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Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. This is Master's in

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Speaker 1: Business with Barry Ridholds on Bloomberg Radio.

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Speaker 2: This week on the podcast, I have an extra special guest.

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Speaker 2: Mike Wilson has been with Morgan Stanley since nineteen eighty nine,

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Speaker 2: rising up through the ranks of institutional sales, trading, investing,

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Speaker 2: banking to eventually becoming chief investment Officer and chief US

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Speaker 2: equity strategist. He has a very interesting approach to thinking

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Speaker 2: about market valuations and strategies and when to deploy capital,

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Speaker 2: when to go with the crowd, when to lean against

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Speaker 2: the crowd, and has amassed and excellent track record in

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Speaker 2: doing so. I thought this conversation was really quite fascinating,

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Speaker 2: and I think you will also, especially if you're not

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Speaker 2: only interested in equity, but curious as to how to

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Speaker 2: combine various aspects of market functions, valuation, economic cycle, fed

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Speaker 2: actions into one coherent strategy. I thought this was fascinating

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Speaker 2: and I think you will also. With no further ado,

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Speaker 2: my conversation with Morgan Stanley's Mike Wilson. Mike Wilson, Welcome

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Speaker 2: to Bloomberg.

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Speaker 1: Thanks Bary, it's great to be here.

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Speaker 2: It's great to have you. I've been looking forward to this.

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Speaker 2: Let's talk a little bit about your background. You get

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Speaker 2: a BBA from University of Michigan, Go Blue, NBA from

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Speaker 2: Kellogg at Northwestern. Was investing always the career plan.

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Speaker 1: Yeah, you know, it was in some way, shape or form.

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Speaker 3: I mean, you know, my mom was a financial advisor

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Speaker 3: in the early eighties. She was kind of an inspiration.

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Speaker 3: With a single parent family household, she was basically making

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Speaker 3: ends meet, and she, you know, with that time, a

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Speaker 3: woman as a broker was, you know, really an endangered species.

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Speaker 3: It didn't exist at all. So she got me interested

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Speaker 3: looking at stocks at a young age. And of course

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Speaker 3: I got hooked early because probably to this day, my

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Speaker 3: largest percentage winner of all time was the first stock

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Speaker 3: I ever.

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Speaker 1: Picked when I was thirteen years old.

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Speaker 2: What was that stuff?

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Speaker 1: So I was thirteen years.

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Speaker 3: Old in nineteen eighty A boy, I can't imagine. I

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Speaker 3: picked Nike, worked out pretty well and ended up paying

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Speaker 3: for a good chunk of tuition. And of course, once

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Speaker 3: you have a winner like that, you're kind of in.

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Speaker 1: So I went to school.

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Speaker 3: I didn't think I would be necessarily doing what I'm

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Speaker 3: doing today, but I knew that I was going to

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Speaker 3: be interested in financial markets of some kind, and I

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Speaker 3: think I probably ended up in the right place. It

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Speaker 3: took a long time to kind of get to the

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Speaker 3: right role, but but yeah, I mean I've always had

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Speaker 3: an interest in markets.

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Speaker 1: For sure.

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Speaker 2: Do you still have that Nike I don't.

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Speaker 1: Actually I sold it. I finally sold it, all of it,

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Speaker 1: I believe, in the late nineties. So I left a

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Speaker 1: lot on the table. Yeah. Yeah, it was still my

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Speaker 1: biggest winner.

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Speaker 2: But still, right, that's a good run.

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Speaker 1: Yeah, that's good.

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Speaker 2: That was the fat part of the curve with them.

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Speaker 2: So I can't help but notice a Northwestern in Chicago

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Speaker 2: and then you come to New York City. What was

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Speaker 2: that transition like from a quiet Midwestern upbringing to New

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Speaker 2: York City.

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Speaker 1: Yeah, I mean it really was.

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Speaker 3: It kind of a you know, a turbulent sort of

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Speaker 3: emotional thing for me. But I had changed school so

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Speaker 3: many times through my childhood. I lived in Illinois, I

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Speaker 3: lived in Texas, and went to a bunch of different schools,

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Speaker 3: so so like new Adventures was not not you know.

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Speaker 1: A challenge for me. But yeah, the big city was.

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Speaker 1: It was a big change. That was I'm a rural guy.

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Speaker 3: I kind of grew up on a you know, farmtown

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Speaker 3: in Illinois and in Texas which is in Dallas, but

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Speaker 3: not really a farm town, but you know, more rural

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Speaker 3: definitely more Midwestern, southern even And so yeah, New York

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Speaker 3: was eye opening.

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Speaker 2: And New York in the nineteen nineties was like a

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Speaker 2: boomtown party totally. What was that first decade like as

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Speaker 2: a junior level banker at Morgan's down A lot of fun.

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Speaker 1: I had a lot of fun.

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Speaker 3: I mean, you know, you work long hours, but you're

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Speaker 3: kind of burning the candle at both ends.

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Speaker 1: You're you know, it's sort of that's.

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Speaker 2: What your twenties are. Four.

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Speaker 3: Yeah, work hard, play hard, and nothing bad, nothing we

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Speaker 3: shouldn't be doing. And it was great the nineties still

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Speaker 3: to this day. I mean it felt in America was

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Speaker 3: really booming. It wasn't just New York City. I mean

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Speaker 3: it was almost a coming of age for the entire country,

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Speaker 3: as you know. I mean, the late nineties was sort

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Speaker 3: of you could say peak USA in many ways. We

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Speaker 3: can measure that in a lot of different ways, and

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Speaker 3: New York was, you know, a big part of that.

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Speaker 1: So it was a lot of fun. It was exciting.

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Speaker 2: What were your experience is like as a junior I

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Speaker 2: banker and.

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Speaker 1: Not so fun.

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Speaker 3: I mean, you know you're learning, but it's you know,

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Speaker 3: it's an entry level job and it's not glamorous. You're

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Speaker 3: punching the clock pretty heavy hours.

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Speaker 1: But boy, you're.

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Speaker 3: Surrounded by some really smart people and you're working on

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Speaker 3: things that are are forcing you to grow intellectually. It

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Speaker 3: really challenges your resolve. Do you want to be in

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Speaker 3: this business?

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Speaker 1: You know?

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Speaker 3: Do you want to because it's constant as you know,

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Speaker 3: I mean being in the in the investment business, being

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Speaker 3: in the financial services business, it's it's a constant you know, evolution.

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Speaker 3: You know, you have to improve your skills. You have

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Speaker 3: to eve all of your skills, and if you don't,

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Speaker 3: you kind of die.

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Speaker 2: So I had a John Mack on the show last

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Speaker 2: year and one of the things that really struck me

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Speaker 2: was his respect and reverence for the culture at Morgan Stanley.

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Speaker 2: Tell a little bit about your your experiences dealing with

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Speaker 2: Morgan Stanley culture.

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Speaker 3: Yeah, I mean for me, I mean it was perfect

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Speaker 3: because I you know, I grew up very independent. You know,

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Speaker 3: my mom put that on me early, and so Morgan

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Speaker 3: Stanley's kind of the same way. It's your career to manage,

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Speaker 3: try to permitted support internally, to make sure that you

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Speaker 3: have what you need, but to generally encourage you to

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Speaker 3: explore your limits. And so that to me has always

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Speaker 3: been a very endearing part of the Morgan Stanley culture.

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Speaker 3: It served me well, it's challenged me, it's made me

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Speaker 3: kind of better. It's forced me to grow and do

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Speaker 3: different jobs. That's, to me, is the biggest takeaway.

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Speaker 2: And thirty five years one firm, your whole career, that's

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Speaker 2: a rarity in the modern era. What's kept you there

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Speaker 2: your entire career.

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Speaker 3: It's just what I said, I mean, they've given me

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Speaker 3: the opportunity to do a lot of different things. I

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Speaker 3: don't think I could have spent thirty five years at

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Speaker 3: any firm doing the same job function.

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Speaker 1: It's just I need a variety.

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Speaker 3: And so I would probably say that I've had six

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Speaker 3: or seven careers over that thirty five year period, and that's.

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Speaker 1: What's kept me interested.

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Speaker 3: It's been exciting, it's been you know, it's been a

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Speaker 3: thrill of a lifetime to be able to do these

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Speaker 3: different types of careers.

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Speaker 2: So we were chatting earlier about our holding periods getting

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Speaker 2: longer as we get older. You and I both started

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Speaker 2: as traders. What was that experience like again, nineteen nineties,

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Speaker 2: big institutional activity at Morgan Stanley. What was your trading

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Speaker 2: career like?

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Speaker 3: Yeah, that came later, So I was really investment banking,

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Speaker 3: and then I went into really more of a sales

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Speaker 3: role in the nineties, and then I became more of

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Speaker 3: a prop trader in the two thousand, sort of post

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Speaker 3: the tech bubble, and I was involved in trading tech

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Speaker 3: stocks proprietarily, you know, helping the desk make money before

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Speaker 3: you know, before that became abolished, you know, POSTGC, right,

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Speaker 3: and and that was another incredible growing experience. I mean,

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Speaker 3: as you know, you know, trading forces you to really

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Speaker 3: look inward. You know, you're basically competing against yourself, right,

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Speaker 3: You're your own worst enemy, You're your own best friend.

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Speaker 1: You know.

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Speaker 3: It's a love hate thing. The P and L is everything.

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Speaker 3: And you know, I discovered I didn't really like that,

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Speaker 3: to be honest, I don't.

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Speaker 1: I didn't. I didn't enjoy you know, being married to

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Speaker 1: a screen every day. That to me is is not investing.

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Speaker 1: That's trading. And I'm not a trader.

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Speaker 3: I mean, I understand trading I'm more of somebody who

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Speaker 3: is intermediate term. I'm a cycles person as opposed to

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Speaker 3: a trading person.

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Speaker 2: So the question that comes to my mind because of

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Speaker 2: my experience doing something very similar is I find that

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Speaker 2: trading has influenced how I look at investing. What has

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Speaker 2: your experience been now that your time horizon is much longer,

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Speaker 2: how did your experience as a trader in the two

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Speaker 2: thousands impact how you see the world?

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Speaker 1: Well, it absolutely helps.

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Speaker 3: I mean, you know, because it forces you to be

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Speaker 3: honest about you know, your positioning, and it forces you

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Speaker 3: to revisit like why am I involved in this call

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Speaker 3: or position?

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Speaker 1: And does it still make sense?

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Speaker 3: And that trader instinct forces you to be honest with

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Speaker 3: yourself where I think if you hadn't done I hadn't

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Speaker 3: done that, I probably wouldn't be, as you know, open

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Speaker 3: minded to things changing. And oh yeah, I could be wrong.

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Speaker 3: You know, it's funny to be a lot of people

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Speaker 3: are afraid to admit the wrong. I'm happy to admit

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Speaker 3: that I'm wrong, because that's how a trader closes out.

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Speaker 1: A position that's exactly right.

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Speaker 3: I mean, like you guys, say I'm wrong, and then okay,

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Speaker 3: I've got to do something different, and I think, you know,

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Speaker 3: my worst mistakes have been when I've been unable to

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Speaker 3: admit that I'm wrong, and so the trading experience helped

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Speaker 3: me to kind of get past that.

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Speaker 2: The line I recall my head trader drumming into my

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Speaker 2: head was it's okay to be wrong, it's unacceptable to

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Speaker 2: stay wrong.

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Speaker 1: Correct.

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Speaker 2: So you hold two roles, and if someone asked me

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Speaker 2: what are the two best gigs in all of Morgan Stanley,

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Speaker 2: my answers would be, I don't know, either chief US

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Speaker 2: Equity Strategist or Chief Investment Officer. You have both of

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Speaker 2: those titles. How does that work? How do you handle

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Speaker 2: both of those?

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Speaker 1: Well?

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Speaker 3: I mean, you know that's also evolved over time. I

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Speaker 3: mean they're very different constituents. So I would say the

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Speaker 3: challenge of having those roles is that our institutional clients

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Speaker 3: are much shorter term, and you know, Morgan Stanley has

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Speaker 3: all types of different clients. We have institutional clients, we

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Speaker 3: have retail clients, we have you know, pension funds, we

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Speaker 3: have endowments, and so it's sort of managing that all

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Speaker 3: of those different constituents with communication. So that's the challenge.

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Speaker 3: I wouldn't say I like one better than the other.

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Speaker 3: But what I would say is I do find more

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Speaker 3: personal satisfaction in helping the asset owner clients who really

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Speaker 3: need the help. Okay, you know, let's be honest. Most

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Speaker 3: of the institutional clients, you know, they're pretty sophisticated and

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Speaker 3: they're looking for an edge. You know, they value our research,

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Speaker 3: they say, they value other people's research, they value the conversations,

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Speaker 3: but they don't necessarily need your help as much as

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Speaker 3: say a retail client or somebody who is really entrusting

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Speaker 3: their entire network to the firm.

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Speaker 1: So it's just different, you know.

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Speaker 3: And what I find challenging and satisfying is that every

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Speaker 3: meeting I do, I almost got to put on a

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Speaker 3: different hat. You know, I go into a meeting and

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Speaker 3: I'm talking to somebody who really doesn't care at all

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Speaker 3: about next week, and they didn't even care about this year.

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Speaker 3: They're thinking about five, ten years down the road. It's

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Speaker 3: a completely different conversation. In fact, we end up talking

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Speaker 3: about their business, how they made their wealth. That's really

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Speaker 3: fascinating to me, Whereas if I'm going into a typical

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Speaker 3: institutional meeting, it's almost like, you know, wash Rent's repeat. Okay,

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Speaker 3: here's what's going on right now, here's how we're thinking

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Speaker 3: about it, which is valuable, but it's a totally different meeting.

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Speaker 2: Huh. Really interesting. So I'm looking at all the various

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Speaker 2: roles you've had at Morgan Stanley over the past three

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Speaker 2: and a half decades, investment banker, trader, salesman, strategist, product manager,

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Speaker 2: and of course chief investment officer. What's your favorite role

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Speaker 2: and if you could create just one sort of amalgam

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Speaker 2: of it, what would that look like.

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Speaker 1: Yeah, that's an interesting question.

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Speaker 3: I mean I would say, you know, I had a

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Speaker 3: lot of fun working on the trading desk.

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Speaker 1: I was younger.

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Speaker 3: We had a group of people kind of the same age,

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Speaker 3: and you're rowing the boat. It's a tight team of

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Speaker 3: fifteen people or so. And that role was essentially I

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Speaker 3: sort of built what we call institutional sector sales, sort

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Speaker 3: of a desk analyst role. We were the first firm

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Speaker 3: to do that. I was a TMT specialist and then

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Speaker 3: I built out that effort over the course of I

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Speaker 3: don't know, five six years for every industry, and it

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Speaker 3: was a it was kind of like your team, and

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Speaker 3: we built it from scratch. Now, every firm has those

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Speaker 3: has that role. So we were the original. We're the

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Speaker 3: og on that and it was a it was a

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Speaker 3: very cohesive group of people. We were analysts, were also traders.

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Speaker 3: We were dealing with clients from a sales standpoint, we

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Speaker 3: were making calls, we were working with our research department,

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Speaker 3: and we'd even work with capital markets, you know, to

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Speaker 3: help them price or think about deals in our sector.

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Speaker 3: So it was a very comprehensive role but also specialized.

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Speaker 3: That to me was had the most fun. But I

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Speaker 3: did it for almost ten years, you know, so I

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Speaker 3: kind of hit my expiration date, you know what I mean,

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Speaker 3: And so I wouln't want to be doing that now

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Speaker 3: because I did it. And that's why I always think

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Speaker 3: about my life, which is the next thing I do

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Speaker 3: is going to be something totally different. I don't even

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Speaker 3: know what it's going to be yet, but I mean,

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Speaker 3: I'm not retiring. I'll be working till you know, God

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Speaker 3: helped me out a little long life, and I'll be

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Speaker 3: doing this for a long time.

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Speaker 2: Huh. Really interesting? All right, So you cover a lot

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Speaker 2: of really one of my favorite topics, the five things

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Speaker 2: that are within your purview US equity markets and trends,

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Speaker 2: economic indicators, how political events impact markets, corporate earnings, and

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Speaker 2: then federal reserve policies. That's the big five in my book.

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Speaker 2: I love that area. There's always things to talk about.

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Speaker 2: We were chatting earlier and I said, I got a

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Speaker 2: lot of questions and emails from clients. Those are the

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Speaker 2: five areas that ninety five percent of the questions that

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Speaker 2: come in cover. How did you narrow it down to

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Speaker 2: these five? What do you like talking about most when

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Speaker 2: you're having conversations with clients.

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Speaker 3: Well, to me, it's all just about the riddle. You know,

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Speaker 3: you're just trying to solve a giant puzzle. I mean,

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Speaker 3: that's that's what makes markets so exciting to me. It's

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Speaker 3: the marrying quite frankly, of macro and micro. So I

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Speaker 3: have a deep background in micro mailing the TMT space,

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Speaker 3: and then I developed this macro affinity starting in two

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Speaker 3: thousand and really twenty nine to ten in that role,

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Speaker 3: and so marrying the two to me is the advantage,

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Speaker 3: you know. The way we kind of laid this out,

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Speaker 3: and we originally took over coverage of US equity strategy,

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Speaker 3: we said there's four pillars to our strategy. First, of all,

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Speaker 3: we're cycle analysts, not to be confused with psychoanalyst, but

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Speaker 3: it's kind of related. Understanding cycles is critical.

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Speaker 2: Are we talking market cycles, economic cycles? Cycles?

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Speaker 3: Every but generally starts with the economic cycle. Where are

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Speaker 3: you in the economic cycle? And then they're the business

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Speaker 3: cycle effectively, and then understanding that there are also market

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Speaker 3: cycles and marrying those two is also a big part

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Speaker 3: of our framework. So you have to have some sort

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Speaker 3: of fundamental framework. Mine has always been based on rate

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Speaker 3: of change analysis. So to me, when people look at data,

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Speaker 3: a lot of times, I don't think they look at

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Speaker 3: data the right way. Now I feel like we educated

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Speaker 3: the street in many ways going back fifteen to twenty

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Speaker 3: years about this rate of change analysis, going back to

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Speaker 3: the early two thousands, and now people are kind of

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Speaker 3: onto it. I'm not saying the only person thinking about

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Speaker 3: rate to change, but it has become a much bigger feature.

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Speaker 3: So the rate of change matters way more than the

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Speaker 3: level in every indicator you're looking at.

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Speaker 2: In other words, oh, were you accelerating or decelerating rather

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Speaker 2: than specific points or exactly.

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Speaker 3: And that can apply to macrodata, and it can apply

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Speaker 3: to microdata, and that should tell you whether or not

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Speaker 3: an asset is probably going to be appreciating or deep creciating.

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Speaker 3: So that's one part of our framework. The second part

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Speaker 3: of our framework is valuation fundamental work, you know, earnings analysis,

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Speaker 3: predicting earnings, whereas a great valuation based on kind of

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Speaker 3: where we are in the cycle. And then of course,

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Speaker 3: policy is a huge impact on how that cycle can

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Speaker 3: be effected.

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Speaker 2: When we say policy, do we mean fed policy, do

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Speaker 2: we mean fiscal policy?

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Speaker 1: We mean everything?

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Speaker 3: Yeah, all types of policy, but mainly fiscal and monetary.

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Speaker 3: Also geopolitical events, and that's probably the least important for

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Speaker 3: us because they're so hard to predict, right, But definitely

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Speaker 3: fiscal and monetary policy. And I think that that's probably

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Speaker 3: taken on a much bigger role in the last twenty

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Speaker 3: years than it was prior to that twenty year period.

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Speaker 3: That policy now has a outsized impact on markets and

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Speaker 3: it did twenty years ago.

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Speaker 2: Huh. Really interesting. Not too long ago you wrote this

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Speaker 2: is a humbling business. That's an attitude I completely share.

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Speaker 2: But I don't see a lot of people in our

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Speaker 2: industry discussing that. Tell us a little bit about what

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Speaker 2: makes this such a humbling business.

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Speaker 3: Well, first of all, it's extremely competitive, probably the smartest,

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Speaker 3: most motivated people in the world that you're competing against.

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Speaker 3: And it's and you're also competing against yourself to try

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Speaker 3: and figure out what's going to happen. So that's that's

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Speaker 3: number one. So your probability of being correct okay is low, right,

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Speaker 3: I mean, like if you're fifty to fifty or sixty

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Speaker 3: forty on your ideas, you're really good.

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Speaker 1: Okay.

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Speaker 3: Think about overachievers, you know, when you and we recruit,

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Speaker 3: you know, we talk to people young people always say

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Speaker 3: you probably haven't even ever had a B on your

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Speaker 3: report card. They can't imagine getting a B. Well, get

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Speaker 3: ready to have a bunch of f's, you know. And

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Speaker 3: that's humbling is to say, hey, you know, like this

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Speaker 3: is difficult and you're going to be wrong a lot.

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Speaker 3: And really the humility is important because you know, failure

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Speaker 3: is all about how.

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Speaker 1: You deal with it.

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Speaker 3: You know, you're all going to be wrong, okay at

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Speaker 3: some point, and how do you deal with that failure?

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Speaker 3: Do you do you double down on your mistakes? Do

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Speaker 3: you do you deny that you made a mistake? Do

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Speaker 3: you learn from your mistake? And to me, that's that

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Speaker 3: really encompasses why I like it so much because you're

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Speaker 3: forced to grow.

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Speaker 1: You're always forced to be growing as a person.

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Speaker 3: As a colleague, as a client service person, and you're

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Speaker 3: always you're constantly learning and relearning.

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Speaker 2: So let's talk about some of that learning. I've tracked

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Speaker 2: your career over the years, and I don't know, a

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Speaker 2: decade or two ago, you are more inclined to make

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Speaker 2: bigger boulder predictions. Now I kind of see you as

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Speaker 2: doing more nuanced strategies. You emphasize relative value you're looking for,

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Speaker 2: where as an edge I can share with clients versus

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Speaker 2: let's see if we can, you know, get the big

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Speaker 2: one right. Why has that philosophy evolved over time and

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Speaker 2: how do you implement it?

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Speaker 3: Yeah, I would say I would say it's changed completely.

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Speaker 3: I think that there are times in the markets where

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Speaker 3: you know, the big pitch is easier to go after.

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Speaker 3: I still I'm a big elephant hunter. I mean, I

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Speaker 3: still view myself as I tend to be more contrarian

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Speaker 3: because I think that's where you make the big money.

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Speaker 3: All my good calls have been going against the grain,

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Speaker 3: whether it's.

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Speaker 1: Bullish or bearish.

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Speaker 3: I would say, you know, we get tagged with being

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Speaker 3: you know, more bearish and bullish. I would say, we're

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Speaker 3: just more balanced, you know. But when we make big

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Speaker 3: calls in the past, they tend to be at important

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Speaker 3: turning points, and of course we don't get all those

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Speaker 3: right either, but I still enjoy that we Lately we

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Speaker 3: have not been doing as much of that because going

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Speaker 3: back to what I said a minute ago, policy has

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Speaker 3: been so important in the last really since COVID that

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Speaker 3: it has kind of screwed up some of our indicators

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Speaker 3: in a way where.

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Speaker 1: It hasn't been as easy to.

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Speaker 3: Have that conviction level that you get run over by policy,

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Speaker 3: both on the upside and the downside. And so what

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Speaker 3: we feel like we have an edge in is calling

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Speaker 3: those relative value trades, and we've had great success in

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Speaker 3: that in the last twelve to eighteen months, even though

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Speaker 3: perhaps maybe our market call in the last twelve months

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Speaker 3: has been not as good.

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Speaker 2: Well, let's give you some credit where credit is due.

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Speaker 2: Earlier this year you had said, hey, we're very overdue

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Speaker 2: for a ten percent correction in the market, and pretty much,

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Speaker 2: you know, July and August, that's about what we've seen

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Speaker 2: in twenty twenty four. Do you find it easier to

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Speaker 2: conceptualize market activity when things become more volatile, How do

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Speaker 2: market dis locations affect your ability to read the tea leaves?

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Speaker 3: Well, I mean, market dislocation always creates sort of opportunity.

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Speaker 3: You know, this year has been very it's been very

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Speaker 3: calm from a volatility standpoint, and that's somewhat boring, right,

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Speaker 3: So we felt like in early July that you know,

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Speaker 3: that had gotten kind of extreme. There was stuff that was,

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Speaker 3: you know, peering its way out, and the risk reward

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Speaker 3: was not as good. Now ten percent corrections are very common,

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Speaker 3: you know, They're not like, that's not really that big

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Speaker 3: of a bold call. That's just saying, hey, things are extended.

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Speaker 3: It worked out. Timing was actually quite good. Okay, great.

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Speaker 3: What I would say is that, you know, the ability

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Speaker 3: to read the tea leaves, I would view myself as

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Speaker 3: very good at that. And that's not a humble statement,

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Speaker 3: but I think it's an accurate statement. Like that's we've

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Speaker 3: built our career being able to see around the corner,

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Speaker 3: maybe a little bit earlier than some people because we

431
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Speaker 3: look at the market so closely. The market tells you

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Speaker 3: kind of what's about to happen. Once again, you can't

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Speaker 3: always be accurate. But I would say a lot of

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Speaker 3: our clients rely on us sometimes to help them see

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Speaker 3: around the corner. And they know that we're not afraid

436
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Speaker 3: to help them.

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Speaker 1: Look around the corner.

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Speaker 3: Okay, whether it's bullish or bearish, that doesn't really matter.

439
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Speaker 3: It's more of like, what's not priced right now? What

440
00:20:39,280 --> 00:20:42,160
Speaker 3: is priced right now is a soft landing, and that

441
00:20:42,320 --> 00:20:45,080
Speaker 3: is the base case scenario for most people. So you

442
00:20:45,080 --> 00:20:47,640
Speaker 3: have to ask yourself, Okay, well, what happens if that

443
00:20:48,040 --> 00:20:51,840
Speaker 3: soft landing narrative is challenged? Doesn't mean it's a hard landing,

444
00:20:51,920 --> 00:20:54,680
Speaker 3: just means it's challenged. Well, it means evaluations are probably

445
00:20:54,920 --> 00:20:58,080
Speaker 3: too high, and that could set off a chain reaction.

446
00:20:58,200 --> 00:21:00,280
Speaker 3: That that's why you get a correction that would kind

447
00:21:00,280 --> 00:21:03,879
Speaker 3: of the rationale back in early July. Those types of

448
00:21:03,920 --> 00:21:06,919
Speaker 3: calls don't come around every week, right, Those types of

449
00:21:06,960 --> 00:21:10,000
Speaker 3: calls tend to happen when things are extreme levels. You

450
00:21:10,040 --> 00:21:13,120
Speaker 3: see the risk reward being unbalanced, and you take a swing.

451
00:21:13,840 --> 00:21:16,320
Speaker 2: Well, let's talk about a swing you took. You got

452
00:21:16,320 --> 00:21:20,400
Speaker 2: twenty twenty two, very right. You said things were expensive

453
00:21:20,920 --> 00:21:24,440
Speaker 2: and not prepared for a fed hiking cycle, and lo

454
00:21:24,560 --> 00:21:28,119
Speaker 2: and behold, not only were stocks down twenty plus percent,

455
00:21:28,280 --> 00:21:32,240
Speaker 2: bonds were down fifteen percent. It was a pretty awful year.

456
00:21:32,840 --> 00:21:36,560
Speaker 2: You got the macro picture right, What led you to

457
00:21:36,640 --> 00:21:40,080
Speaker 2: identify that correctly? And what made the two years that

458
00:21:40,160 --> 00:21:42,440
Speaker 2: followed twenty twenty two so so challenging?

459
00:21:42,840 --> 00:21:44,520
Speaker 3: Yeah, I mean, I think what set us up was

460
00:21:44,560 --> 00:21:47,399
Speaker 3: we you know, we got the low right in twenty

461
00:21:47,480 --> 00:21:50,199
Speaker 3: twenty for the right reasons. We can't came into the

462
00:21:50,240 --> 00:21:53,280
Speaker 3: pandemic more embarrassed than most because we thought it was

463
00:21:53,320 --> 00:21:55,199
Speaker 3: late cycle. Then we got the pandemic and it was

464
00:21:55,480 --> 00:21:58,880
Speaker 3: to us a really fat pitch. So we were very

465
00:21:58,920 --> 00:22:02,000
Speaker 3: aggressive in twenty twenty in twenty twenty one, and you know,

466
00:22:02,000 --> 00:22:04,440
Speaker 3: we don't get necessarily a lot of credit, but our

467
00:22:04,440 --> 00:22:08,000
Speaker 3: clients give us credit. We caught all that upside and

468
00:22:08,080 --> 00:22:10,200
Speaker 3: so part of that call was just like, look, we've

469
00:22:10,200 --> 00:22:13,760
Speaker 3: had this massive move. It's mainly because of policy. Okay,

470
00:22:13,840 --> 00:22:17,520
Speaker 3: we've overshot, We've had we've had over consumption from the pandemic,

471
00:22:17,600 --> 00:22:19,280
Speaker 3: and all the benefits that were sent out to people

472
00:22:19,320 --> 00:22:21,879
Speaker 3: evaluations are now out of touch with the reality. The

473
00:22:21,880 --> 00:22:24,080
Speaker 3: fens you have to raise rates. We kind of use

474
00:22:24,160 --> 00:22:26,720
Speaker 3: this interesting narrative called fire and ice. Right, the inflation

475
00:22:26,760 --> 00:22:29,040
Speaker 3: will lead to, you know, basically slow down because I

476
00:22:29,080 --> 00:22:31,440
Speaker 3: have to raise rates, and that all narrative just really

477
00:22:31,440 --> 00:22:34,159
Speaker 3: worked nicely. Having been so right in twenty twenty and

478
00:22:34,160 --> 00:22:36,640
Speaker 3: twenty twenty one. On the upside, the call to kind

479
00:22:36,640 --> 00:22:39,920
Speaker 3: of fade into twenty one was actually pretty easy. Where

480
00:22:39,960 --> 00:22:43,280
Speaker 3: we where we didn't get right was that we didn't

481
00:22:43,280 --> 00:22:44,840
Speaker 3: think they'd raise five hundred basis points.

482
00:22:44,840 --> 00:22:46,960
Speaker 1: So we in some ways in eighteen months.

483
00:22:46,720 --> 00:22:48,959
Speaker 3: No, I mean so like that that actually made us

484
00:22:49,000 --> 00:22:52,440
Speaker 3: feel then, oh my goodness, they probably overdid it and

485
00:22:52,560 --> 00:22:54,560
Speaker 3: that's going to lead to probably a hard landing in

486
00:22:54,600 --> 00:22:55,400
Speaker 3: twenty twenty three.

487
00:22:55,840 --> 00:22:57,480
Speaker 1: But we weren't alone in that view, by the.

488
00:22:57,480 --> 00:23:01,000
Speaker 2: Way, So let's talk about this that because Man did

489
00:23:01,480 --> 00:23:05,480
Speaker 2: so many macro economists and strategists, they might have gotten

490
00:23:05,480 --> 00:23:09,040
Speaker 2: twenty two right, but twenty three and twenty four was perplexing,

491
00:23:09,200 --> 00:23:13,920
Speaker 2: and we continued to hear recession, recession, recession throughout I'm

492
00:23:13,920 --> 00:23:17,440
Speaker 2: not saying you, I'm saying the street throughout twenty three,

493
00:23:17,560 --> 00:23:20,840
Speaker 2: the first half of twenty four. As of August of

494
00:23:20,840 --> 00:23:24,840
Speaker 2: twenty twenty four, there are no signs of a recession. Yeah,

495
00:23:24,840 --> 00:23:27,320
Speaker 2: the yield curve is still inverted, it's less inverted than

496
00:23:27,359 --> 00:23:31,000
Speaker 2: it was, and the Sam rule arguably ticked off, although

497
00:23:31,040 --> 00:23:34,440
Speaker 2: Claudia Sam says it may not be indicating a recession now.

498
00:23:34,520 --> 00:23:38,840
Speaker 2: But how did so many of the traditional economists types

499
00:23:39,280 --> 00:23:40,600
Speaker 2: get this recession wrong?

500
00:23:40,960 --> 00:23:43,160
Speaker 3: Well, I mean a lot of the traditional indicators were

501
00:23:43,520 --> 00:23:48,560
Speaker 3: a flashed wrong sign. I mean historically that probably would

502
00:23:48,600 --> 00:23:52,080
Speaker 3: have played out. And my personal view is that we

503
00:23:52,160 --> 00:23:56,440
Speaker 3: had incredible policy support last year, mostly on the fiscal side,

504
00:23:56,880 --> 00:24:00,320
Speaker 3: which essentially allowed the cycle to extend itself. I mean,

505
00:24:00,320 --> 00:24:02,720
Speaker 3: if you take out the government spending, you probably are

506
00:24:02,760 --> 00:24:05,280
Speaker 3: in a recession in a private economy. And look, many

507
00:24:05,320 --> 00:24:08,679
Speaker 3: people have highlighted this too, ourselves included. We have been

508
00:24:08,720 --> 00:24:11,480
Speaker 3: in a recession in many sectors, kind of a rolling recession,

509
00:24:11,800 --> 00:24:13,760
Speaker 3: a term that we sort of invented in twenty eighteen,

510
00:24:13,800 --> 00:24:15,919
Speaker 3: which I regret now because now people kind of use

511
00:24:15,960 --> 00:24:18,800
Speaker 3: it in a way which I think is misused. But anyways,

512
00:24:18,840 --> 00:24:20,960
Speaker 3: we can leave that where it is, and I guess

513
00:24:20,960 --> 00:24:22,560
Speaker 3: this is where I come out in the story, which is,

514
00:24:22,840 --> 00:24:25,800
Speaker 3: I don't think that they've extinguished the risk of a

515
00:24:25,800 --> 00:24:28,520
Speaker 3: hard landing, okay, because now we're going into a period

516
00:24:28,520 --> 00:24:30,439
Speaker 3: where probably fiscal support is going to have to wane,

517
00:24:30,840 --> 00:24:32,880
Speaker 3: and we have election obviously that could affect that too,

518
00:24:33,359 --> 00:24:36,440
Speaker 3: and also a policy now from the Fed maybe late

519
00:24:36,560 --> 00:24:38,600
Speaker 3: and forthcoming. We don't know the answer yet, so I

520
00:24:38,600 --> 00:24:40,320
Speaker 3: think it's almost like a mere image of last year.

521
00:24:40,359 --> 00:24:43,200
Speaker 3: Everybody was so certain it was going to be a recession,

522
00:24:43,440 --> 00:24:46,439
Speaker 3: and of course the majority was wrong. Now everybody's so

523
00:24:46,480 --> 00:24:48,520
Speaker 3: certain it's going to be a soft landing. Who's to

524
00:24:48,560 --> 00:24:50,200
Speaker 3: say that they're not going to be wrong. You just

525
00:24:50,280 --> 00:24:53,000
Speaker 3: don't know. So I think that's where I come out

526
00:24:53,000 --> 00:24:54,800
Speaker 3: on the market. Overall, at the index level, we're not

527
00:24:54,800 --> 00:24:57,600
Speaker 3: as bullish as others because we don't think the multiples

528
00:24:57,960 --> 00:25:01,440
Speaker 3: reflect that there's still this risk that's probably twenty thirty

529
00:25:01,480 --> 00:25:03,959
Speaker 3: percent at least, that you could end up in hard

530
00:25:04,040 --> 00:25:05,600
Speaker 3: landing at some point in the next twelve months, and

531
00:25:05,640 --> 00:25:06,879
Speaker 3: that's definitely in that price.

532
00:25:07,040 --> 00:25:09,879
Speaker 2: So you bring something up that I'm fascinated by, and

533
00:25:10,280 --> 00:25:14,560
Speaker 2: it plays right to the economists getting the recession wrong

534
00:25:14,600 --> 00:25:17,800
Speaker 2: in twenty three and twenty four, and that's your focus

535
00:25:17,880 --> 00:25:22,400
Speaker 2: on government, both fiscal and monetary support for the economy.

536
00:25:23,000 --> 00:25:26,440
Speaker 2: When we have a year like twenty twenty, like the pandemic,

537
00:25:26,960 --> 00:25:29,600
Speaker 2: when the Cares Act and there were three CARES Act,

538
00:25:29,640 --> 00:25:33,040
Speaker 2: But the first Cares Act was something like ten percent

539
00:25:33,080 --> 00:25:35,440
Speaker 2: of GDP. We hadn't seen anything like that since World

540
00:25:35,480 --> 00:25:38,439
Speaker 2: War Two. Shouldn't that force people to kind of rethink

541
00:25:38,480 --> 00:25:43,240
Speaker 2: their models when suddenly a few trillion dollars unexpectedly is

542
00:25:43,280 --> 00:25:46,720
Speaker 2: going to pour into the economy. I remember Jeremy Siegel

543
00:25:46,800 --> 00:25:49,800
Speaker 2: jumping up and down, professor at Wharton, saying this is

544
00:25:49,840 --> 00:25:52,640
Speaker 2: going to cause inflation, and nobody paid him any attention

545
00:25:53,119 --> 00:25:57,800
Speaker 2: back in twenty twenty. Shouldn't that government support that you're

546
00:25:57,840 --> 00:26:01,479
Speaker 2: referring to force us to kind of rethink our models

547
00:26:01,480 --> 00:26:01,960
Speaker 2: a little bit.

548
00:26:02,200 --> 00:26:04,040
Speaker 3: And we did, and that's why we got twenty twenty

549
00:26:04,119 --> 00:26:06,800
Speaker 3: twenty one so right, because we agreed with professional single.

550
00:26:06,840 --> 00:26:09,040
Speaker 3: In April of twenty twenty, we said look out for

551
00:26:09,080 --> 00:26:10,920
Speaker 3: the inflation, and people thought we were nuts.

552
00:26:11,440 --> 00:26:11,560
Speaker 1: Right.

553
00:26:11,680 --> 00:26:13,680
Speaker 2: The pushback was pretty fierce there, fierce.

554
00:26:13,720 --> 00:26:15,760
Speaker 3: We got more pushback, by the way, being bullish in

555
00:26:15,840 --> 00:26:18,800
Speaker 3: March and April of twenty twenty than being bearish in

556
00:26:18,800 --> 00:26:21,560
Speaker 3: twenty two because people say we were being insensitive to like,

557
00:26:21,640 --> 00:26:23,800
Speaker 3: you know, the disease, and we're not being insensitive. We're

558
00:26:23,800 --> 00:26:26,280
Speaker 3: just trying to do our job. And anyways, the point

559
00:26:26,320 --> 00:26:29,680
Speaker 3: is that that boom bust we compared exactly to World

560
00:26:29,680 --> 00:26:32,480
Speaker 3: War Two. We wrote extensively about this. The way we

561
00:26:32,520 --> 00:26:34,879
Speaker 3: adjusted it was we said, okay, these cycles now we're

562
00:26:34,920 --> 00:26:39,080
Speaker 3: going to be hotter but shorter. And that's why in

563
00:26:39,119 --> 00:26:41,720
Speaker 3: twenty twenty one into twenty one we said, okay, this

564
00:26:41,800 --> 00:26:42,760
Speaker 3: is the peak of the cycle.

565
00:26:42,920 --> 00:26:44,679
Speaker 1: Rate to change, which by the way, turned out to

566
00:26:44,680 --> 00:26:46,920
Speaker 1: be really accurate. We got people out of all the

567
00:26:46,960 --> 00:26:49,840
Speaker 1: high flying meme stocks and all that, like in March

568
00:26:49,840 --> 00:26:52,119
Speaker 1: of twenty one, because we said, this is silly, this

569
00:26:52,200 --> 00:26:55,440
Speaker 1: is all just COVID over consumption. It's going to be payback.

570
00:26:55,840 --> 00:26:56,960
Speaker 1: So we did adjust all that.

571
00:26:57,160 --> 00:26:59,959
Speaker 3: But once again, barrious, you can't get everything right, you know,

572
00:27:00,040 --> 00:27:03,000
Speaker 3: so we feel like that narrative is still right on track.

573
00:27:03,400 --> 00:27:06,280
Speaker 3: We didn't trade it particularly well. Okay, Now, what we

574
00:27:06,280 --> 00:27:09,520
Speaker 3: did trade well was our defensiveness and our quality bid

575
00:27:09,760 --> 00:27:12,879
Speaker 3: staying away from small caps. We got out of the memes,

576
00:27:12,920 --> 00:27:15,520
Speaker 3: you know, the high flying multiple stocks. People try to

577
00:27:15,560 --> 00:27:17,960
Speaker 3: keep buying those and just got carried out. And what

578
00:27:18,040 --> 00:27:20,920
Speaker 3: I find interesting is, you know, if you're if you're

579
00:27:20,920 --> 00:27:23,960
Speaker 3: burishing wrong, you know, you get you get carried out. Okay,

580
00:27:24,000 --> 00:27:26,600
Speaker 3: and people just hate that. But The reality is is

581
00:27:26,640 --> 00:27:30,040
Speaker 3: that if you're bullish and wrong, you destroy way more

582
00:27:30,080 --> 00:27:33,240
Speaker 3: capital if you're telling people to buy these crazy things

583
00:27:33,240 --> 00:27:35,840
Speaker 3: that have no valuation support. So it's it's just kind

584
00:27:35,840 --> 00:27:37,560
Speaker 3: of ironic, and I'll just throw this out as a

585
00:27:37,560 --> 00:27:39,719
Speaker 3: bit of an advertisement. But like, we run a portfolio

586
00:27:39,800 --> 00:27:42,920
Speaker 3: of ten stocks, that concentrated portfolio ten stocks, ten stocks,

587
00:27:43,200 --> 00:27:45,000
Speaker 3: and so the last six and a half years, that

588
00:27:45,080 --> 00:27:48,640
Speaker 3: portfolio has outperformed the S and P by almost eight

589
00:27:48,720 --> 00:27:52,239
Speaker 3: hundred basis points annually. Wow, annually, that's huge with very

590
00:27:52,280 --> 00:27:54,320
Speaker 3: little draw downs. And we've and we've been underweight to

591
00:27:54,320 --> 00:27:55,720
Speaker 3: the Max seven by like ninety percent.

592
00:27:55,880 --> 00:27:58,520
Speaker 2: So no kidding, I was just immediately assumed it was

593
00:27:58,640 --> 00:28:00,359
Speaker 2: it was all mag seven Max.

594
00:28:00,240 --> 00:28:02,399
Speaker 1: Haven' killed you in twenty two, Right twenty two, that

595
00:28:02,440 --> 00:28:05,200
Speaker 1: portfolio was actually up and it's long only.

596
00:28:05,359 --> 00:28:08,399
Speaker 3: So now what I'm saying is that calling the S

597
00:28:08,440 --> 00:28:12,440
Speaker 3: and P five hundred is not really that important to

598
00:28:12,520 --> 00:28:13,159
Speaker 3: making money.

599
00:28:13,400 --> 00:28:13,520
Speaker 2: Right.

600
00:28:13,680 --> 00:28:17,480
Speaker 3: Making money is, you know, pivoting into things that maybe

601
00:28:17,520 --> 00:28:20,600
Speaker 3: are loved, getting out of things that are overloved at

602
00:28:20,600 --> 00:28:22,680
Speaker 3: the right time, and not overstaying your welcome. And that's

603
00:28:22,720 --> 00:28:26,359
Speaker 3: where I think our research and our advice has been

604
00:28:26,640 --> 00:28:27,360
Speaker 3: really quite good.

605
00:28:27,680 --> 00:28:31,000
Speaker 2: So here's what I'm kind of intrigued by. You have

606
00:28:31,040 --> 00:28:34,040
Speaker 2: all these different roles. You're looking at all these different

607
00:28:34,160 --> 00:28:38,959
Speaker 2: aspects of the market, of the economy, of various government policies.

608
00:28:40,240 --> 00:28:44,160
Speaker 2: How do you take that massive information and communicate it

609
00:28:44,720 --> 00:28:48,840
Speaker 2: to both the Morgan Stanley staff, the sales team, the brokers,

610
00:28:48,840 --> 00:28:53,120
Speaker 2: the asset managers, and the investing public. I know you

611
00:28:53,160 --> 00:28:56,400
Speaker 2: do a weekly podcast on your perspective of the market.

612
00:28:57,080 --> 00:29:00,480
Speaker 2: How do you get all of this information to your

613
00:29:00,600 --> 00:29:02,480
Speaker 2: audience on a timely basis.

614
00:29:02,680 --> 00:29:06,120
Speaker 3: Yeah, it's it's a challenge I would I would say,

615
00:29:06,280 --> 00:29:09,000
Speaker 3: of all the things, all the skills that I've acquired

616
00:29:09,000 --> 00:29:13,080
Speaker 3: over the years, probably my best skill is communication. That

617
00:29:13,280 --> 00:29:17,320
Speaker 3: whether it's verbal, written media of some kind. You know,

618
00:29:18,040 --> 00:29:21,000
Speaker 3: people say I have a face for radios pot two. Yeah,

619
00:29:21,000 --> 00:29:23,720
Speaker 3: the podcast is better. But the point is is I'm

620
00:29:23,800 --> 00:29:27,480
Speaker 3: pretty clear. There's usually there's not really any uncertainty about

621
00:29:27,480 --> 00:29:29,640
Speaker 3: what I'm saying. I could be wrong, but it's very

622
00:29:29,680 --> 00:29:32,640
Speaker 3: clear and people like the clarity of the messaging.

623
00:29:32,720 --> 00:29:33,880
Speaker 1: So we write it out every week.

624
00:29:33,920 --> 00:29:36,360
Speaker 3: There's a cadence to it, right, We've developed as cadence

625
00:29:36,440 --> 00:29:40,280
Speaker 3: with our clients. Every Monday at you know, twelve am

626
00:29:40,600 --> 00:29:42,400
Speaker 3: in the morning the note comes out, so people are

627
00:29:42,440 --> 00:29:45,160
Speaker 3: waiting for that, or we do we do these regular

628
00:29:45,560 --> 00:29:49,720
Speaker 3: touch points and that regular communication, whether it's to the

629
00:29:49,720 --> 00:29:54,280
Speaker 3: institutional community, to the retail community, to our endowment community.

630
00:29:54,040 --> 00:29:55,360
Speaker 1: Whatever that might be. And of course then we do

631
00:29:55,440 --> 00:29:56,080
Speaker 1: a lot of marketing.

632
00:29:56,400 --> 00:29:58,400
Speaker 3: We do a lot of one on one meetings, you know,

633
00:29:58,560 --> 00:30:01,240
Speaker 3: group events, et cetera. So it's all those touch points,

634
00:30:01,600 --> 00:30:05,840
Speaker 3: and the challenge is that we have to deliver the

635
00:30:05,880 --> 00:30:08,720
Speaker 3: message depending on who the audience is. When it becomes

636
00:30:08,800 --> 00:30:11,920
Speaker 3: challenging is if I'm doing a media segment and that

637
00:30:12,000 --> 00:30:14,800
Speaker 3: maybe the messaging is more for the institutional community, but

638
00:30:14,880 --> 00:30:17,440
Speaker 3: then the retail community picks up on it and it's

639
00:30:17,440 --> 00:30:19,720
Speaker 3: really not for them, or vice versa. That's where it

640
00:30:19,720 --> 00:30:21,080
Speaker 3: becomes a bit of a challenge, and that's one of

641
00:30:21,120 --> 00:30:24,120
Speaker 3: the reasons why I'm now more focused on the institutional side.

642
00:30:24,280 --> 00:30:26,760
Speaker 2: Do you ever find yourself when you're putting these weekly

643
00:30:27,920 --> 00:30:31,800
Speaker 2: conversations together, looking at the flow and saying, you know,

644
00:30:32,160 --> 00:30:35,280
Speaker 2: most of the time these data series are just trending,

645
00:30:35,880 --> 00:30:38,400
Speaker 2: and it's when either there's a major reversal or a

646
00:30:38,400 --> 00:30:42,920
Speaker 2: big outlier that it's interesting. But all right, it's consistent

647
00:30:42,960 --> 00:30:45,479
Speaker 2: with last month's trend, in the previous month's trend, do

648
00:30:45,520 --> 00:30:47,440
Speaker 2: you look at that stuff and say, we don't really

649
00:30:47,440 --> 00:30:50,680
Speaker 2: need to talk about ism again, do we? Or how

650
00:30:50,720 --> 00:30:51,400
Speaker 2: do you deal with that?

651
00:30:51,760 --> 00:30:53,840
Speaker 3: Well, I mean it comes down to what we think

652
00:30:53,920 --> 00:30:56,320
Speaker 3: is the most important thing this week. We also, you know,

653
00:30:56,320 --> 00:30:58,360
Speaker 3: it's a bit of an art in terms of Okay,

654
00:30:58,400 --> 00:31:00,600
Speaker 3: when do you press it? When do you lay low?

655
00:31:00,680 --> 00:31:02,360
Speaker 3: When do you make a relative value call? When do

656
00:31:02,360 --> 00:31:04,440
Speaker 3: you make a market call? You know, it's like, well,

657
00:31:04,480 --> 00:31:06,600
Speaker 3: where's the opportunity right now? But we can kind of

658
00:31:06,640 --> 00:31:08,480
Speaker 3: go anywhere. The beauty of my job is I can

659
00:31:08,560 --> 00:31:10,280
Speaker 3: kind of talk about anything. I can talk about rates,

660
00:31:10,320 --> 00:31:12,240
Speaker 3: I can talk about credit, I can talk about stocks.

661
00:31:12,640 --> 00:31:15,320
Speaker 3: So that's that gives me a wide range of things

662
00:31:15,320 --> 00:31:18,520
Speaker 3: that I can have something relevant to say every week.

663
00:31:18,800 --> 00:31:22,120
Speaker 2: Huh, really really interesting. So there's a phrase of yours

664
00:31:22,160 --> 00:31:25,440
Speaker 2: that you use that I'm fascinated by. It's almost a

665
00:31:25,520 --> 00:31:31,360
Speaker 2: wartime phrase. You had written, the fog of uncertainty reveals

666
00:31:31,440 --> 00:31:33,040
Speaker 2: new investment opportunities.

667
00:31:33,240 --> 00:31:36,920
Speaker 3: Explain, Well, that's when things are mispriced the most right,

668
00:31:36,960 --> 00:31:39,400
Speaker 3: when things are when things are certain, you tend to

669
00:31:39,440 --> 00:31:40,840
Speaker 3: get pretty accurate pricing.

670
00:31:41,480 --> 00:31:43,320
Speaker 1: And of course that's dangerous too, because.

671
00:31:43,120 --> 00:31:44,960
Speaker 2: I was going to say, sometimes you get certainty in

672
00:31:45,000 --> 00:31:45,640
Speaker 2: the wrong direction.

673
00:31:45,800 --> 00:31:48,600
Speaker 3: Correct, But when things are really confusing, like during COVID,

674
00:31:48,640 --> 00:31:52,400
Speaker 3: for example, you had incredible value opportunities that popped up

675
00:31:52,400 --> 00:31:56,880
Speaker 3: because nobody knew anything, including us, but we knew the price.

676
00:31:57,480 --> 00:31:59,360
Speaker 3: And that was the main reason we got bullish in

677
00:31:59,480 --> 00:32:01,960
Speaker 3: March of twenty twenty was that we were waiting for

678
00:32:02,040 --> 00:32:04,600
Speaker 3: equity risk premiums to blow out, and they did, and

679
00:32:04,640 --> 00:32:07,360
Speaker 3: I'm like, well, doesn't really matter. Does really matter what

680
00:32:07,400 --> 00:32:09,480
Speaker 3: happens if I'm buying this at a seven hundred basis

681
00:32:09,480 --> 00:32:11,640
Speaker 3: point equity risk premium and yes, I'm gonna make money. Okay,

682
00:32:11,640 --> 00:32:13,560
Speaker 3: I'm gonna I'm gonna make money. Maybe not next week.

683
00:32:13,560 --> 00:32:15,800
Speaker 3: Now it turned out it was actually the low. But

684
00:32:16,040 --> 00:32:19,240
Speaker 3: I mean, like, that's when val evaluation typically doesn't matter,

685
00:32:19,280 --> 00:32:21,840
Speaker 3: But when it matters, it's all that matters. And the

686
00:32:21,880 --> 00:32:25,440
Speaker 3: fog of uncertainty creates those mismatches by the way, it

687
00:32:25,440 --> 00:32:27,680
Speaker 3: creates on the upside too. So for example, in early

688
00:32:27,680 --> 00:32:30,880
Speaker 3: twenty twenty one, we made a pretty important call, which

689
00:32:30,960 --> 00:32:33,880
Speaker 3: was that all the meme stocks are going bananas, right

690
00:32:33,880 --> 00:32:36,080
Speaker 3: because the free money that was floating around like, well,

691
00:32:36,120 --> 00:32:38,920
Speaker 3: these prices are this is not gonna end well, and

692
00:32:38,960 --> 00:32:40,120
Speaker 3: it's sure it didn't.

693
00:32:40,000 --> 00:32:43,200
Speaker 2: Right, never does it never does right? How is the

694
00:32:43,240 --> 00:32:47,720
Speaker 2: fog of uncertainty today? Is that it's clearly not March

695
00:32:47,760 --> 00:32:50,760
Speaker 2: twenty twenty, but there is a sense that people have

696
00:32:50,840 --> 00:32:53,160
Speaker 2: no idea which direction we're gonna head.

697
00:32:53,920 --> 00:32:56,800
Speaker 3: I would say that right now there there is more

698
00:32:56,880 --> 00:33:01,800
Speaker 3: certainty in people's minds than in reality. Okay, and that's

699
00:33:01,840 --> 00:33:05,200
Speaker 3: really where the opportunity comes up, which meaning there seems

700
00:33:05,200 --> 00:33:06,959
Speaker 3: to be a lot of certainty about how things are

701
00:33:06,960 --> 00:33:09,360
Speaker 3: going to play out, not economically but also from an

702
00:33:09,400 --> 00:33:11,560
Speaker 3: earning standpoint. But I've heard these same arguments now for

703
00:33:11,640 --> 00:33:13,880
Speaker 3: four to six months, four to six quarters, quite frankly,

704
00:33:14,280 --> 00:33:18,200
Speaker 3: about this reacceleration in certain things which it keeps being deferred.

705
00:33:18,880 --> 00:33:19,160
Speaker 1: Okay.

706
00:33:19,240 --> 00:33:21,520
Speaker 3: There's also a lot of certainty apparently around FED policy

707
00:33:21,520 --> 00:33:24,160
Speaker 3: because they guide, which I don't think there's any certainty

708
00:33:24,200 --> 00:33:24,960
Speaker 3: around they don't know.

709
00:33:25,280 --> 00:33:28,480
Speaker 2: I mean, the street has, let's be blunt, been dead

710
00:33:28,560 --> 00:33:30,960
Speaker 2: wrong about what the FED was going to do. It

711
00:33:31,000 --> 00:33:33,120
Speaker 2: feels like it's a year and a half for ready, Yeah.

712
00:33:32,920 --> 00:33:35,120
Speaker 1: The Fed has been wrong. Okay, it's a hard job.

713
00:33:35,200 --> 00:33:35,920
Speaker 1: I mean, you know.

714
00:33:35,920 --> 00:33:37,600
Speaker 3: I remember I'll just go back to an example, but

715
00:33:37,680 --> 00:33:41,840
Speaker 3: in December twenty twenty one, there was fifty basis points

716
00:33:41,920 --> 00:33:45,400
Speaker 3: of FED hikes priced in to the next year, okay,

717
00:33:45,640 --> 00:33:48,320
Speaker 3: And I was remember talking to clients going like, do

718
00:33:48,360 --> 00:33:50,840
Speaker 3: you I think this makes sense? I mean they were

719
00:33:51,320 --> 00:33:53,280
Speaker 3: runaway inflation and the FED has told you they're going

720
00:33:53,320 --> 00:33:56,000
Speaker 3: to start raising rage and like, well, yeah, it could

721
00:33:56,040 --> 00:33:57,680
Speaker 3: be more, but like that's what the Fed's telling us.

722
00:33:58,000 --> 00:34:01,080
Speaker 3: Oh okay, well, I mean so that you know this.

723
00:34:01,280 --> 00:34:03,440
Speaker 3: And this goes back to you know, two thousand and

724
00:34:03,480 --> 00:34:08,160
Speaker 3: three with regulation FD, that's when everything kind of changed.

725
00:34:08,160 --> 00:34:11,120
Speaker 1: Well it changed in two ways. So the FED changed with.

726
00:34:11,120 --> 00:34:13,759
Speaker 3: Green span right with all this forward guidance, and then

727
00:34:13,760 --> 00:34:15,480
Speaker 3: of course it's just gotten more and more and more

728
00:34:15,760 --> 00:34:18,279
Speaker 3: dot plot now and it just it's just compounded. You

729
00:34:18,280 --> 00:34:20,040
Speaker 3: give people a little bit of information, they want more.

730
00:34:20,360 --> 00:34:23,840
Speaker 3: So the FED is now provide so much information they

731
00:34:23,880 --> 00:34:26,000
Speaker 3: can't even tie their shoes without telling us first.

732
00:34:26,400 --> 00:34:29,480
Speaker 2: To be fair, when you and I first started, we

733
00:34:29,560 --> 00:34:31,759
Speaker 2: didn't the FED didn't even announce they were tightening. You

734
00:34:31,800 --> 00:34:34,239
Speaker 2: would just see activity in the bond market exactly, and

735
00:34:34,280 --> 00:34:37,279
Speaker 2: someone would say, hey, it looks like the FED raised rates. Now,

736
00:34:37,440 --> 00:34:39,440
Speaker 2: not only do they tell us the raising rates, we

737
00:34:39,480 --> 00:34:41,040
Speaker 2: get the transcript.

738
00:34:40,400 --> 00:34:42,840
Speaker 3: From the meetings, and then they have to basically go

739
00:34:42,920 --> 00:34:45,719
Speaker 3: through every line and they're like parsing each word. It's

740
00:34:45,719 --> 00:34:48,280
Speaker 3: got to the point now where it's almost debilitating, okay,

741
00:34:48,400 --> 00:34:51,439
Speaker 3: because the markets are almost unable to trade away from

742
00:34:51,440 --> 00:34:54,800
Speaker 3: this sort of formal guidance. Now that served a purpose

743
00:34:54,920 --> 00:34:57,439
Speaker 3: to a point. Now I think it's it's outgrown its

744
00:34:57,520 --> 00:34:58,760
Speaker 3: usefulness in many ways.

745
00:34:59,280 --> 00:35:03,440
Speaker 2: Does the FED lose something by giving up the elements

746
00:35:03,440 --> 00:35:06,040
Speaker 2: of surprise, the ability to shock the markets?

747
00:35:06,200 --> 00:35:06,600
Speaker 1: I think so.

748
00:35:07,280 --> 00:35:09,960
Speaker 3: But more importantly, what ends up happening is the market

749
00:35:10,040 --> 00:35:14,359
Speaker 3: now gravitates to you know, pricing in the same outcome. Right,

750
00:35:14,520 --> 00:35:17,640
Speaker 3: No one is willing to go away from the dot

751
00:35:17,680 --> 00:35:20,799
Speaker 3: plot or the like. The market rarely gets away from

752
00:35:20,880 --> 00:35:23,680
Speaker 3: the guidance. And I bring that up because it's the

753
00:35:23,719 --> 00:35:26,200
Speaker 3: same thing in a stock market now right with regulation

754
00:35:26,320 --> 00:35:29,279
Speaker 3: FD and now we have an entire industry dedicated to

755
00:35:29,560 --> 00:35:30,760
Speaker 3: company conference calls.

756
00:35:31,280 --> 00:35:32,480
Speaker 1: So if you look at.

757
00:35:32,440 --> 00:35:37,239
Speaker 3: The variance in estimate analyst estimates, it has absolutely narrowed

758
00:35:37,640 --> 00:35:40,320
Speaker 3: dramatically over the last fifteen or twenty years. In the

759
00:35:40,360 --> 00:35:43,000
Speaker 3: mid or late nineties, when heads funds became a thing,

760
00:35:43,400 --> 00:35:46,360
Speaker 3: and active managers were doing their thing. The variance and

761
00:35:46,480 --> 00:35:49,879
Speaker 3: estimates was all over the place because we didn't have

762
00:35:50,000 --> 00:35:53,600
Speaker 3: this such formal guidance. And so the irony here is

763
00:35:53,600 --> 00:35:57,920
Speaker 3: that in the effort to reduce uncertainty, you actually end

764
00:35:58,000 --> 00:36:02,200
Speaker 3: up creating more volatility because invariably those estimates are going

765
00:36:02,239 --> 00:36:04,080
Speaker 3: to end up being wrong at some point and everybody's

766
00:36:04,080 --> 00:36:05,560
Speaker 3: in the same position.

767
00:36:07,000 --> 00:36:11,680
Speaker 2: Really interesting, So you mentioned earlier your focus on cycles,

768
00:36:11,760 --> 00:36:15,360
Speaker 2: not just economic cycles and business cycles, but market cycles

769
00:36:15,800 --> 00:36:18,000
Speaker 2: tell a little bit about where are we in the

770
00:36:18,080 --> 00:36:20,760
Speaker 2: economic cycle and where are we in the market cycle today.

771
00:36:20,920 --> 00:36:24,000
Speaker 3: So we're pretty convinced that we're late cycle now. Late

772
00:36:24,000 --> 00:36:26,440
Speaker 3: cycle period's gonna last for years. I mean, the late

773
00:36:26,520 --> 00:36:28,080
Speaker 3: nineties is a great example of that. I mean went

774
00:36:28,120 --> 00:36:31,200
Speaker 3: on forever, and so we don't know when it ends.

775
00:36:31,239 --> 00:36:33,880
Speaker 3: But it's very hard to argue that we're mid cycle

776
00:36:33,920 --> 00:36:36,640
Speaker 3: or early cycle because we're unemployment is I mean, you're

777
00:36:36,680 --> 00:36:38,840
Speaker 3: basically at the fifty year low and it's kind of

778
00:36:38,840 --> 00:36:41,600
Speaker 3: turning up. So we think we're pretty much late cycle,

779
00:36:41,640 --> 00:36:44,440
Speaker 3: and that informs us where to be within the market.

780
00:36:44,440 --> 00:36:46,879
Speaker 3: So that's why quality large caps have done so well.

781
00:36:47,000 --> 00:36:49,880
Speaker 3: Quality growth in particular, that's what works, and this idea

782
00:36:49,880 --> 00:36:51,600
Speaker 3: they're going to go back to small caps or low

783
00:36:51,680 --> 00:36:54,360
Speaker 3: quality cycle, it's just it doesn't work. But people, I

784
00:36:54,400 --> 00:36:56,759
Speaker 3: don't think understand or appreciate where we are, or they

785
00:36:56,760 --> 00:36:58,799
Speaker 3: have a different view about where we are in the

786
00:36:58,840 --> 00:37:02,239
Speaker 3: economic cycle. So one example on the on the price

787
00:37:02,320 --> 00:37:05,759
Speaker 3: cycle or market cycles, I mean that tends to be

788
00:37:05,800 --> 00:37:08,319
Speaker 3: around kind of Fed policy kind of bee where the

789
00:37:08,360 --> 00:37:11,040
Speaker 3: interest rate cycle is well there too. It would suggest

790
00:37:11,040 --> 00:37:12,920
Speaker 3: that we're lated cycle because the curves inverted, has been

791
00:37:12,960 --> 00:37:15,440
Speaker 3: inverted for two years, we're now about to resteep it

792
00:37:15,480 --> 00:37:18,520
Speaker 3: and go positive again. That also would argue that you

793
00:37:18,560 --> 00:37:20,279
Speaker 3: want to have your risk kind of dialed back, at

794
00:37:20,360 --> 00:37:22,480
Speaker 3: least from a beta standpoint. You don't want to be

795
00:37:22,520 --> 00:37:26,400
Speaker 3: invested in lower quality balance sheet businesses. You know, credit

796
00:37:26,440 --> 00:37:29,040
Speaker 3: tends to do much better the inequities. That has been

797
00:37:29,120 --> 00:37:31,560
Speaker 3: the case on a risk adjusted basis. Bonds tend to

798
00:37:31,560 --> 00:37:34,440
Speaker 3: be a better buy. That's starting to work now. So yeah,

799
00:37:34,480 --> 00:37:35,920
Speaker 3: I mean there's there's all kinds of things that we

800
00:37:35,960 --> 00:37:38,160
Speaker 3: look at, and then of course there's individual stock cycles

801
00:37:38,520 --> 00:37:39,200
Speaker 3: which we pay.

802
00:37:39,040 --> 00:37:40,000
Speaker 1: Attention to quite a bit.

803
00:37:40,040 --> 00:37:42,880
Speaker 3: So we do use a lot of technical analysis One

804
00:37:42,880 --> 00:37:45,000
Speaker 3: of the reasons we're kind of contrarying is I tend

805
00:37:45,000 --> 00:37:48,520
Speaker 3: to fade like I fade exhaustion, exhaustion meaning things get

806
00:37:48,560 --> 00:37:51,680
Speaker 3: ever bought or things get over sold. I like to

807
00:37:51,920 --> 00:37:54,160
Speaker 3: I like to kind of press into those into those points.

808
00:37:54,480 --> 00:37:57,360
Speaker 2: That's really kind of interesting. So you mentioned the inverted

809
00:37:57,440 --> 00:38:01,320
Speaker 2: yield curve, and now that that's dis and starting to

810
00:38:01,360 --> 00:38:05,040
Speaker 2: steep in, everybody tends to focus on the inversion, but

811
00:38:05,120 --> 00:38:08,640
Speaker 2: that's not where recessions a car. It's after the yield

812
00:38:08,719 --> 00:38:11,600
Speaker 2: curve inversion on wines and things begin to steep in.

813
00:38:12,160 --> 00:38:14,840
Speaker 2: So what are your thoughts on the possibility of a

814
00:38:14,880 --> 00:38:19,719
Speaker 2: recession in twenty twenty four or more likely twenty twenty five.

815
00:38:20,000 --> 00:38:22,040
Speaker 3: Well, once again, like our house call is as soft

816
00:38:22,120 --> 00:38:25,160
Speaker 3: landing's most likely outcome, we don't have to answer, okay,

817
00:38:25,160 --> 00:38:27,040
Speaker 3: And I don't think the curve is resteeping in a

818
00:38:27,080 --> 00:38:30,719
Speaker 3: way that would signal that the recession is more likely

819
00:38:30,760 --> 00:38:33,200
Speaker 3: than not yet, but that can change. So we're very

820
00:38:33,200 --> 00:38:35,640
Speaker 3: focused on that. And usually when the curve and resteepings

821
00:38:35,680 --> 00:38:37,319
Speaker 3: from the front end, meaning the.

822
00:38:37,280 --> 00:38:38,399
Speaker 1: FED is catching up.

823
00:38:38,760 --> 00:38:40,200
Speaker 3: This is why I'm very focused right now in the

824
00:38:40,239 --> 00:38:44,080
Speaker 3: two year yield relative to FED funds. So two year

825
00:38:44,160 --> 00:38:46,600
Speaker 3: yield's got almost one hundred and eighty five basis points

826
00:38:46,640 --> 00:38:47,920
Speaker 3: below FED funds, you.

827
00:38:47,920 --> 00:38:50,840
Speaker 2: Would think is anticipating massive cuts, right.

828
00:38:50,840 --> 00:38:53,879
Speaker 3: Like, not fifty basis points, okay, or seventy five. It's

829
00:38:53,920 --> 00:38:56,040
Speaker 3: predicting one hundred and eighty five basis points of cuts

830
00:38:56,520 --> 00:38:58,480
Speaker 3: over the next probably you know, twelve to eighteen months,

831
00:38:58,480 --> 00:39:01,719
Speaker 3: which is a pretty aggressive FED cutting cycle. And that's

832
00:39:01,800 --> 00:39:04,000
Speaker 3: all it's telling you. It's just telling you that the

833
00:39:04,600 --> 00:39:07,719
Speaker 3: likelihood that the FED is behind the curve is gone

834
00:39:07,800 --> 00:39:11,319
Speaker 3: up once again. Not a recession, but the risk of

835
00:39:11,400 --> 00:39:13,000
Speaker 3: a hard landing has gone up.

836
00:39:13,520 --> 00:39:14,240
Speaker 1: All else equal.

837
00:39:14,760 --> 00:39:17,040
Speaker 2: If the market thinks we're getting almost two hundred basis

838
00:39:17,040 --> 00:39:20,040
Speaker 2: points and cuts, it sounds like the bond market is

839
00:39:20,040 --> 00:39:21,600
Speaker 2: anticipating a recession right now.

840
00:39:21,640 --> 00:39:24,240
Speaker 3: The good news is that has narrowed. So the spread

841
00:39:24,239 --> 00:39:26,360
Speaker 3: now between two years and FED funds is down to

842
00:39:26,400 --> 00:39:29,200
Speaker 3: one forty five. Why because the claims numbers were better.

843
00:39:29,520 --> 00:39:31,600
Speaker 3: We got some you know, ism services data was a

844
00:39:31,640 --> 00:39:34,319
Speaker 3: little bit better. So this like fear that you know,

845
00:39:34,400 --> 00:39:37,239
Speaker 3: got priced in really quickly is now subsided. A bit

846
00:39:37,360 --> 00:39:39,759
Speaker 3: doesn't mean it's extinguished. It just means that we you know,

847
00:39:39,800 --> 00:39:42,720
Speaker 3: the pendulum is swinging back again, and so we're focused

848
00:39:42,800 --> 00:39:43,000
Speaker 3: on that.

849
00:39:43,120 --> 00:39:45,759
Speaker 1: We're watching it closely. I would say the jury is out.

850
00:39:45,920 --> 00:39:46,360
Speaker 1: We don't know.

851
00:39:46,960 --> 00:39:50,320
Speaker 2: So markets in twenty twenty four had a great first

852
00:39:50,400 --> 00:39:53,600
Speaker 2: half of a year. A lot of people expected to

853
00:39:53,800 --> 00:39:56,920
Speaker 2: build on that ten twelve, fourteen percent gains. Depending on

854
00:39:57,440 --> 00:40:00,520
Speaker 2: which markets you were looking at, you I've come out

855
00:40:00,560 --> 00:40:03,359
Speaker 2: and said, I think it's a low probability that there's

856
00:40:03,400 --> 00:40:05,640
Speaker 2: a whole lot more upside for the rest of the year.

857
00:40:06,280 --> 00:40:08,640
Speaker 2: Tell us what you're looking at there and why do

858
00:40:08,680 --> 00:40:11,280
Speaker 2: you think. Hey, the most of the gains for twenty

859
00:40:11,320 --> 00:40:12,680
Speaker 2: twenty four have already been had.

860
00:40:13,000 --> 00:40:16,080
Speaker 3: So all of the gains really since October of last

861
00:40:16,120 --> 00:40:20,200
Speaker 3: fall has been multiple expansion in anticipation of a FED

862
00:40:20,200 --> 00:40:24,200
Speaker 3: cutting cycle and a reacceleration in growth. So we went

863
00:40:24,280 --> 00:40:28,120
Speaker 3: from seventeen times earnings SMP earnings in October of last

864
00:40:28,120 --> 00:40:30,480
Speaker 3: fall to twenty two times earnings in June.

865
00:40:31,120 --> 00:40:33,440
Speaker 1: Well, that's about as rich as you can get.

866
00:40:33,920 --> 00:40:37,400
Speaker 3: So I'm pretty comfortable saying that multiples are likely to

867
00:40:37,440 --> 00:40:40,000
Speaker 3: come down as the FED cuts. That's also something I

868
00:40:40,040 --> 00:40:42,520
Speaker 3: think people don't appreciate. Once the FED like it's easier

869
00:40:42,520 --> 00:40:46,040
Speaker 3: to travel than arrive, so as you're moving to the

870
00:40:46,040 --> 00:40:48,120
Speaker 3: FED cuts. That's the best part of the cycle. We

871
00:40:48,160 --> 00:40:49,960
Speaker 3: wrote about that at the end of last year when

872
00:40:50,000 --> 00:40:51,880
Speaker 3: we sort of you know through in the tiel that

873
00:40:51,920 --> 00:40:53,640
Speaker 3: we were going to have this you know, hard landing.

874
00:40:54,160 --> 00:40:55,160
Speaker 1: We thought there'd be a rally.

875
00:40:55,239 --> 00:40:56,919
Speaker 3: Okay, we didn't think we go to fifty seven hundred,

876
00:40:56,960 --> 00:40:58,960
Speaker 3: but needless to say that that's what happened. But the

877
00:40:59,000 --> 00:41:01,399
Speaker 3: best part of that rat has now occurred. So when

878
00:41:01,400 --> 00:41:05,120
Speaker 3: the FED starts cutting, multiples usually go down and there's

879
00:41:05,200 --> 00:41:09,560
Speaker 3: just not enough earnings growth offset a ten to fifteen

880
00:41:09,600 --> 00:41:12,799
Speaker 3: percent multiple contraction between here and the end of the year.

881
00:41:12,840 --> 00:41:15,640
Speaker 3: We have like eight percent growth built in for next

882
00:41:15,719 --> 00:41:18,879
Speaker 3: year's earnings growth. So that's the math. I mean, you're

883
00:41:18,920 --> 00:41:21,200
Speaker 3: just you have a net drag from the multiple contraction

884
00:41:21,280 --> 00:41:22,920
Speaker 3: relative to what the earnings growth is going to be,

885
00:41:23,000 --> 00:41:25,400
Speaker 3: even in the soft landing outcome. So I would argue

886
00:41:25,880 --> 00:41:28,360
Speaker 3: that we prob the highs for the year and the

887
00:41:28,440 --> 00:41:32,120
Speaker 3: SMP are probably in. That doesn't mean it's a cataclysm, okay,

888
00:41:32,440 --> 00:41:36,160
Speaker 3: just means that the risk reward now is now particularly attractive.

889
00:41:36,560 --> 00:41:40,320
Speaker 2: So you have this very nuance take that. I'm intrigued

890
00:41:40,360 --> 00:41:44,920
Speaker 2: by what you're describing as somewhat cautious. However, the nuances

891
00:41:45,760 --> 00:41:49,759
Speaker 2: pullbacks are opportunities for investors to put money into high

892
00:41:49,840 --> 00:41:54,480
Speaker 2: quality growth companies that have strong financials and high earnings potential.

893
00:41:55,000 --> 00:41:59,840
Speaker 2: That's a very nuanced position relative to the highs are

894
00:41:59,880 --> 00:42:02,440
Speaker 2: in for the year, and we should expect a bumpy

895
00:42:02,520 --> 00:42:03,160
Speaker 2: road from here.

896
00:42:03,400 --> 00:42:04,800
Speaker 3: Well, it's a little bit of both. I mean, I

897
00:42:04,840 --> 00:42:06,920
Speaker 3: would say that I think the trajectory is down. I

898
00:42:06,960 --> 00:42:10,719
Speaker 3: mean nineteen times. You know, next year's numbers is you know,

899
00:42:10,760 --> 00:42:12,239
Speaker 3: which is the end of the year is lower than

900
00:42:12,239 --> 00:42:14,600
Speaker 3: where we're training today. It's sort of that low five

901
00:42:14,600 --> 00:42:16,200
Speaker 3: thousands is supposed to fifty four hundred.

902
00:42:16,920 --> 00:42:20,840
Speaker 2: But what is that five six percent? Not exactly like

903
00:42:20,880 --> 00:42:21,440
Speaker 2: you said, that's.

904
00:42:21,280 --> 00:42:23,320
Speaker 3: Pumpy, it's not, you know, that's the way you phrase

905
00:42:23,360 --> 00:42:25,400
Speaker 3: the question. So I think it is going to be bumpy.

906
00:42:25,719 --> 00:42:29,120
Speaker 3: And that's to forget that we're going into this election season.

907
00:42:29,480 --> 00:42:31,160
Speaker 3: There are some other things going on around the world.

908
00:42:31,160 --> 00:42:33,920
Speaker 3: There is still excess leverage in the system that I'm

909
00:42:33,960 --> 00:42:36,520
Speaker 3: not sure how that's going to be resolved. Necessarily, China's

910
00:42:36,560 --> 00:42:38,799
Speaker 3: not providing the impetus that people were hoping for from

911
00:42:38,800 --> 00:42:41,279
Speaker 3: a growth standpoint, So we just you know, we just

912
00:42:41,440 --> 00:42:42,920
Speaker 3: we need to take a little bit of a of

913
00:42:42,960 --> 00:42:44,759
Speaker 3: a break, you know, and it could just be a

914
00:42:44,800 --> 00:42:48,400
Speaker 3: consolidation period at the index level, which once again lends

915
00:42:48,440 --> 00:42:50,160
Speaker 3: me to say, I want to be up the quality

916
00:42:50,200 --> 00:42:53,120
Speaker 3: curve and I want to skew more defensive than growth,

917
00:42:53,200 --> 00:42:55,000
Speaker 3: because that's typically what works when the FED cuts.

918
00:42:55,239 --> 00:42:58,520
Speaker 2: Let's talk about another nuanced position that you have that

919
00:42:58,840 --> 00:43:03,440
Speaker 2: I find fascinating. Everybody's been so focused on the artificial

920
00:43:03,560 --> 00:43:09,440
Speaker 2: intelligence enablers and Video and all the other semiconductor chip companies,

921
00:43:10,120 --> 00:43:14,759
Speaker 2: but you've made the argument that investors should begin to

922
00:43:14,840 --> 00:43:19,560
Speaker 2: shift from those AI enablers to the AI adopters as

923
00:43:19,719 --> 00:43:23,160
Speaker 2: the big next opportunity. Talk about that, because that's really

924
00:43:23,160 --> 00:43:24,680
Speaker 2: a fascinating concept.

925
00:43:24,760 --> 00:43:27,759
Speaker 3: Yeah, I mean that's sort of my technology background speaking, right.

926
00:43:27,719 --> 00:43:29,400
Speaker 3: I Mean, that's how these cycles work. You buy the

927
00:43:29,400 --> 00:43:32,440
Speaker 3: picks and shovels or the enablers initially, and then the

928
00:43:32,480 --> 00:43:35,360
Speaker 3: real money, the real opportunity, is with the companies that

929
00:43:35,400 --> 00:43:38,680
Speaker 3: can actually deploy that technology into a new business model.

930
00:43:39,080 --> 00:43:41,040
Speaker 3: So if you think about the nineteen ninety as a

931
00:43:41,080 --> 00:43:45,160
Speaker 3: good example, everybody will understand the enablers were the telecom companies,

932
00:43:45,480 --> 00:43:48,360
Speaker 3: the Silicon companies, the telecom equipment companies.

933
00:43:48,040 --> 00:43:52,520
Speaker 2: Cisco, JDSUNI, Phase, all these companies that nobody, really the

934
00:43:52,600 --> 00:43:56,280
Speaker 2: average investor had no idea what their hardware was really doing.

935
00:43:56,120 --> 00:43:59,279
Speaker 3: Right, But these were spectacular stocks, and that was in

936
00:43:59,280 --> 00:44:02,200
Speaker 3: the build out of the Internet itself. But if you

937
00:44:02,239 --> 00:44:05,720
Speaker 3: think about who actually ended up building the big stocks,

938
00:44:05,800 --> 00:44:09,000
Speaker 3: the ones that really worked from the Internet, it's the

939
00:44:09,080 --> 00:44:11,960
Speaker 3: mag seven, right, you know, I mean X you know

940
00:44:12,200 --> 00:44:14,920
Speaker 3: one semi counter company that has gone crazy here recently,

941
00:44:14,960 --> 00:44:17,440
Speaker 3: But generally, these are the businesses that took the Internet

942
00:44:17,600 --> 00:44:21,319
Speaker 3: and then built incredible business models kind of for free.

943
00:44:21,360 --> 00:44:21,960
Speaker 1: I mean they didn't have to.

944
00:44:22,000 --> 00:44:23,920
Speaker 3: They have to spend the money to build a super highway, right,

945
00:44:24,040 --> 00:44:26,239
Speaker 3: the guys who built a super highway, those stocks have

946
00:44:26,280 --> 00:44:27,080
Speaker 3: been terrible.

947
00:44:26,960 --> 00:44:31,239
Speaker 2: Well, Metromedia, Fiber and Global Crossing. They spent thousands of

948
00:44:31,320 --> 00:44:34,000
Speaker 2: dollars a mile and then got sold for pennies on

949
00:44:34,040 --> 00:44:36,720
Speaker 2: the dollar. But that's how you end up with YouTube

950
00:44:36,760 --> 00:44:39,000
Speaker 2: and Facebook and correct and Netflix.

951
00:44:39,120 --> 00:44:41,120
Speaker 3: So that's why it's interesting now, Barry where you know.

952
00:44:41,200 --> 00:44:43,719
Speaker 3: So obviously hyperscalers have been the big winners of the

953
00:44:43,800 --> 00:44:47,319
Speaker 3: last era, and there's nothing wrong with these businesses or companies. Okay,

954
00:44:47,320 --> 00:44:49,920
Speaker 3: they're great, but they're now the ones spending all the

955
00:44:49,960 --> 00:44:54,080
Speaker 3: money on this next generation cloud or AI whatever you want.

956
00:44:53,920 --> 00:44:54,239
Speaker 1: To call it.

957
00:44:54,400 --> 00:44:56,200
Speaker 3: By the way, AI, just to be clear, is really

958
00:44:56,239 --> 00:44:58,799
Speaker 3: just an extension of machine learning. It's you know, I'm

959
00:44:58,840 --> 00:45:01,319
Speaker 3: not sure we're going to have really artificial intelligence. I mean,

960
00:45:01,320 --> 00:45:04,680
Speaker 3: that's an interesting way to get people excited. Okay, it's

961
00:45:04,719 --> 00:45:07,880
Speaker 3: just another investment cycle. There will be use cases in

962
00:45:07,920 --> 00:45:10,560
Speaker 3: business models that are very profitable built on the backbone

963
00:45:10,600 --> 00:45:13,960
Speaker 3: of those cloud networks. Okay, great, We don't even know

964
00:45:13,960 --> 00:45:15,080
Speaker 3: who those companies are yet.

965
00:45:15,120 --> 00:45:15,359
Speaker 1: Okay.

966
00:45:15,440 --> 00:45:18,040
Speaker 3: My guess is they're going to reside in areas where

967
00:45:18,040 --> 00:45:20,839
Speaker 3: great efficiencies are needed, for example, in healthcare, which we

968
00:45:20,840 --> 00:45:23,520
Speaker 3: were talking about earlier, right, like a lot of inefficiencies

969
00:45:23,520 --> 00:45:25,719
Speaker 3: in healthcare. Well, you know, somebody's going to come up

970
00:45:25,719 --> 00:45:28,800
Speaker 3: with a solution to kind of ring out that inefficiency. Okay,

971
00:45:29,040 --> 00:45:33,400
Speaker 3: and there's massive opportunity for that using machine learning. I

972
00:45:33,440 --> 00:45:35,960
Speaker 3: don't know who those companies are yet, Okay, but those

973
00:45:36,000 --> 00:45:38,799
Speaker 3: are going to be really the fat pitch that's going

974
00:45:38,840 --> 00:45:40,840
Speaker 3: to be where the real wealth at the ten twenty

975
00:45:40,920 --> 00:45:44,719
Speaker 3: thirty baggers. Because these companies now they can't grow tenfold.

976
00:45:44,800 --> 00:45:46,960
Speaker 3: They they're already too big, you know what I'm saying.

977
00:45:47,480 --> 00:45:50,640
Speaker 2: It's amazing when you look in the healthcare space, they

978
00:45:50,680 --> 00:45:56,200
Speaker 2: still use fax machines. I mean literally have your doctor facts,

979
00:45:56,280 --> 00:46:00,719
Speaker 2: the prescription to the Why can't you do email? It's

980
00:46:00,760 --> 00:46:03,960
Speaker 2: not secure? Some of this is technology, some of this

981
00:46:04,080 --> 00:46:10,040
Speaker 2: is just, you know, having one focused business methodology that

982
00:46:10,480 --> 00:46:13,400
Speaker 2: seems to not be rooted twenty thirty four. What is

983
00:46:13,440 --> 00:46:18,040
Speaker 2: fax machine? Forty years old? It's amazing. So it's not

984
00:46:18,160 --> 00:46:22,480
Speaker 2: so much AI as just a rapid adoption of better

985
00:46:22,560 --> 00:46:26,120
Speaker 2: technologies and AI helps. How do we conceptualize that?

986
00:46:26,320 --> 00:46:27,960
Speaker 1: It's just faster processing? Right?

987
00:46:28,000 --> 00:46:30,480
Speaker 3: And then once again, it's about the solution that it's

988
00:46:30,480 --> 00:46:31,160
Speaker 3: built around that.

989
00:46:31,280 --> 00:46:31,400
Speaker 1: Right.

990
00:46:31,440 --> 00:46:34,600
Speaker 3: The Internet was a really interesting development. But I mean

991
00:46:34,920 --> 00:46:37,120
Speaker 3: nineteen ninety five, and you remember this, like I did

992
00:46:37,560 --> 00:46:39,640
Speaker 3: you know, We're sitting around in the desk and all

993
00:46:39,680 --> 00:46:41,439
Speaker 3: of a sudden they're like, oh, there's this thing called

994
00:46:41,560 --> 00:46:43,919
Speaker 3: email that we're going to introduce.

995
00:46:43,600 --> 00:46:45,839
Speaker 1: You Like, what is this? But it was such an

996
00:46:45,880 --> 00:46:46,399
Speaker 1: easy apple.

997
00:46:46,480 --> 00:46:48,840
Speaker 2: But don't email clients. You have to get compliance. I

998
00:46:48,840 --> 00:46:51,400
Speaker 2: still prove that yet. Do you recall back in the

999
00:46:51,480 --> 00:46:54,799
Speaker 2: day where you literally had to have approval to send emails.

1000
00:46:54,920 --> 00:46:59,560
Speaker 2: It's amazing that that adoption period was a decade plus long, but.

1001
00:46:59,560 --> 00:47:00,440
Speaker 1: It was fat. It was.

1002
00:47:00,480 --> 00:47:03,440
Speaker 3: I mean, it was pretty immediate and anybody you know,

1003
00:47:03,520 --> 00:47:06,880
Speaker 3: could type, could could use email, and email was I

1004
00:47:06,880 --> 00:47:09,480
Speaker 3: think still to this day, one of the biggest productivity

1005
00:47:09,520 --> 00:47:12,720
Speaker 3: enhancements I've ever seen in my lifetime. Now, the browser

1006
00:47:12,800 --> 00:47:15,440
Speaker 3: was the other killer app. And now the problem is,

1007
00:47:15,440 --> 00:47:17,239
Speaker 3: weren't any websites to go to for a while. But

1008
00:47:18,000 --> 00:47:21,960
Speaker 3: those two sort of apps to me were so obvious,

1009
00:47:22,080 --> 00:47:23,000
Speaker 3: much more obvious than.

1010
00:47:22,880 --> 00:47:26,719
Speaker 1: Say, chat GPT is okay, at least so far. We'll

1011
00:47:26,719 --> 00:47:27,600
Speaker 1: see where that goes.

1012
00:47:27,680 --> 00:47:30,040
Speaker 3: Right now, you know, it does homework for high school

1013
00:47:30,080 --> 00:47:32,160
Speaker 3: students and can help you and I write a nice

1014
00:47:32,160 --> 00:47:34,520
Speaker 3: poem to a loved one, or help us write a

1015
00:47:34,560 --> 00:47:37,840
Speaker 3: speech or something great. But like, is it really enhancing

1016
00:47:37,840 --> 00:47:40,600
Speaker 3: productivity in a meaningful way? Like, we can't use that

1017
00:47:40,680 --> 00:47:42,960
Speaker 3: yet it doesn't. We can't trust it for the numbers,

1018
00:47:43,000 --> 00:47:45,719
Speaker 3: we can't trust it for mission critical type analysis yet.

1019
00:47:45,840 --> 00:47:51,000
Speaker 2: Right, it's a research a dendum, but it still hallucinates.

1020
00:47:51,040 --> 00:47:54,920
Speaker 2: And so my favorite story is I had Bill Dudley

1021
00:47:54,920 --> 00:47:57,520
Speaker 2: the New York Fed and as a guest, and I

1022
00:47:57,640 --> 00:48:01,160
Speaker 2: used chat GPT just to see if I missed anything,

1023
00:48:01,800 --> 00:48:04,880
Speaker 2: And thanks to chat GBT, I learned that he was

1024
00:48:05,360 --> 00:48:08,440
Speaker 2: a linebacker for the Detroit Lions in the nineteen fifties,

1025
00:48:08,760 --> 00:48:11,279
Speaker 2: which kind of interesting because he was also born in

1026
00:48:11,280 --> 00:48:15,600
Speaker 2: the nineteen fifties. Chat gbt couldn't figure out two different

1027
00:48:15,600 --> 00:48:20,680
Speaker 2: William Dudley's that'll eventually get worked out. At what point

1028
00:48:20,960 --> 00:48:24,479
Speaker 2: and this goes right back to your AI adopters. Look,

1029
00:48:24,480 --> 00:48:27,120
Speaker 2: we're all Internet companies, we're all phone companies. We use

1030
00:48:27,160 --> 00:48:30,840
Speaker 2: all these technologies. At what point in the future do

1031
00:48:31,000 --> 00:48:34,560
Speaker 2: the other four hundred and ninety companies in the s

1032
00:48:34,600 --> 00:48:38,480
Speaker 2: and P five hundred, not the AI enablers, but the adopters,

1033
00:48:38,960 --> 00:48:42,120
Speaker 2: when did they start to see the productivity benefits from AI?

1034
00:48:42,239 --> 00:48:44,080
Speaker 2: How far off is that in the future.

1035
00:48:43,920 --> 00:48:46,920
Speaker 3: When the you know, Hyperscalers or somebody else hands them

1036
00:48:46,920 --> 00:48:49,120
Speaker 3: a solution, it's a package solution. I mean, it's no

1037
00:48:49,160 --> 00:48:51,640
Speaker 3: different than software in the nineties, right, sound like you

1038
00:48:51,680 --> 00:48:54,120
Speaker 3: and I were going to go develop Office or we're

1039
00:48:54,120 --> 00:48:57,320
Speaker 3: going to go develop Excel, you know, But somebody developed

1040
00:48:57,320 --> 00:49:00,440
Speaker 3: that for us. We deployed it in our enterprise and

1041
00:49:00,480 --> 00:49:03,279
Speaker 3: our employees became very productive. So we just need the

1042
00:49:03,320 --> 00:49:07,000
Speaker 3: development of those applications. That's the second phase. The other

1043
00:49:07,040 --> 00:49:09,560
Speaker 3: problem that we haven't solved yet is the electricity, you know,

1044
00:49:09,600 --> 00:49:13,120
Speaker 3: the power consumption, the heat you know, and also to

1045
00:49:13,160 --> 00:49:16,279
Speaker 3: build these things out it takes time, and so that's there.

1046
00:49:16,320 --> 00:49:18,680
Speaker 3: There are some there are some snaff oos in here

1047
00:49:18,719 --> 00:49:21,759
Speaker 3: that will you know, retard the expansion and growth of

1048
00:49:22,080 --> 00:49:22,560
Speaker 3: But but.

1049
00:49:22,600 --> 00:49:25,640
Speaker 2: All those things are solvable. It's just a matter of time,

1050
00:49:25,680 --> 00:49:25,920
Speaker 2: you know.

1051
00:49:26,560 --> 00:49:27,760
Speaker 1: But but is it money?

1052
00:49:28,280 --> 00:49:30,200
Speaker 2: Is it decades or is it years?

1053
00:49:30,440 --> 00:49:30,560
Speaker 3: Oh?

1054
00:49:30,600 --> 00:49:31,240
Speaker 1: No, it's years.

1055
00:49:31,600 --> 00:49:35,839
Speaker 3: But I don't think it's fast enough to prevent where

1056
00:49:35,840 --> 00:49:38,160
Speaker 3: we are in the economic cycle. Once again, going back

1057
00:49:38,200 --> 00:49:40,400
Speaker 3: to I think there are people making the argument that, oh,

1058
00:49:40,600 --> 00:49:43,319
Speaker 3: not only did the fiscal kind of bridge us another year,

1059
00:49:43,840 --> 00:49:47,080
Speaker 3: but now AI is going to extend the cycle another

1060
00:49:47,120 --> 00:49:48,160
Speaker 3: three or four years.

1061
00:49:48,640 --> 00:49:50,800
Speaker 1: I'm just out of that belief because that's the next cycle.

1062
00:49:51,000 --> 00:49:52,879
Speaker 1: That's the next cycle. That's what to get, that's what's

1063
00:49:52,920 --> 00:49:53,319
Speaker 1: going to be.

1064
00:49:53,400 --> 00:49:55,920
Speaker 3: That's what you're gonna want to get excited about when

1065
00:49:56,000 --> 00:49:59,000
Speaker 3: valuations come in at some point in the next twelve months,

1066
00:49:59,120 --> 00:50:01,799
Speaker 3: is my guess. And there's a fat pitch that people

1067
00:50:01,840 --> 00:50:02,840
Speaker 3: have forgotten about.

1068
00:50:02,640 --> 00:50:07,160
Speaker 2: All right, last of our standard questions when you look

1069
00:50:07,200 --> 00:50:09,440
Speaker 2: at a market where we are today, When you look

1070
00:50:09,480 --> 00:50:12,080
Speaker 2: at the economy where we are today, what are your

1071
00:50:12,120 --> 00:50:17,319
Speaker 2: favorite metrics to focus on, whether it's valuation or the

1072
00:50:17,360 --> 00:50:20,000
Speaker 2: economy or inflation, what are your big three that you're

1073
00:50:20,200 --> 00:50:20,840
Speaker 2: you're watching.

1074
00:50:21,000 --> 00:50:22,719
Speaker 3: So, once again it goes back to ry to change

1075
00:50:22,760 --> 00:50:24,200
Speaker 3: on a lot of the key metrics. I say, the

1076
00:50:24,280 --> 00:50:27,840
Speaker 3: key metrics I'm focused on now are things like revision factors,

1077
00:50:27,840 --> 00:50:30,760
Speaker 3: So earnings revision factors, that's what stocks are most highly

1078
00:50:30,920 --> 00:50:34,000
Speaker 3: correlated to. That's now rolling over. So the rate to

1079
00:50:34,080 --> 00:50:36,120
Speaker 3: change on that is in a bad slope, which means

1080
00:50:36,200 --> 00:50:37,600
Speaker 3: valuation has come down. It doesn't mean it has to

1081
00:50:37,640 --> 00:50:40,719
Speaker 3: go negative, but you know, it can go negative and

1082
00:50:40,719 --> 00:50:42,920
Speaker 3: then we'll have to adjust, you know, or targets further.

1083
00:50:43,680 --> 00:50:46,440
Speaker 3: Right now, it's in a correction phase from a From

1084
00:50:46,440 --> 00:50:49,760
Speaker 3: that standpoint, From an economic standpoint, it's all labor data. Okay,

1085
00:50:49,840 --> 00:50:50,719
Speaker 3: That's all that matters to me.

1086
00:50:50,800 --> 00:50:51,000
Speaker 2: Now.

1087
00:50:51,160 --> 00:50:53,720
Speaker 3: Everything else is kind of secondary. If the claims data

1088
00:50:53,960 --> 00:50:57,000
Speaker 3: and the payroll data stays okay, soft landing is the outcome.

1089
00:50:57,040 --> 00:50:58,320
Speaker 1: If that deteriorates further.

1090
00:50:58,640 --> 00:51:00,560
Speaker 3: I don't think it can deteriorate a whole lot further

1091
00:51:00,640 --> 00:51:03,120
Speaker 3: before the market start to get nervous.

1092
00:51:03,480 --> 00:51:06,120
Speaker 2: In our last five minutes, Let's jump to our favorite

1093
00:51:06,160 --> 00:51:09,520
Speaker 2: questions that we ask all our guests, and we'll do

1094
00:51:09,560 --> 00:51:13,640
Speaker 2: this in a speed round, starting with tell us what

1095
00:51:13,640 --> 00:51:16,040
Speaker 2: you're streaming, what's giving you entertain these days?

1096
00:51:16,520 --> 00:51:18,839
Speaker 1: Yeah, I'm watching sort of an eclectic group.

1097
00:51:18,920 --> 00:51:21,360
Speaker 3: Now, The Bear. I don't know if you've seen that show.

1098
00:51:22,239 --> 00:51:24,120
Speaker 3: We just finished season three, which I didn't love.

1099
00:51:24,120 --> 00:51:24,799
Speaker 1: The season three is.

1100
00:51:24,760 --> 00:51:27,200
Speaker 2: Season two is still better, but three was interesting.

1101
00:51:27,280 --> 00:51:29,560
Speaker 3: Yeah, it's all good. It's just great character studies, which

1102
00:51:29,600 --> 00:51:32,520
Speaker 3: which we enjoy. My wife and I have enjoyed that series.

1103
00:51:32,520 --> 00:51:34,839
Speaker 3: We just finished it. Other than that, the offer, if

1104
00:51:34,840 --> 00:51:37,080
Speaker 3: you've seen that, no, So the offer is about the

1105
00:51:37,160 --> 00:51:39,440
Speaker 3: making of the movie The Godfather.

1106
00:51:39,560 --> 00:51:41,520
Speaker 2: We were just talking about this over the week.

1107
00:51:41,560 --> 00:51:43,600
Speaker 1: Spectacular. We're not done with that yet, but it is.

1108
00:51:43,680 --> 00:51:46,600
Speaker 2: But I can't remember the last time I saw Godfather too.

1109
00:51:46,640 --> 00:51:49,840
Speaker 2: It had to be decades, yeah, ago. And someone said,

1110
00:51:50,480 --> 00:51:52,480
Speaker 2: watch the offer. It's based on the book that the

1111
00:51:52,520 --> 00:51:56,160
Speaker 2: producer exactly did. And people said, when you go back

1112
00:51:56,160 --> 00:51:59,040
Speaker 2: and rewatch it, everything has a different context.

1113
00:51:59,040 --> 00:52:01,480
Speaker 3: It's spectacular. So I would recommend that. And then I'm

1114
00:52:01,520 --> 00:52:05,040
Speaker 3: watching a Pete Rose documentary right now. I'm in the

1115
00:52:05,080 --> 00:52:07,880
Speaker 3: third of the fourth and it wasn't not what I expected.

1116
00:52:07,920 --> 00:52:09,960
Speaker 3: So I like to watch a lot of documentaries, and

1117
00:52:10,000 --> 00:52:12,120
Speaker 3: that one is pretty fascina really interesting.

1118
00:52:12,520 --> 00:52:15,240
Speaker 2: Tell us about your mentors who helped shape your career.

1119
00:52:15,960 --> 00:52:17,840
Speaker 3: Well, I mean, this is all it is going to

1120
00:52:17,920 --> 00:52:20,800
Speaker 3: sound the writer, you know, dishonest, but it's True's basically

1121
00:52:20,840 --> 00:52:23,520
Speaker 3: my mom and my wife. I mean, these are the

1122
00:52:23,560 --> 00:52:26,799
Speaker 3: two strongest women I've ever met in my life. They've

1123
00:52:26,800 --> 00:52:31,360
Speaker 3: been extremely honest with me and forced me to grow,

1124
00:52:32,160 --> 00:52:33,760
Speaker 3: and so those are the two most important.

1125
00:52:33,840 --> 00:52:36,280
Speaker 1: For sure. There's no one.

1126
00:52:36,120 --> 00:52:39,879
Speaker 3: Person, but many colleagues and many clients. I would say

1127
00:52:39,960 --> 00:52:43,279
Speaker 3: clients have shaped my views on the market's probably more

1128
00:52:43,320 --> 00:52:46,759
Speaker 3: than colleagues, because you know, they're actually putting skin in

1129
00:52:46,800 --> 00:52:49,520
Speaker 3: the game, and they've also helped me make good career

1130
00:52:49,600 --> 00:52:50,600
Speaker 3: decisions and judgments.

1131
00:52:51,000 --> 00:52:54,600
Speaker 2: It's such an interesting observation you're making because we sort

1132
00:52:54,640 --> 00:52:59,440
Speaker 2: of forget how clients force us to rethink certain things.

1133
00:53:00,200 --> 00:53:02,120
Speaker 2: Or someone asked you a question where you think the

1134
00:53:02,200 --> 00:53:04,839
Speaker 2: answer is obvious, but you don't want to just give

1135
00:53:04,880 --> 00:53:07,160
Speaker 2: them a quick answer, so you do the homework and

1136
00:53:07,200 --> 00:53:10,080
Speaker 2: you discover, oh, this is a lot more complicated than

1137
00:53:10,080 --> 00:53:12,960
Speaker 2: I originally thought. I'm glad you brought that up because

1138
00:53:12,960 --> 00:53:16,279
Speaker 2: it comes up so frequently, and I think we don't

1139
00:53:16,280 --> 00:53:20,480
Speaker 2: pay it enough atention. It's really insightful. Let's talk about books.

1140
00:53:20,480 --> 00:53:22,240
Speaker 2: What are some of your favorites? What are you reading

1141
00:53:22,440 --> 00:53:23,000
Speaker 2: right now?

1142
00:53:23,600 --> 00:53:25,680
Speaker 3: You know, if it was up to my wife, I'd

1143
00:53:25,719 --> 00:53:28,160
Speaker 3: be reading like a book a week. She's a literary giant,

1144
00:53:28,200 --> 00:53:31,360
Speaker 3: so she's always handing me books. And I'm kind of

1145
00:53:31,360 --> 00:53:33,560
Speaker 3: an eclectic reader. But I would say some of my

1146
00:53:33,640 --> 00:53:35,960
Speaker 3: favorite books are The Boys in the Boat.

1147
00:53:37,239 --> 00:53:37,840
Speaker 1: Now series.

1148
00:53:37,880 --> 00:53:40,239
Speaker 3: Now also, yeah, there's a movie. I didn't watch the

1149
00:53:40,280 --> 00:53:43,719
Speaker 3: movie because the book was just so detailed. It was fantastic.

1150
00:53:44,360 --> 00:53:47,920
Speaker 3: Like all the classic books, my favorite was Catcher.

1151
00:53:47,680 --> 00:53:48,240
Speaker 1: In the Rye.

1152
00:53:48,480 --> 00:53:51,160
Speaker 3: It's kind of a coming out of age story, you know,

1153
00:53:51,960 --> 00:53:53,960
Speaker 3: animal farm and those types of things, and then like

1154
00:53:54,000 --> 00:53:56,840
Speaker 3: the trashy type stuff, you know, like one of my

1155
00:53:56,920 --> 00:54:00,000
Speaker 3: favorites of all time still to this day is The Firm.

1156
00:54:00,040 --> 00:54:02,840
Speaker 3: If you remember reading the John Grisham novel became a

1157
00:54:02,960 --> 00:54:04,880
Speaker 3: Tom Kruise move. Yeah, but I mean, like so like

1158
00:54:04,960 --> 00:54:06,920
Speaker 3: you know, that's it's a gamut of it right now.

1159
00:54:07,719 --> 00:54:10,279
Speaker 3: I mean, I read so much for work. I don't

1160
00:54:10,320 --> 00:54:12,600
Speaker 3: probably read enough books, Like day to day, but I'd

1161
00:54:12,640 --> 00:54:13,239
Speaker 3: like to read more.

1162
00:54:13,680 --> 00:54:17,880
Speaker 2: Huh really interesting. Our final two questions, what sort of

1163
00:54:17,920 --> 00:54:21,320
Speaker 2: advice would you give to a recent college grad interest

1164
00:54:21,360 --> 00:54:22,880
Speaker 2: in the career in investing.

1165
00:54:24,160 --> 00:54:28,400
Speaker 3: Well, the advice I do give them is just, really,

1166
00:54:28,480 --> 00:54:30,080
Speaker 3: this is not a sexy business.

1167
00:54:30,360 --> 00:54:33,759
Speaker 1: Okay, this is this is a grinder business.

1168
00:54:34,160 --> 00:54:36,400
Speaker 3: So if you come into this business, understand, like we

1169
00:54:36,440 --> 00:54:39,479
Speaker 3: talked earlier, you're gonna be wrong a lot. You gotta

1170
00:54:39,520 --> 00:54:41,680
Speaker 3: have some humility. You're gonna be a lot of highs

1171
00:54:41,680 --> 00:54:44,600
Speaker 3: and lows. When things are feeling really good, take it

1172
00:54:44,640 --> 00:54:47,520
Speaker 3: down a notch. When things are feeling really horrible, don't

1173
00:54:47,719 --> 00:54:50,360
Speaker 3: you know, kill yourself. And it's just it's gonna be

1174
00:54:50,440 --> 00:54:55,400
Speaker 3: a roller coaster. And it takes a long time to

1175
00:54:55,480 --> 00:54:59,040
Speaker 3: become even close to being a domain expert in anything

1176
00:54:59,120 --> 00:55:01,400
Speaker 3: in this business. There's some many smart people. There's so

1177
00:55:01,480 --> 00:55:04,279
Speaker 3: much changing all the time. You know, you got to

1178
00:55:04,320 --> 00:55:07,040
Speaker 3: put ten years in before you know anything. And I

1179
00:55:07,080 --> 00:55:09,520
Speaker 3: think that, you know, I think that's really good advice

1180
00:55:09,560 --> 00:55:11,360
Speaker 3: to a young person. I wish I had had that advice,

1181
00:55:11,440 --> 00:55:13,960
Speaker 3: because you know, we're all ball eyed coming out of

1182
00:55:13,960 --> 00:55:15,840
Speaker 3: college thinking we're going to change the world, and the

1183
00:55:15,880 --> 00:55:17,799
Speaker 3: reality is this is a this is a long road.

1184
00:55:17,840 --> 00:55:19,919
Speaker 3: I mean thirty five years, I'm still learning every day.

1185
00:55:20,719 --> 00:55:24,040
Speaker 2: Really interesting answer. And our final question, what do you

1186
00:55:24,080 --> 00:55:26,600
Speaker 2: know about the world of investing today you wish you

1187
00:55:26,680 --> 00:55:29,279
Speaker 2: knew back in nineteen eighty nine when you were first

1188
00:55:29,360 --> 00:55:30,120
Speaker 2: getting started.

1189
00:55:31,280 --> 00:55:32,520
Speaker 3: Well, I guess part of it is what I just

1190
00:55:32,560 --> 00:55:35,600
Speaker 3: said that it's a you know, it's not a sprint,

1191
00:55:35,760 --> 00:55:41,480
Speaker 3: it's a marathon. You know, cut yourself some slack along

1192
00:55:41,520 --> 00:55:44,759
Speaker 3: the way. You're going to make some wrong turns, and

1193
00:55:44,800 --> 00:55:50,480
Speaker 3: I would say, enjoy it, you know, because it's it's

1194
00:55:50,600 --> 00:55:53,200
Speaker 3: it's a journey, and it's a journey not just about

1195
00:55:53,280 --> 00:55:54,799
Speaker 3: like the people you're working with and the people you're

1196
00:55:54,800 --> 00:55:57,719
Speaker 3: helping your clients. It's joarning about yourself. This is a

1197
00:55:57,760 --> 00:56:00,440
Speaker 3: struggle with yourself. I mean, figuring out markets is an

1198
00:56:00,440 --> 00:56:03,080
Speaker 3: internal battle. It's like probably the book I should have

1199
00:56:03,120 --> 00:56:06,319
Speaker 3: mentioned was Reminiscences of a Stock Operator I have. I've

1200
00:56:06,320 --> 00:56:08,440
Speaker 3: read that like five times and I still go back

1201
00:56:08,440 --> 00:56:09,719
Speaker 3: and refer to it sometimes.

1202
00:56:09,880 --> 00:56:12,560
Speaker 2: I call that the first behavioral economics book.

1203
00:56:13,120 --> 00:56:15,600
Speaker 3: I would agree, and it's a fictional character, but it's

1204
00:56:15,600 --> 00:56:18,640
Speaker 3: a real life experience of just how it goes down

1205
00:56:19,640 --> 00:56:25,520
Speaker 3: and understanding your faults, your own fault. Understanding your weaknesses

1206
00:56:25,560 --> 00:56:27,920
Speaker 3: and your strengths, you know when to press it when

1207
00:56:27,960 --> 00:56:30,520
Speaker 3: not depress it. And then and then you know, unfortunately

1208
00:56:30,560 --> 00:56:32,600
Speaker 3: and that story ends up with you know, killing himself

1209
00:56:33,160 --> 00:56:36,080
Speaker 3: because it just it eats a way too. So that's

1210
00:56:36,120 --> 00:56:37,919
Speaker 3: that's really what I wish I know thirty years ago,

1211
00:56:37,960 --> 00:56:39,960
Speaker 3: like it's gonna it's gonna take a pound of.

1212
00:56:39,880 --> 00:56:43,600
Speaker 2: Flesh, right, Really interesting, Mike, thank you for being so

1213
00:56:43,760 --> 00:56:47,880
Speaker 2: generous with your time. We have been speaking with Mike Wilson,

1214
00:56:48,560 --> 00:56:52,760
Speaker 2: chief US equity strategist and chief investment officer of Morgan Stanley.

1215
00:56:53,120 --> 00:56:55,799
Speaker 2: If you enjoy this conversation, check out any of the

1216
00:56:55,840 --> 00:56:59,520
Speaker 2: five hundred or so we've done over the past ten years.

1217
00:57:00,080 --> 00:57:03,799
Speaker 2: You can find those at iTunes, Spotify, YouTube, wherever you

1218
00:57:03,880 --> 00:57:08,319
Speaker 2: find your favorite podcast. And check out my new podcast,

1219
00:57:08,520 --> 00:57:13,280
Speaker 2: At the Money, short ten minute conversations with experts about

1220
00:57:13,360 --> 00:57:17,160
Speaker 2: everything that affects you and your money, earning it, spending it,

1221
00:57:17,400 --> 00:57:21,320
Speaker 2: and most importantly, investing it At the Money in the

1222
00:57:21,400 --> 00:57:25,080
Speaker 2: Masters and Business podcast feed. I would be remiss if

1223
00:57:25,120 --> 00:57:27,480
Speaker 2: I did not thank the crack team that helps us

1224
00:57:27,520 --> 00:57:30,840
Speaker 2: put these conversations together each week. John Wasserman is my

1225
00:57:31,000 --> 00:57:34,400
Speaker 2: audio engineer. A Tick of Albron is my project manager.

1226
00:57:34,560 --> 00:57:38,440
Speaker 2: Anna Luke is my producer. Sean Russo is my researcher.

1227
00:57:38,880 --> 00:57:41,760
Speaker 2: Sage Bauman is the head of podcasts at Bloomberg.

1228
00:57:42,320 --> 00:57:43,520
Speaker 1: I'm Barry Rayhelts.

1229
00:57:43,880 --> 00:57:48,320
Speaker 2: You've been listening to Masters in Business on Bloomberg Radio.