with for

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Speaker 1: a long time. I came to him and I said

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Speaker 1: to him, Um, there I see an ARB in the

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Speaker 1: market right now. UM, there's a universe of people who

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Speaker 1: are really talented and our staying where they are not

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Speaker 1: because they're happy, but because a better option doesn't exist.

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Speaker 1: And if you created this, I think you could capture

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Speaker 1: that alpha right this this group of individuals that have

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Speaker 1: been phenomenal P and L generators, even in the last

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Speaker 1: few years where it's been very difficult, he's now building

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Speaker 1: that business. So it's both UM working on UM discreet

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Speaker 1: assignments for our clients as well as coming to them

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Speaker 1: with advice about where to take take their how to

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Speaker 1: take their funds forward. That's that's fascinating. So if someone

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Speaker 1: comes to you and they're looking to fill a specific role,

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Speaker 1: what is your thought process like when you're trying to say,

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Speaker 1: who do I know that might be a good fit

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Speaker 1: for this? Or if I don't know anybody in particul

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Speaker 1: killer who comes to mind, how do you go about

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Speaker 1: creating UM a pool of applicants that could fill that role. Well,

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Speaker 1: after again almost two decades doing this, we typically, UM,

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Speaker 1: you know most of the player We kind of No,

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Speaker 1: I'm not going to go so far as to say

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Speaker 1: we have the answer before we begin, although that is

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Speaker 1: often correct, like actually formally begin this like someone says

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Speaker 1: something and you're like, I know, in the back of

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Speaker 1: your head, I have just the p We We've done

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Speaker 1: so much work in every conceivable asset class so many times,

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Speaker 1: um that when we start something, it's rarely truly brand

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Speaker 1: new what it can be because certain strategies are more

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Speaker 1: cyclical than others. So for example, UM, when we did

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Speaker 1: the here's a good example, when we did the head

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Speaker 1: of Emerging markets for one of our clients, he asked

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Speaker 1: me how much work we've done in e M and

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Speaker 1: I told him we had done a fair bit of work.

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Speaker 1: This is going back a few years. But because it's

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Speaker 1: a cyclical strategy, not for a while. UM, So they're

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Speaker 1: what we did is we threw a lasto over the

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Speaker 1: universe sort of as we knew it from when we

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Speaker 1: last left off and when that strategy was last in vogue,

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Speaker 1: and and it was a pretty sizeable universe. But um,

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Speaker 1: and this was a global search as well, right, because

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Speaker 1: it's a head of emerging markets, it's the person could

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Speaker 1: sit here or could sit in London and we just

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Speaker 1: dive in and we build a tapestry of who the

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Speaker 1: best people are, which is both by meeting people that

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Speaker 1: we already know to be good. But even if we

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Speaker 1: have no idea UM, the reality is we're doing so

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Speaker 1: much work in other areas, whether it's credit rates, macro,

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Speaker 1: and if we're doing work at a multi strat and

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Speaker 1: we have the credit candidates or the equities candidates some play,

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Speaker 1: they will also have perspective on who is good in

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Speaker 1: a m right, whether it's at their firm or they

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Speaker 1: may or they may know someone that they respected another firm.

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Speaker 1: And and the common theme is these are people we're

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Speaker 1: reaching out to, people who have who we who we

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Speaker 1: view as best in class and um, talented people tend

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Speaker 1: to recommend other talented people, so we we very quickly

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Speaker 1: um form a picture of who the best people are.

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Speaker 1: And the other thing Barry is just good old fashioned

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Speaker 1: hard work. When we do a search, any search, we're

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Speaker 1: typically going through maybe to three people, even though I

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Speaker 1: know the answer is within ten to fifteen of those.

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Speaker 1: We just want to make sure we're leaving no stone

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Speaker 1: unturned and also building our own depth and breadth of knowledge.

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Speaker 1: So when you make a final recommendation to a firm.

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Speaker 1: I imagine this varies from firm to firms. Do some

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Speaker 1: firms say find me the guy and I'll hire them.

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Speaker 1: Or do firms say give me your best on a

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Speaker 1: three choices and will interview them. What what's the range like?

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Speaker 1: It's really it's usually iterative because again there there is

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Speaker 1: there's the best three choices in its basis form, which

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Speaker 1: is people who are um who can generate Who are

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Speaker 1: the people who can generate consistent P and l over time?

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Speaker 1: UM that meet with with our UM with that meet

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Speaker 1: with our investing you know our investment parameters. But your

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Speaker 1: your version of who the those best three people are

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Speaker 1: may be different than someone else's. Part of it is

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Speaker 1: cultural fit. Part of it is just how flexible you,

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Speaker 1: as a founder are going to be with respect to

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Speaker 1: giving them. You may say you're going to give them

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Speaker 1: a fair degree of you know, a lot of autonomy,

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Speaker 1: but they may need more than what you're willing to

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Speaker 1: give them. Um, they and then there were just nuances.

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Speaker 1: They may You may say you're open to somebody who

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Speaker 1: runs in a in a manner that's quite that's concentrated,

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Speaker 1: in volatile, but their version of concentration and volatility maybe

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Speaker 1: too much for you. So there's a lot of nuances

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Speaker 1: where we you and I um need to iterate on

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Speaker 1: truly who the best quote three are. And the way

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Speaker 1: we work is I'm not gonna we're not gonna throw fifty.

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Speaker 1: We're going to do the work of meeting all the

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Speaker 1: bull but we're going to have you meet let's call

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Speaker 1: it fifteen twenty that many, and they want you as

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Speaker 1: well because we're talking about really good people and they're

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Speaker 1: going to learn something. They're going to learn how other

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Speaker 1: funds are set up, they're going to learn how other

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Speaker 1: um how they're going to get ideas from these people

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Speaker 1: right there. There may be um uh, let's say it's

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Speaker 1: along short equity search. There may be things that that

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Speaker 1: that the candidates are in that are actually helpful for

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Speaker 1: the founder to know about. So if if I told

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Speaker 1: you that a search is a portal to meeting the

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Speaker 1: top fifty people in your universe, you would take every

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Speaker 1: one of those meetings. That's a good use of your time.

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Speaker 1: So this isn't just I need a guy to do this,

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Speaker 1: get me some now, this is a whole big, holistic

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Speaker 1: process that's a really a two way street with a

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Speaker 1: lot of exchange of information. That is the only way

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Speaker 1: we work. And it's and and I will tell you, um,

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Speaker 1: we're doing a search right now where the founder was

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Speaker 1: candid with me. He may not even end up hiring someone.

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Speaker 1: He just sees um an opportunity that he may may

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Speaker 1: being the operative word, want to capitalize upon and wants

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Speaker 1: to meet the smartest people who do this out there.

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Speaker 1: And then let's iterate on what makes sense. So that's

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Speaker 1: not that different than BCG, where I had to sort

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Speaker 1: of help a CEO draw a conclusion on whether to

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Speaker 1: enter a market, and the way we went about that

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Speaker 1: was through competitive benchmarking and speaking to other really smart

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Speaker 1: people who sat in competitive companies and would help us

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Speaker 1: to help him figure it out. So here's the obvious

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Speaker 1: business question. Typically m headhunting and recruitment firms get paid

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Speaker 1: when the hier is placed. If someone says to you, hey,

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Speaker 1: I may may not hire this person, but do all

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Speaker 1: this work, do you have to set up a different

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Speaker 1: sort of consultingly. We we are retained firm. We don't

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Speaker 1: do any work without without so it's a very different

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Speaker 1: structure than the old school. Now we we are at

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Speaker 1: the risk of being totally a modest I will tell you,

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Speaker 1: for a variety of reasons, I don't think we look

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Speaker 1: like anybody else that the most prominent one of which

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Speaker 1: is um are the level we work at and the

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Speaker 1: access to the people that we have. So um It's. Yes,

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Speaker 1: there are discrete roles that founders need to fill. Yes

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Speaker 1: we are hired to complete those searches, but they tend

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Speaker 1: to be really important searches that will move the needle

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Speaker 1: for the for the fund. And if it's a fund

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Speaker 1: that's let's call it somewhere between ten and forty billion,

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Speaker 1: that's a really important person. Um. And and and it's

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Speaker 1: not about who's looking for a job. It's not about

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Speaker 1: um uh, you know who's available. It's that's not how

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Speaker 1: we come in things. If you think of a ven diagram,

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Speaker 1: one bubble being best in class, and there are very

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Speaker 1: few people in any asset class I'd put into that

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Speaker 1: bubble that are really that good. Again, there's all the

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Speaker 1: work we do to make sure we're leaving no stone unturned,

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Speaker 1: but I really have a firm view on who is

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Speaker 1: best in class. My firm does before we start at

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Speaker 1: any sorts. That's why I say, we sort of know

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Speaker 1: the answer, but we just wanted we do all the

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Speaker 1: work to make sure we're not missing anybody. The second

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Speaker 1: bubble is people who are disenfranchised, miserable, looking for jobs.

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Speaker 1: If there's an overlap, and these days, for a variety

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Speaker 1: of reasons we can get into, there's probably more of

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Speaker 1: an overlap than ever before. That's a happy coincidence. It

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Speaker 1: makes our job a little bit easier. All we care about.

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Speaker 1: All we care about is that first bubble and really

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Speaker 1: talented people who are who have accomplished something special. This

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Speaker 1: would not be an unusual profile of a candidate. Somebody

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Speaker 1: who oversees five billion dollars where they sit today has

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Speaker 1: had triple digit p n L every year for the

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Speaker 1: last specifically triple digit. Yeah, it's not even double digit.

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Speaker 1: Triple digit is an actual candidate and this isn't an outlier.

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Speaker 1: This is like, this is every day what we do.

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Speaker 1: So five billion, triple digit p n L and the

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Speaker 1: las four years have been really, really difficult. So that's

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Speaker 1: quite an accomplishment, right, much much tougher environment, which we

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Speaker 1: can talk about um and uh uh. And compensation for

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Speaker 1: him has typically been between twenty and thirty a year.

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Speaker 1: He's not looking for a job, and he's at a

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Speaker 1: great firm, by the way, which is not at all

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Speaker 1: facing the issues other firms are facing. He's coming in

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Speaker 1: to talk to me and my team because he wants

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Speaker 1: to understand given what we do, given all the smart

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Speaker 1: people we meet, and the clients we have, and everything

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Speaker 1: we see across the entire hedge fund landscape. Am I,

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Speaker 1: what do you think about the structure of where I'm sitting? UM?

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Speaker 1: What is what else exists out there? Here's what I've built?

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Speaker 1: Do I take my bag of tricks and do something different?

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Speaker 1: And then what does different look like? What should compensation

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Speaker 1: look like? For me? It's it's it's it's an advisory

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Speaker 1: UM meeting, and in that it is our job to

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Speaker 1: understand everything about his firm before he walks in, which

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Speaker 1: we know. Why do we know because we've met plenty

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Speaker 1: of other people at that firm UM constantly and UM

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Speaker 1: and also understand what all his other options look like.

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Speaker 1: So we have to have deep intelligence on all the

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Speaker 1: other funds that he could theoretically think about, and then

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Speaker 1: have a point of view on which of our clients

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Speaker 1: could make sense. And there are times there isn't although

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Speaker 1: it's rare there you know there isn't something else because

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Speaker 1: our clients tend to be very innovative and creative. To

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Speaker 1: attract someone like that, there are times he should stay

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Speaker 1: exactly where he's at, but more often than not, we

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Speaker 1: can set something up that is structurally superior to where

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Speaker 1: he is. Even at that level, that's a very different

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Speaker 1: dynamic than somebody who like needs a job. Quite fascinating.

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Speaker 1: Let's let's jump into something you alluded to earlier. The

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Speaker 1: past decade has not been especially kind to most hedge funds.

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Speaker 1: A lot of them have been struggling. First question, from

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Speaker 1: your unique vantage point, why is that? And second what

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Speaker 1: can they do to turn of things around? Okay, so

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Speaker 1: I don't know that it's been the past decade. I

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Speaker 1: think it's more from twenty fifteen on. Okay, Okay, so

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Speaker 1: we could that's a whole longer. That's a whole longer discussion.

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Speaker 1: We can talk. But it's it's been it's been a

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Speaker 1: very very tough environment. But but let's talk about what's

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Speaker 1: gone on. And MO went to timing, so um, and

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Speaker 1: let's juxtapose it to when I started, which we talked

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Speaker 1: about earlier, which was two thousand and three, that's when

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Speaker 1: I started my firm, uh five hundred billion of assets

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Speaker 1: under management, three thousand hedge funds. As you said, Barry,

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Speaker 1: Now there's eleven thousand hedge funds and three and a

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Speaker 1: half trillion of a UM. A lot of that growth

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Speaker 1: actually came post crisis. At the time of the in

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Speaker 1: two thousand and eight was one point four trillion, now

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Speaker 1: is three and a half. So that's a lot of growth.

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Speaker 1: Actually in the last is that organic growth of assets

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Speaker 1: or is that just capital flowing? Capital flowing in literally

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Speaker 1: especially post crisis. Right, that's when you saw the shift, right,

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Speaker 1: And that's also you know you mentioned earlier we do

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Speaker 1: UM which we do uh work to find investment talent

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Speaker 1: for the hedge fund industry, but we also do work

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Speaker 1: to find and this is when this started, was was

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Speaker 1: in two thousand and eight. We have a very meaty

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Speaker 1: practice looking at UM non investment talent across functions like president, CEO,

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Speaker 1: head of marketing UM meaning the non investments administrative Well yeah,

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Speaker 1: but but senior UM. But what what what really drove

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Speaker 1: that was post crisis you saw all the the shift

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Speaker 1: from fund of funds and high net worth LPs to

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Speaker 1: institutional LPs because they realized that had they invested in

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Speaker 1: a hedge fund, they would have done much better than

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Speaker 1: buying the market. Right, most hedge funds were down half

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Speaker 1: they were down, but they were down half as much

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Speaker 1: as the SMP on average. So so so institutions said,

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Speaker 1: we'll wait a second. You know this is this is like,

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Speaker 1: this is an asset class that we should be investing in.

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Speaker 1: And so all of a sudden, hedge funds had to

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Speaker 1: look they had to grow up right. It was no

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Speaker 1: wanting legal compliance, accounting operations. We were suddenly they couldn't

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Speaker 1: just be a fly by night sort of a couple

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Speaker 1: of guys working, which is what it was, right, So

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Speaker 1: we were brought in all these founders that we did

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Speaker 1: work for on the investing side, said well, wait a second.

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Speaker 1: You know, my head of marketing isn't going to cut

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00:24:34,240 --> 00:24:36,399
Speaker 1: it anymore, my CEO isn't going to cut So we

432
00:24:36,440 --> 00:24:40,880
Speaker 1: had to revamp these funds and make them institutional, right,

433
00:24:41,000 --> 00:24:44,119
Speaker 1: so they would be attractive to institutional LPs. So what

434
00:24:44,240 --> 00:24:47,920
Speaker 1: happened is you saw all this institutional money pouring into

435
00:24:47,920 --> 00:24:50,320
Speaker 1: the and and pouring into the hedge fund world, and

436
00:24:50,440 --> 00:24:54,400
Speaker 1: institutional LPs were also far less sophisticated back then about

437
00:24:54,400 --> 00:24:56,360
Speaker 1: hedge funds because it was a new asset class to them.

438
00:24:56,760 --> 00:24:59,920
Speaker 1: So what so where so what happened? So we went.

439
00:25:00,160 --> 00:25:04,000
Speaker 1: So you have this huge growth of funds, tremendous amount

440
00:25:04,000 --> 00:25:09,360
Speaker 1: of capital pouring into the industry. UM technology became much

441
00:25:09,400 --> 00:25:13,040
Speaker 1: more sophisticated, right, think about technology in two thousand and

442
00:25:13,080 --> 00:25:17,040
Speaker 1: three to today. So today everyone has access to the

443
00:25:17,160 --> 00:25:20,840
Speaker 1: same information. That's why it's so, that's why scale is

444
00:25:20,880 --> 00:25:23,960
Speaker 1: so important in this business. To have the ability to

445
00:25:24,119 --> 00:25:30,199
Speaker 1: have UM data science and quant and a machine internally

446
00:25:30,320 --> 00:25:33,960
Speaker 1: that can turn that data into alphae signals. Very few

447
00:25:34,000 --> 00:25:36,600
Speaker 1: funds do that successfully, but it gives their people a

448
00:25:36,640 --> 00:25:40,480
Speaker 1: tremendous leg up if if they do create that in house.

449
00:25:41,080 --> 00:25:44,440
Speaker 1: UM so so so everyone has access to the same data.

450
00:25:44,600 --> 00:25:48,480
Speaker 1: Information is much more transparent. Also since two thousand and three,

451
00:25:48,640 --> 00:25:52,000
Speaker 1: you know, to date, you have the platforms. When I

452
00:25:52,040 --> 00:25:54,520
Speaker 1: say the platforms, I talk about the multi managers like

453
00:25:54,600 --> 00:25:57,600
Speaker 1: Citadel and Point seventy two and Millennium and ballet Asney.

454
00:25:57,880 --> 00:26:00,760
Speaker 1: These guys exploded, they got so much bigger. You have

455
00:26:00,840 --> 00:26:05,600
Speaker 1: all these pms now sitting at these shops UM and

456
00:26:05,680 --> 00:26:09,840
Speaker 1: so many more eyes and ears at conferences UM and

457
00:26:09,920 --> 00:26:13,000
Speaker 1: behind a shorting model that can suss out under performance.

458
00:26:13,040 --> 00:26:17,560
Speaker 1: So so if management says something squishy at a conference,

459
00:26:17,720 --> 00:26:20,439
Speaker 1: it used to have three to six months to for

460
00:26:20,520 --> 00:26:23,439
Speaker 1: that under performance to get price fully. Now that happens

461
00:26:23,480 --> 00:26:26,840
Speaker 1: in two days. So the window of efficiency right for

462
00:26:26,920 --> 00:26:30,520
Speaker 1: performance has gotten much smaller. And LPs, as I said,

463
00:26:30,520 --> 00:26:33,399
Speaker 1: have gotten much more sophisticated. And so with all of this,

464
00:26:33,560 --> 00:26:36,240
Speaker 1: returns have come down because the industry is so much

465
00:26:36,240 --> 00:26:40,280
Speaker 1: more crowded. Oh and liquidity right mutual UM funds and

466
00:26:40,320 --> 00:26:43,200
Speaker 1: retail have shrunk, So there's far less liquidity now than

467
00:26:43,240 --> 00:26:46,119
Speaker 1: there was back then. I fewer companies are going public

468
00:26:46,320 --> 00:26:50,520
Speaker 1: right with increased UM regulation and scrutiny. CEO s or like,

469
00:26:50,800 --> 00:26:52,880
Speaker 1: I don't want to go public. If I'm a tech company,

470
00:26:52,920 --> 00:26:54,840
Speaker 1: I can just go to the go to a big

471
00:26:54,880 --> 00:26:58,160
Speaker 1: tech private equity firm and and get funded. That way,

472
00:26:58,200 --> 00:27:00,280
Speaker 1: I don't have to subject myself to this. So for

473
00:27:00,320 --> 00:27:04,000
Speaker 1: all of those reasons, UM, it's become far more difficult

474
00:27:04,040 --> 00:27:07,840
Speaker 1: to generate alpha and what you see literally the last

475
00:27:07,880 --> 00:27:10,320
Speaker 1: good year for most of these funds. And when I

476
00:27:10,400 --> 00:27:14,080
Speaker 1: say most, one other sort of clarification point we talk

477
00:27:14,160 --> 00:27:17,280
Speaker 1: about eleven thousand hedge funds. Most of them are single

478
00:27:17,320 --> 00:27:22,880
Speaker 1: manager funds. They're not multi managers, and they're not multi strats. Although,

479
00:27:23,800 --> 00:27:27,480
Speaker 1: um so, the actual number of hedge funds, the individual

480
00:27:27,480 --> 00:27:31,359
Speaker 1: hedge funds tend to be single manager funds, meaning six

481
00:27:31,480 --> 00:27:34,000
Speaker 1: eight thousand, what what sort of numbers? Probably yeah, I

482
00:27:34,040 --> 00:27:36,240
Speaker 1: mean I don't know the exact number, but that's the

483
00:27:36,280 --> 00:27:40,160
Speaker 1: majority of funds, just because in order to be think

484
00:27:40,160 --> 00:27:42,000
Speaker 1: about it, there aren't who else, you know, there's not

485
00:27:42,160 --> 00:27:45,320
Speaker 1: that many other funds you can name that are multi managers, right,

486
00:27:45,960 --> 00:27:50,640
Speaker 1: um uh. And in terms of multi strats, uh, those

487
00:27:50,640 --> 00:27:54,640
Speaker 1: would be funds like Davidson, Kempner, Golden Triangela, Gordon. These

488
00:27:54,640 --> 00:27:58,359
Speaker 1: are behe myths that are in multiple strategies and managing

489
00:28:00,200 --> 00:28:02,679
Speaker 1: thirty billion or whatever it is dollars. There aren't that

490
00:28:02,720 --> 00:28:05,400
Speaker 1: many funds that look like that. Most funds are are

491
00:28:05,640 --> 00:28:09,720
Speaker 1: actually quite small. Most hedge funds are. I think the

492
00:28:09,920 --> 00:28:13,160
Speaker 1: two thirds of hedge funds are two fifty million or less.

493
00:28:13,160 --> 00:28:15,480
Speaker 1: So this is like a cottage industry of two bit

494
00:28:15,480 --> 00:28:18,000
Speaker 1: players for the most part. Um But I have to

495
00:28:18,080 --> 00:28:19,959
Speaker 1: jump in and ask you this question because you you

496
00:28:20,160 --> 00:28:24,800
Speaker 1: said something previously that um, you just reminded me of,

497
00:28:25,200 --> 00:28:30,000
Speaker 1: which is it's a myth that being a hedge fund

498
00:28:30,040 --> 00:28:35,639
Speaker 1: manager is the route to personal riches. I'm paraphrasing somewhat,

499
00:28:35,880 --> 00:28:39,880
Speaker 1: but you you've said that previously, your explanation of this,

500
00:28:40,280 --> 00:28:43,120
Speaker 1: that the vast majority of hedge funds are single manager

501
00:28:43,160 --> 00:28:46,080
Speaker 1: funds with a couple of hundred million dollars. Is that

502
00:28:46,320 --> 00:28:50,440
Speaker 1: what underlies that statement? Um quote you told the Wall

503
00:28:50,480 --> 00:28:52,680
Speaker 1: Street Journal the biggest myth about working out a hedge

504
00:28:52,680 --> 00:28:56,360
Speaker 1: fund is it's a quick way to um earn great riches.

505
00:28:56,760 --> 00:29:00,160
Speaker 1: Is that what's underlying That's absolutely part of what's underlying that.

506
00:29:00,320 --> 00:29:03,080
Speaker 1: And the other piece which I was getting to that's

507
00:29:03,160 --> 00:29:08,400
Speaker 1: underlying that is now the difficult the difficulty of generating alpha.

508
00:29:08,560 --> 00:29:11,840
Speaker 1: So returns have come. So yes, most funds are small,

509
00:29:12,200 --> 00:29:14,680
Speaker 1: they're inconsequential. You're not going to make a lot of

510
00:29:14,680 --> 00:29:17,840
Speaker 1: money managing like a couple hundred million, and many of

511
00:29:17,880 --> 00:29:20,680
Speaker 1: them are even smaller than that um and they're not

512
00:29:20,720 --> 00:29:23,640
Speaker 1: going to exist. Most of these guys in in or

513
00:29:23,840 --> 00:29:26,600
Speaker 1: or they'll just be okay, managing a little bit of money.

514
00:29:26,600 --> 00:29:29,080
Speaker 1: And that's that's a different business model. That's not what

515
00:29:29,120 --> 00:29:31,160
Speaker 1: you and I are talking about. Right, that's not our

516
00:29:31,200 --> 00:29:34,560
Speaker 1: client base, and that's typically and those small guys they're

517
00:29:34,680 --> 00:29:36,680
Speaker 1: lucky if they're in our office because what we're doing

518
00:29:36,720 --> 00:29:38,920
Speaker 1: with them is we're popping them into bigger funds. We

519
00:29:39,000 --> 00:29:41,040
Speaker 1: do a lot of acquisition of hedge funds as well,

520
00:29:41,360 --> 00:29:43,400
Speaker 1: so they'll get gobbled up by the bigger players if

521
00:29:43,440 --> 00:29:45,040
Speaker 1: there are any good and they should be thankful for

522
00:29:45,040 --> 00:29:48,720
Speaker 1: that because they'll have now a lot more capital, resources

523
00:29:48,800 --> 00:29:52,160
Speaker 1: and um artillery for lack of a better word, to

524
00:29:52,160 --> 00:29:55,080
Speaker 1: be successful. Are they being gobbled up because of their

525
00:29:55,240 --> 00:29:57,880
Speaker 1: alpha generation or is it because of their assets? Is

526
00:29:58,280 --> 00:30:03,600
Speaker 1: more of an a A fund like UM Citadel doesn't

527
00:30:03,640 --> 00:30:06,160
Speaker 1: need the assets of a two d and fifty million

528
00:30:06,200 --> 00:30:09,000
Speaker 1: dollar funds far from that two hundred and fifty million

529
00:30:09,040 --> 00:30:12,000
Speaker 1: dollar fund needs Citadel because they can't grow, they don't

530
00:30:12,040 --> 00:30:15,840
Speaker 1: have scale, they can compete for resources, talent, capital. They

531
00:30:15,880 --> 00:30:19,440
Speaker 1: are they are inconsequential. However, if they've had good returns,

532
00:30:19,600 --> 00:30:21,320
Speaker 1: that's a great place for them to be because now

533
00:30:21,400 --> 00:30:23,880
Speaker 1: they can scale that business. So that becomes an aqua

534
00:30:23,960 --> 00:30:28,200
Speaker 1: hier Is that a fair tech term to aqua higher? Yeah,

535
00:30:28,520 --> 00:30:32,080
Speaker 1: it's an acquisition. We're effectively you're hiring, Yes, that's exactly

536
00:30:32,080 --> 00:30:34,440
Speaker 1: what it is. Um So there's a lot of that

537
00:30:34,440 --> 00:30:36,520
Speaker 1: that we do as well. But but let me, because

538
00:30:36,520 --> 00:30:39,440
Speaker 1: this is an important point come back to why um

539
00:30:39,440 --> 00:30:41,720
Speaker 1: to where we are today? Okay, because we are in

540
00:30:41,720 --> 00:30:44,320
Speaker 1: a very different place today than we were when this

541
00:30:44,440 --> 00:30:48,240
Speaker 1: industry first started, when we when I DW first started

542
00:30:49,240 --> 00:30:54,800
Speaker 1: um so, so, UH, when you look at returns for

543
00:30:54,920 --> 00:30:59,720
Speaker 1: most funds, again, single manager funds, it's like you look

544
00:30:59,720 --> 00:31:04,280
Speaker 1: at UH fifteen, sixteen, seventeen, and eighteen, the last four

545
00:31:04,400 --> 00:31:07,280
Speaker 1: full years, it's a it's really bad. If you add

546
00:31:07,320 --> 00:31:10,320
Speaker 1: up the cumulative return, it's a sea of red and

547
00:31:10,440 --> 00:31:14,600
Speaker 1: pointing to not even positive negative returns for a great

548
00:31:14,720 --> 00:31:16,959
Speaker 1: number of them. Yes, it's like if you add them up,

549
00:31:16,960 --> 00:31:20,720
Speaker 1: it's basically flat to down. So I look, I think

550
00:31:20,760 --> 00:31:23,320
Speaker 1: it's just again it's a more difficult environment. It's harder

551
00:31:23,360 --> 00:31:28,520
Speaker 1: to generate alpha UM And also if when returns come down,

552
00:31:28,680 --> 00:31:32,520
Speaker 1: when we're talking about fees, if returns come down, it's

553
00:31:32,600 --> 00:31:36,040
Speaker 1: very difficult to justify that two and twenty fee structure.

554
00:31:36,200 --> 00:31:39,840
Speaker 1: I'll give you a discrete example. If I'm a fund

555
00:31:40,640 --> 00:31:44,960
Speaker 1: that historically generated in the good old days returns and

556
00:31:45,000 --> 00:31:47,760
Speaker 1: by the way, these guys love to quote inception to

557
00:31:47,840 --> 00:31:50,960
Speaker 1: date returns, which is like nonsense. I mean you you

558
00:31:51,040 --> 00:31:52,880
Speaker 1: have to they have to say that's great. Now let's

559
00:31:52,880 --> 00:31:56,160
Speaker 1: talk about words, okay, and then they like go quiet,

560
00:31:56,480 --> 00:32:00,000
Speaker 1: it's not good. So if you look at the return

561
00:32:00,000 --> 00:32:02,640
Speaker 1: turns of these funds again very bad for the last

562
00:32:02,640 --> 00:32:06,480
Speaker 1: four years, and you look at UM asset flows in

563
00:32:06,520 --> 00:32:10,160
Speaker 1: the industry, they are reflective of what is going on.

564
00:32:11,080 --> 00:32:17,360
Speaker 1: The total amount of net outflows in eighteen was UM

565
00:32:17,400 --> 00:32:19,880
Speaker 1: thirty seven billion. Do you know where we're at to

566
00:32:19,960 --> 00:32:24,640
Speaker 1: date in terms of net outflows? Go ahead over six

567
00:32:25,960 --> 00:32:28,320
Speaker 1: and was a year we saw a lot of big

568
00:32:28,360 --> 00:32:32,400
Speaker 1: fun shutdown, right. We saw high Fields chose to shut down,

569
00:32:33,000 --> 00:32:38,040
Speaker 1: URBIOND shutdown, Criterion Ivory, fold your Hill, Glen Hill, three Bays.

570
00:32:38,080 --> 00:32:39,880
Speaker 1: I'm it can go on and on and on. And

571
00:32:39,960 --> 00:32:43,080
Speaker 1: yet we are fifty percent higher this year than last

572
00:32:43,160 --> 00:32:45,600
Speaker 1: year in terms of net outflows to the industry. So

573
00:32:45,880 --> 00:32:50,600
Speaker 1: LPs are pretty um disappointed in terms of where things

574
00:32:50,600 --> 00:32:53,080
Speaker 1: are at. And so back to my example. If I'm

575
00:32:53,120 --> 00:32:57,880
Speaker 1: a fund which UM returned, let's say the let's just

576
00:32:57,920 --> 00:32:59,640
Speaker 1: say I know it's up higher, but let's say the

577
00:32:59,760 --> 00:33:02,080
Speaker 1: s m P is up fifteen percent and I'm a fund,

578
00:33:02,160 --> 00:33:05,600
Speaker 1: a long short equity fund that runs UM fifty percent

579
00:33:05,760 --> 00:33:09,600
Speaker 1: net long. That means fifty percent of my return one

580
00:33:09,640 --> 00:33:12,480
Speaker 1: could get an LP could get from just buying the SMP.

581
00:33:13,000 --> 00:33:15,280
Speaker 1: And let's say I'm up in line with the SMP

582
00:33:15,400 --> 00:33:19,640
Speaker 1: this year, So fifty percent is beta. Right when you're

583
00:33:19,680 --> 00:33:22,400
Speaker 1: a long short, your your risk parameters are very different.

584
00:33:22,480 --> 00:33:25,040
Speaker 1: And no, but if if if, if fifth, If I'm

585
00:33:25,120 --> 00:33:30,280
Speaker 1: running net fifty percent long, that means that UM fifty

586
00:33:30,360 --> 00:33:34,480
Speaker 1: percent is correlates to the SMP. That's what that means.

587
00:33:34,600 --> 00:33:37,920
Speaker 1: So fifty percent is beta and fifty percent is alpha.

588
00:33:38,080 --> 00:33:40,760
Speaker 1: So if I'm up fifteen and the SMP is up

589
00:33:40,760 --> 00:33:44,960
Speaker 1: fifteen percent, only seven and a half percent is alpha.

590
00:33:45,080 --> 00:33:47,840
Speaker 1: Yet I'm charging two and twenty and that tent is

591
00:33:47,880 --> 00:33:53,040
Speaker 1: on both alpha and beta, So um fifteen So of

592
00:33:53,080 --> 00:33:56,480
Speaker 1: fifteen percent is three percent three plus two is five.

593
00:33:56,640 --> 00:34:00,400
Speaker 1: I'm charging five p on a U m uh five

594
00:34:00,440 --> 00:34:03,040
Speaker 1: percent divided by seven and a half percent. Just follow

595
00:34:03,120 --> 00:34:05,960
Speaker 1: me with the math, and you know, um, your your

596
00:34:06,000 --> 00:34:11,080
Speaker 1: your listeners can uh yeah, I'm sure they can kind

597
00:34:11,120 --> 00:34:15,000
Speaker 1: of work this out for themselves. It's a Mathew group.

598
00:34:15,360 --> 00:34:18,520
Speaker 1: That means two thirds of the alpha. By that equation

599
00:34:18,680 --> 00:34:22,520
Speaker 1: is going to me, the hedge fund manager, and one

600
00:34:22,560 --> 00:34:25,759
Speaker 1: third to the LPs. That's not a winning construct. But

601
00:34:25,800 --> 00:34:28,759
Speaker 1: then you have hedge funds like the multi managers, where

602
00:34:28,760 --> 00:34:32,719
Speaker 1: it's all alpha. Everything they generated alpha. It's uncorrelated, it's

603
00:34:32,800 --> 00:34:35,960
Speaker 1: low volatility. That's why. And and so that's a totally

604
00:34:35,960 --> 00:34:40,320
Speaker 1: defensible business model. And jumping onto another subject, the startup environment.

605
00:34:40,840 --> 00:34:44,040
Speaker 1: While so few funds can scale, and we have so

606
00:34:44,160 --> 00:34:47,680
Speaker 1: we have more closures than startups these days. The exception

607
00:34:47,760 --> 00:34:53,239
Speaker 1: to that rule are funds that splinter off from the

608
00:34:53,360 --> 00:34:56,880
Speaker 1: successful multi managers. That's why we saw Exodus Point have

609
00:34:57,000 --> 00:34:59,359
Speaker 1: the biggest launch and hedge fund history last year at

610
00:34:59,360 --> 00:35:02,480
Speaker 1: eight billion. That's why this year you see Woodline and

611
00:35:02,600 --> 00:35:07,520
Speaker 1: Candlestick Um to Citadel spinouts launched with anywhere somewhere between

612
00:35:07,520 --> 00:35:11,120
Speaker 1: one and three billion UM. Candlestick I think was between

613
00:35:11,120 --> 00:35:14,640
Speaker 1: one and two and will be and uh Woodline is

614
00:35:14,680 --> 00:35:18,600
Speaker 1: between two and three. These are exceptions that prove the

615
00:35:18,680 --> 00:35:21,960
Speaker 1: rule and also shine a light on the efficiency of

616
00:35:22,000 --> 00:35:24,960
Speaker 1: this of the hedge fund universe. You have hedge funds

617
00:35:24,960 --> 00:35:27,200
Speaker 1: that are struggling to come up with a fee structure

618
00:35:27,600 --> 00:35:30,560
Speaker 1: that can address the lack of value creation and then

619
00:35:30,600 --> 00:35:33,680
Speaker 1: you have funds like Element that are charging two and forty. Again,

620
00:35:33,840 --> 00:35:37,680
Speaker 1: it's it's it's efficiency. Our last time, when you discussed

621
00:35:37,719 --> 00:35:41,320
Speaker 1: all sorts of really fascinating things, I wanted to circle

622
00:35:41,480 --> 00:35:47,000
Speaker 1: back to UM in particular about the shifts and where

623
00:35:47,000 --> 00:35:50,480
Speaker 1: institutions are putting their money and the fee structure. So

624
00:35:50,480 --> 00:35:53,200
Speaker 1: so let's start with with the fees. One of the

625
00:35:53,200 --> 00:35:56,000
Speaker 1: things I've seen that's been kind of interesting, and you

626
00:35:56,760 --> 00:36:01,480
Speaker 1: explained earlier why institutions hate to pay alpha prices for

627
00:36:01,600 --> 00:36:05,320
Speaker 1: beta is the rise of a so called Falkrum fee

628
00:36:05,760 --> 00:36:10,879
Speaker 1: where there's a very modest fee on assets and the

629
00:36:10,960 --> 00:36:16,080
Speaker 1: actual profit sharing fee the typical two and twenty. Part

630
00:36:16,080 --> 00:36:19,960
Speaker 1: of the fee is not on what the SMP provides,

631
00:36:20,000 --> 00:36:23,120
Speaker 1: but only on the excess performance, so it might be

632
00:36:23,160 --> 00:36:27,239
Speaker 1: instead of two and twenty five basis points and thirty.

633
00:36:27,400 --> 00:36:29,160
Speaker 1: What what do you think of those sorts of fee

634
00:36:29,160 --> 00:36:34,279
Speaker 1: structures that they have any longevity? I think that we

635
00:36:34,400 --> 00:36:38,120
Speaker 1: need to UM. We need to move to a model

636
00:36:38,480 --> 00:36:40,799
Speaker 1: which is closer for if you're if funds are going

637
00:36:40,800 --> 00:36:46,280
Speaker 1: to charge what they charge whatever, which is sizeable, UM,

638
00:36:46,320 --> 00:36:49,880
Speaker 1: we need to move to a structure where LPs are

639
00:36:49,920 --> 00:36:53,080
Speaker 1: paying for alpha. That's the bottom line. So whether it

640
00:36:53,280 --> 00:36:56,560
Speaker 1: is they lower their fees UM or the just charge

641
00:36:56,600 --> 00:36:59,439
Speaker 1: on alpha that has to be where the industry is going.

642
00:36:59,800 --> 00:37:03,880
Speaker 1: Or and or here's another thought. There are hedge funds

643
00:37:03,880 --> 00:37:07,560
Speaker 1: which UM really and this is true of a of

644
00:37:07,600 --> 00:37:10,400
Speaker 1: a lot of the single manager long short equity cubs

645
00:37:10,800 --> 00:37:14,239
Speaker 1: long short equity funds, whether Tiger cubs or related. Some

646
00:37:14,360 --> 00:37:17,960
Speaker 1: of these guys are really best at generating long alpha.

647
00:37:18,120 --> 00:37:20,719
Speaker 1: They're really not that good on the short side, and

648
00:37:20,760 --> 00:37:23,680
Speaker 1: if you look closely at the composition of their return,

649
00:37:24,200 --> 00:37:29,279
Speaker 1: the shorts are actually volatility enhancers and alpha detractors. But

650
00:37:29,320 --> 00:37:31,799
Speaker 1: they have to short because they're hedge funds, right. They

651
00:37:31,800 --> 00:37:34,520
Speaker 1: can't charge two and twenty without with just having a

652
00:37:34,560 --> 00:37:37,160
Speaker 1: long only model. And it's very hard to short when

653
00:37:37,160 --> 00:37:39,759
Speaker 1: the market has, at least for the first half of

654
00:37:39,800 --> 00:37:43,760
Speaker 1: this bullmarket just rampage straight up from O nine to twenty.

655
00:37:43,960 --> 00:37:46,719
Speaker 1: Let's called it's just it's not there. It's they're not

656
00:37:46,760 --> 00:37:49,719
Speaker 1: it's not what they do best. There are UM and

657
00:37:49,719 --> 00:37:53,120
Speaker 1: they're also not set up UM to do it as

658
00:37:53,200 --> 00:37:58,920
Speaker 1: well as the multi managers that have much broader and

659
00:37:59,000 --> 00:38:02,680
Speaker 1: deeper resource. Is UH to help these guys be successful.

660
00:38:03,000 --> 00:38:07,440
Speaker 1: UM with respect to with respect to managing factor volatility

661
00:38:07,600 --> 00:38:10,239
Speaker 1: and coming up with single name alpha shorts. So the

662
00:38:10,320 --> 00:38:15,880
Speaker 1: best thing these more concentrated directional managers could do would

663
00:38:15,880 --> 00:38:21,520
Speaker 1: be to say, Okay, I'm best degenerating long alpha. Therefore

664
00:38:22,000 --> 00:38:26,319
Speaker 1: let me set myself up in a way where I

665
00:38:26,440 --> 00:38:31,239
Speaker 1: maybe they create an alternative long only fund where and

666
00:38:31,280 --> 00:38:34,680
Speaker 1: I think this is the way of this is how

667
00:38:34,719 --> 00:38:37,280
Speaker 1: a lot of these funds are going to go UM.

668
00:38:37,320 --> 00:38:40,080
Speaker 1: I mean you recently saw in the last year so

669
00:38:40,320 --> 00:38:44,320
Speaker 1: a band even it really converted most of their assets

670
00:38:44,360 --> 00:38:48,440
Speaker 1: to long only. And so the idea being, UM, if

671
00:38:48,480 --> 00:38:51,200
Speaker 1: I'm best degenerating long alpha and I'm not that good

672
00:38:51,200 --> 00:38:54,680
Speaker 1: at managing short term volatility and coming up with UH

673
00:38:55,000 --> 00:38:59,360
Speaker 1: with alpha with alpha shorts, alpha alpha generating single name shorts,

674
00:38:59,800 --> 00:39:03,000
Speaker 1: but I need two to three or four years to

675
00:39:03,080 --> 00:39:06,279
Speaker 1: let my thesis play out. Then you know what, you know,

676
00:39:06,520 --> 00:39:08,400
Speaker 1: maybe you just charge on alpha at the end of

677
00:39:08,400 --> 00:39:11,560
Speaker 1: that time period, and so you have to and it's

678
00:39:11,560 --> 00:39:14,279
Speaker 1: a totally different structure, but that's the point. You need

679
00:39:14,360 --> 00:39:17,040
Speaker 1: to figure out what you're best at. It's so hard

680
00:39:17,120 --> 00:39:20,560
Speaker 1: now UM to generate consistent alpha, and you need to

681
00:39:20,560 --> 00:39:25,040
Speaker 1: figure out what UM structure is going to enable you

682
00:39:25,120 --> 00:39:29,080
Speaker 1: to be competitive, and that may mean locking up capital

683
00:39:29,160 --> 00:39:31,560
Speaker 1: for a longer period of time and charging less or

684
00:39:31,600 --> 00:39:35,280
Speaker 1: just charging on alpha. But the idea that one size

685
00:39:35,320 --> 00:39:37,799
Speaker 1: fits all when it comes to fees, no matter what

686
00:39:37,920 --> 00:39:42,360
Speaker 1: you're investing style is or how much beta you employ

687
00:39:42,480 --> 00:39:45,400
Speaker 1: um is ridiculous. You know, the guy charging to the

688
00:39:45,440 --> 00:39:47,760
Speaker 1: same it's the same fee structure for the guy running

689
00:39:47,800 --> 00:39:51,160
Speaker 1: NET thirty and running NET sixty. So I think there

690
00:39:51,200 --> 00:39:53,839
Speaker 1: should be a hurdle um with respect to how much

691
00:39:53,920 --> 00:39:56,279
Speaker 1: is alpha and how much is beta. You mentioned how

692
00:39:56,320 --> 00:40:01,160
Speaker 1: many hedge fund closings that were in eighteen. Typically when

693
00:40:01,160 --> 00:40:05,360
Speaker 1: a fund shuts down, does that money leave the space

694
00:40:05,760 --> 00:40:07,920
Speaker 1: or does it just rotate to a different hedge fund?

695
00:40:08,400 --> 00:40:12,680
Speaker 1: Um at least from an institutional perspective, Well, given the

696
00:40:12,719 --> 00:40:15,560
Speaker 1: trend line I shared with you earlier, which is we

697
00:40:15,640 --> 00:40:18,680
Speaker 1: have now sixty billion of net outflows to the industry,

698
00:40:18,719 --> 00:40:22,520
Speaker 1: that's that's net outflows, UM, I think money is actually

699
00:40:22,560 --> 00:40:25,080
Speaker 1: leaving the industry. That's where I think things are going.

700
00:40:25,160 --> 00:40:27,319
Speaker 1: And so it could go to another fund, But the

701
00:40:27,360 --> 00:40:30,440
Speaker 1: problem is there are so few good options where it

702
00:40:30,520 --> 00:40:32,879
Speaker 1: doesn't want to go to another fund that has had

703
00:40:32,880 --> 00:40:36,520
Speaker 1: the same me or crappy performance. A lot of the

704
00:40:36,560 --> 00:40:41,320
Speaker 1: better funds candidly are closed. That's the truth, um so.

705
00:40:41,760 --> 00:40:44,879
Speaker 1: And that's why you see when when guys splinter off

706
00:40:44,960 --> 00:40:48,160
Speaker 1: from the funds that are closed and LPs are salivating

707
00:40:48,200 --> 00:40:50,920
Speaker 1: for access to they they're the ones that scale overnight.

708
00:40:50,960 --> 00:40:52,960
Speaker 1: And there're only so many of those. So that's why

709
00:40:53,000 --> 00:40:56,600
Speaker 1: I think we're seeing the the aggregate amount of net

710
00:40:56,600 --> 00:40:59,680
Speaker 1: outflows and also the trend line. The thing on the

711
00:40:59,719 --> 00:41:02,880
Speaker 1: trend line is the only other year in hedge fund

712
00:41:03,000 --> 00:41:06,880
Speaker 1: history where we had four consecutive quarters of net outflows

713
00:41:07,000 --> 00:41:10,040
Speaker 1: was two thousand and eight to two thousand million. We

714
00:41:10,080 --> 00:41:14,880
Speaker 1: are probably Q one was the only other time in

715
00:41:14,880 --> 00:41:18,080
Speaker 1: hedge fund history we saw four consecutive quarters and that

716
00:41:18,200 --> 00:41:22,400
Speaker 1: was and and Q one. This year we had fifteen

717
00:41:22,440 --> 00:41:24,960
Speaker 1: billion of net outflows, where now at sixties something, so

718
00:41:25,040 --> 00:41:28,200
Speaker 1: I guarantee you we're now in our sixth quarter of

719
00:41:28,280 --> 00:41:31,799
Speaker 1: net outflows. That is first time ever in hedge fund history. Wow,

720
00:41:31,800 --> 00:41:34,520
Speaker 1: that's amazing. So the I don't want to call it

721
00:41:34,560 --> 00:41:36,680
Speaker 1: the flavor of the month, which it's a little too

722
00:41:36,880 --> 00:41:41,520
Speaker 1: uh glib, but it's clear that private equity is the

723
00:41:41,560 --> 00:41:44,720
Speaker 1: shiny new thing. Lots of money seems to be flowing

724
00:41:44,800 --> 00:41:48,640
Speaker 1: in that direction. Is that who is the beneficiary of

725
00:41:48,719 --> 00:41:52,879
Speaker 1: the outflows from hedge funds As if you're an institution

726
00:41:52,920 --> 00:41:55,279
Speaker 1: and you know you expected returns for equity is going

727
00:41:55,360 --> 00:41:58,399
Speaker 1: to be five or six percent and bonds yielding less

728
00:41:58,400 --> 00:42:03,359
Speaker 1: than two percent and alter enoughers are promising. Do these

729
00:42:03,400 --> 00:42:07,480
Speaker 1: outflows end up going to private equity? UM? They do.

730
00:42:07,800 --> 00:42:10,480
Speaker 1: But you know, interestingly, and and it's true that in

731
00:42:10,520 --> 00:42:12,960
Speaker 1: the last four or five years, while hedge funds have

732
00:42:13,080 --> 00:42:17,040
Speaker 1: suffered because their returns have come down UM, and for

733
00:42:17,080 --> 00:42:19,200
Speaker 1: most of them, fees have had to readjust or in

734
00:42:19,239 --> 00:42:24,080
Speaker 1: the process of readjusting, private equity was was had the

735
00:42:24,080 --> 00:42:27,560
Speaker 1: hot hand because rates were low and UH, and it

736
00:42:27,640 --> 00:42:32,239
Speaker 1: was you know, it was easier to to buy companies. UM.

737
00:42:32,280 --> 00:42:35,080
Speaker 1: I think that. But it's but you know, I think

738
00:42:35,120 --> 00:42:39,760
Speaker 1: what we're seeing now is the merge merging of UM

739
00:42:39,800 --> 00:42:42,440
Speaker 1: public in private. You see private equity firms trying to

740
00:42:42,480 --> 00:42:46,440
Speaker 1: get into the public markets. You see UM hedge funds

741
00:42:46,560 --> 00:42:52,080
Speaker 1: UH developing their private investing expertise, and so I think

742
00:42:52,120 --> 00:42:55,880
Speaker 1: each one is trying to capitalize upon the other's revenue stream.

743
00:42:55,920 --> 00:42:59,239
Speaker 1: That that's quite interesting. UM. One of the things I

744
00:43:00,080 --> 00:43:04,200
Speaker 1: read about you that I thought was pretty amusing. There

745
00:43:04,360 --> 00:43:07,520
Speaker 1: was a event, a gala that you helped put together

746
00:43:07,600 --> 00:43:10,560
Speaker 1: earlier this year, and one of the co producers of

747
00:43:10,560 --> 00:43:14,160
Speaker 1: the gala was Stevie Cohen of Now Point seventy two,

748
00:43:14,680 --> 00:43:18,440
Speaker 1: and he discussed what a challenge it's been for so

749
00:43:18,480 --> 00:43:21,680
Speaker 1: many hedge funds and basically said, no one's winning the

750
00:43:21,680 --> 00:43:26,520
Speaker 1: hedge fund game. There's this recruitment process where people go

751
00:43:26,719 --> 00:43:29,480
Speaker 1: from one fund to another to another, and the only

752
00:43:29,520 --> 00:43:32,319
Speaker 1: one who wins is you. He kind of dragged you

753
00:43:32,360 --> 00:43:35,040
Speaker 1: a little. No, it was just to be clear. The

754
00:43:35,120 --> 00:43:38,480
Speaker 1: gallo was in honor of me. I was so we

755
00:43:38,760 --> 00:43:40,920
Speaker 1: So it was a little bit of roasting, takeing bit

756
00:43:40,960 --> 00:43:42,920
Speaker 1: of roasting, I think, I hope. I think it was.

757
00:43:43,000 --> 00:43:45,920
Speaker 1: He was introducing me. I was the honoree. So I

758
00:43:46,440 --> 00:43:48,680
Speaker 1: think it was mentioned it was good nature and okay,

759
00:43:49,120 --> 00:43:51,560
Speaker 1: because when you read it, it's like, Wow, Stevie Cohen's

760
00:43:51,600 --> 00:43:53,719
Speaker 1: really dragging a lot, but it's nothing. I think it

761
00:43:53,800 --> 00:43:56,600
Speaker 1: was seen that way. I think his point was, um,

762
00:43:56,640 --> 00:43:59,840
Speaker 1: there is a war for talent because they're so little

763
00:44:00,040 --> 00:44:02,279
Speaker 1: of it right there. Only I said it myself, there

764
00:44:02,280 --> 00:44:04,000
Speaker 1: are only so many people I put in that first

765
00:44:04,000 --> 00:44:07,000
Speaker 1: bubble of best in class in the JASSA class. That

766
00:44:07,160 --> 00:44:09,520
Speaker 1: is true. Um, and you see it with the returns

767
00:44:09,560 --> 00:44:11,920
Speaker 1: of funds. Are only so many funds that are performing

768
00:44:11,920 --> 00:44:15,360
Speaker 1: and only so many people within those funds. P and

769
00:44:15,480 --> 00:44:17,800
Speaker 1: L doesn't lie. That's what I love about this industry.

770
00:44:17,840 --> 00:44:20,000
Speaker 1: It's real time. It's mark to market. You know where

771
00:44:20,040 --> 00:44:25,520
Speaker 1: you stand at all times. Um. Uh. But um, you

772
00:44:25,560 --> 00:44:28,399
Speaker 1: know the so and we so that is true. It's

773
00:44:28,600 --> 00:44:31,200
Speaker 1: there's an intense competition to attract the best. It is

774
00:44:31,239 --> 00:44:33,760
Speaker 1: also true we tend to be in the mix of it. Um.

775
00:44:33,800 --> 00:44:36,879
Speaker 1: But the the other thing that's true is as much

776
00:44:36,920 --> 00:44:40,600
Speaker 1: as there are only so many good people, they're also

777
00:44:40,719 --> 00:44:43,399
Speaker 1: so there are only so many places those people are

778
00:44:43,440 --> 00:44:46,560
Speaker 1: going to be attracted to. And Steve runs a great shop.

779
00:44:46,800 --> 00:44:49,920
Speaker 1: Point seventy two is one of them. Um. Other places

780
00:44:50,000 --> 00:44:54,720
Speaker 1: like Citadel, Millennium, Davidson, Kempner, Golden Tree, you know there

781
00:44:54,760 --> 00:44:58,360
Speaker 1: are there are there are places that have built something

782
00:44:58,640 --> 00:45:01,800
Speaker 1: unique and are going to be able to do something

783
00:45:01,880 --> 00:45:06,320
Speaker 1: special to attract talent and make them more successful because

784
00:45:06,360 --> 00:45:09,239
Speaker 1: of the very fact that they are on those at

785
00:45:09,280 --> 00:45:12,600
Speaker 1: those funds or on those platforms. And that's what creates

786
00:45:12,600 --> 00:45:16,839
Speaker 1: a symbiotic relationship between talent and the best places that

787
00:45:16,880 --> 00:45:19,520
Speaker 1: exist and myself. At the end of the day, we

788
00:45:20,520 --> 00:45:24,040
Speaker 1: I d W has been very deliberate about who we

789
00:45:24,160 --> 00:45:25,960
Speaker 1: choose to work with. I mean, I'm not going to

790
00:45:26,320 --> 00:45:28,759
Speaker 1: name names, but there are places plant no no no

791
00:45:28,880 --> 00:45:30,879
Speaker 1: in terms of the ones we choose not to work

792
00:45:31,960 --> 00:45:34,600
Speaker 1: but because we need it is as good as I'd

793
00:45:34,640 --> 00:45:37,240
Speaker 1: like to think we are at the end of the day.

794
00:45:37,520 --> 00:45:40,400
Speaker 1: The people we are dealing with on the talent side,

795
00:45:40,600 --> 00:45:44,680
Speaker 1: they are very sophisticated, they are very smart and and

796
00:45:44,680 --> 00:45:48,600
Speaker 1: and um, They're not going to go someplace that isn't

797
00:45:48,680 --> 00:45:52,160
Speaker 1: a market step up from where they are today with

798
00:45:52,239 --> 00:45:55,239
Speaker 1: a pathway that is unique, and nor would I feel

799
00:45:55,239 --> 00:45:59,120
Speaker 1: good about trying to convince them to do that. So UM,

800
00:45:59,440 --> 00:46:03,759
Speaker 1: I have tremendous conviction around the I have to have

801
00:46:03,840 --> 00:46:09,240
Speaker 1: tremendous conviction around the um um what around our clients

802
00:46:09,239 --> 00:46:11,440
Speaker 1: and what they've built and what they can provide for

803
00:46:11,520 --> 00:46:15,360
Speaker 1: talent and um and and so again. I think it

804
00:46:15,440 --> 00:46:17,320
Speaker 1: was a joke, but at the end of the day,

805
00:46:17,360 --> 00:46:19,799
Speaker 1: there are only so many places that also talent really

806
00:46:19,840 --> 00:46:22,080
Speaker 1: wants to go. Can you stick around a bit? I

807
00:46:22,120 --> 00:46:25,239
Speaker 1: have so many more questions. We have been speaking with

808
00:46:25,280 --> 00:46:29,480
Speaker 1: Alana Weinstein. She is the founder and CEO of the

809
00:46:29,560 --> 00:46:33,400
Speaker 1: I d W Group, a leading boutique for hedge funds,

810
00:46:33,440 --> 00:46:37,680
Speaker 1: family offices, and private equity, starching out top talent. If

811
00:46:37,719 --> 00:46:40,120
Speaker 1: you enjoy this conversation, we'll be sure and come back

812
00:46:40,160 --> 00:46:42,840
Speaker 1: for the podcast AFTRAS, where we keep the tape rolling

813
00:46:42,880 --> 00:46:47,680
Speaker 1: and continue discussing all things hedge fund and alternatives. You

814
00:46:47,719 --> 00:46:51,960
Speaker 1: can find that at iTunes, Google Podcasts. That's your Spotify,

815
00:46:52,040 --> 00:46:55,880
Speaker 1: wherever your finer podcasts are sold. We love your comments,

816
00:46:55,880 --> 00:46:59,960
Speaker 1: feedback and suggestions right to us at m IB podcast

817
00:47:00,040 --> 00:47:02,040
Speaker 1: us at Bloomberg dot net. Give us a review on

818
00:47:02,120 --> 00:47:06,759
Speaker 1: Apple iTunes. Check out my weekly column on Bloomberg dot com.

819
00:47:06,880 --> 00:47:10,279
Speaker 1: Follow me on Twitter at ripolts. I'm Barry Hults. You're

820
00:47:10,320 --> 00:47:16,840
Speaker 1: listening to Masters and Business on Bloomberg Radio. Welcome to

821
00:47:16,840 --> 00:47:20,640
Speaker 1: the podcast, Alanta. Thank you so much, um for doing this.

822
00:47:20,960 --> 00:47:24,760
Speaker 1: I've been looking forward to this. You really are somebody

823
00:47:24,760 --> 00:47:29,240
Speaker 1: who is maybe in one of the most unique spots

824
00:47:29,320 --> 00:47:33,879
Speaker 1: in the entire alternative space. You see everything, you know everybody,

825
00:47:34,440 --> 00:47:37,160
Speaker 1: your perspective as to what's going on in hedge funds,

826
00:47:37,160 --> 00:47:40,920
Speaker 1: private equity, and maybe not quite as much venture capital,

827
00:47:40,960 --> 00:47:43,359
Speaker 1: but I know that's certainly an area that is not

828
00:47:43,520 --> 00:47:49,719
Speaker 1: outside your UM observations. Is unique too strong a word.

829
00:47:49,760 --> 00:47:53,719
Speaker 1: I don't think anybody else has the vantage point that

830
00:47:53,800 --> 00:47:57,000
Speaker 1: you do about what's going on in the industry. I

831
00:47:57,000 --> 00:48:03,160
Speaker 1: I I mean, yes, it's it's completely accurate. Means it's

832
00:48:03,200 --> 00:48:08,959
Speaker 1: accurate precisely because what we do every day is meet

833
00:48:09,000 --> 00:48:12,000
Speaker 1: with the most talented people in the industry, not because

834
00:48:12,040 --> 00:48:15,080
Speaker 1: they're looking for jobs, but because they want our perspective.

835
00:48:15,120 --> 00:48:17,600
Speaker 1: And it's a virtuous loop. All If all you do

836
00:48:17,680 --> 00:48:20,240
Speaker 1: is meet with really smart people that are best in class,

837
00:48:20,719 --> 00:48:24,800
Speaker 1: you build a picture, a composite of what is driving

838
00:48:24,840 --> 00:48:28,600
Speaker 1: the industry and what the opportunity said is and where

839
00:48:28,600 --> 00:48:32,440
Speaker 1: it's going and UM and so we have so we

840
00:48:32,480 --> 00:48:36,120
Speaker 1: have insight into what is going on at every single fund,

841
00:48:36,600 --> 00:48:39,880
Speaker 1: who is making money, how lumpy the pool of talent is,

842
00:48:40,239 --> 00:48:46,239
Speaker 1: how how precarious each fund is, like what situation they're in,

843
00:48:46,840 --> 00:48:49,919
Speaker 1: UM like I mean, I often say, if LPs knew

844
00:48:49,960 --> 00:48:53,759
Speaker 1: what we know, UM, you know, they'd be pulling capital left,

845
00:48:53,800 --> 00:48:56,960
Speaker 1: right and center and reallocating to the places that we

846
00:48:57,000 --> 00:48:59,640
Speaker 1: tell them too. I have a very clear sense, as

847
00:48:59,719 --> 00:49:03,799
Speaker 1: does team on what's what? And And you know, I

848
00:49:03,800 --> 00:49:07,000
Speaker 1: don't think anyone else does because the level we're recruiting at,

849
00:49:07,320 --> 00:49:12,440
Speaker 1: both in terms of breath um and uh and and

850
00:49:12,480 --> 00:49:14,920
Speaker 1: just the sheer talent that we have coming in the

851
00:49:14,960 --> 00:49:19,399
Speaker 1: door across every assa class and every geography I think,

852
00:49:19,440 --> 00:49:21,640
Speaker 1: I think is second to none. And it does give

853
00:49:21,719 --> 00:49:25,520
Speaker 1: us insight into what to look for and what differentiates

854
00:49:25,600 --> 00:49:28,760
Speaker 1: the bs from the non bs, the good from the great.

855
00:49:28,880 --> 00:49:31,680
Speaker 1: There's there really specific things we're looking for. So let

856
00:49:31,680 --> 00:49:33,960
Speaker 1: me ask you a little bit about something related to that.

857
00:49:34,400 --> 00:49:38,120
Speaker 1: You know, when when I look at different funds, and

858
00:49:38,200 --> 00:49:40,120
Speaker 1: I've spoken to a lot of people from a lot

859
00:49:40,120 --> 00:49:44,120
Speaker 1: of different funds, very different personalities, who founded them, who

860
00:49:44,160 --> 00:49:48,560
Speaker 1: are running them, the corporate cultures seem to very dramatically

861
00:49:49,440 --> 00:49:53,400
Speaker 1: oak Tree Capital very different than Bridgewater, very different than

862
00:49:53,480 --> 00:49:57,520
Speaker 1: point seventy two. How important when you are looking to

863
00:49:57,760 --> 00:50:01,960
Speaker 1: match somebody for a very in your position is that

864
00:50:02,040 --> 00:50:09,239
Speaker 1: corporate culture? Um, it's definitely important, But I don't know

865
00:50:09,360 --> 00:50:16,040
Speaker 1: that there's um is much variability as you as you

866
00:50:16,760 --> 00:50:21,359
Speaker 1: might think. UM, I might over emphasizing Bridgewater because it's

867
00:50:21,360 --> 00:50:24,239
Speaker 1: such a unique I mean, yeah, that's sort of an

868
00:50:24,239 --> 00:50:27,880
Speaker 1: outlier into itself, right, So let's just full full disclosure.

869
00:50:27,920 --> 00:50:30,600
Speaker 1: I've had ray On three times. I love him, I'm

870
00:50:30,680 --> 00:50:34,439
Speaker 1: fascinated by him. He's a brilliant um guy. Some people

871
00:50:34,480 --> 00:50:37,640
Speaker 1: find him quirky. I just find him really fascinating. But

872
00:50:37,840 --> 00:50:40,960
Speaker 1: there there can be no doubt that Bridgewater is not

873
00:50:41,200 --> 00:50:44,160
Speaker 1: the typical So let's let's put that sort of to

874
00:50:44,239 --> 00:50:50,560
Speaker 1: the side. Um. I think the biggest differentiators are um

875
00:50:50,680 --> 00:50:53,239
Speaker 1: how much it's look, no one wants to work in

876
00:50:53,280 --> 00:50:56,080
Speaker 1: a jerky culture, so it neither do I want to

877
00:50:56,080 --> 00:50:59,800
Speaker 1: work with jerky founders. That's not I'm using intentionally, and

878
00:50:59,840 --> 00:51:06,480
Speaker 1: I sir word, I'm thinking really right, So that's consistent,

879
00:51:06,640 --> 00:51:09,440
Speaker 1: that's not you know, and and people. And at the

880
00:51:09,560 --> 00:51:11,440
Speaker 1: end of the day, what's really interesting to me is

881
00:51:11,480 --> 00:51:14,920
Speaker 1: there are certain founders who are dear clients and friends

882
00:51:14,920 --> 00:51:18,200
Speaker 1: of mine who you know, there's this perception that they're

883
00:51:18,280 --> 00:51:22,359
Speaker 1: like big bad wolf and really just tough and and

884
00:51:22,560 --> 00:51:26,120
Speaker 1: make crazy decisions and like, you know, I can be

885
00:51:26,160 --> 00:51:28,680
Speaker 1: there one day and blown out the next, And the

886
00:51:28,760 --> 00:51:33,600
Speaker 1: reality is these are some of the most measured down

887
00:51:33,640 --> 00:51:37,000
Speaker 1: to earth and I will say it good people I know,

888
00:51:37,560 --> 00:51:40,839
Speaker 1: but they also have great commercial instincts. And are not

889
00:51:40,960 --> 00:51:44,560
Speaker 1: afraid to make tough decisions. And if you're really talented,

890
00:51:44,920 --> 00:51:47,160
Speaker 1: you want to be an environment where you can shine

891
00:51:47,560 --> 00:51:50,160
Speaker 1: and aren't going to be dragged down by a bunch

892
00:51:50,200 --> 00:51:53,919
Speaker 1: of deadwood around you, where your your your compensation gets

893
00:51:53,960 --> 00:51:57,520
Speaker 1: netted every year because the founders just like too wimpy

894
00:51:57,560 --> 00:51:59,799
Speaker 1: to make tough decisions. You know, So let me push

895
00:51:59,840 --> 00:52:01,759
Speaker 1: back on you a little bit there. I won't even

896
00:52:01,800 --> 00:52:05,480
Speaker 1: say the funds because we'll see if you have a

897
00:52:05,520 --> 00:52:08,480
Speaker 1: sense of what I'm talking about. There are funds where

898
00:52:08,560 --> 00:52:11,600
Speaker 1: people get hired at and they know from the day

899
00:52:11,640 --> 00:52:15,279
Speaker 1: they're hired, I will eventually be fired for either good

900
00:52:15,320 --> 00:52:18,680
Speaker 1: cause or not, because that's the way this manager operates.

901
00:52:19,040 --> 00:52:24,000
Speaker 1: Is that a fair assessment about some funds? No, I don't.

902
00:52:24,120 --> 00:52:26,480
Speaker 1: I mean, I don't. I there may be funds that

903
00:52:26,560 --> 00:52:29,200
Speaker 1: fall in that category. That's not my client base. It's

904
00:52:29,239 --> 00:52:33,719
Speaker 1: really not. Um uh, there are I come back to

905
00:52:33,960 --> 00:52:36,759
Speaker 1: there are there are. I think the best founders are

906
00:52:36,840 --> 00:52:40,439
Speaker 1: also great business builders, and when they look at their

907
00:52:40,480 --> 00:52:44,920
Speaker 1: investment talent, they don't view it differently than a portfolio.

908
00:52:45,040 --> 00:52:47,760
Speaker 1: They double down on their winners and they cut their losers.

909
00:52:48,160 --> 00:52:51,040
Speaker 1: And and that's what I want if I am a

910
00:52:51,080 --> 00:52:55,400
Speaker 1: talented investment professional, because the biggest issue in this industry

911
00:52:55,560 --> 00:53:02,799
Speaker 1: from talents perspective is UM is not confidence compensation deflation.

912
00:53:03,040 --> 00:53:06,400
Speaker 1: It's it's if a fund does poorly and I did poorly.

913
00:53:06,800 --> 00:53:09,359
Speaker 1: It's a pay for performance industry. I get that I'm

914
00:53:09,400 --> 00:53:11,200
Speaker 1: not going to get paid, and I'm okay with that.

915
00:53:11,560 --> 00:53:14,600
Speaker 1: The biggest issue is when I said at a fund

916
00:53:14,680 --> 00:53:17,960
Speaker 1: and this is not exceptional what I'm telling you, this

917
00:53:18,040 --> 00:53:20,200
Speaker 1: is par for the course. I said, at a fund

918
00:53:20,680 --> 00:53:24,399
Speaker 1: that is eight billion of a UM or ten billion. Okay,

919
00:53:24,440 --> 00:53:28,680
Speaker 1: these are big, these are big funds UM. And I

920
00:53:28,719 --> 00:53:32,160
Speaker 1: am one of two or three people that consistently drive

921
00:53:32,280 --> 00:53:35,239
Speaker 1: P and L every single year. And remember, the last

922
00:53:35,280 --> 00:53:38,600
Speaker 1: three or four years have been really tough. Present year excluded,

923
00:53:38,640 --> 00:53:40,239
Speaker 1: but again a lot of beata in the returns for

924
00:53:40,280 --> 00:53:42,960
Speaker 1: this year, and also snap back from being down last year,

925
00:53:43,120 --> 00:53:45,400
Speaker 1: right right, just riding the market back up. So you

926
00:53:45,480 --> 00:53:48,680
Speaker 1: look for the last four years excluding this year, and

927
00:53:48,719 --> 00:53:51,120
Speaker 1: even this year, I am the I am one of

928
00:53:51,160 --> 00:53:53,920
Speaker 1: two or three primary P and L drivers at a

929
00:53:53,960 --> 00:53:57,160
Speaker 1: fund which has sizeable assets. And what are the other

930
00:53:57,200 --> 00:54:01,080
Speaker 1: people doing year after year? They're noting their weight, They're

931
00:54:01,080 --> 00:54:04,120
Speaker 1: not really contributing, and I'm getting netted because the founder

932
00:54:04,200 --> 00:54:06,680
Speaker 1: having to take from my pocket to pay them, right,

933
00:54:06,719 --> 00:54:08,760
Speaker 1: so those guys have to head out the door stroke.

934
00:54:09,080 --> 00:54:12,560
Speaker 1: So so this idea of like, I have job security,

935
00:54:12,640 --> 00:54:15,600
Speaker 1: but at the end of the day, um well, I said,

936
00:54:15,640 --> 00:54:17,640
Speaker 1: you know, of course you do. You're the star within

937
00:54:17,680 --> 00:54:20,239
Speaker 1: the fund. And the bigger question is why do the

938
00:54:20,280 --> 00:54:22,719
Speaker 1: other people have job security? They should be like the

939
00:54:22,800 --> 00:54:26,200
Speaker 1: founder has a fiduciary duty to Hale's LPs to be

940
00:54:26,719 --> 00:54:29,720
Speaker 1: retiring and retaining the best people. And part of retaining

941
00:54:29,760 --> 00:54:32,480
Speaker 1: them is getting rid of the ones that aren't performing

942
00:54:32,480 --> 00:54:35,080
Speaker 1: and making room for you know, better people. Am i

943
00:54:35,200 --> 00:54:38,080
Speaker 1: am I hearing you say that people think hedge funds

944
00:54:38,080 --> 00:54:40,960
Speaker 1: are cut throat, and you're suggesting some of them aren't

945
00:54:40,960 --> 00:54:44,759
Speaker 1: cut throat enough, then order or say it less emotionally

946
00:54:44,840 --> 00:54:50,840
Speaker 1: less um inflammatory Lee, there are a lot of funds

947
00:54:50,880 --> 00:54:55,640
Speaker 1: that simply aren't acting as a meritocracy. I think that

948
00:54:55,800 --> 00:54:59,560
Speaker 1: founders are often very loath to make tough decisions, and

949
00:54:59,560 --> 00:55:02,640
Speaker 1: we can all that not acting as a meritocracy, or

950
00:55:02,680 --> 00:55:05,279
Speaker 1: not being cut throat, or just candidly being whimps. I

951
00:55:05,320 --> 00:55:07,719
Speaker 1: think that there's an element of the optics of what

952
00:55:07,800 --> 00:55:10,280
Speaker 1: are LP's going to think if I fire these three people.

953
00:55:10,760 --> 00:55:13,960
Speaker 1: LPs would be very smart when they do their all

954
00:55:14,000 --> 00:55:16,959
Speaker 1: their operational due diligence. If I was an LP, here's

955
00:55:16,960 --> 00:55:19,120
Speaker 1: what I would be asking. I'd want to know that's

956
00:55:20,280 --> 00:55:22,880
Speaker 1: the way. Okay, what so let me ask you the

957
00:55:22,960 --> 00:55:26,239
Speaker 1: question what should LPs be doing and what aren't they

958
00:55:26,280 --> 00:55:30,200
Speaker 1: doing today? So UM, and everybody knows LPs limited partners,

959
00:55:30,239 --> 00:55:34,920
Speaker 1: not the fund managers or the actual general partnership. I

960
00:55:34,960 --> 00:55:38,399
Speaker 1: think that they should UM, they should find out from

961
00:55:38,400 --> 00:55:41,040
Speaker 1: the founder. And you know, it's hard because if it's

962
00:55:41,040 --> 00:55:45,319
Speaker 1: a single manager fund, the founder at the end of

963
00:55:45,320 --> 00:55:47,680
Speaker 1: the day is the ultimate decision maker, right if what

964
00:55:47,760 --> 00:55:50,440
Speaker 1: goes into the portfolio and how the portfolio is constructed.

965
00:55:50,719 --> 00:55:53,160
Speaker 1: But ask him, and I'm going to use along short equities,

966
00:55:53,200 --> 00:55:56,360
Speaker 1: one because it's the hedge fund universe, and two just

967
00:55:56,440 --> 00:56:01,040
Speaker 1: to be illustrative, it's an easy example to understand. Ask him, Okay,

968
00:56:01,120 --> 00:56:03,759
Speaker 1: where did your winners come from this year? In what industry?

969
00:56:04,040 --> 00:56:06,920
Speaker 1: Was it industrials? Was it t MT? Was it healthcare? Uh?

970
00:56:07,080 --> 00:56:09,520
Speaker 1: It was healthcare? What about last year? What drove pan

971
00:56:09,640 --> 00:56:12,719
Speaker 1: l oh Again? It was healthcare and industrials? What about

972
00:56:12,760 --> 00:56:15,080
Speaker 1: the year before, what about the year before? And we

973
00:56:15,160 --> 00:56:16,800
Speaker 1: get that at the end of the day, the founder

974
00:56:16,840 --> 00:56:20,560
Speaker 1: again is the ultimate decision maker, but again just behind

975
00:56:20,600 --> 00:56:23,640
Speaker 1: the scenes that's more gray than you. Those people have

976
00:56:23,800 --> 00:56:27,080
Speaker 1: tremendous influence if they're senior and they're good on the portfolio,

977
00:56:27,520 --> 00:56:31,320
Speaker 1: so UM the so LP should also be asking where

978
00:56:31,360 --> 00:56:33,560
Speaker 1: did where were your biggest losers? And you're gonna see

979
00:56:33,560 --> 00:56:36,640
Speaker 1: patterns across the biggest winners and across the biggest losers.

980
00:56:36,719 --> 00:56:39,200
Speaker 1: And then they should be asking the founder, what are

981
00:56:39,200 --> 00:56:41,000
Speaker 1: you doing about getting rid of the guys who are

982
00:56:41,040 --> 00:56:44,359
Speaker 1: covering the three sectors that actually have been a net

983
00:56:44,400 --> 00:56:47,680
Speaker 1: drain on pan L. What are you doing about um

984
00:56:47,840 --> 00:56:52,799
Speaker 1: developing the three sector heads that have generated the most

985
00:56:52,800 --> 00:56:55,239
Speaker 1: pan L. How do you manage paying those guys when

986
00:56:55,239 --> 00:56:56,719
Speaker 1: you have to when you have these other guys that

987
00:56:56,760 --> 00:56:59,400
Speaker 1: you have to pay like these are the tough questions

988
00:57:00,080 --> 00:57:04,879
Speaker 1: that founders really need to be held accountable for. And

989
00:57:04,880 --> 00:57:07,520
Speaker 1: and also LP should be looking at who left Were

990
00:57:07,520 --> 00:57:10,120
Speaker 1: those people that were p m L generators to the

991
00:57:10,120 --> 00:57:13,240
Speaker 1: fund or were those people that were that were pushed

992
00:57:13,280 --> 00:57:15,279
Speaker 1: out right because they didn't do well? And if what

993
00:57:15,320 --> 00:57:17,360
Speaker 1: they're seeing as a trend line of the best people

994
00:57:17,440 --> 00:57:19,080
Speaker 1: leaving and they have to figure out a way to

995
00:57:19,160 --> 00:57:21,520
Speaker 1: get it that. We know that because we're interviewing these

996
00:57:21,520 --> 00:57:24,200
Speaker 1: people and we see the compositive the entire p l

997
00:57:24,240 --> 00:57:26,400
Speaker 1: of the fund and who did what. If the best

998
00:57:26,400 --> 00:57:29,080
Speaker 1: people are leaving, you should be pulling capital. And if

999
00:57:29,320 --> 00:57:33,360
Speaker 1: and if the people who um did not make money

1000
00:57:33,360 --> 00:57:36,040
Speaker 1: are the ones who were leaving and being managed out,

1001
00:57:36,080 --> 00:57:38,600
Speaker 1: then you should deploy because that's a founder who understands

1002
00:57:38,880 --> 00:57:42,480
Speaker 1: how to manage his team and is managing them again

1003
00:57:42,680 --> 00:57:46,040
Speaker 1: like a portfolio, unemotionally and making decisions in their best

1004
00:57:46,040 --> 00:57:49,040
Speaker 1: in you're really answering a question I was about to

1005
00:57:49,080 --> 00:57:52,080
Speaker 1: ask you, which is what should founders do to retain

1006
00:57:52,080 --> 00:57:55,760
Speaker 1: their best people? And what you're effectively saying is pay

1007
00:57:55,840 --> 00:58:00,600
Speaker 1: and bonus the high high performers and cut the people

1008
00:58:00,600 --> 00:58:02,840
Speaker 1: in the night. And I'll go one further. I think

1009
00:58:02,880 --> 00:58:07,040
Speaker 1: that founders need to be willing to go to zero

1010
00:58:07,280 --> 00:58:12,800
Speaker 1: for themselves in times where they don't have much of

1011
00:58:12,840 --> 00:58:15,000
Speaker 1: a performance fee. And that has been true for the

1012
00:58:15,080 --> 00:58:17,800
Speaker 1: last four years. Even this year, a lot of funds

1013
00:58:17,840 --> 00:58:19,560
Speaker 1: may be doing better, but they have a high water

1014
00:58:19,640 --> 00:58:21,560
Speaker 1: mark from the previous year or a group of year,

1015
00:58:21,600 --> 00:58:24,800
Speaker 1: meaning that what you've took as a profit um as

1016
00:58:24,840 --> 00:58:30,120
Speaker 1: a profit distribution. Once we fall off of those market highs,

1017
00:58:30,360 --> 00:58:33,200
Speaker 1: you don't take another profit distribution until you get back

1018
00:58:33,240 --> 00:58:35,360
Speaker 1: over that you lost money last year. You first have

1019
00:58:35,440 --> 00:58:38,640
Speaker 1: to make that back up before you start to get paid. Right. So,

1020
00:58:38,800 --> 00:58:41,000
Speaker 1: if I'm a guy who for the last three or

1021
00:58:41,040 --> 00:58:44,840
Speaker 1: four years is generated tremendous pan L for the firm,

1022
00:58:44,880 --> 00:58:46,480
Speaker 1: and there are guys who come in to meet with

1023
00:58:46,560 --> 00:58:49,880
Speaker 1: us who literally are of the pm L of the

1024
00:58:49,880 --> 00:58:53,040
Speaker 1: fund for a hundred of the p L, other people

1025
00:58:53,040 --> 00:58:56,840
Speaker 1: are a dragon exactly, if the founder would be wise

1026
00:58:56,880 --> 00:58:59,760
Speaker 1: to go into his pocket, go into his management fee

1027
00:59:00,200 --> 00:59:03,280
Speaker 1: and and pay that person right so that they don't

1028
00:59:03,360 --> 00:59:05,920
Speaker 1: that's what they need to do, and and and also

1029
00:59:05,960 --> 00:59:08,360
Speaker 1: be clear about how they're coming up with the number.

1030
00:59:08,360 --> 00:59:10,560
Speaker 1: For many of these guys, if they're not sitting at

1031
00:59:10,560 --> 00:59:14,000
Speaker 1: a multi manager which is formulaic, or they don't have

1032
00:59:14,480 --> 00:59:16,520
Speaker 1: even if they have points in the fund a lot

1033
00:59:16,560 --> 00:59:19,360
Speaker 1: of the times, how UM there's a jump bowl which

1034
00:59:19,400 --> 00:59:23,040
Speaker 1: is discretionary if they don't. If the if the absolute

1035
00:59:23,160 --> 00:59:25,840
Speaker 1: number is disappointing because times are not good and there

1036
00:59:25,840 --> 00:59:28,480
Speaker 1: isn't much of a performance fee, and also assets have dwindled,

1037
00:59:28,520 --> 00:59:32,040
Speaker 1: so the management fee is smaller. Founders need to give

1038
00:59:32,080 --> 00:59:35,320
Speaker 1: people insight into how they're coming up with the numbers,

1039
00:59:35,360 --> 00:59:38,920
Speaker 1: so it's not this black box. Um they they again

1040
00:59:38,960 --> 00:59:42,120
Speaker 1: it comes back to running a business, not just managing

1041
00:59:42,120 --> 00:59:43,840
Speaker 1: a p n L. And that's a mind shift for

1042
00:59:43,880 --> 00:59:46,720
Speaker 1: a lot of founders because they grew up. What they

1043
00:59:46,840 --> 00:59:50,720
Speaker 1: know best is investing, right, not managing people. They need

1044
00:59:50,760 --> 00:59:54,480
Speaker 1: to manage their fun like a business, not because not

1045
00:59:54,600 --> 00:59:57,040
Speaker 1: like a cliptocracy, which is how a lot of these

1046
00:59:57,040 --> 00:59:59,840
Speaker 1: guys view it, that that work the cliptocracy. So let

1047
00:59:59,840 --> 01:00:01,880
Speaker 1: me lip the question from what founders need to do

1048
01:00:01,880 --> 01:00:05,440
Speaker 1: to retain their best people to some of those best

1049
01:00:05,480 --> 01:00:09,040
Speaker 1: people that talent. What are they looking for? What makes

1050
01:00:09,080 --> 01:00:12,720
Speaker 1: them decide not only that I'm ready to move, but

1051
01:00:12,800 --> 01:00:15,520
Speaker 1: I'm going to go there or here? What What are

1052
01:00:15,560 --> 01:00:18,280
Speaker 1: they looking for? So the most important So the things

1053
01:00:18,280 --> 01:00:21,160
Speaker 1: they're looking for having change, they're just more difficult today

1054
01:00:21,160 --> 01:00:24,000
Speaker 1: to come by. They're looking for stability right when you

1055
01:00:24,000 --> 01:00:27,720
Speaker 1: see funds like big funds back and we started with

1056
01:00:27,800 --> 01:00:30,200
Speaker 1: Eaton Park and Perry going out of business and then

1057
01:00:30,240 --> 01:00:32,320
Speaker 1: all the others I mentioned last year, and they'll be

1058
01:00:32,360 --> 01:00:35,600
Speaker 1: more to come. Um that means that there's no more

1059
01:00:35,680 --> 01:00:38,680
Speaker 1: terra firma under their feet. And by the way, you

1060
01:00:38,720 --> 01:00:41,680
Speaker 1: even look at funds that are still that are big,

1061
01:00:41,760 --> 01:00:45,440
Speaker 1: that that are well known names, they're still existing today.

1062
01:00:45,680 --> 01:00:47,960
Speaker 1: It may be interesting for your listeners to look at

1063
01:00:48,000 --> 01:00:51,200
Speaker 1: the a U M drops of these funds. Green Light, Okay,

1064
01:00:51,200 --> 01:00:52,840
Speaker 1: and this is by the way, I'm going back to

1065
01:00:53,280 --> 01:00:56,439
Speaker 1: not circle two thousand and three or two thousand and set.

1066
01:00:56,480 --> 01:00:58,960
Speaker 1: Let let's say right before the crisis two and seven

1067
01:00:59,080 --> 01:01:01,520
Speaker 1: or two. I'm talking about in the last few years.

1068
01:01:01,520 --> 01:01:03,720
Speaker 1: So this is how precipitous the a U M drops were.

1069
01:01:04,080 --> 01:01:06,880
Speaker 1: Green Light was twelve billion now it's sub three billion.

1070
01:01:06,960 --> 01:01:10,120
Speaker 1: Corvis was seven billion, now it's two billion. Discovery was

1071
01:01:10,200 --> 01:01:13,640
Speaker 1: fifteen billion, now it's three billion. For Tree was thirteen billion,

1072
01:01:13,680 --> 01:01:17,080
Speaker 1: now it's five billion. Scopia a year ago, one year

1073
01:01:17,080 --> 01:01:20,320
Speaker 1: ago was almost seven billion. You know what it is

1074
01:01:20,400 --> 01:01:24,560
Speaker 1: today under two billion. So these are again like only

1075
01:01:24,640 --> 01:01:28,200
Speaker 1: so many funds even get into the billion dollar territory, right,

1076
01:01:28,240 --> 01:01:30,680
Speaker 1: So these are the these are the sort of the

1077
01:01:30,760 --> 01:01:33,320
Speaker 1: bigger names, the bigger guys, and they are a shell

1078
01:01:33,480 --> 01:01:37,640
Speaker 1: of their former selves. So stability is like very hard

1079
01:01:37,680 --> 01:01:39,760
Speaker 1: to come by these days. And you may think, oh,

1080
01:01:39,800 --> 01:01:43,120
Speaker 1: that's a well known fund that's stable. NA. Not not

1081
01:01:43,240 --> 01:01:47,200
Speaker 1: the case. Um. The second thing that's really important is netting,

1082
01:01:47,320 --> 01:01:49,680
Speaker 1: which we talked about not being in a construct where

1083
01:01:49,680 --> 01:01:52,680
Speaker 1: you're not going to continuously get netted, right, I mean

1084
01:01:52,760 --> 01:01:56,360
Speaker 1: went by netted. You mean your payment is a little

1085
01:01:56,360 --> 01:01:59,800
Speaker 1: bit of a kibbutz where you're not necessarily well winning

1086
01:02:00,040 --> 01:02:03,480
Speaker 1: all of your uh, your pan l. It gets spread around.

1087
01:02:04,400 --> 01:02:06,439
Speaker 1: As a guy just said to me the other day,

1088
01:02:06,440 --> 01:02:08,160
Speaker 1: and I love this phrase, and I told him I'm

1089
01:02:08,160 --> 01:02:11,000
Speaker 1: going to steal it. He said, I feel like labor arbitrage.

1090
01:02:11,680 --> 01:02:14,640
Speaker 1: That's that's what's got your high performer. They're a low performer.

1091
01:02:14,680 --> 01:02:17,880
Speaker 1: And everybody I'm generating all this pan L, no one

1092
01:02:17,920 --> 01:02:21,160
Speaker 1: else around here is pulling their weight. And every year

1093
01:02:21,400 --> 01:02:23,400
Speaker 1: I'm paid a fraction of what I should be paid.

1094
01:02:24,080 --> 01:02:28,720
Speaker 1: So that's a guy right to be pent. And does

1095
01:02:28,800 --> 01:02:32,560
Speaker 1: management not understand the frustration of a high performer, like

1096
01:02:32,640 --> 01:02:38,600
Speaker 1: we are not talking about um a low octane sort

1097
01:02:38,640 --> 01:02:42,320
Speaker 1: of people work on an hourly basis. This is these

1098
01:02:42,320 --> 01:02:45,840
Speaker 1: are people who are willing to live and die on

1099
01:02:46,120 --> 01:02:52,720
Speaker 1: eating what they kill. And it's it's a really um

1100
01:02:52,760 --> 01:02:57,120
Speaker 1: aggressive industry. It sounds like some firms are sort of

1101
01:02:57,160 --> 01:03:00,240
Speaker 1: trying to soften it and make it more of a group.

1102
01:03:01,320 --> 01:03:03,400
Speaker 1: I think there's a look, there's a lot of inertia

1103
01:03:03,440 --> 01:03:05,960
Speaker 1: in this industry. We saw this with LPs, to this

1104
01:03:06,120 --> 01:03:09,080
Speaker 1: pace of net al flows is only just picking up now.

1105
01:03:09,120 --> 01:03:11,720
Speaker 1: For a long time LPs were sort of just hoping

1106
01:03:11,760 --> 01:03:14,800
Speaker 1: things would get better. Well, the consultants always say to them, hey,

1107
01:03:14,840 --> 01:03:17,280
Speaker 1: this is an off year. Just given another two or

1108
01:03:17,320 --> 01:03:19,400
Speaker 1: three years and we'll be fine. And if to ten

1109
01:03:19,480 --> 01:03:21,760
Speaker 1: years of hearing that people finally figured out and it

1110
01:03:21,880 --> 01:03:24,800
Speaker 1: ain't gonna be fright right, so um So I think

1111
01:03:24,840 --> 01:03:28,600
Speaker 1: there's an element of hoping that things change, hoping that

1112
01:03:28,640 --> 01:03:32,680
Speaker 1: the performance gets better. Um And and and you know,

1113
01:03:32,720 --> 01:03:35,320
Speaker 1: you have to understand, these senior people that we're speaking

1114
01:03:35,360 --> 01:03:38,160
Speaker 1: to have been where they've been for in many cases

1115
01:03:38,200 --> 01:03:40,720
Speaker 1: over a decade. They have a real relationship with the founder,

1116
01:03:40,760 --> 01:03:43,800
Speaker 1: they helped build the fund um they are partners where

1117
01:03:43,840 --> 01:03:47,800
Speaker 1: they're sitting, so it's not as transactional, you know, as

1118
01:03:47,840 --> 01:03:51,240
Speaker 1: one might think. And I and they feel loyal, they

1119
01:03:51,280 --> 01:03:54,440
Speaker 1: feel embedded. But at a certain point, the chickens do

1120
01:03:54,560 --> 01:03:56,640
Speaker 1: come home to roost. And I think we're kind of

1121
01:03:56,680 --> 01:03:59,040
Speaker 1: at that tipping point. We really are at a tipping

1122
01:03:59,080 --> 01:04:02,680
Speaker 1: point in the industry, both with respect to frustration on

1123
01:04:02,720 --> 01:04:07,720
Speaker 1: the part of talent, frustration on the part of LPs, UM,

1124
01:04:08,000 --> 01:04:11,520
Speaker 1: UH and UM. You know, I think that it's it's

1125
01:04:11,640 --> 01:04:14,760
Speaker 1: the shakeout. Is it's happening. We see we see money

1126
01:04:14,800 --> 01:04:18,080
Speaker 1: leaving the industry and the guys who figured it out

1127
01:04:18,360 --> 01:04:21,160
Speaker 1: are the absolute clear winners, and they're going to gobble

1128
01:04:21,240 --> 01:04:25,680
Speaker 1: up the best talent and UM that's they've represent stability,

1129
01:04:26,040 --> 01:04:28,280
Speaker 1: they don't net their talent. And the other few things,

1130
01:04:28,320 --> 01:04:31,320
Speaker 1: just to answer your question, are that these guys do

1131
01:04:31,400 --> 01:04:34,800
Speaker 1: best the winners UM talent. Also what you asked me,

1132
01:04:34,840 --> 01:04:36,959
Speaker 1: what talents looking for? They want to be made better,

1133
01:04:37,240 --> 01:04:40,440
Speaker 1: They want to improve. So, you know, in an environment

1134
01:04:40,440 --> 01:04:42,960
Speaker 1: where returns are so hard to come by, how can

1135
01:04:43,040 --> 01:04:45,240
Speaker 1: I be better at shorting? How can I be better

1136
01:04:45,320 --> 01:04:49,880
Speaker 1: at managing UM volatility? UM? How do I how do

1137
01:04:49,920 --> 01:04:52,600
Speaker 1: I improve? And the and the best places, which are

1138
01:04:52,600 --> 01:04:59,280
Speaker 1: typically UM that have really sophisticated UH technology and data

1139
01:05:00,080 --> 01:05:03,960
Speaker 1: UM and risk management are the best multi managers. They

1140
01:05:03,960 --> 01:05:07,640
Speaker 1: give these guys an unbelievable feedback loop. So they say

1141
01:05:07,640 --> 01:05:10,840
Speaker 1: to them, listen, let's look at your P and L um,

1142
01:05:10,960 --> 01:05:16,080
Speaker 1: you are a lot of it came from um you know,

1143
01:05:16,200 --> 01:05:18,479
Speaker 1: it's actually not like a lot of it came from

1144
01:05:18,720 --> 01:05:22,720
Speaker 1: beta or came from factor exposure. That's not repeatable. So

1145
01:05:22,960 --> 01:05:26,560
Speaker 1: giving them transparency into how they make money sets them

1146
01:05:26,600 --> 01:05:29,440
Speaker 1: up for better success in the future. And and there

1147
01:05:29,440 --> 01:05:31,960
Speaker 1: are very few places that have the same tools and

1148
01:05:32,040 --> 01:05:35,120
Speaker 1: resources um as some of the guys that I mentioned,

1149
01:05:35,440 --> 01:05:39,200
Speaker 1: all the big scalable giant shops that that are not

1150
01:05:39,240 --> 01:05:41,560
Speaker 1: afraid to spend them, but ones. But that's the last

1151
01:05:41,560 --> 01:05:43,840
Speaker 1: part of your sentence is key. There are funds. It's

1152
01:05:43,880 --> 01:05:47,200
Speaker 1: amazing how few funds use scale to their competitive advantage.

1153
01:05:47,280 --> 01:05:49,160
Speaker 1: There's a fun time thinking of which is north of

1154
01:05:49,240 --> 01:05:54,280
Speaker 1: twenty billion. They have nothing internally. They basically they have

1155
01:05:54,360 --> 01:05:57,240
Speaker 1: two people that manage half the a U M. Those

1156
01:05:57,280 --> 01:06:00,560
Speaker 1: two people literally have like two people in beneath them,

1157
01:06:01,000 --> 01:06:04,720
Speaker 1: and there's no infrastructure. There's no there's like five data

1158
01:06:04,760 --> 01:06:08,480
Speaker 1: scientists at the entire firm. There's no real They haven't

1159
01:06:08,520 --> 01:06:12,200
Speaker 1: built the fund in a way which bestows competitive advantage

1160
01:06:12,200 --> 01:06:15,120
Speaker 1: on its people. And the problem with that construct is

1161
01:06:15,480 --> 01:06:20,160
Speaker 1: if the two golden geese leave the fund, there's no interest,

1162
01:06:20,240 --> 01:06:23,800
Speaker 1: there's nothing there after that, So you you hinted at

1163
01:06:23,840 --> 01:06:27,640
Speaker 1: something earlier. I want to get explicit about regarding partnerships.

1164
01:06:28,080 --> 01:06:32,479
Speaker 1: How should these firms be thinking about succession planning? Not

1165
01:06:32,640 --> 01:06:34,760
Speaker 1: just if the founder is hit by a bus, but

1166
01:06:35,200 --> 01:06:37,480
Speaker 1: what happens when they retire, what happens when they want

1167
01:06:37,480 --> 01:06:40,840
Speaker 1: to spend more time away from the office. What should

1168
01:06:40,920 --> 01:06:43,960
Speaker 1: firms be doing about that? Well, you know, the industry

1169
01:06:44,040 --> 01:06:48,080
Speaker 1: is still relatively young, so we haven't had that much

1170
01:06:48,160 --> 01:06:51,520
Speaker 1: succession that's gone on. Right, So the same way I'm

1171
01:06:51,560 --> 01:06:54,000
Speaker 1: still running I DW and I'd like to think I'm

1172
01:06:54,040 --> 01:06:57,920
Speaker 1: still young, right, thank you. Many of these funds that

1173
01:06:58,000 --> 01:07:01,160
Speaker 1: started about the same time, there's no succession going on.

1174
01:07:01,200 --> 01:07:04,320
Speaker 1: These guys are in their forties, right but for but

1175
01:07:04,440 --> 01:07:07,360
Speaker 1: for the But there are some um that have done

1176
01:07:07,360 --> 01:07:09,560
Speaker 1: it successfully, and I think we can look to them

1177
01:07:09,920 --> 01:07:13,440
Speaker 1: for how to do this one. It can't just be

1178
01:07:13,480 --> 01:07:17,000
Speaker 1: a found one founder in his brain that LPs are

1179
01:07:17,000 --> 01:07:20,280
Speaker 1: investing in right and and and a like a bunch

1180
01:07:20,320 --> 01:07:25,440
Speaker 1: of UH investment analysts around him. They have to feel

1181
01:07:25,520 --> 01:07:31,680
Speaker 1: like there is um UH an infrastructure there which will

1182
01:07:31,720 --> 01:07:33,920
Speaker 1: continue to do as well with or without him. And

1183
01:07:33,960 --> 01:07:36,200
Speaker 1: I think there are two models that lend themselves to it.

1184
01:07:36,600 --> 01:07:39,720
Speaker 1: One is the multi manager construct, where there are multiple

1185
01:07:39,800 --> 01:07:44,040
Speaker 1: pms right that have autonomy and are managing capital, and

1186
01:07:44,120 --> 01:07:49,120
Speaker 1: there's also sophisticated risk management in house to help them

1187
01:07:49,360 --> 01:07:52,120
Speaker 1: be as successful as possible. That's not the founder every

1188
01:07:52,200 --> 01:07:55,600
Speaker 1: day walking the floor making sure these guys are thinking

1189
01:07:55,640 --> 01:07:58,640
Speaker 1: about the world in the right way and and sifting

1190
01:07:58,680 --> 01:08:01,600
Speaker 1: through their ideas and say this is interesting, this isn't

1191
01:08:01,720 --> 01:08:04,520
Speaker 1: let's size this, let's short that this is. This is

1192
01:08:04,520 --> 01:08:06,960
Speaker 1: the car that sort of you know, runs on its

1193
01:08:06,960 --> 01:08:10,480
Speaker 1: own UM. And then the other model would be the

1194
01:08:10,560 --> 01:08:14,960
Speaker 1: multi strategy model UM. And we saw this very recently

1195
01:08:15,080 --> 01:08:18,240
Speaker 1: with UM Tom Kempner stepping down name on the door,

1196
01:08:18,360 --> 01:08:21,679
Speaker 1: Davidson Kempner one of the original founders and turned over

1197
01:08:21,720 --> 01:08:24,200
Speaker 1: the reins to Tony use Off and they did not

1198
01:08:24,320 --> 01:08:26,160
Speaker 1: miss a beat. And the reason they were able to

1199
01:08:26,200 --> 01:08:30,160
Speaker 1: do this is it's a real partnership with fourteen engage

1200
01:08:30,240 --> 01:08:34,640
Speaker 1: partners UM. Decision making is done in unison. This is

1201
01:08:34,720 --> 01:08:37,559
Speaker 1: it's not like partnership a lot of hedge funds. Partnership

1202
01:08:37,640 --> 01:08:39,280
Speaker 1: is a nice thing to put on the business card,

1203
01:08:39,320 --> 01:08:41,240
Speaker 1: but at the end of the day, it's still this

1204
01:08:41,280 --> 01:08:45,320
Speaker 1: sort of partner there. It's exactly so this is. This

1205
01:08:45,439 --> 01:08:47,920
Speaker 1: operates kind of like I think it was modeled in

1206
01:08:47,960 --> 01:08:50,960
Speaker 1: some ways after the old Goldman Sachs partnership. It really

1207
01:08:51,600 --> 01:08:55,519
Speaker 1: UM is a group of engage people who make the

1208
01:08:55,560 --> 01:08:59,240
Speaker 1: important investing and operating decisions for the firm. And when

1209
01:08:59,240 --> 01:09:02,360
Speaker 1: they when Tony moved up, they very wisely took two

1210
01:09:02,360 --> 01:09:05,120
Speaker 1: of their people of that group of fourteen and made

1211
01:09:05,120 --> 01:09:08,840
Speaker 1: them um CO deputy managing partners, signaling to l P

1212
01:09:09,040 --> 01:09:11,519
Speaker 1: S there's already a plan in place when and if

1213
01:09:11,560 --> 01:09:15,200
Speaker 1: Tony retires, and the place operates again in a way

1214
01:09:15,400 --> 01:09:19,479
Speaker 1: where the strength of the firm and its secret sauce

1215
01:09:19,640 --> 01:09:21,559
Speaker 1: is not just one guy at the top. So I

1216
01:09:21,600 --> 01:09:23,080
Speaker 1: have to ask you a question, because you and I

1217
01:09:23,120 --> 01:09:27,280
Speaker 1: are both talking about this guy and that guy. Guys, guys, guys,

1218
01:09:28,200 --> 01:09:31,960
Speaker 1: what is to be said? I'm going to man splain

1219
01:09:32,280 --> 01:09:34,280
Speaker 1: the lack of women and hedge funds to you would

1220
01:09:34,280 --> 01:09:37,680
Speaker 1: be pretty hilarious. Why are there such a lack of

1221
01:09:37,680 --> 01:09:41,959
Speaker 1: women in the industry? UM? Generally speaking, it's true in finance,

1222
01:09:42,040 --> 01:09:46,519
Speaker 1: but it is really acute in hedge funds. Why is

1223
01:09:46,600 --> 01:09:50,680
Speaker 1: that and is that ever gonna change in our lifetimes?

1224
01:09:51,200 --> 01:09:56,400
Speaker 1: I have thought about this question a lot. UM So

1225
01:09:56,600 --> 01:09:59,600
Speaker 1: there are a couple of things. One is, there is

1226
01:09:59,640 --> 01:10:04,600
Speaker 1: a twenty two at work where look, people are attracted

1227
01:10:04,640 --> 01:10:08,320
Speaker 1: to industries and into roles where they see people like

1228
01:10:08,400 --> 01:10:11,160
Speaker 1: themselves having success. Has to be a role model somewhere.

1229
01:10:11,200 --> 01:10:14,680
Speaker 1: There isn't right now. So are there any high profile

1230
01:10:14,920 --> 01:10:21,639
Speaker 1: women hedge fund managers? Um, there is really hardly Annie.

1231
01:10:21,760 --> 01:10:25,840
Speaker 1: There's Leader Braga who spun out of Blue Crest, and

1232
01:10:25,960 --> 01:10:31,360
Speaker 1: there is um uh Dawn Fitzpatrick, who's the c I

1233
01:10:31,479 --> 01:10:35,559
Speaker 1: O of Soros. But those are really the only two

1234
01:10:36,000 --> 01:10:39,040
Speaker 1: that come to mind that runs scale businesses, and Dawn

1235
01:10:39,040 --> 01:10:43,400
Speaker 1: didn't found Soros, right, that's so that's a different I think.

1236
01:10:43,439 --> 01:10:48,519
Speaker 1: So yeah, like General Custer's white horse? Right? Um? What

1237
01:10:48,720 --> 01:10:53,439
Speaker 1: what color was that? Uh so? Um? Uh so, so

1238
01:10:53,640 --> 01:10:56,839
Speaker 1: you know there are women quote unquote air quotes running funds,

1239
01:10:56,840 --> 01:10:59,479
Speaker 1: but there are two bit players like they don't you

1240
01:10:59,520 --> 01:11:03,240
Speaker 1: know they It just it's not influential funds and so

1241
01:11:03,400 --> 01:11:06,160
Speaker 1: and and again think about the fact that back in sixteen,

1242
01:11:06,360 --> 01:11:08,840
Speaker 1: ten of the a u M, which was around two

1243
01:11:08,920 --> 01:11:13,200
Speaker 1: point nine trillion back then, was controlled, So ten percent

1244
01:11:13,240 --> 01:11:16,679
Speaker 1: of hedge funds controlled the u M. So that's even

1245
01:11:16,680 --> 01:11:19,479
Speaker 1: smaller now it is very much a fat headlong tail.

1246
01:11:19,560 --> 01:11:23,000
Speaker 1: It is not the normal distribution, right, So back to women,

1247
01:11:23,120 --> 01:11:26,479
Speaker 1: so the one they don't really have role models to. Again,

1248
01:11:26,560 --> 01:11:29,200
Speaker 1: the industry is still fairly young. When you compare it

1249
01:11:29,240 --> 01:11:33,320
Speaker 1: to finance, like investment banking or UM. You compare it

1250
01:11:33,360 --> 01:11:35,760
Speaker 1: to consulting, or you compare it to medicine. Those are

1251
01:11:35,800 --> 01:11:38,599
Speaker 1: all industries that have been around much longer, so they've

1252
01:11:38,600 --> 01:11:40,719
Speaker 1: had more of a chance to catch up to for

1253
01:11:40,960 --> 01:11:44,080
Speaker 1: you know, to make it for for women to UM

1254
01:11:44,240 --> 01:11:47,320
Speaker 1: have a bigger percentage. But when when we look at

1255
01:11:47,320 --> 01:11:51,879
Speaker 1: things like law and medicine and consulting, women are forty

1256
01:11:52,080 --> 01:11:54,840
Speaker 1: plus percent. When we look at finance, there's been a

1257
01:11:54,840 --> 01:11:58,160
Speaker 1: lot of gains in the past decade, but it's still

1258
01:11:59,040 --> 01:12:03,599
Speaker 1: really tilted towards the male side. UM. I can name

1259
01:12:03,720 --> 01:12:08,960
Speaker 1: two dozen chief economists, uh market strategists. I mean, there's

1260
01:12:09,040 --> 01:12:13,240
Speaker 1: tons of women in very visible places today that didn't

1261
01:12:13,280 --> 01:12:17,639
Speaker 1: exist twenty years ago. But find it's still very It's

1262
01:12:17,680 --> 01:12:20,040
Speaker 1: still so much better than the hedge fund industry. It

1263
01:12:20,120 --> 01:12:23,519
Speaker 1: really is. So that the hedge fund industry is worse

1264
01:12:23,560 --> 01:12:27,599
Speaker 1: than finance. So finance is bad, right, So fine, So

1265
01:12:28,000 --> 01:12:30,479
Speaker 1: that's my man explaining about the lack of women. If

1266
01:12:30,560 --> 01:12:33,439
Speaker 1: I always find my always laugh at myself when I'm like,

1267
01:12:33,640 --> 01:12:35,720
Speaker 1: are you man explaining this too harsh? And know it's

1268
01:12:35,760 --> 01:12:38,320
Speaker 1: more about this stuff than you ever will, but it's

1269
01:12:38,360 --> 01:12:40,680
Speaker 1: true there are so few women. So we need to

1270
01:12:40,720 --> 01:12:43,439
Speaker 1: do a better job of pulling women in earlier and

1271
01:12:43,520 --> 01:12:47,920
Speaker 1: explaining to them that this is an industry that is

1272
01:12:47,920 --> 01:12:51,120
Speaker 1: not just hospitable to women, we are dying for women.

1273
01:12:51,200 --> 01:12:54,479
Speaker 1: It is rare that I do a search, um where

1274
01:12:54,520 --> 01:12:58,080
Speaker 1: the client at some point does not say to me,

1275
01:12:58,560 --> 01:13:01,240
Speaker 1: you know, we love for the a successful candidate to

1276
01:13:01,280 --> 01:13:03,599
Speaker 1: be a woman and and the problem but the problem

1277
01:13:03,720 --> 01:13:07,759
Speaker 1: is we have a fiduciary duty to hire the best person,

1278
01:13:08,360 --> 01:13:11,200
Speaker 1: not the best woman. And so by the time we

1279
01:13:11,240 --> 01:13:14,000
Speaker 1: get involved, which is really at the most senior end

1280
01:13:14,000 --> 01:13:16,439
Speaker 1: of the industry. If you think about a mountain, if

1281
01:13:16,479 --> 01:13:19,760
Speaker 1: at the base there are so few, you know, it's

1282
01:13:19,800 --> 01:13:23,320
Speaker 1: the pool you start out with, and then by the

1283
01:13:23,360 --> 01:13:27,439
Speaker 1: time we get there very much against right. And so

1284
01:13:27,560 --> 01:13:30,800
Speaker 1: I think that that, um, that's the issue as well

1285
01:13:30,840 --> 01:13:34,080
Speaker 1: as UM the fact that there's something about the P

1286
01:13:34,280 --> 01:13:36,240
Speaker 1: and L and the volatility of the P and L

1287
01:13:36,320 --> 01:13:40,000
Speaker 1: that is that is um. You know, it's it's you

1288
01:13:40,040 --> 01:13:42,400
Speaker 1: can't control it. Even in private equity, you have more

1289
01:13:42,439 --> 01:13:44,360
Speaker 1: control than you do in the public markets. You have

1290
01:13:44,439 --> 01:13:47,120
Speaker 1: ten uere money, you have full information, you're one of

1291
01:13:47,160 --> 01:13:49,840
Speaker 1: eight on a deal team. Trump tweets something that portfolio

1292
01:13:49,920 --> 01:13:55,759
Speaker 1: isn't going to go. Hey, you can be the darling

1293
01:13:55,800 --> 01:13:58,000
Speaker 1: of the industry one moment and be out of business

1294
01:13:58,040 --> 01:14:01,640
Speaker 1: the next. And that is not that all so um,

1295
01:14:01,680 --> 01:14:04,800
Speaker 1: you know, can be scary. So I don't know, UM,

1296
01:14:04,840 --> 01:14:07,200
Speaker 1: I don't know if that is less appealing to women,

1297
01:14:07,400 --> 01:14:10,680
Speaker 1: but maybe that factors into it as well. Huh. That

1298
01:14:10,920 --> 01:14:16,639
Speaker 1: that's that's quite fascinating. So in terms of coming trying

1299
01:14:16,640 --> 01:14:20,200
Speaker 1: to bring women into the industry earlier on last week,

1300
01:14:20,600 --> 01:14:22,400
Speaker 1: and I am trying to you know, I'm doing what

1301
01:14:22,479 --> 01:14:26,600
Speaker 1: I can. Last week, I actually um went out to

1302
01:14:26,920 --> 01:14:30,840
Speaker 1: the University of Michigan to be the keynote speaker for

1303
01:14:30,960 --> 01:14:34,360
Speaker 1: the their Undergraduate Investment Conference, which is like the sound

1304
01:14:34,439 --> 01:14:38,479
Speaker 1: conference for for exactly for undergrads, and uh really to

1305
01:14:38,600 --> 01:14:41,519
Speaker 1: signal to them that this is an industry that wants

1306
01:14:41,560 --> 01:14:44,360
Speaker 1: women and try to encourage all these undergrads to come

1307
01:14:44,400 --> 01:14:47,240
Speaker 1: if they're interested, Like this is a this is a

1308
01:14:48,120 --> 01:14:52,480
Speaker 1: um uh play, this is an industry that is salivating

1309
01:14:52,520 --> 01:14:57,280
Speaker 1: for talent and UM, it is totally meritocratic and if

1310
01:14:57,320 --> 01:15:00,920
Speaker 1: you're talented, nobody cares if you're a man, woman or otherwise.

1311
01:15:01,040 --> 01:15:04,439
Speaker 1: It's just this is like, you know, it's that's a uh,

1312
01:15:05,040 --> 01:15:07,600
Speaker 1: that's what the focus is on. And one of the

1313
01:15:07,640 --> 01:15:10,400
Speaker 1: women towards the end when we had the Q and A,

1314
01:15:10,400 --> 01:15:14,960
Speaker 1: asked me the question of what can women do? How

1315
01:15:14,960 --> 01:15:19,320
Speaker 1: do we become more, UM, fearless? How do we go

1316
01:15:19,479 --> 01:15:21,920
Speaker 1: for it? How do we set ourselves up to be

1317
01:15:22,000 --> 01:15:24,400
Speaker 1: more successful in life? And I, you know, I answered

1318
01:15:24,400 --> 01:15:29,400
Speaker 1: the question in terms of just UMU having you know,

1319
01:15:29,439 --> 01:15:31,479
Speaker 1: you may not have the confidence early on, but that

1320
01:15:31,520 --> 01:15:35,559
Speaker 1: comes with success and UM building it over time and

1321
01:15:35,600 --> 01:15:37,920
Speaker 1: just sort of not you know, going for it. That's

1322
01:15:37,960 --> 01:15:41,559
Speaker 1: the bottom line. But I but I UM. What bothered

1323
01:15:41,560 --> 01:15:43,880
Speaker 1: me about the question is I do think that there

1324
01:15:44,080 --> 01:15:50,000
Speaker 1: is a UM sometimes a little bit of a orientation

1325
01:15:50,080 --> 01:15:53,639
Speaker 1: of like, how do we how can we be UM,

1326
01:15:53,680 --> 01:15:56,360
Speaker 1: how can we set ourselves up better for success? How

1327
01:15:56,400 --> 01:15:59,360
Speaker 1: can we be more as you put it, fearless? Why

1328
01:15:59,360 --> 01:16:02,440
Speaker 1: are we at the world as though we have a handicap.

1329
01:16:02,560 --> 01:16:05,280
Speaker 1: Everybody's scared when they're young, everybody's scared to make a

1330
01:16:05,320 --> 01:16:08,479
Speaker 1: mistake every you know, but you just whether whether you're

1331
01:16:08,520 --> 01:16:11,040
Speaker 1: a man or a woman, you have to sort of

1332
01:16:11,240 --> 01:16:14,000
Speaker 1: buck up and and as I said, go for it.

1333
01:16:14,080 --> 01:16:19,080
Speaker 1: And this idea that, um, because we're female, we're somehow

1334
01:16:19,160 --> 01:16:22,800
Speaker 1: disadvantage by our very nature pisces me off. And I

1335
01:16:22,840 --> 01:16:24,640
Speaker 1: sort of said that to her. I said, there's, like,

1336
01:16:25,040 --> 01:16:27,559
Speaker 1: you know, this sort of cont impacted idea that you

1337
01:16:27,600 --> 01:16:31,280
Speaker 1: need special handling or there's something about you that we

1338
01:16:31,320 --> 01:16:34,479
Speaker 1: need to treat differently. Why. I mean, you know, as

1339
01:16:34,520 --> 01:16:38,000
Speaker 1: long as we're all being good actors and behaving correctly,

1340
01:16:39,360 --> 01:16:41,360
Speaker 1: why should we Why do why do we need sort

1341
01:16:41,400 --> 01:16:44,000
Speaker 1: of a different way of treating you? That as that

1342
01:16:44,160 --> 01:16:47,559
Speaker 1: as long as is a loaded phrase because I recall

1343
01:16:47,640 --> 01:16:50,200
Speaker 1: the early days in my career on a trading desk.

1344
01:16:50,720 --> 01:16:53,880
Speaker 1: It was horrific. That can't go on anymore. And it doesn't.

1345
01:16:53,920 --> 01:16:56,800
Speaker 1: You see ken foot happen with ken Fisher's contra, right,

1346
01:16:56,920 --> 01:17:00,559
Speaker 1: So it's my good business, it's not good business. It's

1347
01:17:00,600 --> 01:17:03,840
Speaker 1: not gonna lead to a successful outcome. And come back

1348
01:17:03,880 --> 01:17:05,840
Speaker 1: to at the end of the day, there's so few

1349
01:17:05,880 --> 01:17:08,880
Speaker 1: talented people. If that person happens to be a woman,

1350
01:17:09,360 --> 01:17:12,040
Speaker 1: There is no hedge fund manager in his right mind

1351
01:17:12,080 --> 01:17:15,920
Speaker 1: that will do anything to make the environment inhospitable to her.

1352
01:17:15,960 --> 01:17:17,640
Speaker 1: Not to mention, it's you can't get away with that

1353
01:17:17,640 --> 01:17:20,479
Speaker 1: stuff anymore. So the world has changed completely. I don't

1354
01:17:20,479 --> 01:17:23,920
Speaker 1: know if it's changed completely. I'm again, like you know,

1355
01:17:24,000 --> 01:17:26,479
Speaker 1: we just saw with Fisher. There are still people who

1356
01:17:26,800 --> 01:17:29,920
Speaker 1: act out of turn. But in an industry that is

1357
01:17:30,000 --> 01:17:34,560
Speaker 1: measured minute to minute, and you're only as good as UM,

1358
01:17:34,640 --> 01:17:38,320
Speaker 1: your last p m L, you cannot do things which

1359
01:17:38,360 --> 01:17:42,040
Speaker 1: are going to scare away the very people that can

1360
01:17:42,160 --> 01:17:45,599
Speaker 1: have a real impact on your business. It's just, it's

1361
01:17:45,640 --> 01:17:48,280
Speaker 1: so there's so much clarity in terms of who the

1362
01:17:48,320 --> 01:17:51,360
Speaker 1: winners and losers are. And to have half the population

1363
01:17:51,960 --> 01:17:54,880
Speaker 1: UM not be a source of talent is insanity. And

1364
01:17:54,880 --> 01:17:57,080
Speaker 1: there's no hedge fund manager that would think that way

1365
01:17:57,240 --> 01:17:59,960
Speaker 1: and that's going to be successful. But when we see

1366
01:18:00,160 --> 01:18:05,000
Speaker 1: the academic studies on male versus female mutual fund managers UM,

1367
01:18:05,040 --> 01:18:08,320
Speaker 1: the data shows that the women tend to do better

1368
01:18:08,400 --> 01:18:11,639
Speaker 1: than the men. The women don't have the same ego issues.

1369
01:18:11,720 --> 01:18:14,439
Speaker 1: They certainly don't suffer from the test what some people

1370
01:18:14,439 --> 01:18:18,519
Speaker 1: have called testosterone poisoning. That they are more measured and

1371
01:18:18,720 --> 01:18:22,800
Speaker 1: less aggressive in a negative way than the male fund managers.

1372
01:18:23,080 --> 01:18:28,400
Speaker 1: So the data even supports female fund managers can outperform

1373
01:18:28,400 --> 01:18:31,920
Speaker 1: male fund managers with without any change to who they

1374
01:18:31,960 --> 01:18:34,320
Speaker 1: are with. You know, it's funny. I had drinks with

1375
01:18:34,360 --> 01:18:36,280
Speaker 1: a woman that I'm not going to name her, but

1376
01:18:36,320 --> 01:18:38,519
Speaker 1: I was so pleased when she did end up being

1377
01:18:38,520 --> 01:18:40,880
Speaker 1: this successful candidate for search we did a year ago,

1378
01:18:42,000 --> 01:18:44,720
Speaker 1: very successful PM. One of the few who ran a

1379
01:18:44,760 --> 01:18:47,000
Speaker 1: lot of capital where she was she ran two billion.

1380
01:18:47,080 --> 01:18:50,080
Speaker 1: Now she's running four billion as a real team underneath her.

1381
01:18:50,360 --> 01:18:52,760
Speaker 1: And we were talking about somebody that she recently had

1382
01:18:52,800 --> 01:18:54,479
Speaker 1: to let go, and it was just so I had

1383
01:18:54,520 --> 01:18:56,320
Speaker 1: such a smile playing on my face as she was

1384
01:18:56,400 --> 01:19:00,479
Speaker 1: describing how emotional he was and he wasn't making rational decisions,

1385
01:19:00,479 --> 01:19:03,479
Speaker 1: and he was constantly complaining about, you know where where

1386
01:19:03,560 --> 01:19:05,200
Speaker 1: his p n L was at? And she's like, I

1387
01:19:05,240 --> 01:19:07,040
Speaker 1: know where you're p P and L is at. I'm

1388
01:19:07,040 --> 01:19:09,559
Speaker 1: watching it, get with it and fix it, and so

1389
01:19:09,840 --> 01:19:12,800
Speaker 1: you know, it's anyway, it's just a sort of sidebar

1390
01:19:13,000 --> 01:19:17,040
Speaker 1: on there is no difference these flighty emotional men. I mean,

1391
01:19:17,840 --> 01:19:20,360
Speaker 1: how can I exactly what I have to deal with?

1392
01:19:21,479 --> 01:19:24,679
Speaker 1: But but you know that is a genuine perception issue

1393
01:19:25,280 --> 01:19:29,679
Speaker 1: and the reality is how So this was a question

1394
01:19:29,720 --> 01:19:32,280
Speaker 1: I didn't get to, but I wanted to ask h

1395
01:19:33,040 --> 01:19:36,200
Speaker 1: You have said the people best suited for this industry

1396
01:19:36,479 --> 01:19:39,639
Speaker 1: are the ones who remain cool under pressure. That that's

1397
01:19:39,640 --> 01:19:42,640
Speaker 1: a quote of yours, which certainly is who's going to

1398
01:19:42,760 --> 01:19:46,600
Speaker 1: argue with that? How can you identify that in a

1399
01:19:46,880 --> 01:19:50,879
Speaker 1: sort of casual conversation until you see them under pressure?

1400
01:19:50,920 --> 01:19:52,439
Speaker 1: How do you know how they're going to react. Well,

1401
01:19:52,479 --> 01:19:58,320
Speaker 1: it's less about the person, you know, the how they act,

1402
01:19:58,400 --> 01:20:01,679
Speaker 1: so to speak, it's more about the comes. So decision

1403
01:20:01,760 --> 01:20:05,880
Speaker 1: is not necessary. I'm looking at consistent pan l over time,

1404
01:20:05,880 --> 01:20:08,200
Speaker 1: and whether you do that by standing on your head

1405
01:20:08,680 --> 01:20:11,200
Speaker 1: or you know, crossing your fingers and toes and screaming,

1406
01:20:11,240 --> 01:20:14,040
Speaker 1: or whatever the case may be. If you can generate,

1407
01:20:14,080 --> 01:20:16,479
Speaker 1: particularly in the last four or five years, where has

1408
01:20:16,479 --> 01:20:20,200
Speaker 1: been so difficult and there's not been this tailwind to performance,

1409
01:20:20,240 --> 01:20:24,679
Speaker 1: if you can generate consistent pan l over time, that

1410
01:20:24,760 --> 01:20:29,120
Speaker 1: to me says you're somebody who possesses um a whole

1411
01:20:29,160 --> 01:20:31,719
Speaker 1: bunch of other qualities which come with that. You're somebody

1412
01:20:31,720 --> 01:20:36,040
Speaker 1: who is flexible and humble. You are You're You're not

1413
01:20:36,200 --> 01:20:39,960
Speaker 1: so wetted to your positions that you can't um take

1414
01:20:40,040 --> 01:20:42,639
Speaker 1: new inputs and shift you know, on a dime where

1415
01:20:42,680 --> 01:20:48,280
Speaker 1: you need to um you um uh and and and

1416
01:20:48,320 --> 01:20:51,120
Speaker 1: so so. Looking at pan L over a period of

1417
01:20:51,160 --> 01:20:54,040
Speaker 1: time gives me insight as well as some of the

1418
01:20:54,400 --> 01:20:57,439
Speaker 1: you know what makes some people vulnerable, which is the

1419
01:20:57,479 --> 01:21:00,360
Speaker 1: founder is often more vulneratible than they are in that. Again,

1420
01:21:00,400 --> 01:21:03,200
Speaker 1: I'm not talking about behavior, although that comes with it sometimes,

1421
01:21:03,240 --> 01:21:06,200
Speaker 1: you know, I mean decision making. It's a guy who

1422
01:21:06,240 --> 01:21:08,799
Speaker 1: comes into my office and says, you know, this happened

1423
01:21:08,840 --> 01:21:11,759
Speaker 1: two years ago. Um he sat at a large hedge fund.

1424
01:21:12,080 --> 01:21:14,559
Speaker 1: He was responsible for a big for a big chunk

1425
01:21:14,560 --> 01:21:19,040
Speaker 1: of it, and um uh, even though he was doing well,

1426
01:21:19,160 --> 01:21:21,880
Speaker 1: the fund was not, and he had he was the

1427
01:21:21,880 --> 01:21:25,840
Speaker 1: most robust uh short, had the most robust short book

1428
01:21:25,880 --> 01:21:28,920
Speaker 1: within the fund, which was not the founder strength or

1429
01:21:29,000 --> 01:21:31,400
Speaker 1: skill set. And the founder came in over the top,

1430
01:21:31,479 --> 01:21:34,439
Speaker 1: took off all his alpha generating shorts, put on index shorts,

1431
01:21:34,479 --> 01:21:36,800
Speaker 1: and erased a lot of this guy's pan L. So

1432
01:21:37,000 --> 01:21:41,920
Speaker 1: you know enough of that kind of stuff happening is

1433
01:21:42,280 --> 01:21:45,479
Speaker 1: you know, it's the differentiation between the founder acting out

1434
01:21:45,520 --> 01:21:48,400
Speaker 1: of sort of panic and emotion and not really understanding

1435
01:21:48,400 --> 01:21:51,760
Speaker 1: what's going on, and this guy pointing to consistent pan

1436
01:21:51,880 --> 01:21:54,439
Speaker 1: l and where he's gotten tripped up is when he's

1437
01:21:54,479 --> 01:21:59,320
Speaker 1: been overridden by um, somebody who isn't taking a more

1438
01:21:59,320 --> 01:22:01,639
Speaker 1: measured approach. We assume that guy is no longer at

1439
01:22:01,640 --> 01:22:05,479
Speaker 1: that fund. We can. I have a million more questions

1440
01:22:05,479 --> 01:22:08,040
Speaker 1: for you, but I know I don't have you all day,

1441
01:22:08,080 --> 01:22:10,960
Speaker 1: So why don't I go to some of my uh

1442
01:22:11,120 --> 01:22:13,599
Speaker 1: favorite questions. This hasn't been too painful, it's been a

1443
01:22:13,600 --> 01:22:15,360
Speaker 1: lot of fun. Oh, I'm so glad you've said that.

1444
01:22:15,439 --> 01:22:17,840
Speaker 1: So let's jump. And I don't know if you're gonna

1445
01:22:17,840 --> 01:22:20,479
Speaker 1: be able to answer this question because you were born

1446
01:22:20,520 --> 01:22:23,720
Speaker 1: in Brooklyn and moved to Manhattan. Um, but let me

1447
01:22:23,760 --> 01:22:26,000
Speaker 1: ask you the question, what was the first car you

1448
01:22:26,080 --> 01:22:30,519
Speaker 1: ever owned? You're making model? Okay, Barry, you don't drive?

1449
01:22:30,760 --> 01:22:33,960
Speaker 1: You got it. You are the first person I've been

1450
01:22:34,040 --> 01:22:37,040
Speaker 1: waiting for someone to say that to me. And I

1451
01:22:37,080 --> 01:22:39,639
Speaker 1: was expecting, like a millennial to say, oh I uber

1452
01:22:39,800 --> 01:22:42,600
Speaker 1: or Isaip drive. See I'm ahead of my time. You

1453
01:22:42,680 --> 01:22:46,200
Speaker 1: are so you never owned a car, never owned a car,

1454
01:22:46,439 --> 01:22:48,920
Speaker 1: never drove a car. I took a feely I took

1455
01:22:48,920 --> 01:22:52,360
Speaker 1: a few lessons, uh like ten years ago and I

1456
01:22:52,439 --> 01:22:54,400
Speaker 1: was just like, this is a waste of time. I'm

1457
01:22:54,439 --> 01:22:56,920
Speaker 1: never I'm never going to create the muscle memory to

1458
01:22:57,560 --> 01:23:00,000
Speaker 1: know how to do this. I'll probably kill someone or myself.

1459
01:23:00,080 --> 01:23:02,200
Speaker 1: So if we get you on a track, it's a

1460
01:23:02,240 --> 01:23:04,559
Speaker 1: lot of fun. Could be surprised. Can we do? Like

1461
01:23:04,640 --> 01:23:06,639
Speaker 1: the what do you call them? The bumper cars? Though?

1462
01:23:07,680 --> 01:23:10,760
Speaker 1: So now those bumper cars are all electric. There's a

1463
01:23:10,840 --> 01:23:13,680
Speaker 1: place called RPM. There's a bunch of them around this

1464
01:23:13,760 --> 01:23:17,040
Speaker 1: one in Farmingdale and it's just the most amount of

1465
01:23:17,080 --> 01:23:18,800
Speaker 1: I would love to have. It's a blas I should

1466
01:23:18,840 --> 01:23:20,680
Speaker 1: do that with my fifteen year old who tells me

1467
01:23:20,920 --> 01:23:23,160
Speaker 1: in star contrast to myself he's going to have his

1468
01:23:23,360 --> 01:23:26,600
Speaker 1: learners permit when he's sixteen, which well I'm terrified of.

1469
01:23:26,760 --> 01:23:29,759
Speaker 1: But you know, it's such a different having that happen

1470
01:23:30,360 --> 01:23:34,000
Speaker 1: pre Internet, if you lived outside of a major city,

1471
01:23:34,080 --> 01:23:39,200
Speaker 1: a car represented freedom. Now everybody's playing everything. It's just

1472
01:23:39,240 --> 01:23:42,920
Speaker 1: such a different So let's talk a little bit about, um, you,

1473
01:23:43,120 --> 01:23:46,800
Speaker 1: what's the most important thing we don't know about? Allana Weinstein?

1474
01:23:47,520 --> 01:23:49,519
Speaker 1: Although I think you may have just revealed it. I

1475
01:23:49,560 --> 01:23:51,680
Speaker 1: think you I may have just revealed it. That I

1476
01:23:51,920 --> 01:23:54,679
Speaker 1: never have driven a car, never during a car. Yeah.

1477
01:23:54,960 --> 01:23:58,000
Speaker 1: And and you know what everyone in this industry knows

1478
01:23:58,040 --> 01:24:01,000
Speaker 1: me is like a very um which is true to

1479
01:24:01,080 --> 01:24:05,120
Speaker 1: the point, um, no nonsense, say it like it is

1480
01:24:05,560 --> 01:24:08,880
Speaker 1: businesswoman all true. But Barry, I do have a soft

1481
01:24:08,920 --> 01:24:11,920
Speaker 1: and gooey center, right, I don't believe that it's true.

1482
01:24:12,320 --> 01:24:15,519
Speaker 1: What is your soft and gooey center? Like? What what

1483
01:24:16,200 --> 01:24:19,280
Speaker 1: it's meaning? What? Um? So? What is what is yours?

1484
01:24:19,320 --> 01:24:21,280
Speaker 1: So maybe this is the thing we don't know about you.

1485
01:24:21,320 --> 01:24:26,720
Speaker 1: What you work in a tough industry, male dominated, very sharp, elbowed,

1486
01:24:26,880 --> 01:24:30,200
Speaker 1: very competitive. What are you soft and gooey about? And

1487
01:24:30,240 --> 01:24:32,559
Speaker 1: you brought this up? Not me? Yeah, I mean it's

1488
01:24:32,600 --> 01:24:36,080
Speaker 1: just more you know, it's my it's my alter ego,

1489
01:24:36,360 --> 01:24:39,120
Speaker 1: non work persona. It's uh, you have to have a

1490
01:24:39,160 --> 01:24:42,320
Speaker 1: yang and yang, my yang or yang or whatever you

1491
01:24:42,320 --> 01:24:44,400
Speaker 1: want to whatever. The opposite one is that we're referring

1492
01:24:44,439 --> 01:24:48,400
Speaker 1: to is you know, it's just you have to enjoy life.

1493
01:24:48,479 --> 01:24:50,280
Speaker 1: And and that's a big part of who I am.

1494
01:24:50,320 --> 01:24:54,400
Speaker 1: Fair enough, Who are your mentors? Who has influenced your career?

1495
01:24:54,600 --> 01:24:57,320
Speaker 1: Well it might be a cliche answer, but my parents

1496
01:24:57,400 --> 01:25:04,000
Speaker 1: are tremendous mentors. Um. Uh my mom in particular, even

1497
01:25:04,000 --> 01:25:06,840
Speaker 1: though she was a stay at home mom, she is

1498
01:25:06,880 --> 01:25:10,400
Speaker 1: an incredibly bright woman who kind of managed the family.

1499
01:25:10,479 --> 01:25:13,560
Speaker 1: I'd say in some ways similarly to a how a

1500
01:25:13,640 --> 01:25:16,880
Speaker 1: CEO manages his you know, best employees, but with lots

1501
01:25:16,880 --> 01:25:20,360
Speaker 1: of love, very but very no nonsense. Very kind of

1502
01:25:20,400 --> 01:25:22,439
Speaker 1: like the advice I gave this girl at you of

1503
01:25:22,520 --> 01:25:25,120
Speaker 1: them like, get up and go for it, stop whining,

1504
01:25:26,040 --> 01:25:30,120
Speaker 1: just get it done. And um, and that gave me

1505
01:25:30,280 --> 01:25:33,120
Speaker 1: you know, and and forcing my and that made me strong,

1506
01:25:33,880 --> 01:25:37,960
Speaker 1: um and creates winds and then it creates real confidence. Um.

1507
01:25:37,960 --> 01:25:43,200
Speaker 1: Other mentors were just you know. I've cultivated great relationships, um,

1508
01:25:43,240 --> 01:25:46,160
Speaker 1: great relationships with my clients who have given me great

1509
01:25:46,160 --> 01:25:51,880
Speaker 1: advice along the way. UM. I mean everywhere I've worked,

1510
01:25:52,000 --> 01:25:54,559
Speaker 1: I've just um, I've had the good fortune of finding

1511
01:25:54,600 --> 01:26:00,160
Speaker 1: great people who um I learned a lot from quite interesting. UM.

1512
01:26:00,240 --> 01:26:02,240
Speaker 1: Tell us about your favorite books. What do you like

1513
01:26:02,320 --> 01:26:06,479
Speaker 1: to read when you're not out recruiting talent. I love

1514
01:26:06,600 --> 01:26:10,559
Speaker 1: books by and I think there's some commonality between them.

1515
01:26:10,600 --> 01:26:14,559
Speaker 1: I love John krak Our, Tom Wolfe, Michael Lewis. They

1516
01:26:14,680 --> 01:26:21,240
Speaker 1: all right, real stories um that are almost read like thrillers.

1517
01:26:21,400 --> 01:26:23,840
Speaker 1: And Tom Wolfe is fiction, but he's really writing about

1518
01:26:23,880 --> 01:26:29,479
Speaker 1: moments in time that right, a bonfire, right, even I am.

1519
01:26:29,560 --> 01:26:32,559
Speaker 1: Charlotte Simmons is based on you know, real LuFe. Do

1520
01:26:32,560 --> 01:26:35,280
Speaker 1: you know that book? It's great, It's uh. I read

1521
01:26:35,320 --> 01:26:38,680
Speaker 1: it a few years ago. It's a woman's um, a

1522
01:26:38,720 --> 01:26:44,000
Speaker 1: young woman's travails and experience at undergrad. I think it's

1523
01:26:44,040 --> 01:26:46,639
Speaker 1: it's meant to be a big Ten's type school and

1524
01:26:46,680 --> 01:26:49,400
Speaker 1: everything she goes through. It's a very thick book, but

1525
01:26:50,040 --> 01:26:52,880
Speaker 1: I thought it was so on point in terms of

1526
01:26:52,920 --> 01:26:55,680
Speaker 1: what the undergraduate experience is like. I'm sure based on

1527
01:26:56,040 --> 01:26:59,000
Speaker 1: characters that he knew. Well, maybe Ben his own family.

1528
01:26:59,439 --> 01:27:01,479
Speaker 1: Give us some more book titles. You mentioned a number

1529
01:27:01,479 --> 01:27:04,200
Speaker 1: of authors. Um, I have to think the Big Short

1530
01:27:04,320 --> 01:27:07,200
Speaker 1: is right in your love. In fact, it's funny you

1531
01:27:07,200 --> 01:27:10,280
Speaker 1: bring that up. I was on a long flight a

1532
01:27:10,320 --> 01:27:12,559
Speaker 1: few weeks ago and I didn't reread the book, but

1533
01:27:12,640 --> 01:27:16,240
Speaker 1: I did see the movie again and I actually called

1534
01:27:16,360 --> 01:27:18,720
Speaker 1: a number of my clients and said, you have to

1535
01:27:18,720 --> 01:27:20,880
Speaker 1: watch this again. And I made my son watch it again.

1536
01:27:20,960 --> 01:27:24,080
Speaker 1: It's so good, and I have so much respect for

1537
01:27:24,120 --> 01:27:26,559
Speaker 1: how Michael Lewis did that. How he you know, he

1538
01:27:26,600 --> 01:27:29,600
Speaker 1: found it's just it's so many. It's a tough subject

1539
01:27:29,640 --> 01:27:33,599
Speaker 1: to understand for a late person. He totally explained it well.

1540
01:27:34,080 --> 01:27:37,920
Speaker 1: And he takes these stories and builds these not builds

1541
01:27:37,920 --> 01:27:40,519
Speaker 1: they were, but brings to life these characters that were

1542
01:27:41,200 --> 01:27:45,600
Speaker 1: interesting in esoteric and dynamic in their own ways and contrarians.

1543
01:27:45,680 --> 01:27:47,759
Speaker 1: And then there's this That's why I call it a thriller,

1544
01:27:47,800 --> 01:27:49,839
Speaker 1: like how is how is it all going to come together?

1545
01:27:49,880 --> 01:27:51,479
Speaker 1: And how did they figure this out? And how did

1546
01:27:51,479 --> 01:27:54,679
Speaker 1: they all sort of end up interweaving um and tells

1547
01:27:54,720 --> 01:27:58,640
Speaker 1: the story which is so multidimensional. I just brilliant. That

1548
01:27:58,760 --> 01:28:03,600
Speaker 1: is the Michael Lewis form. Find an esoteric, quirky outsider,

1549
01:28:04,320 --> 01:28:09,000
Speaker 1: and we've a narrative not from the center, but from

1550
01:28:09,000 --> 01:28:13,240
Speaker 1: the people on the periphery who identify in a contrarian basis.

1551
01:28:14,160 --> 01:28:17,360
Speaker 1: Wait what what does everybody seem to misunderstand? And then

1552
01:28:17,400 --> 01:28:19,680
Speaker 1: the next level is how can we capitalize on it?

1553
01:28:19,760 --> 01:28:22,280
Speaker 1: And you know what, you just describe what we do,

1554
01:28:23,120 --> 01:28:25,280
Speaker 1: what you do, what I do as a hunter, What

1555
01:28:25,400 --> 01:28:27,840
Speaker 1: I do as a headhunter. It's finding the people who

1556
01:28:28,040 --> 01:28:31,519
Speaker 1: who see something, who can come at things differently, who

1557
01:28:31,560 --> 01:28:36,040
Speaker 1: are um who are able to generate Alpha consistently over

1558
01:28:36,080 --> 01:28:39,160
Speaker 1: time in spite of everyone else, And what do they

1559
01:28:39,320 --> 01:28:43,000
Speaker 1: and what does that mean in terms of UM where

1560
01:28:43,040 --> 01:28:45,240
Speaker 1: they can be most successful and where the industry is

1561
01:28:45,280 --> 01:28:47,760
Speaker 1: going Give me one more book title, UM, because I'm

1562
01:28:47,800 --> 01:28:49,479
Speaker 1: curious as to what else you read, And then I'm

1563
01:28:49,479 --> 01:28:51,640
Speaker 1: going to share two with you. I'm gonna bet you

1564
01:28:51,680 --> 01:28:53,519
Speaker 1: probably well. One of them hasn't come out yet, but

1565
01:28:53,560 --> 01:28:56,280
Speaker 1: one of them I wonder if you read. I'm in

1566
01:28:56,280 --> 01:28:58,439
Speaker 1: the middle of one right now, which is not something

1567
01:28:58,479 --> 01:29:00,720
Speaker 1: I normally read, but someone into to me and I'm

1568
01:29:00,720 --> 01:29:04,720
Speaker 1: actually really into it. It's called hacking Darwin. Have you

1569
01:29:04,760 --> 01:29:06,920
Speaker 1: read I'm familiar with it. I haven't ready. So it's

1570
01:29:06,960 --> 01:29:13,960
Speaker 1: it's written by this UM technology futurist and it's all

1571
01:29:14,120 --> 01:29:17,920
Speaker 1: real stuff, which is amazing UM. And he's the premise

1572
01:29:18,000 --> 01:29:20,240
Speaker 1: being we can hack the genetic code the same way

1573
01:29:20,280 --> 01:29:22,439
Speaker 1: you can have a computer, which we know we can,

1574
01:29:22,520 --> 01:29:25,519
Speaker 1: you know, do things now with the genetic code UM

1575
01:29:25,560 --> 01:29:29,280
Speaker 1: to make people healthier, to make them smarter. Uh. And

1576
01:29:29,360 --> 01:29:32,240
Speaker 1: it's just I'm only midway through it. But it's both

1577
01:29:32,320 --> 01:29:37,080
Speaker 1: the UM ethical challenges inherent in that as well as

1578
01:29:37,080 --> 01:29:41,640
Speaker 1: the socioeconomic challenges. If we decide something's not ethical, but

1579
01:29:41,680 --> 01:29:44,640
Speaker 1: another country decides it is. Does that create sort of

1580
01:29:44,640 --> 01:29:47,400
Speaker 1: a superior population to us? You know? There's there's so

1581
01:29:47,479 --> 01:29:49,280
Speaker 1: much in it that I think is interesting, and it's

1582
01:29:49,280 --> 01:29:53,400
Speaker 1: written in a way that a non um medical person

1583
01:29:53,479 --> 01:29:57,080
Speaker 1: like myself can totally understand. Jamie Metzel, yes is the

1584
01:29:57,120 --> 01:29:59,920
Speaker 1: author courtesy of Google. So the two books I have

1585
01:30:00,000 --> 01:30:03,920
Speaker 1: to ask you about because you kind of describe them both.

1586
01:30:04,600 --> 01:30:07,519
Speaker 1: One is The Spider Network, but I think it's David

1587
01:30:07,560 --> 01:30:12,519
Speaker 1: and Trust about the libor manipulation scandal, same sort of

1588
01:30:12,560 --> 01:30:15,479
Speaker 1: thing where it's a financial book, but it reads like

1589
01:30:15,520 --> 01:30:18,200
Speaker 1: a thriller and all the characters are odd and interesting.

1590
01:30:18,200 --> 01:30:20,479
Speaker 1: I'm totally going to read that. Yeah, that's it. And

1591
01:30:20,520 --> 01:30:24,479
Speaker 1: then the new Greg Zuckerman book on renaissance technologies and

1592
01:30:24,560 --> 01:30:29,519
Speaker 1: Jim Simon's The Man Who, um I'm trying to remember

1593
01:30:29,520 --> 01:30:32,000
Speaker 1: with the title is the Man Who figure who solved

1594
01:30:32,000 --> 01:30:36,400
Speaker 1: the Markets? Another one that reads like a thriller, And

1595
01:30:36,400 --> 01:30:40,080
Speaker 1: and how do we figure out um, we figure out

1596
01:30:40,080 --> 01:30:42,679
Speaker 1: commodities and futures? How do we apply that and figure

1597
01:30:42,720 --> 01:30:48,479
Speaker 1: out equities? Really a fascinating that's such a unknown entity

1598
01:30:48,560 --> 01:30:52,360
Speaker 1: and there's so little public information on renaissance Um, the

1599
01:30:52,439 --> 01:30:54,800
Speaker 1: Jim Simon's book is really quite fun. Thank you. I'm

1600
01:30:54,840 --> 01:30:57,000
Speaker 1: totally picking those two up. Can I tell you? I

1601
01:30:57,080 --> 01:31:00,240
Speaker 1: know that the Simon's book is just gonna go crazy

1602
01:31:00,400 --> 01:31:02,760
Speaker 1: only because it's, uh, it's a black box. No one

1603
01:31:02,800 --> 01:31:06,800
Speaker 1: knows what goes on and post election um everything that

1604
01:31:06,920 --> 01:31:11,320
Speaker 1: happened with them, Uh Simon's partner who who had such

1605
01:31:11,360 --> 01:31:17,000
Speaker 1: an impact on the Trump candidacy. That that's the I

1606
01:31:17,080 --> 01:31:18,600
Speaker 1: just see that book is blowing up. I could be

1607
01:31:18,640 --> 01:31:21,639
Speaker 1: completely wrong and what I'm interested in very often other

1608
01:31:21,640 --> 01:31:24,080
Speaker 1: people aren't. But I think you would, really, you especially

1609
01:31:24,120 --> 01:31:27,160
Speaker 1: would really appreciate both of those done. I'm totally reading them.

1610
01:31:27,240 --> 01:31:30,080
Speaker 1: Next question, tell us about a time you failed and

1611
01:31:30,120 --> 01:31:35,200
Speaker 1: what you learned from the experience. So I'm going to

1612
01:31:35,360 --> 01:31:38,720
Speaker 1: cite something that happened early on in my career, like

1613
01:31:39,520 --> 01:31:43,720
Speaker 1: inconsequential looking back, but I remember it because it was

1614
01:31:43,800 --> 01:31:49,320
Speaker 1: so scary and crazy at the time. Uh. And this

1615
01:31:49,439 --> 01:31:51,800
Speaker 1: was my first as my first job. I was a

1616
01:31:51,840 --> 01:31:59,559
Speaker 1: Goldman UM and I had done this analysis and submitted

1617
01:31:59,600 --> 01:32:04,160
Speaker 1: it and I got pulled into the partner's office who

1618
01:32:04,280 --> 01:32:08,400
Speaker 1: ran my division, and he started reaming me out, like

1619
01:32:08,680 --> 01:32:12,120
Speaker 1: totally carrying on and screaming and yelling, and I'm sitting there,

1620
01:32:12,200 --> 01:32:14,960
Speaker 1: white knuckles, grabbing the chair, wondering what the heck did

1621
01:32:15,000 --> 01:32:17,479
Speaker 1: I do? I worked so hard on this, like, well,

1622
01:32:17,520 --> 01:32:20,160
Speaker 1: how did I screw this up so badly? And I

1623
01:32:20,280 --> 01:32:22,800
Speaker 1: just I'm my head was exploding. I was listening as

1624
01:32:22,840 --> 01:32:24,760
Speaker 1: I said, well, I don't I don't understand what what

1625
01:32:24,880 --> 01:32:27,160
Speaker 1: because it had been submitted to some other partner that

1626
01:32:27,240 --> 01:32:30,519
Speaker 1: was senior than him, so I can't make this up.

1627
01:32:30,680 --> 01:32:34,519
Speaker 1: I had left off the middle initial of the partner

1628
01:32:34,760 --> 01:32:37,920
Speaker 1: who was the ultimate recipient of this analysis. I had

1629
01:32:38,000 --> 01:32:39,439
Speaker 1: left off I think it was an A. I remember

1630
01:32:39,479 --> 01:32:41,160
Speaker 1: to this point, to this day, I remember his name,

1631
01:32:41,160 --> 01:32:43,719
Speaker 1: but I remember the middle initial was an A and

1632
01:32:43,840 --> 01:32:46,439
Speaker 1: it was so insane. Wait, wait, that's what he was

1633
01:32:46,520 --> 01:32:50,080
Speaker 1: upset about. This guy had his higher up. It reamed

1634
01:32:50,120 --> 01:32:53,160
Speaker 1: him out because I attention to details, she left off

1635
01:32:53,200 --> 01:32:59,640
Speaker 1: my middle initial, so I can't see exactly. Um, but

1636
01:33:00,040 --> 01:33:05,000
Speaker 1: on crazy I know, so UM. But you know what

1637
01:33:06,680 --> 01:33:09,680
Speaker 1: I ended up doing was calling the guy who was

1638
01:33:10,520 --> 01:33:14,360
Speaker 1: the middle initial A guy and asking to meet with him,

1639
01:33:14,400 --> 01:33:18,160
Speaker 1: and we ended up having lunch and Um. As it

1640
01:33:18,160 --> 01:33:20,439
Speaker 1: turns out, he wasn't nearly as upset as I think

1641
01:33:20,479 --> 01:33:22,080
Speaker 1: the guy who called me into his office was just

1642
01:33:22,120 --> 01:33:25,599
Speaker 1: having a bad day or you know, whatever the case was. Um,

1643
01:33:25,600 --> 01:33:28,479
Speaker 1: but it it taught me about dealing with things head

1644
01:33:28,520 --> 01:33:32,000
Speaker 1: on and not letting someone else speak for me, um

1645
01:33:32,080 --> 01:33:37,599
Speaker 1: and uh and diffusing the situation um again by just

1646
01:33:37,680 --> 01:33:40,960
Speaker 1: having a candid conversation, you know, sort of person to

1647
01:33:41,080 --> 01:33:45,840
Speaker 1: person and so UM it was. You know, it stuck

1648
01:33:45,880 --> 01:33:49,840
Speaker 1: with me because I it was a ballsy move, but

1649
01:33:49,880 --> 01:33:52,280
Speaker 1: it ended up okay as a result. Quite quite interesting.

1650
01:33:52,520 --> 01:33:53,920
Speaker 1: What do you do for fun? What do you do

1651
01:33:54,000 --> 01:33:57,160
Speaker 1: when you're not um up to your elbows in the

1652
01:33:57,240 --> 01:34:01,360
Speaker 1: hedge fun industry? So I've discovered inner athlete in the

1653
01:34:01,439 --> 01:34:03,960
Speaker 1: last few years. I you know, growing up in New York,

1654
01:34:04,200 --> 01:34:07,040
Speaker 1: I uh, I don't know. I didn't like I went

1655
01:34:07,080 --> 01:34:09,000
Speaker 1: to Stuybison. It wasn't like I was. I wasn't a

1656
01:34:09,000 --> 01:34:11,320
Speaker 1: big sports person. I took ballet that was about as

1657
01:34:11,320 --> 01:34:16,200
Speaker 1: athletic as I as I was. UM. So I found

1658
01:34:16,280 --> 01:34:19,479
Speaker 1: that I love cycling. Go on all these cycling trips

1659
01:34:19,520 --> 01:34:22,800
Speaker 1: now like all over the world. I have a buddy

1660
01:34:22,800 --> 01:34:26,439
Speaker 1: who does that. They have a Chase van and they

1661
01:34:26,880 --> 01:34:29,080
Speaker 1: they went through Italy, they went through So I do

1662
01:34:29,240 --> 01:34:31,439
Speaker 1: this in style. I'm not like you know, I mean,

1663
01:34:31,640 --> 01:34:33,800
Speaker 1: so there is a van that follows us. We stay

1664
01:34:33,840 --> 01:34:38,400
Speaker 1: in phenomenal places. We eat crazy copious amounts of food

1665
01:34:38,439 --> 01:34:44,040
Speaker 1: because we can. We're cycling fifty six. You see stuff

1666
01:34:44,080 --> 01:34:46,240
Speaker 1: you would never see as a tourist, you know, you

1667
01:34:46,280 --> 01:34:49,840
Speaker 1: really and we picked places that are just that are

1668
01:34:49,880 --> 01:34:52,240
Speaker 1: like you know, they're beautiful to cycle. Where have you

1669
01:34:52,280 --> 01:34:59,080
Speaker 1: give us a few names? Provence, Croatia, uh, other parts

1670
01:34:59,080 --> 01:35:03,560
Speaker 1: of France. Um which is off the coast of LaRochelle.

1671
01:35:03,640 --> 01:35:13,760
Speaker 1: It's kind of like the Hampton's of Paris, Umu, Costa Rica. Yeah,

1672
01:35:13,800 --> 01:35:17,280
Speaker 1: that that sounds fascinating. Let me ask you UM this

1673
01:35:17,360 --> 01:35:20,519
Speaker 1: question about the industry. What are you most optimistic and

1674
01:35:20,560 --> 01:35:26,719
Speaker 1: most pessimistic about the world of finance. So I think

1675
01:35:26,920 --> 01:35:29,760
Speaker 1: that this this shakeout is going to be for the better,

1676
01:35:30,040 --> 01:35:33,760
Speaker 1: because I really think the industry has gotten tagged with

1677
01:35:33,920 --> 01:35:37,240
Speaker 1: the poor performance of the majority of hedge funds and

1678
01:35:37,360 --> 01:35:41,439
Speaker 1: if they go away UM or, then I think what

1679
01:35:41,520 --> 01:35:44,439
Speaker 1: we're left with are the guys that are actually really

1680
01:35:44,479 --> 01:35:49,799
Speaker 1: delivering on um a business model that works for LPs.

1681
01:35:49,880 --> 01:35:51,800
Speaker 1: And so I'm I'm as much as this is a

1682
01:35:51,840 --> 01:35:54,040
Speaker 1: painful moment in time for a lot of funds. I

1683
01:35:54,040 --> 01:35:57,040
Speaker 1: think the shakeout will happen the way it's supposed to.

1684
01:35:57,400 --> 01:36:00,400
Speaker 1: Before we get to the pessimistic I meant to to

1685
01:36:00,600 --> 01:36:04,760
Speaker 1: quote you something from Jim Chanos who said thirty years

1686
01:36:04,760 --> 01:36:07,080
Speaker 1: ago there were a hundred hedge funds. They all created alpha.

1687
01:36:07,439 --> 01:36:09,960
Speaker 1: Now this eleven thousand hedge funds, and it's those same

1688
01:36:10,040 --> 01:36:12,760
Speaker 1: hundreds that are creating the alpha. Is that a fair

1689
01:36:12,800 --> 01:36:15,519
Speaker 1: statement or you Now I don't I don't think that's true,

1690
01:36:15,640 --> 01:36:18,519
Speaker 1: or you wouldn't see funds again like Eating Perry and

1691
01:36:18,600 --> 01:36:21,360
Speaker 1: I mean sorry, Eating Park and Perry going out of business,

1692
01:36:22,000 --> 01:36:24,479
Speaker 1: or High Fields closing its doors or Blue Ridge closing

1693
01:36:24,479 --> 01:36:26,559
Speaker 1: its stores. Those two were by choice. The first two

1694
01:36:27,040 --> 01:36:30,759
Speaker 1: we're you know, I'm not sure they were. UM and

1695
01:36:30,760 --> 01:36:33,120
Speaker 1: and again all those funds that I mentioned that are

1696
01:36:33,160 --> 01:36:36,080
Speaker 1: now shells of their former selves. Right, we talked about

1697
01:36:36,160 --> 01:36:39,200
Speaker 1: the A U M drops of funds like green Light

1698
01:36:39,280 --> 01:36:42,000
Speaker 1: and Corvax and Discovery and fir Tree. So those that's

1699
01:36:42,000 --> 01:36:46,080
Speaker 1: not indicative of funds that have delivered great performance for

1700
01:36:46,080 --> 01:36:48,919
Speaker 1: the past four or five years. Again this year exclusion.

1701
01:36:49,160 --> 01:36:51,679
Speaker 1: So I don't agree with that. UM. I think now

1702
01:36:52,040 --> 01:36:57,439
Speaker 1: what what UM is the differentiator? Are really funds that

1703
01:36:57,560 --> 01:37:01,519
Speaker 1: have set up an infrastructure that bestows competitive advantage to

1704
01:37:01,600 --> 01:37:04,400
Speaker 1: their people. So what sort of advice would you give

1705
01:37:04,439 --> 01:37:07,559
Speaker 1: to a recent college grad who was interested in going

1706
01:37:07,600 --> 01:37:11,680
Speaker 1: into finance. I think they need to They need to

1707
01:37:11,800 --> 01:37:15,920
Speaker 1: understand whether it's finance, whether it's investment banking, or it's

1708
01:37:15,920 --> 01:37:18,240
Speaker 1: going directly to a hedge fund or really my advice

1709
01:37:18,280 --> 01:37:22,440
Speaker 1: would be no different to whether it's consulting anything. They

1710
01:37:22,680 --> 01:37:25,760
Speaker 1: need to be prepared to work harder than everybody else

1711
01:37:25,800 --> 01:37:28,080
Speaker 1: if they wanted differentiate themselves. And I tell this to

1712
01:37:28,160 --> 01:37:30,719
Speaker 1: my son all the time. Everyone thinks they work hard.

1713
01:37:31,080 --> 01:37:33,360
Speaker 1: The truth is is you and I know Barry, most

1714
01:37:33,360 --> 01:37:36,120
Speaker 1: people don't actually work that hard. And I think, particularly

1715
01:37:36,120 --> 01:37:40,800
Speaker 1: with millennial millennials, UM, they I don't think people these

1716
01:37:40,880 --> 01:37:43,360
Speaker 1: days we interview young kids from Goldman even to join

1717
01:37:43,439 --> 01:37:45,920
Speaker 1: our firm, to my firm, they're not working the way

1718
01:37:45,960 --> 01:37:47,599
Speaker 1: I used to work when I was a Goldman, And

1719
01:37:47,640 --> 01:37:51,680
Speaker 1: so I working hard that hard in being that overprepared

1720
01:37:51,680 --> 01:37:54,759
Speaker 1: in the beginning is what will set you up for success,

1721
01:37:54,840 --> 01:38:00,080
Speaker 1: because you'll be ready for unexpected um questions. UM. It

1722
01:38:00,120 --> 01:38:02,880
Speaker 1: sets up a work ethic which UM, I think just

1723
01:38:03,160 --> 01:38:05,240
Speaker 1: serves you well in life. You know, and I that's

1724
01:38:05,360 --> 01:38:07,880
Speaker 1: that's the ethos I live by still to this day.

1725
01:38:08,120 --> 01:38:11,360
Speaker 1: It's the ethos of my firm. It's just it's being

1726
01:38:11,920 --> 01:38:15,519
Speaker 1: paranoid that you're missing something and making sure that every

1727
01:38:15,600 --> 01:38:19,320
Speaker 1: last stone is uncovered. I've read certain coaches say that

1728
01:38:19,479 --> 01:38:22,240
Speaker 1: given a choice between hard work and talent, I'll take

1729
01:38:22,280 --> 01:38:25,439
Speaker 1: the hard work. Quite interesting, and our final question, what

1730
01:38:25,520 --> 01:38:28,719
Speaker 1: do you know about the world of alternatives and talents

1731
01:38:29,160 --> 01:38:32,400
Speaker 1: and recruitment today that you wish you knew twenty plus

1732
01:38:32,520 --> 01:38:37,160
Speaker 1: years ago? So I think there's a special cocktail of

1733
01:38:37,520 --> 01:38:42,320
Speaker 1: art and science that goes into what makes the best people.

1734
01:38:43,080 --> 01:38:45,280
Speaker 1: And when I look at the people I thought were

1735
01:38:45,320 --> 01:38:48,240
Speaker 1: good fifteen twenty years ago, you know, when I when

1736
01:38:48,240 --> 01:38:50,280
Speaker 1: I see them now, a lot of these people, I'm like,

1737
01:38:50,520 --> 01:38:54,599
Speaker 1: what was I thinking? It's just what? So our judgment

1738
01:38:54,680 --> 01:38:57,960
Speaker 1: has certainly become a lot more refined as we've seen

1739
01:38:58,000 --> 01:39:01,559
Speaker 1: people evolved through different markets. But there are certain things

1740
01:39:01,760 --> 01:39:04,320
Speaker 1: that are common traits. Is what we've distilled from that

1741
01:39:04,320 --> 01:39:06,439
Speaker 1: that I know now that I wish I knew then.

1742
01:39:06,840 --> 01:39:10,000
Speaker 1: So those fall into two categories science and art. On

1743
01:39:10,040 --> 01:39:15,080
Speaker 1: the science front, what we're looking for is a defined process.

1744
01:39:15,600 --> 01:39:18,839
Speaker 1: We're looking for people who come at things through systematic research,

1745
01:39:19,000 --> 01:39:23,680
Speaker 1: through systematic um independent research, not through talking to their

1746
01:39:23,720 --> 01:39:27,320
Speaker 1: hedge fund buddies. We're looking for velocity of ideas. I

1747
01:39:27,400 --> 01:39:29,960
Speaker 1: want somebody who's constantly thinking out of the box and

1748
01:39:30,040 --> 01:39:33,120
Speaker 1: coming up with things, regardless of how tough it. Maybe.

1749
01:39:33,479 --> 01:39:38,559
Speaker 1: I want somebody who can UM run a scale business.

1750
01:39:38,680 --> 01:39:41,360
Speaker 1: You know, being able to deploy ten million dollars is

1751
01:39:41,360 --> 01:39:43,519
Speaker 1: different than a hundred, is different than a billion. For

1752
01:39:43,640 --> 01:39:46,120
Speaker 1: our clients, I need the guy who can deploy a

1753
01:39:46,120 --> 01:39:49,360
Speaker 1: billion dollars successfully and generate consistent alpha over time. And

1754
01:39:49,360 --> 01:39:51,920
Speaker 1: that goes to my last point on science. I want

1755
01:39:51,960 --> 01:39:54,479
Speaker 1: somebody who can be effective in different kinds of markets.

1756
01:39:54,560 --> 01:39:56,920
Speaker 1: Isn't just a one trick pony. So that's on that's

1757
01:39:56,920 --> 01:39:59,479
Speaker 1: a that's a toll order. That's on the science front.

1758
01:39:59,479 --> 01:40:02,639
Speaker 1: But you can have of people who have great science

1759
01:40:02,720 --> 01:40:05,280
Speaker 1: and no art and can't really generate P and L

1760
01:40:06,080 --> 01:40:09,600
Speaker 1: and on the and art is you know, it's a

1761
01:40:10,360 --> 01:40:12,519
Speaker 1: I think it's a little bit. You know it when

1762
01:40:12,560 --> 01:40:15,920
Speaker 1: you see it, certainly for us, And I'm not sure

1763
01:40:16,000 --> 01:40:18,800
Speaker 1: how much of it UM can really be taught. I

1764
01:40:18,840 --> 01:40:22,040
Speaker 1: don't think you learned this stuff that Wharton or it's

1765
01:40:22,040 --> 01:40:24,080
Speaker 1: hard to It's just it's there's a d N a

1766
01:40:24,200 --> 01:40:27,800
Speaker 1: composition to it, and it comes to passion. UM. I

1767
01:40:27,840 --> 01:40:29,759
Speaker 1: know it when I see it. I know somebody who's

1768
01:40:29,920 --> 01:40:34,040
Speaker 1: really into their subject matter. You can't fake that um

1769
01:40:34,160 --> 01:40:39,920
Speaker 1: intensity uh an intense desire to learn and grow. We

1770
01:40:39,920 --> 01:40:44,519
Speaker 1: spoke about this earlier, humility, um arrogance as a killer

1771
01:40:44,680 --> 01:40:47,439
Speaker 1: in this industry. It's what it's what kills performance. You

1772
01:40:47,520 --> 01:40:49,280
Speaker 1: have to be willing to pivot and come at things

1773
01:40:49,280 --> 01:40:53,360
Speaker 1: differently and evolve. And I think, but I do think

1774
01:40:53,360 --> 01:40:56,160
Speaker 1: the art can be made better if if you're somewhere

1775
01:40:56,200 --> 01:40:58,000
Speaker 1: that can make the science better and gives you the

1776
01:40:58,040 --> 01:41:01,960
Speaker 1: tools to refine your process and comment research more effectively,

1777
01:41:02,479 --> 01:41:06,720
Speaker 1: then you can you can have more confidence in terms

1778
01:41:06,760 --> 01:41:10,320
Speaker 1: of relying on things like your non intellectual judgment and

1779
01:41:10,360 --> 01:41:12,640
Speaker 1: your willingness to take risk and be wrong. So I

1780
01:41:12,680 --> 01:41:15,479
Speaker 1: do think they're all those pieces fit together, and it's

1781
01:41:15,479 --> 01:41:18,800
Speaker 1: about being somewhere which can really help you develop the

1782
01:41:18,920 --> 01:41:23,040
Speaker 1: right foundation. Quite quite fascinating. Thank you Alanna for being

1783
01:41:23,080 --> 01:41:25,640
Speaker 1: so generous with your time. We have been speaking with

1784
01:41:25,720 --> 01:41:29,880
Speaker 1: Alana Weinstein of I d W Group. If you enjoy

1785
01:41:29,920 --> 01:41:31,920
Speaker 1: this conversation, we'll be sure to look up an inch

1786
01:41:32,000 --> 01:41:34,599
Speaker 1: or down an inch on Apple iTunes and you could

1787
01:41:34,600 --> 01:41:37,760
Speaker 1: see any of the previous three hundred or so such

1788
01:41:37,800 --> 01:41:41,080
Speaker 1: conversations we've had over the past five years. We love

1789
01:41:41,120 --> 01:41:44,760
Speaker 1: your comments, feedback and suggestions right to us at m

1790
01:41:44,760 --> 01:41:48,320
Speaker 1: IB podcast at Bloomberg dot net. If you're still here,

1791
01:41:49,000 --> 01:41:51,600
Speaker 1: uh this deep into the conversation, then you must have

1792
01:41:51,720 --> 01:41:54,680
Speaker 1: enjoyed it. Give us a lovely review on Apple iTunes.

1793
01:41:55,240 --> 01:41:58,439
Speaker 1: Check out my weekly column on Bloomberg dot com. Sign

1794
01:41:58,520 --> 01:42:02,280
Speaker 1: up from my daily reads at Ritholtz dot com. I

1795
01:42:02,360 --> 01:42:04,519
Speaker 1: would be remiss if I did not thank the crack

1796
01:42:04,600 --> 01:42:08,719
Speaker 1: staff that helps put this conversation together each week. Michael

1797
01:42:08,720 --> 01:42:12,839
Speaker 1: Boyle is my producer. Attica Valbrand is our project manager.

1798
01:42:13,000 --> 01:42:16,879
Speaker 1: Michael Batnick is my head of research. I'm Barry Ritolts.

1799
01:42:17,040 --> 01:42:20,479
Speaker 1: You've been listening to Masters in Business on Bloomberg Radio.