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

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Speaker 1: My guest today is somebody who I know for a

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Speaker 1: very long time. Her name is liz Ane Sandres, and

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Speaker 1: she's the chief market strategist for a little outfit called

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Speaker 1: Charles Schwab that is running several trillion dollars in client assets.

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Speaker 1: Way back when I began doing media, the very first

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Speaker 1: television show I did was with a gentleman named Larry Cudlow,

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Speaker 1: and it was done in this tiny, little hole of

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Speaker 1: a studio in Englewood, New Jersey. Not the big, giant

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Speaker 1: modern studio that you know today, but it was really

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Speaker 1: kind of a small office park. And I had showed up,

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Speaker 1: probably a little early because of traffic getting there from Manhattan.

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Speaker 1: And while I was in the green room waiting to

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Speaker 1: go on the air, it was live to tape. Over

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Speaker 1: the course of an hour, I started drinking diet coke

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Speaker 1: and the next thing you know, I finish two cans

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Speaker 1: of soda and I get up to go to the

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Speaker 1: bathroom when the producer comes in and says, Okay, let's go,

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Speaker 1: it's live. But I have to no, no, it's now,

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Speaker 1: it's live. So I'm hyper caffeinated. I'm sitting at this

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Speaker 1: round table. There's Larry Cudlow to my left, which is

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Speaker 1: an unusual place for him to be because he's usually

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Speaker 1: to everybody's right. And they're directly across from me is

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Speaker 1: liz Ane Sanders. And a friend who had been doing

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Speaker 1: television for a long time gave me a little bit

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Speaker 1: of advice. He had said, pick something to focus on,

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Speaker 1: and don't dart your eyes, and don't look nervous. Just

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Speaker 1: focus on that one thing. And liz Anne began speaking,

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Speaker 1: and she had the whitest teeth I had ever seen.

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Speaker 1: She explains how her teeth cut so white during our interview.

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Speaker 1: The secret is no coffee. But anyway, during the show,

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Speaker 1: I just fixated on this. Oh my god, look at

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Speaker 1: those white choppers. She's so articulate, she's so beautiful, and

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Speaker 1: her teeth are so damn white. It's it's incredible. So

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Speaker 1: that was my first experience doing television. I managed not

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Speaker 1: to throw up on the glass table, which was a

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Speaker 1: genuine possibility. I know these days, Uh, many of your

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Speaker 1: favorite TV pundits looked so comfortable and casual on screen.

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Speaker 1: The first time you do it, it's kind of a

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Speaker 1: nerve wracking experience. Anyway, I had a great time chatting

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Speaker 1: with Liz. She has an amazing background, from Marty's Wide

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Speaker 1: who was a legend on Wall Street, to Lewis Ruth Kaiser,

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Speaker 1: now to Charlie Schwab. I mean talk about being blessed

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Speaker 1: with working with amazing people. She has had just an

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Speaker 1: unusual background and not what you typically expects. Never really

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Speaker 1: ran into the old boys club, never really ran into

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Speaker 1: the sort of stereotypical, misogynistic Wall Street ways that we've

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Speaker 1: heard about over the years. She considers itself very fortunate,

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Speaker 1: and there have been several of our other female guests

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Speaker 1: who have referenced her as you know, a a um,

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Speaker 1: one of the pioneers who basically cleared a path for

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Speaker 1: them to become strategists and analysts and others. So, without

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Speaker 1: any further ado or me babbling on, here's my conversation

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Speaker 1: with Charles Schwab's liz An Saunders. This is Masters in

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

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Speaker 1: this week is liz An Saunders. She is the chief

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Speaker 1: investment strategist at Charles Schwab. Liz, Welcome to Bloomberg thanks

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Speaker 1: very so, Liz, and I go way back. In fact,

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Speaker 1: the very first television appearance I ever did, you're the

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Speaker 1: other guest with Larry Cudlow about a hundred years ago,

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Speaker 1: was was it Cudlow and Company? Or with that it's

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Speaker 1: like Cudlo and Kramer. No, it was Cudlow and Clock.

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Speaker 1: So which which was before Cudlow Report? Right? Was that?

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Speaker 1: The thin after? I think it went Cudlo and Kramer,

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Speaker 1: Cudlow and Company, and then the Cudlow report that they

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Speaker 1: were changing it constantly. Before we digress too far, let

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Speaker 1: me give you a little bit of background as to

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Speaker 1: whom my guess is. She was named Smart Money's Power

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Speaker 1: thirty list of most influential people on Wall Street, one

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Speaker 1: of the most one of the twenty five most powerful

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Speaker 1: women in finance by American Banker, and she was a

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Speaker 1: regular panelist and actually was a guest host on PBSS

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Speaker 1: Wall Street Week with Louis Rukaiser. Thank you so much

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Speaker 1: for joining us, Thanks for having me. So let's start

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Speaker 1: with the real basics. How did you get into the

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Speaker 1: financial services industry? You know, it was a little bit

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Speaker 1: of a fluke. I went to undergraduate school University of Delaware,

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Speaker 1: go Hens, Blue Hens, Colue, Hens, home of Flacco and

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Speaker 1: Gannon and some other notables, and I had a well.

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Speaker 1: I started with what was effectively a double major in

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Speaker 1: economics and political science, which ultimately became a major in

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Speaker 1: international relations, not that I had any idea what I

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Speaker 1: wanted to do at the time. With that thought about

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Speaker 1: going to graduate school right after undergraduate little from political science.

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Speaker 1: But then I thought, I took my g R E

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Speaker 1: S and I thought, what am I doing? Um, Why

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Speaker 1: am I going to full time to school again? Not

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Speaker 1: knowing what I want to do. So I put that

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Speaker 1: on hold. I said, let me let me go up

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Speaker 1: to New York. I knew I wanted to live in

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Speaker 1: and be in New York, and just hit the pavement.

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Speaker 1: So I had grandparents living at the time, my families

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Speaker 1: from Brooklyn. So went up lived with my grandfather for

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Speaker 1: a couple of weeks and reached out to a couple

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Speaker 1: of head hunters that we knew that did entry level

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Speaker 1: positions and interviewed at every variety of firm marketing firms,

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Speaker 1: at agencies, Wall Street firms. And there's something just clicked

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Speaker 1: about this interview I had with those Avatar organization, and

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Speaker 1: I had developed some familiarity with Marty's Wage during my

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Speaker 1: college years, so I was a little bit star struck.

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Speaker 1: Really like the people, like the size of the firm,

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Speaker 1: like their willingness and interest in the past at promoting

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Speaker 1: from within. So I started there and and I was

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Speaker 1: there for thirteen years and went to business school at night.

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Speaker 1: So let's talk a little bit about Marty's Wig for

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Speaker 1: the young uns who are listening who may not know

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Speaker 1: who he was. Zwig was really a legend on Wall legend,

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Speaker 1: truly a legend. And and I I was introduced to

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Speaker 1: Marty and then interestingly Lewis Ruckiser and Wall Street Week

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Speaker 1: during college when one of my tas for I think

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Speaker 1: a macro economics course suggested watching Wall Street Week on

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Speaker 1: Friday nights as a good way half hour before going

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Speaker 1: out at night, before starting to drink, to get a

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Speaker 1: recap of what happened that week. So in other words,

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Speaker 1: you would you would watch Ruckeiser and then you would

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Speaker 1: have to get a drink, and then I would, now, well,

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Speaker 1: then I would go out and uh and have a

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Speaker 1: differ and kind of fun to do what college students.

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Speaker 1: And Marty had been a regular panelist really from the

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Speaker 1: show's inception in the early nineteen seventies. So that was

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Speaker 1: how I became familiar with Marty and then joined in

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Speaker 1: nineteen eighty six, which to your point, he was he

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Speaker 1: was already godlike in the business, had one best selling

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Speaker 1: book under his belt, was writing those wage forecasts, which

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Speaker 1: Hulbert had ranked the number one newsletter. He had wagged

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Speaker 1: him into Partners, was one of the first hedge funds.

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Speaker 1: He had branded mutual funds, and he was he was

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Speaker 1: really iconic even at that point. And for people who

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Speaker 1: still may not know who he is, go to YouTube

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Speaker 1: and google Marty's wage ru Kaiser seven oct a week

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Speaker 1: before the crib Friday, before we before the broadcast Friday,

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Speaker 1: but it was recorded record that day and and he

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Speaker 1: basically explains why, after being fairly constructive all year, pretty

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Speaker 1: much flipped and said, I'm really concerned about the state

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Speaker 1: of this market, and I think it's set up for

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Speaker 1: a serious, serious correction. He said crash. Did he say crash?

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Speaker 1: Is that what it was? And then on Monday it

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Speaker 1: was Black Monday, And and not only did he suggest

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Speaker 1: that the crash was coming, he laid out very precisely

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Speaker 1: what he thought. The next few days thereafter would look

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Speaker 1: like the retest of the lows and then a massive rebound.

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Speaker 1: And you know, we were a tactical asset allocation for

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Speaker 1: a market timing firm, and we had been effectively fully

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Speaker 1: invested in equities leading into the peak in August and

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Speaker 1: then started to trim back exposure. We're only about invested

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Speaker 1: on the eve of the crash, and then the day

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Speaker 1: after the crash we started buying. So here I am

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Speaker 1: twenty two years old, brand new in the business, thinking, well,

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Speaker 1: what's the big deal? You just figure out before when

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Speaker 1: it's going to crash, get out, and then everything goes

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Speaker 1: on sale, get back in, done? What could be? What

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Speaker 1: are all these people complaining about? My naivete assumed that

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Speaker 1: that was something many could do easily, and we know

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Speaker 1: that's something that's that's so fascinating. You know. Dave Rosenberg,

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Speaker 1: who I know, you know, tells the story of his

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Speaker 1: first day in the private sector after having been a

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Speaker 1: government economist, was essentially that Monday, and he just walked

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Speaker 1: around astonished at at the sheer turmoil and panic. It

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Speaker 1: was really incredible. But you had a very different experience.

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Speaker 1: We had a different experience because we weren't facing massive

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Speaker 1: losses and client portfolios. We weren't looking at the potential

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Speaker 1: demise of the firm. Quite the contrary. You know, we

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Speaker 1: had so nailed it. And I love to use the

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Speaker 1: term week now as if I had anything to do

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Speaker 1: with it at twenty two years old. But it was such,

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Speaker 1: it was such a boom for everything Marty did and

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Speaker 1: and the success of our firm and performance that year,

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Speaker 1: that I had a very different perspective than a lot

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Speaker 1: of people, to say the least. We're speaking with liz

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Speaker 1: Anne Saunders of Charles Schwab. When we continue our conversation,

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Speaker 1: we'll disc us the role these days of women on

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Speaker 1: Wall Street. You're listening to Masters in Business with Barry

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Speaker 1: rid Holts on Bloomberg Radio. I'm Barry rid Holts. You're

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Speaker 1: listening to Masters in Business on Bloomberg Radio. My special

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Speaker 1: guest today is liz Anne Saunders. She is the chief

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Speaker 1: investment strategist at Charles Schwab, which these days is running

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Speaker 1: how much money? Well, we have client assets of about

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Speaker 1: two and a half trillion, not too shabby, not too shabby,

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Speaker 1: and um, you also have a number of divisions where

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Speaker 1: you're managing money directly yourself. So yes, personally. We made

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Speaker 1: acquisition about four years ago of what at the time

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Speaker 1: was called Windward Investments, now called Windhaven Investments. It's a

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Speaker 1: global tactical asset allocation firm managing via e t f

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Speaker 1: S model driven and uh I joined the team as

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Speaker 1: chair of the Investment committee last June in addition to

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Speaker 1: my chief investment strategist role at SCHWAB. So does the

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Speaker 1: experience with Marty help you? It does. In fact, when

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Speaker 1: when we were in the early stages of of disseminating

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Speaker 1: the change and the information about me joining the team,

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Speaker 1: there was this assumption that the main reason why I

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Speaker 1: was tapped for this role was because I was known

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Speaker 1: in the retail world, certainly among our investors, and that

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Speaker 1: it would be an easy transition without a lot of

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Speaker 1: people realizing that my background through my thirteen years at

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Speaker 1: swy Avatar was in tactical ascid allocation model driven. In fact,

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Speaker 1: the founder of of wind Haven, Steve Kokierrow, when putting

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Speaker 1: together the model many many many years ago and writing

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Speaker 1: the white paper associated with how the model looks at

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Speaker 1: asset classes it makes its decisions, he actually cited Marty

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Speaker 1: in a couple of occasions, particularly the famous line of

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Speaker 1: Marty's the phrase he coined, which is don't fight the Fed.

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Speaker 1: Don't fight the Fed. And there have been people fighting

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Speaker 1: the Fed this entire cycle. I can't begin to count

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Speaker 1: how often I see an email about the FEDS doing

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Speaker 1: this and that, and well, okay, but the market's up two.

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Speaker 1: So what you're saying is this hasn't happened yet. Is

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Speaker 1: what you're fearing certainly hasn't happened. And the response is

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Speaker 1: always just you wait, well it's six years. It's anybody

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Speaker 1: who listened to your advice has either lost their money

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Speaker 1: or been fired. You you can't as a professional, you

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Speaker 1: just can't ignore that sort of move. You can't now.

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Speaker 1: I'm also, though, I guess, in a in a bit

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Speaker 1: of a middle camp in that absolutely don't fight the

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Speaker 1: FED and their provision of liquidity and monetary conditions absolutely

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Speaker 1: as always an important driver behind moves in in the

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Speaker 1: equity market. But I also am not in the camp

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Speaker 1: that believes it's only been three rounds of quantitative easy

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Speaker 1: and exert that has been the support under the stock market.

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Speaker 1: I think many of the other traditional fundamentals have also

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Speaker 1: been supports, So I don't know they would have gotten

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Speaker 1: this same power and magnitude of gain and consistency of

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Speaker 1: performance had it not been at the FED. But it's

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Speaker 1: one of many conditions that have allowed the market to

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Speaker 1: do what it's So let's let's go over some of those.

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Speaker 1: As long as as as we're going down this path,

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Speaker 1: let's talk a little bit about earnings. Right, we saw

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Speaker 1: an absolute earnings collapse, they came snapping back. Are earning

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Speaker 1: supportive of this sort of Earnings are up very consistent

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Speaker 1: with what the appreciation and the market has been looking

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Speaker 1: at past cycles, and you've had valuation expansion off of

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Speaker 1: the you know, the epic low in invaluations this time

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Speaker 1: actually post stated at the two thousand and nine low.

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Speaker 1: You ultimately got the low in pe s in two

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Speaker 1: thousand and ten. Just because the earning cycle doesn't always

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Speaker 1: match the market cycle, earnings accelerated at that point faster

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Speaker 1: than the market. So despite a rally, PE ratios actually fell.

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Speaker 1: Markets went up and made stocks look cheaper, which is

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Speaker 1: not only that, but corporations have been such huge buyers

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Speaker 1: of their own stocks too. I often get the question

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Speaker 1: because I talked a lot about investor trends and investor

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Speaker 1: sentiment and the persistent skepticism by individual investors, and the

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Speaker 1: lack of interest in the market and very weak mutual

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Speaker 1: fund flows, all of those facets that we look at

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Speaker 1: all the time. Then I get asked, Okay, well, it's

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Speaker 1: obviously hasn't been the individual that's been the big buyer.

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Speaker 1: Hasn't been the hedge funds, hasn't been big institutions where

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Speaker 1: you're not seeing that in droves either. Hedge fund that

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Speaker 1: long exposure has not gone stratospheric really during this entire

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Speaker 1: bowl market, and we've seen that. We've seen that in

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Speaker 1: hedge fund performance grammatically underperformed, specifically because they didn't have

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Speaker 1: enough US equity and specifically in the last couple of years.

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Speaker 1: So even this many years into a rip roaring bull market,

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Speaker 1: there has been this pervasive skepticism where we have seen

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Speaker 1: consistent buying and has been the most powerful buyer supporting

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Speaker 1: this bull market has been companies themselves buying backgrounds. So

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Speaker 1: so do you track the number of shares or the

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Speaker 1: dollar amount? How significant is corporate share buy backs to

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Speaker 1: to the underlying rally. I think it's been. It's certainly

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Speaker 1: not the entire piece of it, but I think it

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Speaker 1: in terms of buying interest in the market. If you

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Speaker 1: look at the various faction traditional pension funds, um other

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Speaker 1: you know, mutual funds, hedge funds, even high frequency trading

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Speaker 1: firms they're in and at all the time. Or the

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Speaker 1: big wammy the individual investor. By far, its corporations that

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Speaker 1: have been the most consistent buyer. My colleague Josh Brown

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Speaker 1: calls that the relentless bid the combination of acid allocation

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Speaker 1: models which just buy every time money flows in the

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Speaker 1: share buy biocks that are going out there. And you know,

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Speaker 1: people forget, you've still been in a relentless bond bull

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Speaker 1: market and every time there's a rebalance, that's money that

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Speaker 1: flows out of bonds into equities. It's been amazing, It

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Speaker 1: has been amazing. So so let's let's continue along this

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Speaker 1: this path. Before we get into, um the role of

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Speaker 1: women on Wall Street, maybe we'll save that for a

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Speaker 1: little later. Let's talk a little bit about E t

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Speaker 1: F s versus passive investing. I know Schwab has a

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Speaker 1: number of different funds they men how significant is this

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Speaker 1: move towards passive and e t F s. So I

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Speaker 1: think what we're seeing at Schwab probably is fairly consistent

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Speaker 1: with the broader industry. I think we represent obviously a

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Speaker 1: good chunk of the of the industry. But at the

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Speaker 1: end of last year, e t f s that were

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Speaker 1: custodied at Schwab amounted to about two thirty billion dollars,

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Speaker 1: but traditional mutual funds were one point one trillion dollars,

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Speaker 1: So they're still big. Yes, Now the growth rate of

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Speaker 1: e t f s is much higher than the growth

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Speaker 1: rate of mutual funds. There's still positive growth rates, but

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Speaker 1: the growth rate is greatly exceeded in ETFs than than

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Speaker 1: than mutual funds. But mutual funds aren't going away anytime soon.

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Speaker 1: And I think the shift between active and passive to

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Speaker 1: some degree tracks a market cycle. When you're in a

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Speaker 1: fairly consistent, low drama equity US centric equity bowl market

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Speaker 1: like we've been in the last several years, that tends

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Speaker 1: to have investor shift more toward passive strategies. And we

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Speaker 1: actually think that there is a home for both in

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Speaker 1: portfolios that a lot of investors probably should be taking

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Speaker 1: a more passive approach UH indexing to UH whatever the

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Speaker 1: you know, whether it's brought market into caes or if

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Speaker 1: they want to take more of an endowment approach their

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Speaker 1: portfolios and have asset allocation across asset classes that historically

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Speaker 1: we're not that accessible. E t F s allow them that. However,

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Speaker 1: when you get into a less highly correlated, more volatile

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Speaker 1: market period, like I would argue we are in the

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Speaker 1: beginning of now, that's when you start to see some

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Speaker 1: active strategies start to do a little bit better. I'm

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

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Speaker 1: My special guest this week is liz An Saunders. She

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Speaker 1: is the chief strategist at Charles Schwab and when we

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Speaker 1: were talking earlier, I mentioned that you had been named

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Speaker 1: one of the twenty five most powerful women in Finance

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Speaker 1: by American Banker because of how you bench press room,

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Speaker 1: or maybe because us is that is it? It sometimes

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Speaker 1: feels that way, It sometimes feels. So I'm gonna give

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Speaker 1: you a quote that I really liked from Michelle Myers,

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Speaker 1: one of the other few women we've had on the show,

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Speaker 1: uh and the first being Shiela Bear of the FDI C.

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Speaker 1: But Michelle Myers said had cited the quote lack of

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Speaker 1: women at the top of the industry as a challenge

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Speaker 1: for women in finance. Do you agree with that? So

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Speaker 1: my view has always been from my perspective and the

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Speaker 1: career path I have chosen in this business, being a

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Speaker 1: woman has actually been a huge advantage. But my chosen

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Speaker 1: career path was not ultimately to be the CEO of

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Speaker 1: a major investment bank. So I think if if I

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Speaker 1: was trying to climb a ladder to that type of

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Speaker 1: senior management position, I probably would have a lot of

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Speaker 1: bruises on my head from the glass ceiling. It's just

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Speaker 1: not something I have encountered. And that's what I try

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Speaker 1: to impart to young women who I speak with. Just

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Speaker 1: in the last week, I've spoken at to universities my

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Speaker 1: alma mater graduate school as well as my son's current

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Speaker 1: college right now, spoke to two groups of of women

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Speaker 1: there and have encouraged them that there are great opportunities

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Speaker 1: for women on Wall Street. And I think the reason

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Speaker 1: why it's increasingly important going forward is that very soon

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Speaker 1: we are going to cross the point where women control

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Speaker 1: more of the wealth in this country than men do,

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Speaker 1: and they more often than not like to work with

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Speaker 1: with other women. So are you referring to the transition

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Speaker 1: that's taking place amongst the baby boomers. As that wealth

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Speaker 1: trans there's two wealth transfers that are going to take place,

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Speaker 1: on average, and I'm only speaking statistically on average, the

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Speaker 1: husband dies first. Men have a shorter lifespan. At that point,

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Speaker 1: the wife will end up holding all those assets, and

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Speaker 1: then those assets will eventually pass, much of them will

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Speaker 1: pass to the next generation. So and that next generation

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Speaker 1: there's more women graduating from college and graduate school than

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Speaker 1: there are men, so to the extent that that has

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Speaker 1: a tie to career and financial success, that that next

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Speaker 1: generation is likely to have a little bit of a

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Speaker 1: female bias as well amongst people in the industry or

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Speaker 1: just amongst whoever is inheriting those is ever inheriting those assets.

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Speaker 1: So there there's going to be control majority control of

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Speaker 1: the investible assets in this country by women within the

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Speaker 1: next several years. But isn't that true statistically for many

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Speaker 1: different things that involve women, that they're going to be

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Speaker 1: greater in numbers they're graduating college and greater numbers grad school.

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Speaker 1: Go down the list of things that were once frowned

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Speaker 1: upon within society that that really seems to be changing.

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Speaker 1: So the question for you is Joe's a woman starting

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Speaker 1: out in this industry still encounter the same sort of

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Speaker 1: obstacles that you did when you began, or you you

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Speaker 1: might have but got fortunate. A lot of it was, Um,

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Speaker 1: I was in the right place at the right time

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Speaker 1: and doing the right things in terms of the early

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Speaker 1: stages of my career. And of course I'm twenty nine

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Speaker 1: years in the business now, so I don't have direct

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Speaker 1: experience with what it's like today for women coming into

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Speaker 1: the business. I do think it's probably a little bit easier.

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Speaker 1: I just think the approach to gender differentiation on Wall

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Speaker 1: Street generically has changed from kind of the go go

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Speaker 1: days of the early eights the right when you when

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Speaker 1: you look at some of the more popular movies or

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Speaker 1: shows about that era of Wall Street, it is concentrated

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Speaker 1: in that era exaggerated, no question about that. But I

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Speaker 1: think that being a woman in this business, number one,

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Speaker 1: you're a minority, which has a negative tone to it,

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Speaker 1: that word, but it also means you're a little bit different.

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Speaker 1: And I think being a little bit different relative to

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Speaker 1: I don't know called the middle aged white guy that

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Speaker 1: dominates Wall Street is not necessarily a bad thing. It

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Speaker 1: it gives you that level of differentiation right out of

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Speaker 1: the blocks, before you've done anything or said anything. And

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Speaker 1: I I I hope that women do consider this as

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Speaker 1: an industry. To the point about women controlling more assets,

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Speaker 1: they like to work with other women. It's why I

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Speaker 1: think in the r i A space independent investment advisors,

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Speaker 1: there's a lot more women owned investment advisors and they're

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Speaker 1: very popular with other women investors because they like that camaraderie.

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Speaker 1: There tends to be more women are I A s.

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Speaker 1: Than there are female traders or female brokers. It's just

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Speaker 1: more conducive to that one on one RelA and I

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Speaker 1: to your point, I think that's the pocket of the

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Speaker 1: business that is still very very male dominated and probably

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Speaker 1: hard to infiltrate, which is trading desks and sales trading,

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Speaker 1: a position trading. And I'm not sure that changes in

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Speaker 1: in my career lifetime, but that wasn't an area I

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Speaker 1: was ever involved in, so it never hit me personally,

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Speaker 1: but I've certainly watched, you know, friends and colleagues have

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Speaker 1: a much more difficult time trying to infant infiltrate what

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Speaker 1: is still probably a boy's network. I started on a

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Speaker 1: training's desk, it was very rough and tumble, of a

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Speaker 1: lot of sharp elbows, And I don't know if that

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Speaker 1: is as much mail as it was just generally a

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Speaker 1: different philosophical approach the world. I'm Barry Ridholt. You're listening

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Speaker 1: to Masters in Business on Bloomberg Radio. My guest today

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Speaker 1: is liz Ane Saunders. She is the chief investment strategist

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Speaker 1: at Charles Schwab, managing two point something trillion dollars? Is

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Speaker 1: that right? You gonna have trillion? But I wouldn't managing yes, incline,

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Speaker 1: I don't think anybody is really managed trillion dollars that

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Speaker 1: at least not not that we're aware of. Um. So

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Speaker 1: let's talk a little bit about where we are in

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Speaker 1: the cycle and what you see as things that investors

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Speaker 1: are doing right and things that are are investors are

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Speaker 1: doing wrong. Let's let's start with the first question. When

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Speaker 1: when you look at an investment, how do you go

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Speaker 1: about evaluating that? What's your process? Like? Well, depends on

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Speaker 1: the investment. Most of my work that I do, uh

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Speaker 1: in my in my role as strategists at Schwab is

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Speaker 1: very top down foot view. So unlike my y Avatar

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Speaker 1: days when I was actually picking stock on a day

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Speaker 1: to day basis, that's largely not what I do right now,

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Speaker 1: so I'm looking at at major macro trends. But I

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Speaker 1: would say that the thing that I look for most,

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Speaker 1: whether it's at the industry level, the sector level, the

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Speaker 1: asset class level, is inflection points. And I think that

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Speaker 1: is one of the things that trips investors up more

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Speaker 1: than anything else, is not understanding the power of inflection

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Speaker 1: points and the fact that the market, the stock market

430
00:24:26,000 --> 00:24:29,280
Speaker 1: as a leading indicator, is going to often have its

431
00:24:29,359 --> 00:24:32,280
Speaker 1: best performance when it launches off one of those inflection points.

432
00:24:32,320 --> 00:24:33,640
Speaker 1: But if you think about it, if you think about

433
00:24:33,680 --> 00:24:37,480
Speaker 1: how the stock market relates to the economy, an inflection

434
00:24:37,520 --> 00:24:39,720
Speaker 1: point on the downside is the bottom of the V,

435
00:24:39,960 --> 00:24:42,679
Speaker 1: so when the data has stopped getting worse, but it's

436
00:24:42,720 --> 00:24:45,719
Speaker 1: only starting to get better. But by definition, the bottom

437
00:24:45,760 --> 00:24:47,920
Speaker 1: of an inflection point, that point at the V where

438
00:24:47,920 --> 00:24:50,760
Speaker 1: things turn. That's when the data is most ugly in

439
00:24:50,760 --> 00:24:53,600
Speaker 1: an absolute sense. You you don't have the benefit of

440
00:24:53,640 --> 00:24:55,760
Speaker 1: looking ahead to say, okay, we're at the bottom. We

441
00:24:55,800 --> 00:24:58,800
Speaker 1: know it's moving forward, but the market's job is to

442
00:24:58,920 --> 00:25:01,880
Speaker 1: find that point and move higher. And I think that's

443
00:25:01,880 --> 00:25:05,359
Speaker 1: what investors missed quite often as they because there's so

444
00:25:05,440 --> 00:25:08,280
Speaker 1: much emotional tie to our money that they want to

445
00:25:08,359 --> 00:25:12,120
Speaker 1: feel good about the data that surrounds them, the economic data,

446
00:25:12,160 --> 00:25:15,560
Speaker 1: the earnings data, all the broad fundamental data that they

447
00:25:15,600 --> 00:25:18,560
Speaker 1: miss off. They missed those opportunities because they want that

448
00:25:18,640 --> 00:25:21,399
Speaker 1: confirmation to come from the data that isn't going to

449
00:25:21,480 --> 00:25:24,880
Speaker 1: confirm until it's largely well into the process. So let's

450
00:25:24,920 --> 00:25:27,520
Speaker 1: use the last cycle as an example. Market bottomed in

451
00:25:27,680 --> 00:25:31,560
Speaker 1: March o nine. The recession officially ended when June nine,

452
00:25:31,640 --> 00:25:34,879
Speaker 1: Juno and we didn't learn that from the nb R

453
00:25:35,000 --> 00:25:38,920
Speaker 1: until it was I think months later, it was September.

454
00:25:40,320 --> 00:25:42,840
Speaker 1: So if you waited to find out that the old

455
00:25:42,920 --> 00:25:48,240
Speaker 1: clear whistle had been blown, you probably missed or so absolutely.

456
00:25:48,359 --> 00:25:51,840
Speaker 1: And I remember I had an interesting appearance on Good

457
00:25:51,840 --> 00:25:54,840
Speaker 1: Morning America in May of two thousand and nine, and

458
00:25:54,880 --> 00:25:57,280
Speaker 1: it was one Diane Sawyer was still hosting the show,

459
00:25:57,760 --> 00:25:59,800
Speaker 1: and she did the pre interview with me that i'd

460
00:25:59,800 --> 00:26:01,439
Speaker 1: be war and I was scheduled to come on to

461
00:26:01,480 --> 00:26:04,359
Speaker 1: talk not about the recession of the market, but really

462
00:26:04,400 --> 00:26:08,520
Speaker 1: about the A b c's of credit to fault swaps.

463
00:26:08,640 --> 00:26:11,000
Speaker 1: I was coming on to attempt to explain to their

464
00:26:11,040 --> 00:26:14,639
Speaker 1: more broad audience what these derivatives were, that we're causing

465
00:26:14,720 --> 00:26:17,399
Speaker 1: so much trouble. Yet at the end of our conversation

466
00:26:17,440 --> 00:26:19,320
Speaker 1: the night before, she said, so, do you think this

467
00:26:19,359 --> 00:26:21,520
Speaker 1: thing will ever end? And I said, well, I think

468
00:26:21,560 --> 00:26:24,320
Speaker 1: the bear market's already over, and I think the recession

469
00:26:24,400 --> 00:26:27,040
Speaker 1: is ending. I think it's probably over now, maybe a

470
00:26:27,080 --> 00:26:29,600
Speaker 1: month from now, maybe two months from now. So unbeknounts

471
00:26:29,640 --> 00:26:31,159
Speaker 1: to me. The next morning, I go on air and

472
00:26:31,240 --> 00:26:33,679
Speaker 1: she introduces me by saying, Liz Anna is here to

473
00:26:33,880 --> 00:26:37,719
Speaker 1: declare the recession officially over. And I laughed. I said, well,

474
00:26:37,800 --> 00:26:40,199
Speaker 1: last time I checked, I had no official capacity to

475
00:26:40,320 --> 00:26:44,240
Speaker 1: declare recessions. Um, you know, having started her over, I

476
00:26:44,320 --> 00:26:47,040
Speaker 1: got so much hate mail from that appearance, from people

477
00:26:47,160 --> 00:26:51,000
Speaker 1: saying everything from your an idiot two. Isn't it easy

478
00:26:51,040 --> 00:26:53,000
Speaker 1: for you to say things are getting better because you

479
00:26:53,080 --> 00:26:56,840
Speaker 1: have a job and you're employed, And but the point

480
00:26:56,880 --> 00:26:59,159
Speaker 1: I was trying to make was I think things have

481
00:26:59,240 --> 00:27:01,800
Speaker 1: stopped getting but at the point they stopped getting worse,

482
00:27:01,960 --> 00:27:04,919
Speaker 1: they are at their most brutal point in time. It

483
00:27:05,000 --> 00:27:08,359
Speaker 1: still looks horrible. You know. The funny thing is about

484
00:27:08,480 --> 00:27:13,160
Speaker 1: the pushback you get. I did a piece some time

485
00:27:13,200 --> 00:27:16,440
Speaker 1: ago and it was not supposed to be a market call.

486
00:27:16,920 --> 00:27:20,040
Speaker 1: It was simply, hey, let's do an evaluation of the

487
00:27:20,119 --> 00:27:22,240
Speaker 1: dow and figure out where it was. And this was

488
00:27:22,920 --> 00:27:25,720
Speaker 1: later oh six or early o seven, and and basically

489
00:27:25,760 --> 00:27:29,120
Speaker 1: you come up with a number, housing and banking all

490
00:27:29,160 --> 00:27:31,920
Speaker 1: the stuff, and you come up with a number about hundred.

491
00:27:32,240 --> 00:27:35,000
Speaker 1: And at the time, I want to say the dow

492
00:27:35,160 --> 00:27:38,840
Speaker 1: was twelve thousand or thirteen thousand, and the pushback is

493
00:27:38,960 --> 00:27:41,119
Speaker 1: oh my, And and then within the piece it was

494
00:27:41,560 --> 00:27:44,560
Speaker 1: and by the way, if we break ten thousand on

495
00:27:44,600 --> 00:27:47,320
Speaker 1: the way to hundred, hey, who knows? You could see

496
00:27:47,359 --> 00:27:49,960
Speaker 1: sixty eight hundred. It was like buried. It was not

497
00:27:50,480 --> 00:27:53,080
Speaker 1: the piece was in, Hey, we're going to down sixty hundred.

498
00:27:53,119 --> 00:27:56,920
Speaker 1: It's hey, let's figure out what the look at. And

499
00:27:57,080 --> 00:27:59,760
Speaker 1: so for two years all I heard was your perma bear,

500
00:27:59,840 --> 00:28:03,040
Speaker 1: you hate to you asked you. Hey. So around the

501
00:28:03,080 --> 00:28:05,320
Speaker 1: same time we had the bullish call, it was just

502
00:28:05,440 --> 00:28:08,520
Speaker 1: every indicator we tracked was pinned all the way, like

503
00:28:08,600 --> 00:28:12,520
Speaker 1: the VU meters. For you kids, that's an analog meter

504
00:28:12,760 --> 00:28:15,960
Speaker 1: on the old stereos and for you younger kids, that's

505
00:28:15,960 --> 00:28:19,560
Speaker 1: how people used to listen to music. But um, but

506
00:28:19,920 --> 00:28:22,760
Speaker 1: at that point suddenly I'm a perma bowl and it

507
00:28:22,880 --> 00:28:25,520
Speaker 1: dawned on me. It's like, oh, these people don't care

508
00:28:25,640 --> 00:28:29,120
Speaker 1: anything about what I'm saying. They're seeing the world through

509
00:28:29,160 --> 00:28:33,320
Speaker 1: a pained, money losing perspective of whatever is going on

510
00:28:33,400 --> 00:28:39,680
Speaker 1: is hurting their portfolio, and therefore it's Liz and Sander's fault, right.

511
00:28:41,080 --> 00:28:44,320
Speaker 1: So so I I've learned. I've learned to use that

512
00:28:44,600 --> 00:28:50,400
Speaker 1: as a you know, a bit of confirmation. When when

513
00:28:50,440 --> 00:28:53,240
Speaker 1: you were out on a limb and you know, Herb

514
00:28:53,240 --> 00:28:56,400
Speaker 1: Greenberg used to call it, the hate ometer was spinning

515
00:28:56,400 --> 00:28:58,920
Speaker 1: out of control. That's usually a good sign that you're

516
00:28:58,920 --> 00:29:02,600
Speaker 1: onto something. You know, Sir Baron Rothschild, by when there's by,

517
00:29:02,600 --> 00:29:04,480
Speaker 1: when there's blood in the street, even if it's your own,

518
00:29:04,640 --> 00:29:07,040
Speaker 1: any number of Warren Buffett quotes, I want to buy

519
00:29:07,040 --> 00:29:10,240
Speaker 1: when everybody else is selling. There's a reason why the

520
00:29:10,360 --> 00:29:13,440
Speaker 1: great investors have coined phrases like that. They're trying to

521
00:29:13,480 --> 00:29:15,480
Speaker 1: get the heart of what we're talking about. Let me

522
00:29:15,520 --> 00:29:19,160
Speaker 1: tell you one other absolutely dead true story, and I

523
00:29:19,200 --> 00:29:22,160
Speaker 1: won't name names to protect the not so innocent at

524
00:29:22,160 --> 00:29:25,760
Speaker 1: the time. Now I'm not saying names. The weekend, the

525
00:29:25,920 --> 00:29:29,080
Speaker 1: literally the weekend before the bottom in March of oh nine,

526
00:29:29,200 --> 00:29:31,560
Speaker 1: which was March nine was the bottom. So whatever, whatever

527
00:29:31,600 --> 00:29:34,240
Speaker 1: the Friday or Saturday night date was. My husband and

528
00:29:34,320 --> 00:29:35,760
Speaker 1: I are at a cocktail party and we live in

529
00:29:35,840 --> 00:29:38,360
Speaker 1: Dairy in Connecticut, which had the lovely distinction in two

530
00:29:38,360 --> 00:29:40,560
Speaker 1: thousand and eight of being named made the cover of

531
00:29:40,600 --> 00:29:43,240
Speaker 1: Business Week as the number one town in the country

532
00:29:43,280 --> 00:29:45,880
Speaker 1: most affected by the financial crisis based on a certain

533
00:29:45,920 --> 00:29:49,720
Speaker 1: population in below. So I'm surrounded by Wall Street people.

534
00:29:49,760 --> 00:29:52,239
Speaker 1: Our entire circle of friends are Wall Street people. So

535
00:29:52,320 --> 00:29:55,600
Speaker 1: the conversation, naturally at that time was about what was

536
00:29:55,640 --> 00:29:57,800
Speaker 1: going on. And one of my friends who has been

537
00:29:57,840 --> 00:30:01,400
Speaker 1: in the business thirty five years, said, las Anne, I

538
00:30:01,080 --> 00:30:04,240
Speaker 1: I don't envy you. I think there's no reason ever

539
00:30:04,280 --> 00:30:06,320
Speaker 1: again why an individual investor would want to be in

540
00:30:06,320 --> 00:30:08,960
Speaker 1: the market, and it has to make you wonder about

541
00:30:09,280 --> 00:30:14,040
Speaker 1: the sustainability of schwab and I I sort of looked

542
00:30:14,040 --> 00:30:15,920
Speaker 1: at him, and my husband looked at me kind of funny,

543
00:30:15,960 --> 00:30:17,480
Speaker 1: and I said, well, I you know, I beg to

544
00:30:17,520 --> 00:30:20,760
Speaker 1: differ um. In fact, I think that the conditions are

545
00:30:20,800 --> 00:30:22,640
Speaker 1: starting to look pretty interesting. We get in the car

546
00:30:22,680 --> 00:30:24,880
Speaker 1: and my husband looked at me. He said, did you

547
00:30:24,920 --> 00:30:27,080
Speaker 1: hear it, and I knew immediately what he meant. I said,

548
00:30:27,120 --> 00:30:28,920
Speaker 1: you mean the bell ringing? He said, I knew you

549
00:30:28,920 --> 00:30:30,880
Speaker 1: were thinking that as soon as he said it. Which

550
00:30:30,920 --> 00:30:32,920
Speaker 1: we all know the phrase they never ring a bell

551
00:30:33,000 --> 00:30:35,959
Speaker 1: at tops and bottoms, but that was one of those. Okay,

552
00:30:36,120 --> 00:30:39,160
Speaker 1: the last man standing is down. There's just no one

553
00:30:39,200 --> 00:30:42,080
Speaker 1: else left. And that's what bottoms feel like. See, I've

554
00:30:42,080 --> 00:30:44,240
Speaker 1: always learned that they don't ring a bell at the top,

555
00:30:44,440 --> 00:30:48,520
Speaker 1: but the bottom. You know, if it's not a bell,

556
00:30:48,800 --> 00:30:51,560
Speaker 1: when your bell has been wrong more than you could

557
00:30:51,560 --> 00:30:55,000
Speaker 1: possibly take, that's more often than not the bottom. There

558
00:30:55,120 --> 00:30:59,400
Speaker 1: is a visceral panic on the streets. Like I know,

559
00:30:59,600 --> 00:31:03,720
Speaker 1: Manhattan isn't America. Manhattan is a small island off the

560
00:31:03,720 --> 00:31:06,440
Speaker 1: east coast of America. But you could walk down the

561
00:31:06,480 --> 00:31:09,280
Speaker 1: streets in February and March of oh nine and it

562
00:31:09,320 --> 00:31:14,120
Speaker 1: was palpa. There was genuine fear and angst and dare

563
00:31:14,160 --> 00:31:17,120
Speaker 1: I say panic. It was out there, and if you

564
00:31:17,160 --> 00:31:19,240
Speaker 1: were tuned to it, it was really just a question

565
00:31:19,280 --> 00:31:22,920
Speaker 1: of when do you you're gonna risk being a little early.

566
00:31:23,040 --> 00:31:25,080
Speaker 1: You could break it up into four pieces, put a

567
00:31:25,080 --> 00:31:26,880
Speaker 1: little to work now, a little to work next week,

568
00:31:26,960 --> 00:31:30,440
Speaker 1: next month, but at that point that was pretty much

569
00:31:30,760 --> 00:31:34,280
Speaker 1: you know, that sensation of ringing a bell. A handful

570
00:31:34,640 --> 00:31:37,680
Speaker 1: more people claim to have heard it today than actually

571
00:31:37,720 --> 00:31:41,719
Speaker 1: heard it. Everybody is fantastic in hindsight, myself included. Hindsight

572
00:31:41,840 --> 00:31:44,840
Speaker 1: bias is the greatest thing. But there's no doubt that

573
00:31:44,880 --> 00:31:47,320
Speaker 1: you walked around and it it was. It was visceral.

574
00:31:47,600 --> 00:31:49,680
Speaker 1: So so let's talk a little bit about here we are.

575
00:31:49,800 --> 00:31:52,680
Speaker 1: We're in year six of a bull market. We're up

576
00:31:52,720 --> 00:31:56,400
Speaker 1: over two on the SMP five hundred. We've had prior

577
00:31:56,520 --> 00:31:59,480
Speaker 1: guests like Ralph at Kampora and Las law Borrini and

578
00:31:59,560 --> 00:32:02,080
Speaker 1: Jeff's out. I know, you know most of these gentlemen

579
00:32:02,440 --> 00:32:07,000
Speaker 1: who are in the secular bull market camp Dittoh. So

580
00:32:07,000 --> 00:32:08,760
Speaker 1: that was the question, is I think we're I think

581
00:32:08,800 --> 00:32:11,800
Speaker 1: I think what we we started a secular bull market. No. Nine,

582
00:32:11,800 --> 00:32:16,120
Speaker 1: there's there's no Investipdia definition for a secular bowl market.

583
00:32:16,160 --> 00:32:19,400
Speaker 1: You can it's it's it's more I can do well

584
00:32:19,440 --> 00:32:21,280
Speaker 1: if it walks like a duck and quacks like a duck.

585
00:32:21,360 --> 00:32:23,560
Speaker 1: So you have to look at what ultimately were the

586
00:32:23,680 --> 00:32:27,640
Speaker 1: various characteristics of the three big secular bowl market markets

587
00:32:27,680 --> 00:32:31,560
Speaker 1: we've had. In the post so the nineteen twenties, the

588
00:32:31,600 --> 00:32:34,080
Speaker 1: mid forties to mid sixties, and then the Big one

589
00:32:34,120 --> 00:32:37,680
Speaker 1: eight two to two thousand, and you had negative real

590
00:32:37,720 --> 00:32:40,600
Speaker 1: interest rates at their beginning. You actually had a very high,

591
00:32:40,720 --> 00:32:43,800
Speaker 1: sort of secular high unemployment rate. In other words, you

592
00:32:43,840 --> 00:32:48,280
Speaker 1: know epic economic problem that that ultimately finally came to

593
00:32:48,360 --> 00:32:52,520
Speaker 1: a head with a double digit unemployment rate um and

594
00:32:52,880 --> 00:32:55,880
Speaker 1: secular low kind of valuations which many argue that we

595
00:32:55,880 --> 00:32:58,720
Speaker 1: didn't quite have this time, because you're really only very

596
00:32:58,800 --> 00:33:03,160
Speaker 1: quickly dipped into single digit territory at the lows. The difference, though,

597
00:33:03,200 --> 00:33:06,200
Speaker 1: is that versus two, when I think the PE got

598
00:33:06,240 --> 00:33:09,000
Speaker 1: down to around six, is you had runaway inflation and

599
00:33:09,040 --> 00:33:12,640
Speaker 1: double digging interest rates, which risk for huge downward pressure

600
00:33:12,680 --> 00:33:15,200
Speaker 1: on valuation. Risk free rate of return in eight two

601
00:33:15,400 --> 00:33:17,840
Speaker 1: is like twelve percent. Why would I want? I can

602
00:33:17,880 --> 00:33:21,080
Speaker 1: get twelve percent with no risk from Uncle Sam? Why

603
00:33:21,120 --> 00:33:23,320
Speaker 1: on earth where I want to buy equities as opposed

604
00:33:23,360 --> 00:33:26,920
Speaker 1: to getting three from Uncle Sam? All right, I'll take Hey,

605
00:33:26,960 --> 00:33:29,280
Speaker 1: I get a three percent dividend yields and I have

606
00:33:29,360 --> 00:33:32,480
Speaker 1: potential upside. That's why you never saw that same. But

607
00:33:32,560 --> 00:33:35,360
Speaker 1: I think a nine PE was certainly low enough in

608
00:33:35,400 --> 00:33:38,560
Speaker 1: that kind of background to suggest that those conditions are places.

609
00:33:38,640 --> 00:33:40,720
Speaker 1: And now just look at the six years of returns

610
00:33:40,720 --> 00:33:43,760
Speaker 1: that we have had. Uh, you know, pretty much straight

611
00:33:43,800 --> 00:33:47,000
Speaker 1: shot up and uh, and that just does not happen

612
00:33:47,040 --> 00:33:49,640
Speaker 1: if we were still in a secular bear market. We've

613
00:33:49,640 --> 00:33:53,200
Speaker 1: been speaking with liz Anne Saunders, chief investment strategist at

614
00:33:53,240 --> 00:33:55,760
Speaker 1: Charles Schwab. If people want to find your writings or

615
00:33:55,800 --> 00:33:58,120
Speaker 1: follow you, what's the best way for them to dot com?

616
00:33:58,680 --> 00:34:00,280
Speaker 1: You don't have to be a client. You just on

617
00:34:00,320 --> 00:34:03,920
Speaker 1: the public site and it's all there for people to

618
00:34:03,920 --> 00:34:06,560
Speaker 1: read the insights section. Yep, it's not hard to find.

619
00:34:06,920 --> 00:34:09,480
Speaker 1: If you've enjoyed this conversation, be sure and listen to

620
00:34:09,520 --> 00:34:11,759
Speaker 1: all of our podcast extras where we let the tape

621
00:34:11,840 --> 00:34:15,240
Speaker 1: run and continue chatting. You can check out my daily

622
00:34:15,320 --> 00:34:17,920
Speaker 1: column on Bloomberg View dot com or follow me on

623
00:34:17,960 --> 00:34:22,040
Speaker 1: Twitter at Ridhults. I'm Barry Ridhoults. You're listening to Masters

624
00:34:22,040 --> 00:34:25,160
Speaker 1: in Business on Bloomberg Radio. Welcome back to the show.

625
00:34:25,440 --> 00:34:29,080
Speaker 1: This is the podcast portion where we basically kick off

626
00:34:29,120 --> 00:34:31,720
Speaker 1: our shoes. Relax. I'm gonna take my headphones off because

627
00:34:32,280 --> 00:34:34,680
Speaker 1: my engineer doesn't need to tell me how much time

628
00:34:34,800 --> 00:34:38,359
Speaker 1: is left in this segment. If if the buildings on

629
00:34:38,400 --> 00:34:41,600
Speaker 1: fire or something, just jump up and down. So a

630
00:34:41,640 --> 00:34:43,840
Speaker 1: few let's get a few things um out of the

631
00:34:43,840 --> 00:34:46,360
Speaker 1: way before we go. I didn't get your Twitter handle

632
00:34:46,760 --> 00:34:50,360
Speaker 1: mentioned on the radio at liz Ane Saunders. How's anyone

633
00:34:50,400 --> 00:34:53,000
Speaker 1: gonna remember though? At l I Z A N N

634
00:34:53,320 --> 00:34:57,400
Speaker 1: NO E S O N D E R S not Sanders,

635
00:34:57,440 --> 00:34:59,839
Speaker 1: not Sanders. If you google your name, it comes up.

636
00:34:59,840 --> 00:35:03,080
Speaker 1: And that about the fourth thing you just have to start.

637
00:35:03,360 --> 00:35:05,400
Speaker 1: You just have to put Lizanne in. And so let

638
00:35:05,480 --> 00:35:08,400
Speaker 1: me ask you. We weren't planning on talking about this,

639
00:35:08,760 --> 00:35:11,399
Speaker 1: and I don't even know what you're about to talk

640
00:35:11,440 --> 00:35:14,879
Speaker 1: about Twitter. Let's talk. We were just talking during the break.

641
00:35:14,880 --> 00:35:17,399
Speaker 1: We're talking about new, brand new on Twitter. So how

642
00:35:17,400 --> 00:35:21,160
Speaker 1: long have you been on Twitter? All right? A couple

643
00:35:21,200 --> 00:35:24,879
Speaker 1: of months ago, Morgan Stanley came out or some other

644
00:35:24,920 --> 00:35:27,960
Speaker 1: big house I don't remember, might not have been Morgan Stanley,

645
00:35:28,000 --> 00:35:29,680
Speaker 1: I think it was. But before I throw them under

646
00:35:29,719 --> 00:35:32,520
Speaker 1: the bus, some big wirehouse came out with a set

647
00:35:32,520 --> 00:35:36,479
Speaker 1: of guidelines for Twitter and they basically create a list

648
00:35:36,520 --> 00:35:39,440
Speaker 1: of pre approved tweets that anybody who works for them,

649
00:35:39,480 --> 00:35:42,400
Speaker 1: and it was really kind of absurd. So my question

650
00:35:42,440 --> 00:35:44,200
Speaker 1: for you is, how do you have a lot of

651
00:35:44,280 --> 00:35:48,920
Speaker 1: room to well? At this stage everything does have to

652
00:35:48,920 --> 00:35:52,560
Speaker 1: be pre approved, but I have yet to get told

653
00:35:52,600 --> 00:35:56,080
Speaker 1: I could not tweet something that I suggested I wanted

654
00:35:56,120 --> 00:35:58,799
Speaker 1: to everything's been approved. How much are you tweeting, like, hey,

655
00:35:58,840 --> 00:36:02,520
Speaker 1: here's my weekly? Not as often as I will probably

656
00:36:02,640 --> 00:36:05,680
Speaker 1: when I don't have to go through the process. We're

657
00:36:05,800 --> 00:36:07,480
Speaker 1: very soon at the point where we won't have to

658
00:36:07,480 --> 00:36:10,120
Speaker 1: get pre approval to tweet links to things we've done,

659
00:36:10,280 --> 00:36:13,840
Speaker 1: or radio appearances or TV appearances that will basically happen

660
00:36:13,880 --> 00:36:16,560
Speaker 1: whenever we want. You're kind of a live wire. Are

661
00:36:16,600 --> 00:36:18,960
Speaker 1: they're afraid you're gonna be you know, you're a you're

662
00:36:19,000 --> 00:36:21,560
Speaker 1: a bomb throw are They're afraid you're gonna really cause them.

663
00:36:21,840 --> 00:36:24,520
Speaker 1: They hope to get to the point very soon where

664
00:36:24,640 --> 00:36:27,320
Speaker 1: they make the same assumption about me and other subject

665
00:36:27,360 --> 00:36:29,520
Speaker 1: matter experts that they do when they allow us or

666
00:36:29,560 --> 00:36:32,520
Speaker 1: send us off to do radio or TV, which every

667
00:36:32,600 --> 00:36:35,440
Speaker 1: characters is essentially we're not right, We're not going to

668
00:36:35,480 --> 00:36:39,799
Speaker 1: embarrass ourselves or or shame the firm, And but we're

669
00:36:39,840 --> 00:36:42,160
Speaker 1: we're new at at the firm, in in being out

670
00:36:42,200 --> 00:36:44,920
Speaker 1: there in there I give them credit for giving you

671
00:36:45,000 --> 00:36:47,840
Speaker 1: some rope to give some rope, but you know, Schwab,

672
00:36:48,560 --> 00:36:50,520
Speaker 1: part of our our our culture is to be on

673
00:36:50,560 --> 00:36:52,320
Speaker 1: top of things like this. And I think the reason

674
00:36:52,360 --> 00:36:57,359
Speaker 1: why we came through the financial crisis relatively unscathed was

675
00:36:57,520 --> 00:37:02,200
Speaker 1: because it's a it's a culture of honesty and integrity,

676
00:37:02,280 --> 00:37:04,279
Speaker 1: and we want to maintain that and everything that we do.

677
00:37:04,680 --> 00:37:08,759
Speaker 1: It's it's a conservative approach to all right, we'll get

678
00:37:08,800 --> 00:37:11,279
Speaker 1: involved in this, but we'll go a little slow. I

679
00:37:11,360 --> 00:37:14,120
Speaker 1: didn't have My most fun tweet was actually just today

680
00:37:14,480 --> 00:37:18,080
Speaker 1: because of well yeah, because I was in my office

681
00:37:18,280 --> 00:37:21,520
Speaker 1: and I hadn't thought about tweeting it, and one of

682
00:37:21,640 --> 00:37:24,399
Speaker 1: you know, many headlines today came across of the Duke

683
00:37:24,480 --> 00:37:27,000
Speaker 1: win and I looked up and I realized, I looked

684
00:37:27,000 --> 00:37:29,200
Speaker 1: on my shelf in my office, and there is my

685
00:37:29,480 --> 00:37:34,200
Speaker 1: signed ball from Coach k from having I was a

686
00:37:34,200 --> 00:37:37,399
Speaker 1: guest lecturer at Duke in two thousand and six, and

687
00:37:37,480 --> 00:37:40,000
Speaker 1: the thank you was as signed ball that's in a

688
00:37:40,120 --> 00:37:43,520
Speaker 1: loose sight box. So I took a photo of it

689
00:37:43,680 --> 00:37:45,759
Speaker 1: and and just said, uh, you know, I had the

690
00:37:45,760 --> 00:37:47,680
Speaker 1: great pleasure of being a guest lecture a number of

691
00:37:47,760 --> 00:37:51,240
Speaker 1: years ago. How cool is this gift now having gotten

692
00:37:51,239 --> 00:37:54,239
Speaker 1: and that was obviously pre the thousandth win, So I

693
00:37:54,239 --> 00:37:57,200
Speaker 1: don't know whether now between that having happened, the thousand

694
00:37:57,320 --> 00:38:00,319
Speaker 1: win and now me tweeting it, I may have you

695
00:38:00,360 --> 00:38:04,239
Speaker 1: get some money for it on eBay. Yeah, that's the sore.

696
00:38:04,800 --> 00:38:07,600
Speaker 1: They're loosening up a little bit. In other words, and

697
00:38:07,640 --> 00:38:10,200
Speaker 1: it's been fun. Twitter is a is a lot of fun.

698
00:38:10,680 --> 00:38:14,279
Speaker 1: Very close friend of mine is who you may know

699
00:38:14,480 --> 00:38:18,799
Speaker 1: is Anthony Nodo who is the Sacks and now the UM.

700
00:38:19,360 --> 00:38:21,799
Speaker 1: I don't know him, but I certainly Twitter. So he's

701
00:38:21,800 --> 00:38:24,200
Speaker 1: our next door neighbor and close friends. I'll have to

702
00:38:24,200 --> 00:38:25,759
Speaker 1: bring him in for the show. That would be fun.

703
00:38:26,000 --> 00:38:28,360
Speaker 1: He would be an interesting he would be He would

704
00:38:28,360 --> 00:38:31,120
Speaker 1: be great because he brought Twitter public when he was

705
00:38:31,120 --> 00:38:34,160
Speaker 1: at Goldman and and then when one of the things

706
00:38:34,239 --> 00:38:36,160
Speaker 1: I always ask guest says, hey, who do you think

707
00:38:36,200 --> 00:38:37,919
Speaker 1: would be good for the show. I think he'd be great.

708
00:38:37,920 --> 00:38:40,359
Speaker 1: He's to the extent he's listening, He's probably gonna say

709
00:38:40,360 --> 00:38:43,200
Speaker 1: what is she doing? But if you remember, before going

710
00:38:43,280 --> 00:38:45,920
Speaker 1: back to Goldman, Sachs, he did a stint at the

711
00:38:46,000 --> 00:38:49,040
Speaker 1: NFL as the CFO of the NFL under Roger Goodell,

712
00:38:50,080 --> 00:38:53,200
Speaker 1: he's got something. He's got some and no head injuries,

713
00:38:53,200 --> 00:38:56,279
Speaker 1: no lasting problems, not as far as we can The

714
00:38:56,280 --> 00:38:59,400
Speaker 1: CFOs were very different helmets than the rest of the players,

715
00:38:59,480 --> 00:39:04,319
Speaker 1: and they got a player at Army, so he and

716
00:39:04,360 --> 00:39:06,520
Speaker 1: he was an army ranger, so he might have had some.

717
00:39:07,320 --> 00:39:10,080
Speaker 1: So he's a he's a serious thing. Yeah, he'd he'd

718
00:39:10,080 --> 00:39:11,600
Speaker 1: be a good he'd be a good one for you know,

719
00:39:11,719 --> 00:39:14,239
Speaker 1: that's really that's fascinating something I find myself as his

720
00:39:14,320 --> 00:39:17,200
Speaker 1: pitch pitch woman here right. It's um, well, you know,

721
00:39:17,680 --> 00:39:20,799
Speaker 1: it's always very easy to just we all have a

722
00:39:20,840 --> 00:39:24,920
Speaker 1: circle of contacts and friends, and I'm always looking to,

723
00:39:25,840 --> 00:39:29,120
Speaker 1: you know, move outside of that comfort zone. I'm a

724
00:39:29,120 --> 00:39:31,239
Speaker 1: little bit of a foodie. This I promise this is

725
00:39:31,280 --> 00:39:34,160
Speaker 1: not fast food over here. But a few weeks ago

726
00:39:34,160 --> 00:39:37,360
Speaker 1: we had Bobby Flag and it was a fascinating conversation.

727
00:39:37,520 --> 00:39:39,960
Speaker 1: Down to earth New York or no BS sort of guy.

728
00:39:40,160 --> 00:39:42,719
Speaker 1: And it forces you to think, like you said earlier,

729
00:39:43,000 --> 00:39:46,920
Speaker 1: as a woman in what's predominantly a male business, it

730
00:39:47,040 --> 00:39:49,480
Speaker 1: kind of forces you to be a little different, think

731
00:39:49,480 --> 00:39:53,080
Speaker 1: outside of the box, and force forces everybody else around

732
00:39:53,080 --> 00:39:55,719
Speaker 1: you to to interact in a slightly different way. So

733
00:39:56,040 --> 00:40:00,399
Speaker 1: I'm always saying what can we do? That's just not

734
00:40:00,400 --> 00:40:02,239
Speaker 1: not that we've done a thousand of these and it's

735
00:40:02,280 --> 00:40:06,560
Speaker 1: become boring. They're always interesting, They're always my engineer makes

736
00:40:06,560 --> 00:40:09,399
Speaker 1: fun of me. Count how many times Barry says fascinating

737
00:40:09,840 --> 00:40:12,640
Speaker 1: during during the interview. Because I find this stuff fast,

738
00:40:12,960 --> 00:40:15,640
Speaker 1: I agree. I think, first of all, this is this

739
00:40:15,719 --> 00:40:18,680
Speaker 1: is a very cool conversation to have because it's it's

740
00:40:18,840 --> 00:40:22,480
Speaker 1: real topics for in depth, in depth, full sentences, not

741
00:40:22,560 --> 00:40:25,240
Speaker 1: sound bites. What's your favorite stock pick? Where's the market

742
00:40:25,239 --> 00:40:27,600
Speaker 1: gonna be a year coming back? We'll you know, it's

743
00:40:27,600 --> 00:40:30,319
Speaker 1: that sort of stuff I used, like what is the

744
00:40:30,400 --> 00:40:33,239
Speaker 1: value to zero? Value to that? Right? And and a

745
00:40:33,320 --> 00:40:36,080
Speaker 1: lot of people do so talking about really cool. You

746
00:40:36,120 --> 00:40:40,279
Speaker 1: worked for Marty's Wide for how long? Thirteen years? I mean,

747
00:40:40,280 --> 00:40:42,600
Speaker 1: by the way, he passed away sadly two years ago,

748
00:40:42,719 --> 00:40:45,279
Speaker 1: not too long ago. And I wrote a I wrote

749
00:40:45,280 --> 00:40:51,359
Speaker 1: a tribute that and it I The title of it

750
00:40:51,440 --> 00:40:53,680
Speaker 1: was a take on the book he recommended that I

751
00:40:53,719 --> 00:40:56,160
Speaker 1: read when I first joined the firm, which is Reminiscences

752
00:40:56,160 --> 00:41:00,120
Speaker 1: of a stock operator. So now is this true? So

753
00:41:00,200 --> 00:41:03,840
Speaker 1: let's let's there's a million digressions here. So I heard

754
00:41:03,960 --> 00:41:07,920
Speaker 1: that that book was kind of a lost book until

755
00:41:08,000 --> 00:41:11,480
Speaker 1: Marty's Wig started talking about it and it suddenly became

756
00:41:11,520 --> 00:41:14,440
Speaker 1: a best set. It's very possible. And Laslow Barrini too,

757
00:41:15,440 --> 00:41:19,200
Speaker 1: that's his baby. In fact, all his his weekly or

758
00:41:19,239 --> 00:41:22,359
Speaker 1: monthly Pecity puts out his called reminiscences. He always has

759
00:41:22,400 --> 00:41:24,799
Speaker 1: a quote from the book, so that I get it,

760
00:41:24,880 --> 00:41:27,120
Speaker 1: and I view people from that eighties era that we're

761
00:41:27,160 --> 00:41:31,080
Speaker 1: real acolytes of that. I get Laslow stuff, and he

762
00:41:31,160 --> 00:41:34,080
Speaker 1: was a guest on the show, and I never put

763
00:41:34,160 --> 00:41:39,960
Speaker 1: together like you recognize reminiscence as a reminiscence of a

764
00:41:40,000 --> 00:41:43,400
Speaker 1: stock stock operator or reminiscence of a trade role, however

765
00:41:44,200 --> 00:41:46,080
Speaker 1: you want to describe it. But I didn't realize that

766
00:41:46,080 --> 00:41:49,400
Speaker 1: that was his reference. That's really fascinating. So this this

767
00:41:49,440 --> 00:41:52,839
Speaker 1: tribute that I wrote was Reminiscences of Marty's Wig, and

768
00:41:53,600 --> 00:41:56,799
Speaker 1: it um is the number one most read report I

769
00:41:56,800 --> 00:41:59,880
Speaker 1: have ever written in all my years. And that's amazing that.

770
00:42:00,960 --> 00:42:03,480
Speaker 1: So I get emails all the time on the show.

771
00:42:04,239 --> 00:42:05,960
Speaker 1: A lot of kids in college, a lot of people

772
00:42:05,960 --> 00:42:09,359
Speaker 1: in grad school, and the question that always comes up

773
00:42:09,440 --> 00:42:14,520
Speaker 1: is how much is this contextualized for them relative to

774
00:42:15,560 --> 00:42:19,600
Speaker 1: Who's Marty's Why? And you know the interesting thing about Google,

775
00:42:19,960 --> 00:42:22,880
Speaker 1: which is a phenomenal company and Google as a search

776
00:42:24,160 --> 00:42:25,600
Speaker 1: I showed some of the other day. You know, you

777
00:42:25,600 --> 00:42:27,880
Speaker 1: can drag an image to Google search and you'll find

778
00:42:28,360 --> 00:42:32,120
Speaker 1: similar or the source of Very often I have an

779
00:42:32,200 --> 00:42:34,520
Speaker 1: image and I'm like, where is this from? You drag

780
00:42:34,600 --> 00:42:36,120
Speaker 1: it to the search box and it will show you

781
00:42:36,160 --> 00:42:41,080
Speaker 1: where facial recognition. It's it's crazy. However, the one flaw

782
00:42:41,560 --> 00:42:46,240
Speaker 1: that Google has is that stuff that predates the late nineties.

783
00:42:46,960 --> 00:42:49,040
Speaker 1: You know, you search for Marty's Why, and you'll get

784
00:42:49,040 --> 00:42:51,040
Speaker 1: the book and you'll get a couple of things. But

785
00:42:51,280 --> 00:42:54,880
Speaker 1: he obviously didn't have a big Internet footprints because there

786
00:42:54,920 --> 00:42:58,120
Speaker 1: wasn't an Internet. There wasn't an Internet. So I think

787
00:42:58,200 --> 00:43:02,960
Speaker 1: people who are you know, history didn't begin in nineteen two.

788
00:43:03,560 --> 00:43:07,080
Speaker 1: It goes further back. So explain to people who maybe

789
00:43:07,120 --> 00:43:09,680
Speaker 1: a little younger and may not be familiar with Marty's Wide.

790
00:43:09,680 --> 00:43:12,040
Speaker 1: We talked a little bit about his phenomenal call on

791
00:43:12,200 --> 00:43:15,240
Speaker 1: around the eighty seven crash, but that was really one

792
00:43:15,440 --> 00:43:17,480
Speaker 1: in a series of really and it was and it

793
00:43:17,520 --> 00:43:20,520
Speaker 1: was what what he looked at the way he analyzed

794
00:43:20,600 --> 00:43:23,759
Speaker 1: markets that allowed him to see what was happening. And

795
00:43:23,800 --> 00:43:26,680
Speaker 1: I think we were already talked about the fact that

796
00:43:26,680 --> 00:43:30,440
Speaker 1: he coined the phrase don't fight the Fed, just a

797
00:43:30,480 --> 00:43:33,240
Speaker 1: little quip that became famous. It was his whole basis

798
00:43:33,280 --> 00:43:37,880
Speaker 1: for thinking about the role of monetary liquidity in financial markets,

799
00:43:38,200 --> 00:43:40,960
Speaker 1: which is what ultimately led to this cute little phrase,

800
00:43:41,040 --> 00:43:43,360
Speaker 1: But it was really what was underneath it. He also

801
00:43:43,440 --> 00:43:45,640
Speaker 1: created the pot call ratio, which a lot of people

802
00:43:45,640 --> 00:43:48,360
Speaker 1: don't realize what coal ratio meaning looking at the options,

803
00:43:48,600 --> 00:43:51,640
Speaker 1: how many are bullish? How many embarrash? Ratio was invented

804
00:43:51,640 --> 00:43:54,680
Speaker 1: by by Marty. I didn't know. That's interesting. He was

805
00:43:55,200 --> 00:43:59,800
Speaker 1: the creator of, and pioneer of, and and probably first

806
00:44:00,080 --> 00:44:03,759
Speaker 1: user of many of the sentiment indicators that we all

807
00:44:03,760 --> 00:44:06,920
Speaker 1: look at very regularly now, and and really believed that

808
00:44:07,000 --> 00:44:11,080
Speaker 1: more than anything that crowd psychology that moved from fear

809
00:44:11,120 --> 00:44:15,000
Speaker 1: and greed so dominated many of the traditional fundamentals. In fact,

810
00:44:15,040 --> 00:44:17,520
Speaker 1: he was often asked the question if you could pick

811
00:44:17,640 --> 00:44:20,359
Speaker 1: one of your hundreds of indicators that you look at

812
00:44:20,400 --> 00:44:23,200
Speaker 1: only one You had two time markets based on one

813
00:44:23,239 --> 00:44:27,520
Speaker 1: single indicator, and his answer was always time and newsweek covers.

814
00:44:28,920 --> 00:44:31,680
Speaker 1: We have. If you had a bull or a bear

815
00:44:32,040 --> 00:44:35,520
Speaker 1: on both covers within a week, trouble trouble, well, the

816
00:44:35,560 --> 00:44:38,600
Speaker 1: opposite were typically happy. And that was to our point,

817
00:44:38,800 --> 00:44:44,040
Speaker 1: pre Internet, pre all of the financial media and publications

818
00:44:44,080 --> 00:44:46,160
Speaker 1: that we have right now, where you had a much

819
00:44:46,160 --> 00:44:50,640
Speaker 1: smaller subset, and if on those two big popular national

820
00:44:50,680 --> 00:44:53,840
Speaker 1: magazines you had double bulls, you know, watch out below

821
00:44:54,080 --> 00:44:57,480
Speaker 1: or vice versa. Paul McCray Montgomery, who passed away last year,

822
00:44:57,680 --> 00:45:01,960
Speaker 1: was the guy who literally invent of the magazine cover indicator.

823
00:45:02,360 --> 00:45:04,880
Speaker 1: I want to say about thirty years ago. But he

824
00:45:04,920 --> 00:45:09,359
Speaker 1: would write about it in a very academic way. It

825
00:45:09,440 --> 00:45:11,400
Speaker 1: wasn't oh look this is on the cover, We're going

826
00:45:11,440 --> 00:45:14,880
Speaker 1: to hell. It was always there's actual research, right, here's

827
00:45:14,920 --> 00:45:17,600
Speaker 1: the data. He also was the one who started looking

828
00:45:17,640 --> 00:45:20,680
Speaker 1: at the length of women's skirts as a potential indicator.

829
00:45:20,719 --> 00:45:23,560
Speaker 1: He looked at a lot of Super Bowl indicator guides, no, no, but,

830
00:45:23,680 --> 00:45:26,600
Speaker 1: and the Super Bowl indicator turns out to be pretty

831
00:45:26,680 --> 00:45:30,040
Speaker 1: much nonsense, just a lot a lot of them. Um,

832
00:45:30,080 --> 00:45:34,040
Speaker 1: So what else, uh did Marty look at in his

833
00:45:34,480 --> 00:45:37,960
Speaker 1: So I'm going to a different question, So let me

834
00:45:38,000 --> 00:45:40,000
Speaker 1: not beat around the bush and get to it. A

835
00:45:40,040 --> 00:45:42,960
Speaker 1: line I've heard my whole career is hey, you know,

836
00:45:43,160 --> 00:45:46,319
Speaker 1: there's no such thing as a wealthy technician. Marty kind

837
00:45:46,320 --> 00:45:47,960
Speaker 1: of proves that to be. I think he did not

838
00:45:48,280 --> 00:45:51,759
Speaker 1: prove that, but there was. It was not just technical indicators.

839
00:45:51,760 --> 00:45:54,360
Speaker 1: He was not just a chartist. He was, but he

840
00:45:54,480 --> 00:45:57,600
Speaker 1: also believed and I think he kind of co coined

841
00:45:58,160 --> 00:46:00,520
Speaker 1: the phrase the trend is your friend with with our

842
00:46:00,560 --> 00:46:03,719
Speaker 1: other friend ned Davis, who had worked with Marty many

843
00:46:03,719 --> 00:46:07,520
Speaker 1: many years sharing research and schwab is still big clients

844
00:46:07,520 --> 00:46:12,720
Speaker 1: of ned Davis and retired. Now he's still he's still

845
00:46:12,760 --> 00:46:16,319
Speaker 1: relatively active. He still writes UM he's got a big,

846
00:46:16,400 --> 00:46:20,439
Speaker 1: huge organization and the phenomenal They sold it last year

847
00:46:20,480 --> 00:46:23,640
Speaker 1: to UM or two years ago? Was it Alliance Bernstein?

848
00:46:23,960 --> 00:46:26,200
Speaker 1: Somebody bought them. I don't remember who it was. I

849
00:46:26,280 --> 00:46:30,359
Speaker 1: don't yes had a parent now, UM I know, as

850
00:46:30,440 --> 00:46:33,480
Speaker 1: I s I sold to Avercre. Really luth Old is

851
00:46:33,560 --> 00:46:38,160
Speaker 1: under a Weeden. So is ned Davis still independent of somebody?

852
00:46:39,120 --> 00:46:40,600
Speaker 1: I don't know. That's a very good Quest's go to

853
00:46:40,640 --> 00:46:44,360
Speaker 1: the Google machine. There you go. But you know, Marty

854
00:46:44,640 --> 00:46:47,719
Speaker 1: so he certainly looked at a lot of technical factors,

855
00:46:47,719 --> 00:46:50,120
Speaker 1: many of the traditional ones that we look at right

856
00:46:50,160 --> 00:46:54,160
Speaker 1: now um sentiment indicators, but also to the point of

857
00:46:54,200 --> 00:46:57,680
Speaker 1: the trend is your friend? He he looked at momentum factors.

858
00:46:57,760 --> 00:47:00,160
Speaker 1: But the biggest component, if you wanted to look us

859
00:47:00,160 --> 00:47:03,960
Speaker 1: at the breakdown of the model, the biggest component was

860
00:47:04,040 --> 00:47:08,279
Speaker 1: the monetary environment. Was was economic liquidity um which is

861
00:47:08,440 --> 00:47:11,399
Speaker 1: in the seventies, eighties, nineties or across. Yes, yes, and yes.

862
00:47:12,560 --> 00:47:16,160
Speaker 1: He looked at monetary policy. What the central we basically

863
00:47:16,200 --> 00:47:19,840
Speaker 1: had monetary liquidity, investor liquidity, and momentum. Where the three

864
00:47:20,040 --> 00:47:24,200
Speaker 1: categories of indicators, so monetary liquidity would be all the

865
00:47:24,239 --> 00:47:29,960
Speaker 1: interest rate fed policy indicators, monetary base, money supply. Do

866
00:47:30,000 --> 00:47:32,240
Speaker 1: you remember the days when you would wait till Friday

867
00:47:32,280 --> 00:47:36,680
Speaker 1: afternoon for the money supply? Isn't an incredible waves you

868
00:47:36,800 --> 00:47:39,759
Speaker 1: go through in almost thirty years in the business of

869
00:47:39,920 --> 00:47:43,600
Speaker 1: what are the hot popular indicators? You wait with bated

870
00:47:43,640 --> 00:47:45,760
Speaker 1: breath together, I remember when it was a trade deficit.

871
00:47:46,080 --> 00:47:48,759
Speaker 1: It really is amazing what sort of captures And in

872
00:47:48,800 --> 00:47:53,680
Speaker 1: many cases it's because those are more market moving figures

873
00:47:53,800 --> 00:47:56,239
Speaker 1: at the time, but it is incredible. You're right, you look,

874
00:47:58,280 --> 00:48:00,800
Speaker 1: nobody pays attention to that anymore. Yeah, fans got a

875
00:48:00,800 --> 00:48:03,879
Speaker 1: four trillion dollar balance sheet, but so who cares about

876
00:48:03,920 --> 00:48:07,680
Speaker 1: the weekly uh weekly factors? By the way, Ned davis

877
00:48:08,000 --> 00:48:13,719
Speaker 1: majority stake purchased by Euromoney in June two thousand and eleven. So,

878
00:48:13,760 --> 00:48:16,279
Speaker 1: and I also, they've they've been, they've kept I think

879
00:48:16,719 --> 00:48:19,839
Speaker 1: a distance because I didn't even know that, and then

880
00:48:20,000 --> 00:48:24,040
Speaker 1: I've been They're still running it independently from from all

881
00:48:24,040 --> 00:48:27,680
Speaker 1: indications to this user. Before this show launched, I did

882
00:48:27,719 --> 00:48:30,719
Speaker 1: an interview with Ned Davis and it was really the

883
00:48:32,640 --> 00:48:36,200
Speaker 1: format that set this show up. It was, I want

884
00:48:36,239 --> 00:48:39,640
Speaker 1: to say, about two or three years ago, absolutely fascinating. Um.

885
00:48:39,680 --> 00:48:41,279
Speaker 1: It was a privilege speaking to him. And I know

886
00:48:41,400 --> 00:48:44,200
Speaker 1: his partner, Ed Mendel, who's also so I think one

887
00:48:44,200 --> 00:48:47,040
Speaker 1: of the owners of the Atlanta Falcons also a delight,

888
00:48:47,200 --> 00:48:50,480
Speaker 1: just invited me to a game. That really tell him.

889
00:48:50,520 --> 00:48:52,600
Speaker 1: I said, hello, I hope to be able to work

890
00:48:52,640 --> 00:48:56,000
Speaker 1: it into my schedule. He he's a really interesting guy.

891
00:48:56,360 --> 00:48:59,000
Speaker 1: Another see if I get him up here to sit down.

892
00:48:59,360 --> 00:49:02,759
Speaker 1: He's like one of these guys that's a very insightful

893
00:49:03,320 --> 00:49:06,400
Speaker 1: business person. It happens to be the business of finance,

894
00:49:06,600 --> 00:49:09,760
Speaker 1: but it's still a business. But he understands the business

895
00:49:09,920 --> 00:49:12,800
Speaker 1: better than you know. It's really is a great combination

896
00:49:12,800 --> 00:49:17,520
Speaker 1: because because Ned understood the markets and and and ands

897
00:49:17,560 --> 00:49:21,120
Speaker 1: to the business and was really a great a great partnership. Um.

898
00:49:21,160 --> 00:49:27,000
Speaker 1: But I remember was it big mo was the chart

899
00:49:27,200 --> 00:49:30,120
Speaker 1: that everybody used to look at and I think, uh,

900
00:49:30,200 --> 00:49:33,239
Speaker 1: and you are still present. It's well, as long as

901
00:49:33,239 --> 00:49:36,080
Speaker 1: it's it's showing work, it works. So so tell us

902
00:49:36,160 --> 00:49:39,800
Speaker 1: what life was like working on a daily basis with

903
00:49:39,800 --> 00:49:42,400
Speaker 1: with his why what what was that? And I have

904
00:49:42,520 --> 00:49:45,120
Speaker 1: to give credit to Marty's partner, Ned Babbitt to who

905
00:49:45,280 --> 00:49:50,279
Speaker 1: who is also a well known guy. Not no, not

906
00:49:50,480 --> 00:49:53,880
Speaker 1: quite to the level of Marty because he his writings

907
00:49:53,880 --> 00:49:59,040
Speaker 1: were a little bit more quiet and but a little

908
00:49:59,040 --> 00:50:01,239
Speaker 1: bit um he was he was sort of he was

909
00:50:01,280 --> 00:50:04,319
Speaker 1: a former broker and he a Futton broker, um, but

910
00:50:05,000 --> 00:50:06,920
Speaker 1: knew how to run the business. And then actually the

911
00:50:07,360 --> 00:50:11,399
Speaker 1: third guy that I must give credit to the head

912
00:50:11,440 --> 00:50:15,040
Speaker 1: of marketing effectively that that really grew both this wide

913
00:50:15,040 --> 00:50:17,080
Speaker 1: side of the business and the avatar side of the business,

914
00:50:17,080 --> 00:50:20,080
Speaker 1: which was the institutional side, was Bruce pollo Quin who

915
00:50:20,200 --> 00:50:23,000
Speaker 1: was just got um was just made a member of

916
00:50:23,080 --> 00:50:26,759
Speaker 1: the House of Representatives representing Mains, just got elected and

917
00:50:26,800 --> 00:50:29,120
Speaker 1: then November, so he was sworn in and I guess

918
00:50:29,200 --> 00:50:32,719
Speaker 1: January whenever they do that, Um, he's I think he's

919
00:50:32,760 --> 00:50:39,440
Speaker 1: on the House Financial uh Services whatever committee committee. Um,

920
00:50:39,520 --> 00:50:42,520
Speaker 1: so he now gets quoted anytime there's discussion about the budget.

921
00:50:42,920 --> 00:50:47,520
Speaker 1: So would you say these three guys were oh, oh absolutely, absolutely,

922
00:50:47,960 --> 00:50:53,120
Speaker 1: And they were very different personalities. Bruce was a hyperactive

923
00:50:53,320 --> 00:50:57,840
Speaker 1: Harvard Prep school kind of guy, looked at two with

924
00:50:57,880 --> 00:51:00,960
Speaker 1: the horn room glasses and talked a million miles a

925
00:51:01,000 --> 00:51:03,440
Speaker 1: minute and go, go, go, go go. And Ned was

926
00:51:03,480 --> 00:51:07,560
Speaker 1: a little bit more quiet and reserved and um, and

927
00:51:07,600 --> 00:51:12,200
Speaker 1: Marty was Marty was was a character. He really was.

928
00:51:12,320 --> 00:51:17,799
Speaker 1: He was um uh. Many people saw him as as

929
00:51:17,800 --> 00:51:22,360
Speaker 1: fairly volatile and personality, um would you know, throw pencils

930
00:51:22,360 --> 00:51:25,680
Speaker 1: and break stuff, but the biggest heart in in in

931
00:51:25,719 --> 00:51:29,680
Speaker 1: the world. And he was known as a warrior. Um.

932
00:51:29,760 --> 00:51:31,799
Speaker 1: But in the tribute I wrote to him, I said,

933
00:51:31,800 --> 00:51:35,200
Speaker 1: he really was a warrior. He just he was so

934
00:51:35,360 --> 00:51:38,760
Speaker 1: seeped in in markets and wanted to understand them and

935
00:51:38,760 --> 00:51:41,520
Speaker 1: and was so engrossed in it. And he was just

936
00:51:41,680 --> 00:51:43,759
Speaker 1: he was a really neat guy. They all were really

937
00:51:43,840 --> 00:51:46,920
Speaker 1: neat guys to to work for. And it was very

938
00:51:47,040 --> 00:51:50,279
Speaker 1: much not the Wall Street Boys network. I think that

939
00:51:50,360 --> 00:51:52,960
Speaker 1: was probably also what was intriguing to me and maybe

940
00:51:52,960 --> 00:51:55,239
Speaker 1: why I had have the Hollis had the view that

941
00:51:55,280 --> 00:51:56,920
Speaker 1: I have that being a woman in this business is

942
00:51:56,960 --> 00:51:59,920
Speaker 1: a great thing because I wasn't ever jaded in my

943
00:52:00,040 --> 00:52:04,120
Speaker 1: early years from being in an environment like that. Uh,

944
00:52:04,320 --> 00:52:07,640
Speaker 1: there was not a chauvinistic bone in in any of them,

945
00:52:07,640 --> 00:52:11,080
Speaker 1: which was a special experience that that's really fascinating. And

946
00:52:11,160 --> 00:52:15,600
Speaker 1: people may not realize this, but when Marty passed away,

947
00:52:16,120 --> 00:52:20,080
Speaker 1: his I believe his wife put the apartment they lived

948
00:52:20,080 --> 00:52:21,920
Speaker 1: in up for sale and it was known as the

949
00:52:21,960 --> 00:52:25,560
Speaker 1: most expensive or most valuable apartment in New York City.

950
00:52:25,600 --> 00:52:29,680
Speaker 1: Is a stunning apartment, really beautiful apartment. It's the top

951
00:52:29,719 --> 00:52:34,040
Speaker 1: of the Pierre Um and really quite extraordinarily beautiful. And

952
00:52:34,080 --> 00:52:37,120
Speaker 1: it's where Marty had some, though not all, of his

953
00:52:37,200 --> 00:52:39,840
Speaker 1: memorabilias well. It was also well known for being a

954
00:52:39,920 --> 00:52:43,680
Speaker 1: memorabilia collector and he had he had them. He was

955
00:52:43,760 --> 00:52:46,680
Speaker 1: the one that bought the Marilyn Monroe Happy Birthday dress.

956
00:52:47,040 --> 00:52:51,520
Speaker 1: Oh really had the Harley Davidson from Easy Writer, that

957
00:52:51,640 --> 00:52:55,560
Speaker 1: Fonda Road and you name it. Music memorabili and guitars

958
00:52:55,680 --> 00:53:00,720
Speaker 1: and gold records and the original Terminator costume just really

959
00:53:00,719 --> 00:53:04,239
Speaker 1: really cool uh stuff. So he was fun. He was

960
00:53:04,280 --> 00:53:09,520
Speaker 1: a quirky, fun different guy. Not not the usual walls,

961
00:53:09,800 --> 00:53:12,400
Speaker 1: not far from it, and I think that was always

962
00:53:12,480 --> 00:53:15,960
Speaker 1: part of his charm. So his tactical model, what was

963
00:53:16,000 --> 00:53:18,759
Speaker 1: the thinking behind it? How did that? And I'm not

964
00:53:18,840 --> 00:53:22,239
Speaker 1: asking for secrets, I'm asking generally speaking, how did the

965
00:53:22,280 --> 00:53:26,880
Speaker 1: tactical model run? Again, it was I'm trying to remember

966
00:53:26,880 --> 00:53:29,400
Speaker 1: the weights. It's now been so I I left in

967
00:53:31,280 --> 00:53:33,680
Speaker 1: so that was a long time ago. But I think

968
00:53:33,719 --> 00:53:41,960
Speaker 1: it was economic liquidity, investor liquidity and percent momentum. What

969
00:53:42,120 --> 00:53:48,680
Speaker 1: is investor liquidity that's basically sentiment, so measuring direct sentiment

970
00:53:48,760 --> 00:53:51,360
Speaker 1: in the sense that you're actually looking at asset flows

971
00:53:51,360 --> 00:53:54,160
Speaker 1: in cash levels that investors will have. And then the

972
00:53:54,200 --> 00:53:58,080
Speaker 1: attitudinal measures of sentiment like the Pook call ratio, like

973
00:53:58,320 --> 00:54:02,239
Speaker 1: AII or investors in intelligence, those types of measures that

974
00:54:02,320 --> 00:54:05,120
Speaker 1: measure the attitudes of investors. So that was what we

975
00:54:05,200 --> 00:54:09,040
Speaker 1: called investor liquidity. And then fift was momentum, which is

976
00:54:09,040 --> 00:54:13,319
Speaker 1: a lot of those shorter term technical in with the

977
00:54:13,360 --> 00:54:16,319
Speaker 1: trend that type of those of indicators. So now let's

978
00:54:16,400 --> 00:54:19,000
Speaker 1: let's get into some of the questions we missed earlier.

979
00:54:19,640 --> 00:54:22,080
Speaker 1: I asked you what what it was like working um

980
00:54:22,080 --> 00:54:24,839
Speaker 1: with Marty? What's a day in the life of liz

981
00:54:24,840 --> 00:54:29,160
Speaker 1: An Sanders at Schwab Like, Oh, gosh, depends on the day.

982
00:54:30,520 --> 00:54:32,879
Speaker 1: Can I tell you When people say to me, God,

983
00:54:32,920 --> 00:54:34,879
Speaker 1: you're up so early. You could work so early every day?

984
00:54:34,920 --> 00:54:37,760
Speaker 1: What what's it like? My answer is always, Hey, it's different.

985
00:54:37,760 --> 00:54:40,960
Speaker 1: Everything's different every which is what You're absolutely right. It's

986
00:54:41,080 --> 00:54:44,280
Speaker 1: it's the thing I think that is most intriguing about this,

987
00:54:44,280 --> 00:54:47,239
Speaker 1: this industry, certainly what you and I do, is it

988
00:54:47,320 --> 00:54:50,719
Speaker 1: changes every day. I had a funny comment made of me, uh,

989
00:54:50,800 --> 00:54:52,920
Speaker 1: or made to me. Uh. This is maybe about a

990
00:54:53,000 --> 00:54:55,720
Speaker 1: year ago, and I was speaking at a large client

991
00:54:55,760 --> 00:54:59,239
Speaker 1: event and an investor who had been there the last

992
00:54:59,280 --> 00:55:01,160
Speaker 1: time I was in whatever city it was a couple

993
00:55:01,160 --> 00:55:04,520
Speaker 1: of years before, said something funny. He said, are you

994
00:55:04,560 --> 00:55:08,439
Speaker 1: giving the same speech you gave two years ago? Which

995
00:55:08,520 --> 00:55:11,279
Speaker 1: I didn't want to laugh in his face. But first

996
00:55:11,320 --> 00:55:14,040
Speaker 1: of all, I don't write speeches. I speak off the cuff.

997
00:55:14,080 --> 00:55:17,520
Speaker 1: I don't use notes, no bullet point. Now I have

998
00:55:17,680 --> 00:55:20,200
Speaker 1: I have charts that I show, so I always have

999
00:55:20,239 --> 00:55:23,360
Speaker 1: a PowerPoint presentation, so in effect, that serves as an outline.

1000
00:55:23,400 --> 00:55:25,640
Speaker 1: If I do the same thing and people said to me,

1001
00:55:25,680 --> 00:55:27,440
Speaker 1: you know you said, and I'm like, I don't know.

1002
00:55:27,480 --> 00:55:31,320
Speaker 1: I just the art comes up and I describe in context.

1003
00:55:31,600 --> 00:55:34,040
Speaker 1: But so you can use the same set of slides,

1004
00:55:34,560 --> 00:55:37,640
Speaker 1: but it's a different but even I might even use

1005
00:55:37,680 --> 00:55:39,960
Speaker 1: the same exact deck if you want to call it that.

1006
00:55:40,080 --> 00:55:42,440
Speaker 1: But it's an event and an evening event. And if

1007
00:55:42,480 --> 00:55:46,080
Speaker 1: the lunch event are advisors that are on Schwab's platform,

1008
00:55:46,160 --> 00:55:48,319
Speaker 1: so they're professional money managers. And then I use the

1009
00:55:48,360 --> 00:55:52,000
Speaker 1: same charts talking to an audience of individual investors, are

1010
00:55:52,040 --> 00:55:56,160
Speaker 1: Retail on its same exact visuals, very different message, very

1011
00:55:56,200 --> 00:55:59,640
Speaker 1: different in terms of what I what I choose to explain,

1012
00:55:59,719 --> 00:56:01,839
Speaker 1: what I don't, the assumptions I make, Not that I'm

1013
00:56:01,920 --> 00:56:05,879
Speaker 1: dumbing it down, it's just but the funny comment back

1014
00:56:05,920 --> 00:56:08,680
Speaker 1: to the sky was number one. I don't write a

1015
00:56:08,760 --> 00:56:12,680
Speaker 1: speech and then recite it, but to suggest that I

1016
00:56:12,719 --> 00:56:15,120
Speaker 1: could be talking about the same things two years later.

1017
00:56:16,120 --> 00:56:19,319
Speaker 1: No thing's changed. What's changed over to But that's what

1018
00:56:19,560 --> 00:56:22,680
Speaker 1: makes this this business and what we do so fascinating

1019
00:56:22,719 --> 00:56:26,600
Speaker 1: because it's something different every day and I I would say,

1020
00:56:26,440 --> 00:56:28,920
Speaker 1: but a day in the life of las Anne is

1021
00:56:29,000 --> 00:56:32,000
Speaker 1: I read, write, and talk, So read and talk. I

1022
00:56:32,040 --> 00:56:35,160
Speaker 1: like that. That's essentially that's what we do. We read,

1023
00:56:35,160 --> 00:56:36,920
Speaker 1: write and talk. When I'm on the road, which I

1024
00:56:36,960 --> 00:56:40,640
Speaker 1: travel every week, um um talking, traveled that much on

1025
00:56:40,640 --> 00:56:43,120
Speaker 1: the road everywhere. Not Monday through Friday every week, but

1026
00:56:43,280 --> 00:56:45,839
Speaker 1: once a week at least, I'm going somewhere every week.

1027
00:56:46,160 --> 00:56:48,960
Speaker 1: I get a little reprieve in the August time frame

1028
00:56:49,080 --> 00:56:52,120
Speaker 1: because big events are not happening, typically in the dead

1029
00:56:52,160 --> 00:56:55,080
Speaker 1: of vacation season, and then I get a little reprieve

1030
00:56:55,120 --> 00:56:59,360
Speaker 1: in the December, you know, Thanksgiving. Usually beginning of December

1031
00:56:59,360 --> 00:57:01,760
Speaker 1: is still pretty big Z. But mid December to early

1032
00:57:01,840 --> 00:57:03,800
Speaker 1: January is a break, and then mid July to the

1033
00:57:03,880 --> 00:57:05,560
Speaker 1: end of August as a break. But other than that,

1034
00:57:05,640 --> 00:57:08,319
Speaker 1: it's it's it's every week. So when I'm on the road,

1035
00:57:08,360 --> 00:57:11,320
Speaker 1: I'm talking, and when I'm not I'm reading and writing.

1036
00:57:11,560 --> 00:57:15,279
Speaker 1: So um I. Mondays are generally publishing days, so that's

1037
00:57:15,280 --> 00:57:17,920
Speaker 1: what I'm doing a lot of my writing. The Friday

1038
00:57:17,920 --> 00:57:20,800
Speaker 1: before and the weekend is a lot of prep and

1039
00:57:20,880 --> 00:57:27,280
Speaker 1: thinking and editing, writing notes and sending torturing. My research

1040
00:57:27,320 --> 00:57:29,400
Speaker 1: assistant with can you put this chart together? Can you

1041
00:57:29,400 --> 00:57:33,120
Speaker 1: get this data for me? And and then I read constantly.

1042
00:57:33,280 --> 00:57:35,959
Speaker 1: I haven't read a fun book in forever, but I

1043
00:57:36,160 --> 00:57:38,320
Speaker 1: the day to day stuff I read constantly. They make

1044
00:57:38,360 --> 00:57:40,400
Speaker 1: fun of me in the office. I go on vacation

1045
00:57:40,680 --> 00:57:43,480
Speaker 1: like February, talking about February, and I'll bring a stack

1046
00:57:43,520 --> 00:57:46,560
Speaker 1: of eight books with me and they're all, it'll be

1047
00:57:47,000 --> 00:57:50,880
Speaker 1: seven unrelated finance books and then whatever Michael Lewis's last

1048
00:57:50,880 --> 00:57:53,520
Speaker 1: book is, and they're like, why would you bring that? Well,

1049
00:57:53,560 --> 00:57:55,800
Speaker 1: I'll read them on the way. Who reads it? You

1050
00:57:55,840 --> 00:57:59,960
Speaker 1: can't read two books a day, flash boys. I start

1051
00:58:00,040 --> 00:58:03,200
Speaker 1: that after Breakfast on the Beach finished the same day, absolutely,

1052
00:58:03,240 --> 00:58:05,280
Speaker 1: And it was a fact the year, A couple of

1053
00:58:05,360 --> 00:58:08,520
Speaker 1: years before the big short started on. I actually saved

1054
00:58:08,560 --> 00:58:11,080
Speaker 1: it for Wednesday. I didn't want to peek too soon

1055
00:58:11,160 --> 00:58:13,919
Speaker 1: in my now, but you are you happened? That would

1056
00:58:13,920 --> 00:58:16,480
Speaker 1: be talking about somebody who's really cornered the market on

1057
00:58:16,560 --> 00:58:19,680
Speaker 1: business books that are also really really fun and enjoyable

1058
00:58:19,720 --> 00:58:22,160
Speaker 1: and fascinating to But there are lots of other books,

1059
00:58:22,240 --> 00:58:25,120
Speaker 1: all right. So this last vacation and they were making

1060
00:58:25,120 --> 00:58:27,080
Speaker 1: fun of me because they're like, why are you slipping

1061
00:58:27,120 --> 00:58:31,200
Speaker 1: all these books, so Carrie always is the person who

1062
00:58:31,240 --> 00:58:35,440
Speaker 1: played Princess Brian. That's exactly right. So he has this

1063
00:58:35,480 --> 00:58:40,520
Speaker 1: book out that's charming and delightful about his experience making

1064
00:58:40,520 --> 00:58:44,840
Speaker 1: the movie, and it's just love it's lovely and my

1065
00:58:44,920 --> 00:58:48,400
Speaker 1: first date with my husband. Really, we've always loved that movie.

1066
00:58:48,440 --> 00:58:51,960
Speaker 1: It's it's a lightful, delightful movie. Very different character for

1067
00:58:52,080 --> 00:58:55,040
Speaker 1: Robin Wright than the one she's playing now, to say

1068
00:58:55,080 --> 00:58:57,520
Speaker 1: the least. And she is just so gorgeous in that

1069
00:58:57,560 --> 00:59:01,280
Speaker 1: movie and everybody in mean, there are famous lines from

1070
00:59:01,320 --> 00:59:03,560
Speaker 1: that movie that we say sometimes and people look at

1071
00:59:04,520 --> 00:59:06,520
Speaker 1: I don't think that word means what what you think?

1072
00:59:07,200 --> 00:59:09,880
Speaker 1: Have fun storming the castle? We say that to people

1073
00:59:09,880 --> 00:59:11,280
Speaker 1: all the time. They're like, what are you what are

1074
00:59:11,280 --> 00:59:14,760
Speaker 1: you talking about? Um? But I finished that book before lunch.

1075
00:59:14,840 --> 00:59:18,640
Speaker 1: That's not a heavy And then the third book I

1076
00:59:18,640 --> 00:59:21,320
Speaker 1: I actually one of the books I only got like

1077
00:59:21,360 --> 00:59:24,080
Speaker 1: halfway through. So some you could finish by lunch, some

1078
00:59:24,160 --> 00:59:26,120
Speaker 1: you could kill in a day. How to Be Less

1079
00:59:26,160 --> 00:59:29,560
Speaker 1: Wrong was by a mathematician that explains how do you

1080
00:59:29,640 --> 00:59:32,320
Speaker 1: statistics in everyday life? And it's really you know, it

1081
00:59:32,320 --> 00:59:35,800
Speaker 1: starts out with this wonderful anecdote of and I'm forgetting

1082
00:59:35,800 --> 00:59:38,160
Speaker 1: the gentleman's name, but he was a professor of Columbia.

1083
00:59:38,440 --> 00:59:40,080
Speaker 1: So the Army comes to him, and the Air Force

1084
00:59:40,080 --> 00:59:42,200
Speaker 1: comes to him. There really wasn't an air force then

1085
00:59:42,320 --> 00:59:45,160
Speaker 1: it was the Army Air Corps comes to him during

1086
00:59:45,160 --> 00:59:47,560
Speaker 1: World War Two and says, we're trying to figure out

1087
00:59:47,560 --> 00:59:52,120
Speaker 1: the optimal place to add armor to our various bombers.

1088
00:59:52,640 --> 00:59:56,480
Speaker 1: And here's what we have coming back to us, and

1089
00:59:56,560 --> 00:59:59,600
Speaker 1: here's the dispersion pattern. Here's what's on the wings, and

1090
00:59:59,640 --> 01:00:01,520
Speaker 1: here's what on the fuselage, and here's what's on the

1091
01:00:01,520 --> 01:00:04,760
Speaker 1: tail and blow and he says, um, you don't have

1092
01:00:04,800 --> 01:00:08,919
Speaker 1: any planes coming back with holes in about the engine. Yeah,

1093
01:00:08,960 --> 01:00:13,400
Speaker 1: that's adequately armored. And you know they're all He's like, no, no, no,

1094
01:00:13,480 --> 01:00:17,760
Speaker 1: you get hit there, you don't come back. You completely

1095
01:00:17,800 --> 01:00:23,040
Speaker 1: misunderstanding the whole statistics. This sample set is giving you information.

1096
01:00:23,360 --> 01:00:25,520
Speaker 1: You're just looking at it backwards. And the answer is

1097
01:00:25,920 --> 01:00:29,880
Speaker 1: you need more armor on your actual engines if you

1098
01:00:29,920 --> 01:00:32,760
Speaker 1: want those planes to come back as opposed to astray

1099
01:00:32,840 --> 01:00:36,240
Speaker 1: you know, even a nick sending them down. So it

1100
01:00:36,320 --> 01:00:38,840
Speaker 1: was kind of as it got further along the book,

1101
01:00:38,840 --> 01:00:40,200
Speaker 1: it got a little heavy, are a little more in

1102
01:00:40,240 --> 01:00:43,160
Speaker 1: depth mathematics, and so you start to slow down. You're

1103
01:00:43,240 --> 01:00:46,920
Speaker 1: you're reading pace. But um, that's my only like you,

1104
01:00:47,160 --> 01:00:50,600
Speaker 1: that's my time. I'm not a big book reader. And

1105
01:00:50,600 --> 01:00:52,600
Speaker 1: there's so many I and I and I get them.

1106
01:00:52,640 --> 01:00:57,280
Speaker 1: I get lovely gifts from people a good finance or

1107
01:00:57,400 --> 01:01:00,760
Speaker 1: generally generally I read constantly, But it's all the day

1108
01:01:00,800 --> 01:01:03,960
Speaker 1: to day stuff that right from all the research providers

1109
01:01:04,000 --> 01:01:07,560
Speaker 1: that I get, and your stuff and blogs and and

1110
01:01:07,760 --> 01:01:10,160
Speaker 1: so keeping up with that fire hose and stuff. It

1111
01:01:10,240 --> 01:01:13,520
Speaker 1: is totally drinking from a fire hose. So we had

1112
01:01:13,520 --> 01:01:17,200
Speaker 1: a conversation in our office, I want to say last year,

1113
01:01:18,000 --> 01:01:22,760
Speaker 1: and all of us made a commitment to read more

1114
01:01:22,880 --> 01:01:26,040
Speaker 1: finance related books stop and thinking about you have Marty

1115
01:01:26,160 --> 01:01:29,040
Speaker 1: Zack's book. Here's a guy who's sitting on right, a

1116
01:01:29,160 --> 01:01:33,720
Speaker 1: legendary investor who basically says, I'm going to take a

1117
01:01:33,880 --> 01:01:38,120
Speaker 1: thousand hours out of my year to explain to you

1118
01:01:38,240 --> 01:01:42,360
Speaker 1: everything I've learned about markets over the past four decades.

1119
01:01:42,960 --> 01:01:45,240
Speaker 1: Now you could do that, or you could read a

1120
01:01:45,240 --> 01:01:48,160
Speaker 1: newspaper and watch television. Which do you think net net

1121
01:01:48,480 --> 01:01:50,760
Speaker 1: is going to have a longer lasting impact on you?

1122
01:01:50,840 --> 01:01:54,240
Speaker 1: As an investor, so so we kind of all And

1123
01:01:54,280 --> 01:01:56,240
Speaker 1: I always have a giant queue of books and I'm

1124
01:01:56,280 --> 01:02:00,800
Speaker 1: always working my way through it, and I find finding

1125
01:02:01,160 --> 01:02:05,320
Speaker 1: interesting books that are not written by finance people but

1126
01:02:05,360 --> 01:02:10,080
Speaker 1: are applicable to finance is really fascinating. And whether it's

1127
01:02:10,120 --> 01:02:15,680
Speaker 1: about science and technology or just about ways of thinking.

1128
01:02:15,880 --> 01:02:19,439
Speaker 1: Have you read Abundance by Peter Diamonds. It's on my

1129
01:02:21,120 --> 01:02:23,280
Speaker 1: I haven't. I haven't read it cover to cover, like

1130
01:02:23,360 --> 01:02:26,640
Speaker 1: a like a novel. It's dog eared, and I've probably

1131
01:02:26,680 --> 01:02:30,600
Speaker 1: read every word in various times and for different reasons.

1132
01:02:30,640 --> 01:02:32,840
Speaker 1: But I'll tell you if you want, if you are

1133
01:02:32,880 --> 01:02:35,400
Speaker 1: feeling at all pessimistic about the future of our world,

1134
01:02:35,440 --> 01:02:37,800
Speaker 1: the future of this country, that's a book you got

1135
01:02:37,800 --> 01:02:39,920
Speaker 1: to read. It is it is such a He's the

1136
01:02:39,920 --> 01:02:42,960
Speaker 1: founder of the X Prize um, and it just talks

1137
01:02:43,000 --> 01:02:45,880
Speaker 1: about you never know where a brilliant idea is going

1138
01:02:45,920 --> 01:02:48,000
Speaker 1: to come from, and where where you're going to find

1139
01:02:48,000 --> 01:02:50,240
Speaker 1: creativity and innovation, and when you have two to three

1140
01:02:50,280 --> 01:02:53,760
Speaker 1: billion more people coming into the world of innovation and information,

1141
01:02:54,320 --> 01:02:56,080
Speaker 1: you just never know where a good idea is going

1142
01:02:56,160 --> 01:02:58,760
Speaker 1: to come from. He uses as an example one of

1143
01:02:58,760 --> 01:03:01,680
Speaker 1: the more recent X prize was for anybody. You know,

1144
01:03:01,720 --> 01:03:05,240
Speaker 1: the Exerprize is about setting up a financial incentive for

1145
01:03:05,360 --> 01:03:09,200
Speaker 1: people to solve problems. And it might be a large

1146
01:03:07,880 --> 01:03:12,800
Speaker 1: could be could be for a you know, an individual

1147
01:03:12,840 --> 01:03:16,360
Speaker 1: in their garage just you know. X y Z company

1148
01:03:16,400 --> 01:03:19,320
Speaker 1: is sponsoring a twenty million dollar exerprize to figure out

1149
01:03:19,520 --> 01:03:21,400
Speaker 1: fill in the blank. And one of them was figure

1150
01:03:21,400 --> 01:03:24,760
Speaker 1: out how to contain an oil spill immediately after it's

1151
01:03:24,760 --> 01:03:27,960
Speaker 1: happened so that it doesn't spread. And he talks about

1152
01:03:28,000 --> 01:03:33,160
Speaker 1: the fact that the winner of that was a tattoo artist. Oh,

1153
01:03:33,200 --> 01:03:36,520
Speaker 1: he said, the light bulb went on when he thought

1154
01:03:36,560 --> 01:03:41,240
Speaker 1: about how whatever chemicals are used to prevent the ink

1155
01:03:41,280 --> 01:03:44,200
Speaker 1: when it's applied from spreading and on the skin, and

1156
01:03:44,280 --> 01:03:47,560
Speaker 1: he adopted the same thinking and I think partnered up

1157
01:03:47,600 --> 01:03:51,160
Speaker 1: with with chemists and ultimately won the prize. So he

1158
01:03:51,200 --> 01:03:54,680
Speaker 1: just used as an example of you never know where

1159
01:03:54,800 --> 01:03:58,080
Speaker 1: the next great thing is going to come from. And uh,

1160
01:03:58,120 --> 01:04:02,400
Speaker 1: you know, don't don't don't assume that that the greatness

1161
01:04:02,480 --> 01:04:07,520
Speaker 1: of us as innovators and creative people is diminishing. That's

1162
01:04:07,520 --> 01:04:11,600
Speaker 1: funny because I had a conversation with a reporter yesterday.

1163
01:04:11,640 --> 01:04:15,040
Speaker 1: A young gentleman at U n C who was asking,

1164
01:04:15,200 --> 01:04:17,840
Speaker 1: I'm sorry, that's wrong. It was a different reporter and

1165
01:04:17,880 --> 01:04:19,760
Speaker 1: it was UM, I think it was U S News

1166
01:04:20,440 --> 01:04:24,920
Speaker 1: and World Report about they had looked into something and

1167
01:04:24,960 --> 01:04:28,439
Speaker 1: I had written about in two thousand, Fortune did this,

1168
01:04:28,760 --> 01:04:31,720
Speaker 1: you know, ten stocks you know for the next ten years,

1169
01:04:31,720 --> 01:04:34,560
Speaker 1: and it was a debut, you know, it was Enron

1170
01:04:34,600 --> 01:04:36,680
Speaker 1: and a bunch of others. It was just a horror show.

1171
01:04:37,240 --> 01:04:39,560
Speaker 1: And so now there was more recently and I remember

1172
01:04:39,560 --> 01:04:43,360
Speaker 1: who did it, UM thirty stocks for the next thirty years.

1173
01:04:43,520 --> 01:04:46,240
Speaker 1: And the person asked me, why is this a bad idea?

1174
01:04:46,400 --> 01:04:50,640
Speaker 1: And to your concept, I said, there is a kid today,

1175
01:04:50,880 --> 01:04:56,320
Speaker 1: he's fourteen. Right in thirteen years or so, he will

1176
01:04:56,360 --> 01:04:59,240
Speaker 1: be out of college at a grad school, twenty seven

1177
01:04:59,320 --> 01:05:02,760
Speaker 1: years old, at some startups somewhere, and I can't tell

1178
01:05:02,800 --> 01:05:04,920
Speaker 1: you what the hell this guy is going to invent,

1179
01:05:05,600 --> 01:05:10,400
Speaker 1: but it's gonna cure cancer or change change batteries. So

1180
01:05:10,440 --> 01:05:12,400
Speaker 1: it's just an article of the day about, hey, if

1181
01:05:12,440 --> 01:05:16,600
Speaker 1: we swap aluminum for this, I odd this this diode

1182
01:05:16,680 --> 01:05:22,200
Speaker 1: in batteries, it's you know, lighter, last longer, and by

1183
01:05:22,240 --> 01:05:24,480
Speaker 1: the way, you could recharge a battery in thirty seconds.

1184
01:05:25,200 --> 01:05:28,080
Speaker 1: Nobody has the slightest clue where this next thing is

1185
01:05:28,120 --> 01:05:29,880
Speaker 1: going to go. So how are you going to pick

1186
01:05:29,960 --> 01:05:33,959
Speaker 1: thirty companies for thirty years? Go back thirty years ago?

1187
01:05:34,360 --> 01:05:36,920
Speaker 1: Most of them don't even don't even exist, you know,

1188
01:05:37,000 --> 01:05:40,240
Speaker 1: look at the nifty you know they by the way

1189
01:05:40,240 --> 01:05:45,600
Speaker 1: they NASA and its construction in two thousand relative to

1190
01:05:45,880 --> 01:05:49,200
Speaker 1: what it is right now. Does So you've been around

1191
01:05:49,200 --> 01:05:54,240
Speaker 1: long enough as have I to remember the nineties really vividly.

1192
01:05:55,160 --> 01:05:59,040
Speaker 1: Microsoft essentially bailed out Apple with a hundred and fifty

1193
01:05:59,080 --> 01:06:03,320
Speaker 1: million dollar investment, and my thesis at the time was, well,

1194
01:06:03,360 --> 01:06:06,360
Speaker 1: they wanted another operating system to keep the Justice Department

1195
01:06:06,400 --> 01:06:09,320
Speaker 1: at Bay. Had Apple gone under, there would have been

1196
01:06:09,360 --> 01:06:12,080
Speaker 1: really the only oh yes, it would have been anti

1197
01:06:12,080 --> 01:06:14,520
Speaker 1: trust problem. If I would have said to you, by

1198
01:06:14,520 --> 01:06:17,880
Speaker 1: the way, that was a terrible mistake Microsoft made. Apple

1199
01:06:17,960 --> 01:06:19,480
Speaker 1: is going to come out with all these great products

1200
01:06:19,480 --> 01:06:22,640
Speaker 1: and they're just gonna kick Microsoft. But Microsoft is still

1201
01:06:22,680 --> 01:06:25,840
Speaker 1: be a cash cow, right right. I got an email

1202
01:06:25,880 --> 01:06:28,960
Speaker 1: from a friend and her signature is typed on glass

1203
01:06:28,960 --> 01:06:32,520
Speaker 1: sent by Magic, which is really what an iPhone or

1204
01:06:32,600 --> 01:06:36,280
Speaker 1: iPad is, by the way, so we're not even talking

1205
01:06:36,280 --> 01:06:38,960
Speaker 1: a hundred years from that. We're talking fifteen years from now,

1206
01:06:39,840 --> 01:06:43,160
Speaker 1: Apple become the biggest market cap in the world. Microsoft

1207
01:06:43,200 --> 01:06:45,120
Speaker 1: will still be a cash cow, but they'll really have

1208
01:06:45,400 --> 01:06:49,480
Speaker 1: no waning influence on technology. You would have said, you've

1209
01:06:49,520 --> 01:06:53,000
Speaker 1: lost your mind. You're hallucinating that. Not only is that

1210
01:06:53,080 --> 01:06:58,080
Speaker 1: not realistic, it's probably impossible. And that's like all of

1211
01:06:58,200 --> 01:07:01,760
Speaker 1: fifteen sixteen years ago. So now double that thirty years

1212
01:07:01,800 --> 01:07:06,480
Speaker 1: from now. Which of these companies. So whether it's you know,

1213
01:07:06,560 --> 01:07:10,360
Speaker 1: Moore's law with the speed with which things are changing

1214
01:07:10,400 --> 01:07:15,120
Speaker 1: and innovations kicking in grows exponentially and uh so that's

1215
01:07:15,160 --> 01:07:17,919
Speaker 1: you know, also that Peter Diamandous concept, and he named

1216
01:07:17,920 --> 01:07:22,000
Speaker 1: a university off of its singularity, And uh, I agree,

1217
01:07:22,040 --> 01:07:24,440
Speaker 1: I think that there is. I think that's beyond our lifetime,

1218
01:07:24,440 --> 01:07:28,120
Speaker 1: the singularity. I'm hoping it's beyond lifetime. So when I

1219
01:07:28,160 --> 01:07:30,720
Speaker 1: had Byron ween on, he talked about he left a

1220
01:07:30,720 --> 01:07:32,640
Speaker 1: lot of money to Harvard, he gave a lot of

1221
01:07:32,640 --> 01:07:36,800
Speaker 1: money to all these different charities. He's very much a philanthropist.

1222
01:07:37,640 --> 01:07:41,360
Speaker 1: But he made a bunch of money investing in biotechs

1223
01:07:41,760 --> 01:07:43,320
Speaker 1: twenty five years ago. And he goes, I don't even

1224
01:07:43,320 --> 01:07:44,600
Speaker 1: look at my bought him, I put him a wife

1225
01:07:44,600 --> 01:07:46,880
Speaker 1: for twenty five years, and now they're worth millions and

1226
01:07:46,920 --> 01:07:50,720
Speaker 1: millions of dollars. People are just starting You had the

1227
01:07:50,760 --> 01:07:52,720
Speaker 1: sixty minutes piece not too long ago. You had the

1228
01:07:52,800 --> 01:07:58,280
Speaker 1: vice piece not too long ago about the combination of genomics, immunalogy,

1229
01:07:58,800 --> 01:08:03,240
Speaker 1: and and there was one other factor where essentially cancer

1230
01:08:03,600 --> 01:08:08,400
Speaker 1: for the first time ever seems to be coming up

1231
01:08:08,440 --> 01:08:13,200
Speaker 1: on a potential cure, right, which I I think, not

1232
01:08:13,320 --> 01:08:15,800
Speaker 1: because I have any medical expertise, but maybe it's just

1233
01:08:15,920 --> 01:08:19,479
Speaker 1: hope is in our lifetime thing. I don't even think

1234
01:08:19,479 --> 01:08:21,880
Speaker 1: it's in our lifetime. I think it's somewhere in the

1235
01:08:21,880 --> 01:08:24,680
Speaker 1: next five to ten years. So if you if you

1236
01:08:24,760 --> 01:08:29,360
Speaker 1: see the sixty minutes piece, showed them taking um polio

1237
01:08:29,479 --> 01:08:33,960
Speaker 1: vax polio virus, not even the vaccine, genetically alterning it

1238
01:08:34,080 --> 01:08:37,439
Speaker 1: and dripping it into the brain to kill what is

1239
01:08:37,560 --> 01:08:40,559
Speaker 1: normally and now granted it's only a fifty percent success rate,

1240
01:08:41,000 --> 01:08:45,320
Speaker 1: but that's huge. Fifty This was a fatal You get

1241
01:08:45,360 --> 01:08:48,720
Speaker 1: that that diagnosis, get your personal affairs in order and

1242
01:08:48,720 --> 01:08:50,760
Speaker 1: now and now we're giving it to people in order

1243
01:08:50,760 --> 01:08:53,719
Speaker 1: to cure. So so I don't know when we're gonna

1244
01:08:53,760 --> 01:08:56,600
Speaker 1: there are some four hundred different types of cancer, and

1245
01:08:56,600 --> 01:08:58,599
Speaker 1: it's going to be a process before all of them

1246
01:08:58,960 --> 01:09:01,040
Speaker 1: are gotten. And maybe we don't get all of them,

1247
01:09:01,040 --> 01:09:04,720
Speaker 1: but we get some. But that has changed so rapidly.

1248
01:09:04,920 --> 01:09:08,360
Speaker 1: If I would have asked somebody five years ago, hey,

1249
01:09:08,400 --> 01:09:10,479
Speaker 1: what do you think about curing cancer? You have been

1250
01:09:10,479 --> 01:09:13,080
Speaker 1: hearing that my whole life. It's a century away. And

1251
01:09:13,160 --> 01:09:16,960
Speaker 1: suddenly a couple of different technologies. You get the ability

1252
01:09:17,000 --> 01:09:19,800
Speaker 1: to manipulate DNA, you get all of the increases in

1253
01:09:19,840 --> 01:09:23,799
Speaker 1: technology that everything gets finer and finer. How does anyone

1254
01:09:23,840 --> 01:09:25,880
Speaker 1: have a clue where the next great idea is going

1255
01:09:25,920 --> 01:09:27,720
Speaker 1: to come from? I couldn't agree more. That's why I

1256
01:09:27,760 --> 01:09:32,720
Speaker 1: love the acronym brain, which is biotechnology, robotics, artificial intelligence,

1257
01:09:32,800 --> 01:09:38,160
Speaker 1: nanotechnology for what are just the whether you hear it

1258
01:09:38,200 --> 01:09:41,680
Speaker 1: reference to this is what kids should be studying, like

1259
01:09:41,720 --> 01:09:46,680
Speaker 1: the STEM, which was science technology. Yeah, my son just

1260
01:09:47,040 --> 01:09:50,320
Speaker 1: called us about two months ago. He's a freshman at

1261
01:09:50,360 --> 01:09:52,519
Speaker 1: Indiana University, and part of the reason why he went

1262
01:09:52,560 --> 01:09:55,160
Speaker 1: there was the Kelly School of Business, which is a

1263
01:09:55,280 --> 01:09:58,840
Speaker 1: very very well round, world rounded business undergraduate business school.

1264
01:09:59,000 --> 01:10:01,759
Speaker 1: But he called a couple of months ago and said, um,

1265
01:10:01,880 --> 01:10:04,360
Speaker 1: I think I want a minor in business, but major

1266
01:10:04,360 --> 01:10:09,519
Speaker 1: in math. That's a combat. That's an absolute comma. Even

1267
01:10:09,560 --> 01:10:13,320
Speaker 1: Wall Street firms are looking for math oriented, no doubt

1268
01:10:13,360 --> 01:10:16,559
Speaker 1: about it. Look if you if you look at the

1269
01:10:16,600 --> 01:10:20,439
Speaker 1: world of quantitative investing, if you say, let's put away

1270
01:10:20,479 --> 01:10:23,360
Speaker 1: the historic myths and the things that are unproven and

1271
01:10:23,439 --> 01:10:27,800
Speaker 1: just say, what do we know actually works mathematically, whether

1272
01:10:27,840 --> 01:10:31,360
Speaker 1: it's Jim O'Shaughnessy or rob or not. Or we had

1273
01:10:31,360 --> 01:10:34,960
Speaker 1: Cliff ass In this recently who basically laid out the

1274
01:10:34,960 --> 01:10:40,760
Speaker 1: the argument for value and momentum together is very much

1275
01:10:40,760 --> 01:10:44,000
Speaker 1: an unbeatable combination. And the reason we know that is

1276
01:10:44,040 --> 01:10:48,759
Speaker 1: mathematics as opposed to all the specific myths. Uh. We see.

1277
01:10:49,120 --> 01:10:51,559
Speaker 1: So in the last couple of minutes we have you

1278
01:10:51,600 --> 01:10:52,960
Speaker 1: for I know we have to get you out of

1279
01:10:52,960 --> 01:10:57,120
Speaker 1: here eventually. Let's see if there's a handful of questions

1280
01:10:57,120 --> 01:10:59,080
Speaker 1: I want to come up with you. Well, one, I'm

1281
01:10:59,120 --> 01:11:01,240
Speaker 1: going to jump in and answer something you haven't asked

1282
01:11:01,240 --> 01:11:04,200
Speaker 1: me yet, because we've talked so much about mentors and

1283
01:11:04,600 --> 01:11:08,920
Speaker 1: Martin um. But how how cool I'll sort of ask

1284
01:11:11,080 --> 01:11:14,200
Speaker 1: the sheer luck but bliss that I have had in

1285
01:11:14,240 --> 01:11:18,400
Speaker 1: my career going from working for Marty's wage to working

1286
01:11:18,439 --> 01:11:20,960
Speaker 1: for Charles Schwab, for Chuck the man, and people don't

1287
01:11:20,960 --> 01:11:23,800
Speaker 1: realize Charles Schwab is a real person. Chuck still is

1288
01:11:23,840 --> 01:11:27,280
Speaker 1: the chairman of the company right and and very active

1289
01:11:27,360 --> 01:11:29,920
Speaker 1: chairman that somebody else we should get it. Very active chairman.

1290
01:11:30,880 --> 01:11:32,960
Speaker 1: I'm going to have you extend and invite. Also, he's

1291
01:11:33,120 --> 01:11:35,719
Speaker 1: I think we could say he's a master of business.

1292
01:11:36,160 --> 01:11:39,679
Speaker 1: He has certainly a master point something. He's about as iconic.

1293
01:11:39,760 --> 01:11:43,800
Speaker 1: He really he democratized investing for these So again for

1294
01:11:43,840 --> 01:11:46,880
Speaker 1: the young uns who don't understand this, there used to

1295
01:11:46,920 --> 01:11:51,360
Speaker 1: be fees that were set for everybody, and then there

1296
01:11:51,400 --> 01:11:55,799
Speaker 1: was a rule change that allowed competition by reducing fees,

1297
01:11:56,120 --> 01:11:59,360
Speaker 1: and Schwab essentially said, okay, let's go. We were the

1298
01:11:59,400 --> 01:12:02,840
Speaker 1: first disc out brokerage firm, first discount brokerage the early

1299
01:12:02,920 --> 01:12:10,479
Speaker 1: seventy years ago. So we just last year celebrated and

1300
01:12:10,600 --> 01:12:14,200
Speaker 1: he really he he changed the business as we know

1301
01:12:14,320 --> 01:12:18,800
Speaker 1: it um and has been a pioneer all along the way.

1302
01:12:19,080 --> 01:12:21,479
Speaker 1: Um stepped back in a CEO a number of years

1303
01:12:21,520 --> 01:12:25,400
Speaker 1: ago and and then ultimately found his successor in Walt Bettinger,

1304
01:12:25,479 --> 01:12:27,639
Speaker 1: who is our CEO now. But he is still chairman

1305
01:12:27,680 --> 01:12:31,000
Speaker 1: of the board and a very active chairman, much to

1306
01:12:31,040 --> 01:12:33,439
Speaker 1: the thrill of all of us that get to still

1307
01:12:33,479 --> 01:12:35,240
Speaker 1: have him around on a day to day basis. And

1308
01:12:35,240 --> 01:12:38,040
Speaker 1: he's been in the business for more than four years.

1309
01:12:38,160 --> 01:12:42,639
Speaker 1: How old was he when he started? Seventies seven now

1310
01:12:43,000 --> 01:12:45,120
Speaker 1: really so, yeah, he was in his thirty. He looks

1311
01:12:45,120 --> 01:12:47,519
Speaker 1: pretty good for seven. He looks fantastic. He stays in

1312
01:12:47,560 --> 01:12:50,679
Speaker 1: great shape. He's a ski or a golfer and no kidding, yeah,

1313
01:12:50,680 --> 01:12:53,600
Speaker 1: and he's uh, he's he's a prince among men. And

1314
01:12:53,840 --> 01:12:57,400
Speaker 1: so I have and then my my media part of

1315
01:12:57,400 --> 01:13:00,639
Speaker 1: what I do. I got to start on Wall Street

1316
01:13:00,640 --> 01:13:05,080
Speaker 1: week with Lewis Rukaiser. Really seriously you Marty's wide Lewis Ruckeiser,

1317
01:13:05,360 --> 01:13:09,400
Speaker 1: Chuck Schwab. That pinched me, you should be buying lottery

1318
01:13:09,400 --> 01:13:12,160
Speaker 1: tickets every other week. Basic that I have, I have

1319
01:13:12,240 --> 01:13:15,719
Speaker 1: been very, very blessed. That's amazing. One of the questions

1320
01:13:15,760 --> 01:13:18,040
Speaker 1: I had asked you earlier, who else were some of

1321
01:13:18,120 --> 01:13:23,799
Speaker 1: your mentors? You actually guest hosted for ru Kaiser? Right, so, um,

1322
01:13:23,840 --> 01:13:26,320
Speaker 1: I was a regular. I was a guest initially in

1323
01:13:27,880 --> 01:13:29,360
Speaker 1: and then he right away I got asked to be

1324
01:13:29,360 --> 01:13:32,439
Speaker 1: a regular panelist. So my first show as a regular

1325
01:13:32,439 --> 01:13:36,280
Speaker 1: panelist was in early and then maybe it was two

1326
01:13:36,360 --> 01:13:38,799
Speaker 1: or three years later. I don't remember exact time frame,

1327
01:13:39,080 --> 01:13:43,760
Speaker 1: but there was a small subset about three of us

1328
01:13:43,800 --> 01:13:47,679
Speaker 1: of panelists that Lou picked to stand in for him

1329
01:13:47,720 --> 01:13:50,599
Speaker 1: if he was on vacation or not feeling well. And

1330
01:13:50,720 --> 01:13:53,479
Speaker 1: so only one time, but um I got to play

1331
01:13:53,560 --> 01:13:56,160
Speaker 1: Lewis Ruckeiser. So I did the walk in, I did

1332
01:13:56,160 --> 01:13:58,719
Speaker 1: the monologue, I walked over to the table, sat down

1333
01:13:58,720 --> 01:14:01,719
Speaker 1: with the panelist, went an interview you a guest, and

1334
01:14:02,080 --> 01:14:05,799
Speaker 1: it was it was incredibly nerve wracking. You're a natural,

1335
01:14:06,080 --> 01:14:08,200
Speaker 1: you know what I I don't. Fortunately, I don't get

1336
01:14:08,280 --> 01:14:10,920
Speaker 1: jitters either when I to public speaking or this type

1337
01:14:10,920 --> 01:14:14,280
Speaker 1: of thing. But standing in loose show shoes for a

1338
01:14:14,320 --> 01:14:17,280
Speaker 1: four power show. Uh. And it was, you know, quite

1339
01:14:17,280 --> 01:14:18,960
Speaker 1: a few years ago, so I was much younger than

1340
01:14:18,960 --> 01:14:21,519
Speaker 1: I am now. It was it was daunting but fun.

1341
01:14:21,800 --> 01:14:24,519
Speaker 1: I tell the story. You you actually play a role

1342
01:14:24,720 --> 01:14:28,000
Speaker 1: in my media career because I tell the story the

1343
01:14:28,080 --> 01:14:33,920
Speaker 1: first time I did you and I the first time before,

1344
01:14:34,520 --> 01:14:37,200
Speaker 1: I had just finished a diet coke in the green

1345
01:14:37,280 --> 01:14:39,479
Speaker 1: room and I was heading to the bathroom when they

1346
01:14:39,479 --> 01:14:42,080
Speaker 1: tapped me, Hey, we're on the let's go, and they

1347
01:14:42,120 --> 01:14:44,559
Speaker 1: bring me in and it's I'm sitting here. It's a

1348
01:14:44,600 --> 01:14:48,200
Speaker 1: small round table. Next to my left was Larry Caudlow.

1349
01:14:48,280 --> 01:14:50,679
Speaker 1: To my right was you and a friend of mine

1350
01:14:50,840 --> 01:14:53,960
Speaker 1: who was a strategist at a at a firm I

1351
01:14:53,960 --> 01:14:56,479
Speaker 1: had worked at previously. I got a gentleman named Barry

1352
01:14:56,520 --> 01:15:00,000
Speaker 1: Hyman had said to me, look, don't look nervous, don't

1353
01:15:00,120 --> 01:15:02,519
Speaker 1: dart your eyes back and forth. Find something to look at.

1354
01:15:02,880 --> 01:15:04,639
Speaker 1: And I was looking for something to go. Liz Anna

1355
01:15:04,640 --> 01:15:08,800
Speaker 1: Sanders has the whitest teeth I've ever seen. And I

1356
01:15:08,800 --> 01:15:11,320
Speaker 1: swear this every word is true. That was my focus.

1357
01:15:11,360 --> 01:15:14,720
Speaker 1: I was just looking at you. Think about the conversation

1358
01:15:14,760 --> 01:15:17,240
Speaker 1: we had before we walked down into the studio. What

1359
01:15:17,280 --> 01:15:19,679
Speaker 1: was it about. Oh I don't know them so long ago.

1360
01:15:19,760 --> 01:15:25,599
Speaker 1: Oh that's right. Oh that's hilarious. That's absolutely hilarious. No smoking,

1361
01:15:25,640 --> 01:15:28,320
Speaker 1: no cost never never had a cigarette, Never had a

1362
01:15:28,320 --> 01:15:32,679
Speaker 1: cup of coffee. Don't drink, don't smoke, um, well, drink

1363
01:15:32,840 --> 01:15:37,280
Speaker 1: other stuff, just okay, no coffee. So um So that

1364
01:15:37,360 --> 01:15:39,720
Speaker 1: was my first show, and I remember it was a

1365
01:15:39,760 --> 01:15:43,040
Speaker 1: glass table, which was the only thing that prevented me

1366
01:15:43,120 --> 01:15:46,599
Speaker 1: from throwing up, because I remember thinking, if you puke

1367
01:15:46,680 --> 01:15:51,360
Speaker 1: on this table, it's just gonna skitter it in my lap,

1368
01:15:51,400 --> 01:15:55,479
Speaker 1: all over my It was just, you know, my father

1369
01:15:55,520 --> 01:15:57,639
Speaker 1: in law, who's no longer with us, was the only

1370
01:15:57,680 --> 01:16:01,080
Speaker 1: person who was honest with me. I go back into

1371
01:16:01,120 --> 01:16:04,800
Speaker 1: the office the next day thunderous applause, or at least

1372
01:16:04,800 --> 01:16:08,200
Speaker 1: that's how I remember. There were five standing ovation. It

1373
01:16:08,280 --> 01:16:11,720
Speaker 1: was just great, and everybody, my supervisor in the head

1374
01:16:11,720 --> 01:16:14,680
Speaker 1: of everybody loved so I called Harry. So, Harry, what

1375
01:16:14,720 --> 01:16:18,040
Speaker 1: do you think. I don't know. You looked kind of nervous.

1376
01:16:18,240 --> 01:16:20,519
Speaker 1: You you would your lips would draw. You was smacking.

1377
01:16:20,960 --> 01:16:23,800
Speaker 1: So every time, this is absolutely true, every time I

1378
01:16:24,080 --> 01:16:27,879
Speaker 1: the first three or four times I did television, everybody

1379
01:16:27,880 --> 01:16:29,840
Speaker 1: loved it, and Harry was the only guy give me

1380
01:16:29,880 --> 01:16:34,400
Speaker 1: the straight dope. So by the fifth or sixth appearance,

1381
01:16:34,680 --> 01:16:36,320
Speaker 1: how was that, He goes, I have to tell you,

1382
01:16:36,320 --> 01:16:39,720
Speaker 1: you looked very comfortable. You were articulate. You sounded like

1383
01:16:39,720 --> 01:16:43,560
Speaker 1: you knew that was That was when I said, oh, okay,

1384
01:16:43,640 --> 01:16:48,840
Speaker 1: So I really appreciated him, not sugarcoating it. You gotta

1385
01:16:48,880 --> 01:16:51,640
Speaker 1: work a little bit. You You looked very uncomfortable. All

1386
01:16:51,760 --> 01:16:53,720
Speaker 1: I guess I gotta I gotta work on that. So

1387
01:16:53,880 --> 01:16:55,600
Speaker 1: this isn't about me, though this is supposed to be

1388
01:16:55,600 --> 01:16:58,640
Speaker 1: about you. You were the there at the first and

1389
01:16:58,680 --> 01:17:03,440
Speaker 1: I remember thinking, God, she is just so smooth and effortless.

1390
01:17:03,680 --> 01:17:07,080
Speaker 1: Can I tell you the best tip I got ever

1391
01:17:07,760 --> 01:17:10,720
Speaker 1: that I have I've It's always in my mind when

1392
01:17:10,760 --> 01:17:13,280
Speaker 1: I do something like this, or I do a TV appearance,

1393
01:17:13,400 --> 01:17:15,080
Speaker 1: or I get up in front of a room. Came

1394
01:17:15,120 --> 01:17:17,960
Speaker 1: from Lewis Ruckaiser. So the very first time I was

1395
01:17:18,000 --> 01:17:20,640
Speaker 1: on the show was as a guest. So I was

1396
01:17:20,680 --> 01:17:23,640
Speaker 1: doing the ten minute interview after the discussion around the

1397
01:17:23,640 --> 01:17:25,400
Speaker 1: table with the pans. Were you working at the time

1398
01:17:26,120 --> 01:17:30,200
Speaker 1: at Gavatar? And I had not met lou before. I

1399
01:17:30,280 --> 01:17:32,440
Speaker 1: was a huge fan, but I had not met him.

1400
01:17:32,520 --> 01:17:35,320
Speaker 1: And just before he came out to do his monologue,

1401
01:17:35,720 --> 01:17:37,519
Speaker 1: I was behind the scenes and that was when I

1402
01:17:37,560 --> 01:17:40,160
Speaker 1: met him literally for the first time, shook hands. He said,

1403
01:17:40,200 --> 01:17:41,679
Speaker 1: thank you for being on the show. Are you nervous?

1404
01:17:41,760 --> 01:17:44,719
Speaker 1: I said a little bit, he said, and he asked

1405
01:17:44,760 --> 01:17:46,800
Speaker 1: me what I thought wasn't an odd question at the time,

1406
01:17:47,000 --> 01:17:49,479
Speaker 1: two part questions. He said, are your parents still alive?

1407
01:17:49,479 --> 01:17:51,439
Speaker 1: Are they still with us. I said yes. He said,

1408
01:17:51,479 --> 01:17:56,240
Speaker 1: are they in the business? I said, uh, television, business, finance?

1409
01:17:56,360 --> 01:17:58,080
Speaker 1: He said, no, your business are they? Are they Wall

1410
01:17:58,120 --> 01:18:00,439
Speaker 1: Street people? I said no, no, no, are from it.

1411
01:18:00,520 --> 01:18:03,320
Speaker 1: My my my mom was largely a stay at home mom.

1412
01:18:03,360 --> 01:18:05,679
Speaker 1: She had some jobs, but not certainly not in finance,

1413
01:18:05,920 --> 01:18:08,840
Speaker 1: and my dad was an ad sales person for a

1414
01:18:08,880 --> 01:18:14,160
Speaker 1: trade magazine. He grabbed both of my elbows and said, Okay,

1415
01:18:14,360 --> 01:18:16,519
Speaker 1: I want you to do me a favor when you

1416
01:18:16,560 --> 01:18:18,760
Speaker 1: come out here to do the interview with me. Get

1417
01:18:18,760 --> 01:18:21,560
Speaker 1: them to understand what you're talking about. And I have

1418
01:18:21,640 --> 01:18:24,320
Speaker 1: always taken that to heart because I think even though

1419
01:18:24,320 --> 01:18:26,400
Speaker 1: what we do is fairly complicated, what's going on in

1420
01:18:26,400 --> 01:18:29,080
Speaker 1: the world is often fairly complicated, there is a way

1421
01:18:29,160 --> 01:18:31,400
Speaker 1: to explain it and talk about it to investors that

1422
01:18:31,600 --> 01:18:34,719
Speaker 1: is much less complicated. And I find that the people

1423
01:18:34,760 --> 01:18:36,960
Speaker 1: who have come up to me and said thank you

1424
01:18:37,040 --> 01:18:39,519
Speaker 1: for speaking in in plain English and not using a

1425
01:18:39,520 --> 01:18:42,679
Speaker 1: lot of jargon and making it easier and understand more

1426
01:18:42,720 --> 01:18:45,200
Speaker 1: often than not, those are people on the more sophisticated

1427
01:18:45,240 --> 01:18:48,080
Speaker 1: end of the spectrum than they are on the lesser end.

1428
01:18:48,120 --> 01:18:50,760
Speaker 1: And I find I'm almost thirty years in this business. Now,

1429
01:18:51,120 --> 01:18:53,320
Speaker 1: to me, there's nothing that's more of a turn off

1430
01:18:53,439 --> 01:18:55,200
Speaker 1: than when I hear somebody get up on stage or

1431
01:18:55,200 --> 01:18:58,120
Speaker 1: on TV that one wants to sound like the smartest

1432
01:18:58,120 --> 01:19:01,040
Speaker 1: guy in the room and is throwing all sorts of jargon,

1433
01:19:01,080 --> 01:19:04,040
Speaker 1: and they're very William F. Buckley like in there in

1434
01:19:04,080 --> 01:19:07,960
Speaker 1: the way they speak. And I just much more appreciate

1435
01:19:08,120 --> 01:19:11,800
Speaker 1: somebody who just speaks in plain English, doesn't try to

1436
01:19:11,840 --> 01:19:16,479
Speaker 1: get overly flowery in the language. And and I that's

1437
01:19:16,479 --> 01:19:19,080
Speaker 1: always in the back of my mind. Okay, get your

1438
01:19:19,120 --> 01:19:20,760
Speaker 1: get mom and dad to understand what you're talking. But

1439
01:19:20,920 --> 01:19:24,600
Speaker 1: it's funny you say that because my mother is now retired,

1440
01:19:24,680 --> 01:19:27,920
Speaker 1: was a real estate agent. My wife is an art teacher.

1441
01:19:28,439 --> 01:19:31,000
Speaker 1: And that's the same concept in my head. That's my tale.

1442
01:19:31,160 --> 01:19:33,080
Speaker 1: You do the same thing. Speak to mom, speak to

1443
01:19:33,120 --> 01:19:35,799
Speaker 1: my wife. So neither of them in the business. Although

1444
01:19:35,880 --> 01:19:38,559
Speaker 1: my mom was kind of a she's the one who

1445
01:19:38,600 --> 01:19:43,200
Speaker 1: first turned me onto equities. Okay, so she was an

1446
01:19:43,240 --> 01:19:47,560
Speaker 1: investor in the eighties and and and nineties, and but

1447
01:19:47,720 --> 01:19:50,439
Speaker 1: she was really she was a real estate agent by profession.

1448
01:19:50,520 --> 01:19:53,320
Speaker 1: That was what she did. So the issue was always

1449
01:19:53,400 --> 01:19:57,840
Speaker 1: get her to understand these complex economic issues or the

1450
01:19:57,920 --> 01:20:00,800
Speaker 1: sentiment issues or any of the technical shoes. If you

1451
01:20:00,880 --> 01:20:04,080
Speaker 1: could get somebody who's not a Wolf Street professional to

1452
01:20:04,240 --> 01:20:07,720
Speaker 1: get it, hey, then everybody should be all right. So

1453
01:20:07,880 --> 01:20:10,519
Speaker 1: in the last few minutes we have and I'm really

1454
01:20:11,160 --> 01:20:15,599
Speaker 1: enjoying these digressions, but I know our time is only finite.

1455
01:20:15,680 --> 01:20:18,759
Speaker 1: Let me ask you a few of the standard questions

1456
01:20:18,800 --> 01:20:23,600
Speaker 1: I'd like to ask people. Um, and there are a

1457
01:20:23,640 --> 01:20:26,679
Speaker 1: whole bunch of other questions. So we discussed investing books,

1458
01:20:26,760 --> 01:20:32,160
Speaker 1: we discussed investors, we mentors, and who the other investors were.

1459
01:20:32,680 --> 01:20:36,440
Speaker 1: So so let me ask you these last two questions.

1460
01:20:37,600 --> 01:20:39,760
Speaker 1: M M, I really don't love that question, and I

1461
01:20:39,800 --> 01:20:42,599
Speaker 1: don't like this question. We you know, can I tell

1462
01:20:42,640 --> 01:20:45,439
Speaker 1: you something? I write all these questions down and we

1463
01:20:45,560 --> 01:20:50,519
Speaker 1: got a conversation through. So there are two questions I

1464
01:20:50,560 --> 01:20:53,280
Speaker 1: always ask people, and let me give you these. The

1465
01:20:53,400 --> 01:20:56,200
Speaker 1: first one is, we've seen a whole lot of changes

1466
01:20:56,400 --> 01:20:59,320
Speaker 1: over the past your twenty nine years in the market,

1467
01:20:59,680 --> 01:21:05,000
Speaker 1: every thing from decimalization to market crashes to high frequency trading.

1468
01:21:05,479 --> 01:21:08,280
Speaker 1: What sort of shifts do you see coming in the

1469
01:21:08,439 --> 01:21:12,280
Speaker 1: not too distant future that you think are significant for

1470
01:21:12,960 --> 01:21:17,720
Speaker 1: investors thinking over the next several years. So call it

1471
01:21:17,800 --> 01:21:22,320
Speaker 1: a medium term time horizon, I think we will continue

1472
01:21:22,400 --> 01:21:27,280
Speaker 1: to see greater access to a variety of asset classes,

1473
01:21:27,920 --> 01:21:32,200
Speaker 1: so further democratization of investing for many individuals, I think,

1474
01:21:32,640 --> 01:21:35,800
Speaker 1: whether it's through E t f s or or other

1475
01:21:35,960 --> 01:21:41,759
Speaker 1: avenues through which individuals can take almost an endowment approach

1476
01:21:42,080 --> 01:21:45,240
Speaker 1: to their own portfolios and further moving away from that

1477
01:21:45,360 --> 01:21:49,560
Speaker 1: traditional stocks, bonds, cash. But I also think we're in

1478
01:21:49,640 --> 01:21:54,479
Speaker 1: a period of likely greater volatility in those asset classes,

1479
01:21:54,600 --> 01:21:58,760
Speaker 1: so not necessarily a smooth ride for investors trying to

1480
01:21:59,040 --> 01:22:02,360
Speaker 1: navigate that, which means that I hope there's an additional

1481
01:22:02,479 --> 01:22:06,840
Speaker 1: place for education. And we're also at SCHWAB we are

1482
01:22:06,920 --> 01:22:10,120
Speaker 1: big proponents of investor education, and I would like to

1483
01:22:10,160 --> 01:22:12,200
Speaker 1: see more coming down the pike on that front. And

1484
01:22:12,280 --> 01:22:17,000
Speaker 1: I'm not just talking about seminars for investors of an

1485
01:22:17,040 --> 01:22:20,280
Speaker 1: older age. I actually wrote a letter to the principle

1486
01:22:20,560 --> 01:22:22,920
Speaker 1: of my kids high school, my my son's now out

1487
01:22:22,960 --> 01:22:25,960
Speaker 1: of high school, my daughters in high school, um, just

1488
01:22:26,960 --> 01:22:30,120
Speaker 1: asking whether they had ever considered having some sort of course,

1489
01:22:30,880 --> 01:22:33,479
Speaker 1: not in the stock market, but something that I would

1490
01:22:33,520 --> 01:22:37,760
Speaker 1: call life economics. How absurd is it that at that level,

1491
01:22:37,880 --> 01:22:40,439
Speaker 1: or even before we don't teach the basics of how

1492
01:22:40,479 --> 01:22:43,519
Speaker 1: a credit card works, and how compound interest works, and

1493
01:22:43,560 --> 01:22:46,639
Speaker 1: how to balance a checkbook and how taxes are taken

1494
01:22:46,640 --> 01:22:49,479
Speaker 1: out of our paycheck. I'm all for the arts, and

1495
01:22:49,640 --> 01:22:51,639
Speaker 1: I love when my daughter has to do a map

1496
01:22:51,760 --> 01:22:54,280
Speaker 1: of what ancient Greece look like, But I think shouldn't

1497
01:22:54,320 --> 01:22:58,000
Speaker 1: that also be in conjunction with the way money works

1498
01:22:58,400 --> 01:23:00,600
Speaker 1: in our economy? You know, we what a four oh

1499
01:23:00,680 --> 01:23:03,280
Speaker 1: one k is, what an I ra is, all these

1500
01:23:03,439 --> 01:23:06,560
Speaker 1: basic things that that we sort of get thrown to

1501
01:23:06,640 --> 01:23:10,680
Speaker 1: the wolves. So I would like to see we're we're

1502
01:23:10,800 --> 01:23:13,080
Speaker 1: as a firm sort of on a mission because it's

1503
01:23:13,120 --> 01:23:14,640
Speaker 1: it's a it's a big part of what we do

1504
01:23:14,760 --> 01:23:17,040
Speaker 1: it at shua But I'd like to see that become

1505
01:23:17,120 --> 01:23:20,599
Speaker 1: more pervasive, so that we start the education about money

1506
01:23:21,080 --> 01:23:22,720
Speaker 1: at a much younger age than we do now. So

1507
01:23:22,840 --> 01:23:26,280
Speaker 1: that's my longer term hope. That's that's really fascinating. That's um.

1508
01:23:26,840 --> 01:23:29,680
Speaker 1: You know, we talked about the lack of civics. You know,

1509
01:23:29,720 --> 01:23:31,840
Speaker 1: it used to be something on a civic Here's how

1510
01:23:31,880 --> 01:23:33,880
Speaker 1: you learn how to be a citizen and in a

1511
01:23:34,040 --> 01:23:36,519
Speaker 1: complex modern world, here's how you learn how to handle

1512
01:23:36,600 --> 01:23:40,240
Speaker 1: your own money. That would be a fantastic Uh, it

1513
01:23:40,240 --> 01:23:42,360
Speaker 1: should be. It should be a required course at least

1514
01:23:42,439 --> 01:23:44,160
Speaker 1: in high school. So we're gonna have to nominate you

1515
01:23:44,280 --> 01:23:47,720
Speaker 1: for the Board of Education. No politics. And so the

1516
01:23:47,920 --> 01:23:51,800
Speaker 1: last question I I always ask people and I get

1517
01:23:51,800 --> 01:23:56,360
Speaker 1: a variety of really interesting responses, but let's see yours is, so,

1518
01:23:56,600 --> 01:24:00,960
Speaker 1: what do you know today about investing, markets, finance that

1519
01:24:01,120 --> 01:24:04,920
Speaker 1: you wish you knew when you started your career. I

1520
01:24:05,000 --> 01:24:07,560
Speaker 1: think I wish I truly knew, even though when I

1521
01:24:07,680 --> 01:24:10,960
Speaker 1: started my career was working for somebody that spent a

1522
01:24:11,000 --> 01:24:13,839
Speaker 1: lot of time focusing on the behavioral side of markets

1523
01:24:13,920 --> 01:24:17,759
Speaker 1: and crowd psychology and the sentiment around peaks and valleys

1524
01:24:17,760 --> 01:24:21,720
Speaker 1: in the market. It's not until now that I realized

1525
01:24:21,760 --> 01:24:24,400
Speaker 1: that that really matters more than anything else. And if

1526
01:24:24,439 --> 01:24:27,960
Speaker 1: you can figure that out, you can maybe not nail

1527
01:24:28,040 --> 01:24:31,519
Speaker 1: perfectly tops and bottoms, but that I think is generally

1528
01:24:31,600 --> 01:24:33,240
Speaker 1: what keeps you on the right side of things, and

1529
01:24:33,360 --> 01:24:36,280
Speaker 1: which often means as as someone who's doing the investing,

1530
01:24:36,520 --> 01:24:38,679
Speaker 1: you know we we we observe the world of investing,

1531
01:24:38,720 --> 01:24:42,040
Speaker 1: but we're also investors. Um some of the best decisions

1532
01:24:42,080 --> 01:24:45,519
Speaker 1: are often some of the most uncomfortable ones. So I

1533
01:24:45,800 --> 01:24:47,639
Speaker 1: I wish I would have understood. I think I probably

1534
01:24:47,640 --> 01:24:50,760
Speaker 1: would have been made better calls and decisions around the

1535
01:24:50,800 --> 01:24:54,040
Speaker 1: peak in two thousand than I did. UM, but it

1536
01:24:54,120 --> 01:24:56,960
Speaker 1: certainly helped me and some of the more recent inflection

1537
01:24:57,000 --> 01:24:59,640
Speaker 1: points in the market. Liz, thank you so much for

1538
01:24:59,720 --> 01:25:02,280
Speaker 1: being so generous with your time this. This has really

1539
01:25:02,360 --> 01:25:05,000
Speaker 1: been great for those of you who are joining us late.

1540
01:25:05,200 --> 01:25:09,040
Speaker 1: I don't know how that's possible. UM at Liz Anne

1541
01:25:09,080 --> 01:25:14,440
Speaker 1: Saunders or schwab dot com for all of the various commentary,

1542
01:25:14,600 --> 01:25:18,600
Speaker 1: research analysis she puts out. If you enjoy this conversation,

1543
01:25:18,880 --> 01:25:21,840
Speaker 1: you're probably looking at it on iTunes, so look up

1544
01:25:21,880 --> 01:25:23,840
Speaker 1: an inch or down an inch and you'll see the

1545
01:25:24,000 --> 01:25:27,719
Speaker 1: rest of the series. This may actually be the fort

1546
01:25:28,720 --> 01:25:32,000
Speaker 1: show we've done. We started almost a year ago, and UM,

1547
01:25:32,439 --> 01:25:37,080
Speaker 1: you may be looking them with forty. That's right you

1548
01:25:37,160 --> 01:25:39,800
Speaker 1: when you said twenty nine, I'm like, you're twenty nine

1549
01:25:41,080 --> 01:25:44,040
Speaker 1: a year or too older than twenty nine. You look

1550
01:25:44,120 --> 01:25:47,559
Speaker 1: fantastic for whatever age you were at. So that's UM.

1551
01:25:48,000 --> 01:25:50,519
Speaker 1: I'm gonna stop there before I take a hole. Um,

1552
01:25:50,600 --> 01:25:53,280
Speaker 1: you've been listening to Masters in Business on Bloomberg Radio.

1553
01:25:53,280 --> 01:25:56,800
Speaker 1: I want to thank Charles Moulmer, my engineer, Michael bat Nick,

1554
01:25:56,960 --> 01:26:00,800
Speaker 1: my head of research. I'm Barry rit Halts. You're listening

1555
01:26:00,840 --> 01:26:02,800
Speaker 1: to Masters and Business on Bloomberg Radio.