Speaker 1: This is Masters in Business with Barry Ridholds on Bloomberg Radio.
Speaker 1: So I'm I'm really excited about this week's guest. Jason's Wige.
Speaker 1: He is a reporter, columnist, author. UM. You probably know
Speaker 1: his work as the Weekend Investor column in the Wall
Speaker 1: Street Journal. I'm a big fan of some of his books,
Speaker 1: including Your Money and Your Brain, which is one of
Speaker 1: the earliest looks at neuroeconomics and neurofinance. He has a
Speaker 1: book coming up, uh it's an updated version of inspired
Speaker 1: by Ambrose Bierce's Devil's Dictionary. It's called The Devil's Financial Dictionary.
Speaker 1: And we we talked about that. We talk a little
Speaker 1: bit about journalism and what it's gonna be like going forward,
Speaker 1: or the impact of social media, Twitter, etcetera. I've read
Speaker 1: him for so many years and know his work for
Speaker 1: for just so long. It was really interesting sitting down
Speaker 1: and talking with him about his assess and who his
Speaker 1: mentors and influences were, and what sort of advice he
Speaker 1: would give to somebody in the in the finance world.
Speaker 1: And I just found it to be really quite fascinating.
Speaker 1: We probably went about ninety minutes, so given how long
Speaker 1: that is. UM rather than me, Babil, Let me just
Speaker 1: say here is my conversation with Jason's Why this is
Speaker 1: Masters in Business with Barry Ridholds on Bloomberg Radio This
Speaker 1: week on Masters in Business, our special guest is journalist
Speaker 1: and author Jason's Wage. He is a columnist for The
Speaker 1: Wall Street Journal. He is also the author of the
Speaker 1: upcoming The Devil's Financial Dictionary, loosely based on Ambrose Bierce's
Speaker 1: famous Devil's Dictionary. I actually have read several of his
Speaker 1: previous books and really enjoyed him, one of which Your
Speaker 1: Money and Your Brain Might have been one of the
Speaker 1: first books that looked at behavioral economics from the investor's perspective.
Speaker 1: He also helped Danny Kahneman edit Thinking Fast and Slow,
Speaker 1: as well as being the editor of the revised edition
Speaker 1: of Benjamin Graham's classic The Intelligent Investor. Jason's Wide Welcome
Speaker 1: to Bloomberg. Great to be here. Mary. So you have
Speaker 1: a long and storied history and financial journalism, and we'll
Speaker 1: we'll get into some of the more granular stuff, but
Speaker 1: let's let's just go a little bit over your background. UM,
Speaker 1: I would be remiss if I didn't mention in two
Speaker 1: thousand and thirteen you won the Lobe Award for Personal
Speaker 1: Finance Writing. You've also been a writer for Money magazine, Time, CNN,
Speaker 1: you covered mutual funds for Forbes, and today you're the
Speaker 1: personal finance writer at The Journal. How did you find
Speaker 1: your way into financial journalism? Well, I think, like a
Speaker 1: lot of your guests, Barry, I'm gonna talk about luck.
Speaker 1: I think I'm anybody who has done read intably well
Speaker 1: in just about any field who doesn't credit luck first
Speaker 1: and foremost is kidding himself? Or isn't that fascinating? When
Speaker 1: when I finally sit down and put together the Book
Speaker 1: of Masters in Business, how many guests, and not just
Speaker 1: guests who had like one lucky break, but guys who
Speaker 1: were billionaires like Howard Marks and Leon Cooperman. He'd say, well,
Speaker 1: you know, you got really lucky. That's an amazing statement,
Speaker 1: isn't it. It's and I think it's totally true. And
Speaker 1: we all like to pride ourselves on our abilities and
Speaker 1: our skills, but without luck, I'm not sure any of
Speaker 1: us would be where we are today. I mean, I
Speaker 1: always wanted to be a writer. I was always fascinated
Speaker 1: by business. I have no formal training in business or economics.
Speaker 1: You went to Columbia, but you didn't go to Columbia
Speaker 1: Business school. You went to Columbia College, And would you
Speaker 1: study undergraduate art history? And so of course that makes
Speaker 1: perfect sense. You go from that to prest fun right,
Speaker 1: and and I think it's probably worth pointing out that, uh,
Speaker 1: one of your former guests, Charlie Ellis, also also spent
Speaker 1: some time studying art history. What a delightful gentleman. He's great,
Speaker 1: one of the best. So so you you The real
Speaker 1: question I always wanted to ask you, and I'll do
Speaker 1: it now, is how did you manage to avoid a
Speaker 1: career and asset management. Uh? Well, I think I I
Speaker 1: learned early enough in my career as a financial journalist
Speaker 1: that uh, luck is supremely important in investment management, and
Speaker 1: very early on I had a hard time distinguishing luck
Speaker 1: from skill. And I still do. You need a long
Speaker 1: period and lots of data and the right decision making
Speaker 1: environment to stand a chance of telling whether something is
Speaker 1: luck or skill. But that's just a long way of
Speaker 1: saying that I didn't want to go into investment management
Speaker 1: because I felt I I sort of knew where the
Speaker 1: fundamental body was buried. And the body that was buried
Speaker 1: was that a lot of people who think they're skillful
Speaker 1: are just lucky. And I didn't really want to go
Speaker 1: through my professional career with that on my conscience. I
Speaker 1: guess I have other things on my conscience than that.
Speaker 1: The flip side of that is a lot of people
Speaker 1: who think they're unlucky merely or unskillful. Correct. So you
Speaker 1: mentioned you always were fascinated by business. We always interested
Speaker 1: in stocks and investing or was that something you came
Speaker 1: to later. Yeah, I bought my first stock when I
Speaker 1: was sixteen, Barry, it was, and it was a fascinating experience,
Speaker 1: especially in hindsight. I bought a stock based on an
Speaker 1: absolutely god awful book that when I was sixteen thought
Speaker 1: was pretty persuasive. It was called How I Made two
Speaker 1: Million Dollars in the Stock Market by Nicholas Darvis. I
Speaker 1: read that a long time. Yeah, and you remember that
Speaker 1: thing he talks about where you know, increasing volume on
Speaker 1: rising price proceeds price exactly and you wait for the
Speaker 1: price to confirm the volume, and then you then you buy.
Speaker 1: So you're a closet technician, Well I was, at least
Speaker 1: I was. This is actually an interesting story because I
Speaker 1: I did exactly what he suggested. I took graph paper
Speaker 1: and I tracked ten stocks and um I had a
Speaker 1: copy of the SNP Stock Guide. This was five or six.
Speaker 1: It's not a great time to be an equity investor
Speaker 1: in the first place. And I found a stock that
Speaker 1: was called and I'm saying called mac a F. I
Speaker 1: didn't know what it was. The SNP Stock Guide said
Speaker 1: that it uh it produced liquorice and I think ball
Speaker 1: bearings or something like that, and uh so and it
Speaker 1: it turned out to be a perfect Darvis stock. And
Speaker 1: I bought a hundred shares at nine and five eighths
Speaker 1: with my you know, summer earnings, and it went up
Speaker 1: to twelve and seven eighths in a matter of days.
Speaker 1: And I didn't know a thing about the company other
Speaker 1: than this ridiculous theory that appeared to be confirmed. It
Speaker 1: turned out later to be mc andrews and Forbes Ron
Speaker 1: Perlman's original takeover vehicle. And I think this was around
Speaker 1: the time that he was first amassing shares. So I
Speaker 1: bought it for the wrong reason. I made money in
Speaker 1: it for the wrong reason, and I got stopped out
Speaker 1: at twelve and seven eighths, but this was so I
Speaker 1: didn't know I had been stopped out until the trade
Speaker 1: confirm arrived in the mail about a week later, and
Speaker 1: I went bonkers and I was like, I'm writing this
Speaker 1: thing all the way to twenty and I called my
Speaker 1: parents broker and I said, get me back in and
Speaker 1: then he flat out refused, and my dad had to
Speaker 1: buy it for me and went to fourteen and a
Speaker 1: quarter or something, and my dad browbeat me into selling it.
Speaker 1: And then where did it ultimately go? I it did
Speaker 1: very well in the long run. I don't think it
Speaker 1: did too well. Right after that, you're listening to Masters
Speaker 1: in Business on Bloomberg Radio. My guest this week is
Speaker 1: Jason's Wide, author of the upcoming The Devil's Financial Dictionary.
Speaker 1: Before we get into the book, I want to talk
Speaker 1: a little bit about social media. I see you tweeting
Speaker 1: pretty regularly. One of the questions I had for you
Speaker 1: as a professional journalist, what's the impact of Twitter, and
Speaker 1: to a lesser degree, blobs on the changing nature of
Speaker 1: financial journalism. Well, I think it's I think it's really big, Barry,
Speaker 1: and it's it's good and bad, And maybe let me
Speaker 1: talk about the bad first. You know, uh, up until
Speaker 1: a few years ago, certainly until ten years ago, probably five,
Speaker 1: um reading and investing public could rely on major media
Speaker 1: outlets to be their filters of information. If you saw
Speaker 1: something in the Wall Street Journal or the New York Times,
Speaker 1: for that matter, you could be fairly sure it was reliable, vetted,
Speaker 1: somebody had looked into what it wasn't just a random
Speaker 1: It's just not somebody spouting or repeating information generated by
Speaker 1: people with an axe to grind without checking at first.
Speaker 1: And I think the danger that we're in in a
Speaker 1: world dominated by social media and kind of insta pundits
Speaker 1: through the blog of sphere that's literally a blog inst
Speaker 1: the plan yeah I know, um, but I wasn't referring
Speaker 1: to them in particular, is that it's it's much harder
Speaker 1: today to make qualitative judgments as a consumer of news
Speaker 1: about what's reliable and what's not, because you're just drinking
Speaker 1: from a fire hose all day long. And I think
Speaker 1: the value of Twitter is that by giving you those
Speaker 1: mic o bursts of information and opinion from people, you
Speaker 1: get to see that, you get to see what they
Speaker 1: think in short spurts, and you can fairly quickly form
Speaker 1: a judgment about how objective they are, how reliable their
Speaker 1: information is, and I think ultimately it's going to help
Speaker 1: people separate the good from the bad. You know, one
Speaker 1: of my favorite aspects about Twitter is just how easy
Speaker 1: it is to derive a conclusion from somebody's Twitter numbers.
Speaker 1: So if someone's got eighty thousand tweets and a hundred
Speaker 1: and forty seven followers, that's a pretty fair assessment that
Speaker 1: this person is not pranking out quality tweets. On the
Speaker 1: other hands, when and Warren Buffett is probably the extreme
Speaker 1: opposite of that, He's got four tweets and six million followers.
Speaker 1: But between those extremes there's a spectrum. And you know,
Speaker 1: I have under a hundred thousand followers, My partner has
Speaker 1: over a hundred thousand followers, and we have a lot
Speaker 1: less tweets than we have followers. So somebody who's looking
Speaker 1: at that can say, oh, there has to be something
Speaker 1: worthwhile and substance if here not that followers or everything. Otherwise,
Speaker 1: if that was the case, Justin Bieber would be philosopher king.
Speaker 1: And we know that's not the case, but that's a
Speaker 1: real good shorthand to say, hey, is this person putting
Speaker 1: out anything of quality? Is there some way to double check, validate,
Speaker 1: see if the crowd has any wisdom and they've endorsed
Speaker 1: this person. Isn't it remarkable? Barry? How how hard that
Speaker 1: simple algorithm you've just expressed is for so many people
Speaker 1: to understand? I mean every day on Twitter you see
Speaker 1: recommended lists of people who tweet, and then you look
Speaker 1: at them and you see, oh, here's somebody they're recommending
Speaker 1: because he has fifty thou followers without even noting that
Speaker 1: he follows eighty thousand people and he's tweeted forty thousand times.
Speaker 1: So you know, a lot of people are still using
Speaker 1: followers alone. No, it can't be as the metric. You
Speaker 1: have to it has to be a combination of quantitative
Speaker 1: and qualities. You have to say, has the crowd vallet
Speaker 1: you know, it's sort of like when when you go
Speaker 1: to Metacritic, you basically say what were the reviews? Like
Speaker 1: what did the audience say? When when you get a
Speaker 1: movie like Jurassic Park or Mission Impossible and both the
Speaker 1: reviewers like it and the crowd likes it. So that's
Speaker 1: how I use the Twitter numbers, and we've now lost
Speaker 1: half our audience let's let's let's turn to The Devil's
Speaker 1: Financial Dictionary, which comes out in October. I've got a
Speaker 1: preliminary copy of of the book, and that's one of
Speaker 1: the reasons why I wanted to sit down and chat
Speaker 1: with you. I found it. Let me let me rather
Speaker 1: than me telling you what I think, let me go
Speaker 1: some of the early reviews. Bob Schiller, Nobel winner and
Speaker 1: Professor of Finance at Yale University. The most amusing presentation
Speaker 1: of principle is the finance I've ever seen. John Bogel,
Speaker 1: founder of the Vanguard Group. Laugh, cry, and learn as
Speaker 1: you enjoy the sparkling Devil's Financial Dictionary. The List of
Speaker 1: people who have given you blurbs Burton Malkiel, author author
Speaker 1: of Random Walked Down Wall Street, delightfully humorous and stunningly irreverent.
Speaker 1: James Grant opened this wonderful book to any page, try
Speaker 1: not to laugh, I dare you. And then Bill Sharp
Speaker 1: essentially created the Sharp ratio and another Nobel laureate at
Speaker 1: Stanford The run of People You got to um. I
Speaker 1: was like disappointed, No Buffett, and then I scrolled down
Speaker 1: and there's Warren Buffett's blured it. It's Um, it's an
Speaker 1: amazing run of people. Tell us a little bit about
Speaker 1: the motivation and thought process behind the book. Well, I've
Speaker 1: always loved Ambrose Beers's Devil's Dictionary. You know. Beers is
Speaker 1: maybe the most unjustly elected author of the nineteenth century
Speaker 1: in America. He was a contemporary of Mark Twain's. He
Speaker 1: was at least as brilliant. He wrote some of the
Speaker 1: most devastating epigrams ever written. And um, he was brutally
Speaker 1: cynical about American society and institutions, and he took on
Speaker 1: a few He he basically compiled The Devil's Dictionary as
Speaker 1: a collection of satirical definitions of terms most people think
Speaker 1: of in a very conventional way. And he just blew
Speaker 1: up every sort of bit of conventional wisdom and turned
Speaker 1: them all on their head. And it just occurred to
Speaker 1: me about two years ago that this project that I
Speaker 1: had had in mind for about fifteen years would be
Speaker 1: easier to do than I realized. And I just started
Speaker 1: doing it in my spare time. And my wife heard
Speaker 1: me cackling in the kitchen at night, and I really,
Speaker 1: if I was bothering her, I must be having fun.
Speaker 1: And I just kept at it. And you know, my
Speaker 1: goal was to try to do something like what Beers
Speaker 1: did and bring it to the world of Wall Street.
Speaker 1: And you know a couple of definitions from the original
Speaker 1: Devil's Dictionary or worth keeping in mind. I mean these
Speaker 1: are bear in mind. I'm going to read these. And
Speaker 1: first comes the word, then comes to the part of speech,
Speaker 1: then comes to the definition. So this is ambrose beers
Speaker 1: ambidextrous adjective able to pick with equal skill a right
Speaker 1: hand pocket or a left I gotta like that. In
Speaker 1: the in the last thirty seconds we have of this segment, Um,
Speaker 1: what are some of your favorite ones from the new
Speaker 1: Financial Devil's Dictionary. I'll give you one of my favorite
Speaker 1: day trader see idiot. Yeah, that's to get some hate
Speaker 1: mail on that one. That might be my favorite too.
Speaker 1: And maybe we can, maybe we can get into some
Speaker 1: of the longer ones. A bit later, you're listening a
Speaker 1: Master's in Business on Bloomberg Radio. I'm speaking with jason's Wage,
Speaker 1: personal finance writer and author of numerous books, his most
Speaker 1: recent being The Devil's Financial Dictionary. Tell me, uh, some
Speaker 1: of your favorite selections from this volume? Well, Barry, maybe
Speaker 1: I can, maybe I can read one quickly, and you know,
Speaker 1: I'll read the definition, the part of speech, and then
Speaker 1: I have to warrnt everybody. There are what I call
Speaker 1: flights of fancy in these, okay, which are these little
Speaker 1: um imaginary passages featuring people who bear no resemblance to
Speaker 1: anyone you and I might? Alright, So option nown the
Speaker 1: right to buy or sell a financial asset at a
Speaker 1: fixed price on or before a specific time from the
Speaker 1: Latin opt o. I choose a boon for stockholders whose
Speaker 1: clients don't understand how options work and generate a fortune
Speaker 1: in commissions as they attempt to learn. And here comes
Speaker 1: the flight of fancy stockholders of stockbrokers. Stockbrokers, explained you,
Speaker 1: asking me, a client of the broker age firm born
Speaker 1: rich and how I put two children through Harvard by
Speaker 1: trading options. Unfortunately they were my broker's children. That's great,
Speaker 1: so um obviously ambrosepers huge, huge influence. You mentioned you
Speaker 1: were working on this at night. How long did it
Speaker 1: take you to assemble this is a pretty thorough financial distinary.
Speaker 1: How how long did this stake? It didn't take very long, actually, U.
Speaker 1: You know a lot of these I'd had in my
Speaker 1: head for a long time, so it's just a matter
Speaker 1: of getting it out and on some page. Yeah. The
Speaker 1: real what I'm trying to do with this book is
Speaker 1: in each case when I define a term, I'm saying
Speaker 1: to myself, you know, after more than a quarter century
Speaker 1: of you know, researching and reporting on the financial markets,
Speaker 1: can I take everything I've learned and boil it down
Speaker 1: into a hundred fifty words or less? And then if
Speaker 1: I can do that, how about fifty words? And in
Speaker 1: some cases I got them down to a single word?
Speaker 1: Give me us an example other than the day trader. Um. Uh, well,
Speaker 1: there's one which is human adjective biased. We're gonna talk
Speaker 1: a little more about the biases and cognitive issues of
Speaker 1: humans coming up in a bit. Uh. Who is the
Speaker 1: ideal audience for this? Is this scared for the professional?
Speaker 1: Is this for a mom and pop investor? Who are
Speaker 1: you thinking about when you were writing this? Well? Really everybody.
Speaker 1: There's a lot of inside jokes in this book that
Speaker 1: I think only a professional audience will get and will
Speaker 1: certainly be annoyed by and I hope amused by. I
Speaker 1: think one of the wonderful things about the Wall Street
Speaker 1: community is that people do have an ability to laugh
Speaker 1: at themselves. UM, at least the better people in the
Speaker 1: in the field do. And there's a lot to laugh about,
Speaker 1: so to say the least, I'm curious as to how
Speaker 1: the research for this win. I know you said this
Speaker 1: has been kicking around your head for fifteen years, but yeah,
Speaker 1: I just picture you doing a pretty deep dive, if
Speaker 1: not wearing the white gloves and the stacks of Yale,
Speaker 1: certainly working your way through UM either Lexus or Google
Speaker 1: to try and find some so early ideology of some
Speaker 1: of these words. Yeah, a lot in a lot of cases,
Speaker 1: because it is a true dictionary. So I was trying
Speaker 1: to get at where a lot of these terms derived from.
Speaker 1: And in many cases, people who use these terms all
Speaker 1: day long don't really know what they mean, so they're
Speaker 1: just using them as jargon, not as as true exactly.
Speaker 1: And and so yes, there's I did a lot of
Speaker 1: historical and archival research trying to figure out when a
Speaker 1: certain term was first used, where came from. I spent
Speaker 1: a lot of time with the Oxford English Dictionary and
Speaker 1: UM all kinds of historical research as well. And you
Speaker 1: have quite the background as an editor. One of the
Speaker 1: questions I had to ask, So, the very famous classic
Speaker 1: book by Benjamin Graham, The Intelligent Investor, you actually were
Speaker 1: the editor of the revised edition. How on earth did
Speaker 1: that invitation come along? Well, I don't think it hurt
Speaker 1: that I was a Graham afficionado. I mean I I
Speaker 1: first read The Intelligent Investor in March when I started
Speaker 1: as a financial journalist at Forbes Magazine, and I probably
Speaker 1: read it cover to cover at least six times. I'd
Speaker 1: read almost all of Graham's shorter writings as well, and
Speaker 1: all the biographies of him that existed at the time.
Speaker 1: But ultimately it was it was uck like everything else
Speaker 1: we've been talking about. Um. A friend of mine had
Speaker 1: written a book for Harbercollins. Uh, one of the top
Speaker 1: editors at the publishing house, was out to lunch with
Speaker 1: her and said, uh, you know, we have this book.
Speaker 1: Who do you think should do it? And she said, oh, well,
Speaker 1: there was only one person who should do it, and
Speaker 1: she told him to ask me. And why did she
Speaker 1: do that? Because we had both been at a party
Speaker 1: about a month beforehand. We hadn't seen each other in years.
Speaker 1: I had seen her across the room and I said, oh,
Speaker 1: I haven't seen her in years, and so I made
Speaker 1: a special point going to say hi. And if I
Speaker 1: hadn't said hi to her, she would have recommended somebody else.
Speaker 1: You're listening to Master's in Business on Bloomberg Radio. We're
Speaker 1: speaking with Jason's Wide, personal finance writer and author. Um.
Speaker 1: One of the things I wanted to really go over
Speaker 1: with you, uh, is your perspective as a personal finance columnist.
Speaker 1: And I'm going to start by quoting you and then
Speaker 1: and then we'll discuss it. You once wrote, my job
Speaker 1: is to write the exact same thing between fifty and
Speaker 1: one hundred times a year in such a way that
Speaker 1: neither my editors nor my readers will ever think I'm
Speaker 1: repeating myself. Explain. Um, Yeah, there's a simple reason for that, Barry.
Speaker 1: I'm and I think you and I think alike on this.
Speaker 1: There's there's really only a handful of things you can
Speaker 1: tell investors about their portfolios that are true before you
Speaker 1: get into things that are bad for them. And you know,
Speaker 1: we could disagree about the number. There might be six
Speaker 1: things they are good for people, there might be thirty,
Speaker 1: but there aren't a hundred. And I'm and there's at
Speaker 1: most a couple dozen. So We're not going to see
Speaker 1: a daily television show for you where an hour day
Speaker 1: you wax eloquence on the issues of the moment. Well,
Speaker 1: probably not, because you know, as I, as I also
Speaker 1: mentioned in the same piece you're quoting from, you know,
Speaker 1: five per cent of the time, the right thing for
Speaker 1: people to do is nothing. And uh, there's a financial
Speaker 1: media that exists all day long, NonStop, having to provide
Speaker 1: people with what appears to be information, well certainly content content.
Speaker 1: And if you you can't do that, if you believe
Speaker 1: that the right thing to tell people to do is nothing,
Speaker 1: So that Jason's wide TV show would be have a
Speaker 1: broadly diversified asset allocation model, rebalance regularly, watch your fees,
Speaker 1: see you tomorrow. Yeah, diversify, buy and hold, minimize your
Speaker 1: costs and your taxes. And I keep your hands in
Speaker 1: your pockets, don't. Don't just do something? Sit there right
Speaker 1: and keep other people's hands out of your pockets. That
Speaker 1: makes sense. So let me let me re ask that
Speaker 1: that question in a slightly different way, along the same
Speaker 1: spirit of that that question, what does good financial advice
Speaker 1: look like? Good financial advice on keeps people from being
Speaker 1: their own worst enemies? You know. Benjamin Graham famously wrote
Speaker 1: about that in the introduction to the Intelligent Investor, and
Speaker 1: I think it all really boils down to one very
Speaker 1: very simple thing, which is that markets regrets to the mean,
Speaker 1: and the way you in the short run, the way
Speaker 1: you attract attention to yourself if you're providing financial advice,
Speaker 1: is by encouraging people to bet against regression to the mean.
Speaker 1: So if an asset is rapidly going up in price,
Speaker 1: you tell people buy more while you still can, and
Speaker 1: if it's going down, you tell him to sell before
Speaker 1: it's too late. But if you're trying to help people
Speaker 1: get on the right side of regression to the mean,
Speaker 1: then you give them countercyclical advice. When an asset is
Speaker 1: going up and Brice, you tell them be cautious, and
Speaker 1: when it's going down, you tell them to become more aggressive.
Speaker 1: Quite interesting, So let me ask you the flip side
Speaker 1: of that. Uh, why is it that so much bad
Speaker 1: advice seems to hang around and not die? Why why?
Speaker 1: Or or as slightly differently, why is there so much
Speaker 1: zombie advice for investors? Well? I think it boils down
Speaker 1: to something very simple. Barry. I think you know, humans
Speaker 1: have a profound um, a profound desire to believe in magic.
Speaker 1: People want to be lied to? And was it you
Speaker 1: who recently wrote um the three ways to make money
Speaker 1: as a as a writer lie to. If you, if
Speaker 1: you tell people to truth, truth who don't want to
Speaker 1: hear it, you're not gonna make any money. If you
Speaker 1: tell people truth who want to hear the truth, they're
Speaker 1: they're gonna make some money. But if you a lot
Speaker 1: of the people who want to be lied to, you're
Speaker 1: gonna make the most amount of Yeah, if you, if
Speaker 1: you tell the truth to people who want to be
Speaker 1: lied to, you'll starve. That's unbelievable. It's true. And so
Speaker 1: what is it within our makeup that wants us to
Speaker 1: be told the soft, easy, comfortable thing and not Hey, here,
Speaker 1: here's you know, tough love, here's the cold, hard reality.
Speaker 1: The sooner you learn that, the better off you are. Well,
Speaker 1: people are people are machines, right, and their machines that
Speaker 1: are designed to optimize a few things. Pattern recognition, self
Speaker 1: enhancement m HM, and self delusion. I mean, human beings
Speaker 1: are really good at those three things. We're we almost
Speaker 1: certainly have evolved to maximize is those things and that's
Speaker 1: why people are so susceptible to bad advice, because bad
Speaker 1: advice praise on that stuff emotionally, praise to those emotional
Speaker 1: hot buttons. Exactly. Interesting. So let's let's talk about some
Speaker 1: more good advice. Who are the young writers that you
Speaker 1: were reading today that you find to be giving the
Speaker 1: sort of good advice or or good writing that is
Speaker 1: beneficial to investors? And yeah, I think I I think
Speaker 1: I I like some of the same people you do.
Speaker 1: Barry Well, it's not a coincidence. You being here is
Speaker 1: just my confirmation bias that works, Yes, exactly, and mine too. Um.
Speaker 1: You know the first person I would name would be Morgan.
Speaker 1: How is only the Moley fool? I think? Um? I
Speaker 1: think he does just incredibly sharp, really insightful stuff. Love
Speaker 1: his work. Ben Carlson a wealth of common sense, really
Speaker 1: that's his does great stuff. James Osborne at Basin Asset
Speaker 1: Management does also really cool stuff. There's a bunch of
Speaker 1: other people as well, I'm who are terrific. It's amazing
Speaker 1: how the meritocracy of financial writing, how these names have
Speaker 1: risen up to the top fairly quickly. Ben Carlson as
Speaker 1: an example, I mean he started blogging. I don't know,
Speaker 1: a year ago, maybe less really relative, maybe it's two
Speaker 1: years ago relatively short time, quickly found an institutional audience
Speaker 1: and puts out really really good stuff on a regular Yeah.
Speaker 1: And I think this is a very hopeful sign for
Speaker 1: the future. You know, there are a lot of people
Speaker 1: and Charlie Munger is one worrying what does he blog away?
Speaker 1: I know I recognized that he. Uh, he's very worried
Speaker 1: about the institutional impact of the decline of the traditional
Speaker 1: great newspaper. And we don't know yet what's going to
Speaker 1: replace it. But the fact that that really talented, bright
Speaker 1: young people have been able to sort of rise to
Speaker 1: the top, I think is is a hopeful sign for
Speaker 1: the future. I can't say I I disagree. Um, what
Speaker 1: are the writers do you read? Who else have you
Speaker 1: read over the years that really stood out as as
Speaker 1: a powerful and influential voice to you? Well, a lot
Speaker 1: of them are are now of another generation. Um, Charlie
Speaker 1: Ellis was a very big influence on me. I'm Ben Graham,
Speaker 1: of course. Uh. Probably the single biggest influences on the
Speaker 1: on the way I try to think, uh would be
Speaker 1: Richard Feineman, the physicist m yes um uh. Who's wonderful
Speaker 1: books these oral streets, And there's a series of them.
Speaker 1: There's four or five of them I think are among
Speaker 1: the most engaging books on how to think. I believe
Speaker 1: you could find anywhere. And of course Danny Kahneman the
Speaker 1: Thinking Fast Uh and Slow Ye was a huge influence
Speaker 1: on me as well, and I was very fortunate to
Speaker 1: be able to work with him and help him on
Speaker 1: the book that that was a fascinating book, which leads
Speaker 1: to a question. So you and I both found behavioral
Speaker 1: economics fairly early in our career. How did you stumble
Speaker 1: into that space? Uh? Well, I realized around that I
Speaker 1: was running out of interesting questions. I didn't think. I
Speaker 1: I didn't think by any means I had all the answers.
Speaker 1: But as someone who didn't have professional training in finance
Speaker 1: or economics, but who sort of sat at the feet
Speaker 1: of the smartest people, I could find a lot of
Speaker 1: the questions were starting to feel repetitive to me, my
Speaker 1: questions and other people's questions. And there was still this
Speaker 1: this fundamental mystery that nobody seemed to have an answer to,
Speaker 1: which is why do smart people do such stupid things?
Speaker 1: When it comes to money. It's amazing. History is replete
Speaker 1: with examples, whether it's Isaac Newton, Mark Twain, go down
Speaker 1: the list of various brilliant, insightful people who will manage
Speaker 1: to just blow up in the stock mark. Ye. And
Speaker 1: and that's really the central question that has obsessed me
Speaker 1: for the past twenty years is why do smart people
Speaker 1: become stupid when money comes into the room. Well, we've
Speaker 1: run out of time for this segment. If you enjoy
Speaker 1: this conversation, be sure and check out our podcast extras
Speaker 1: with a tape keeps rolling and we continue our conversation. Uh.
Speaker 1: If you want to catch more of Jason's wives work,
Speaker 1: you can follow him on Twitter. Your Twitter handle is
Speaker 1: Jason's wag w s J. I'm Barry RIH Halts. Be
Speaker 1: sure and check out my daily column on Bloomberg View
Speaker 1: dot com. Follow me on Twitter at rid Halts. You've
Speaker 1: been listening to Masters in Business on Bloomberg Radio. Welcome
Speaker 1: to the podcast Extras. My guest this week is Jason's
Speaker 1: Wage and there's so much stuff I want to ask
Speaker 1: you about. You know, it's funny those segments that are
Speaker 1: seven minutes, eight minutes, six minutes, eleven minutes, I lose
Speaker 1: a little bit of rhythm because I'm always aware of
Speaker 1: the time. And then we get to this segment and
Speaker 1: we could kind of take our shoes off and kick
Speaker 1: back and relax. So let me go over some of
Speaker 1: the questions that I skipped that I wanted to to
Speaker 1: ask you. And these are really print real questions printed out.
Speaker 1: You know you can you can get the home copies
Speaker 1: if you want. Um. We talked briefly about Twitter and
Speaker 1: blogs and social media. Um. What I wanted to ask
Speaker 1: was not so much about commentary in and now lissis,
Speaker 1: which is always its own separate page in a newspaper,
Speaker 1: but what about just straight up reporting. We keep seeing
Speaker 1: various media outlets just ending various local reporting, city hall
Speaker 1: that the other thing, what does this mean for the
Speaker 1: future of of actual not what you and I do,
Speaker 1: but actual reporting with people go out and try and
Speaker 1: find the facts in current events and tell the rest
Speaker 1: of the world about it. Yeah, I think that I
Speaker 1: think you know, all of this is like is sort
Speaker 1: of like a Newton's law of thermodynamics, right, Barry. I mean,
Speaker 1: for everything created, something is destroyed. And you know, the
Speaker 1: the Internet and the advent of social media have democratized
Speaker 1: the spread and for that matter, in the generation of
Speaker 1: news and information, so that anyone with a cell phone
Speaker 1: hand become a broadcaster or a reporter. The problem is
Speaker 1: that anybody who has done shoe leather investigative reporting in
Speaker 1: one of the great newsrooms of America like the Wall
Speaker 1: Street Journal or or the New York Times or the
Speaker 1: Washington Post or the l A Times, any of the
Speaker 1: great or or once great newspapers in this country or
Speaker 1: magazines for that manner, can tell you that reporting is
Speaker 1: brutally hard work to get it right. It's really hard
Speaker 1: work to do. It's really hard work to prevent yourself
Speaker 1: from injecting your own viewpoint, bias, personality. It's and it's
Speaker 1: absolutely essential to a functioning democrat. It's I mean, it's not.
Speaker 1: The press is not called the fourth Estate for nothing.
Speaker 1: And Charlie Munger's fear, and this is the fear that
Speaker 1: I share, is that when reporting gets atomized the way
Speaker 1: we see it unfolding on the Internet and in social media,
Speaker 1: you don't have that institutional memory and historical tradition, and
Speaker 1: most importantly, that professional training in newsrooms the way you
Speaker 1: once did. You don't have reporters doing two three five
Speaker 1: years of understudy with unmasters, and and so the attention
Speaker 1: to fairness and detail and proper methodology falls by the wayside.
Speaker 1: And if you think about House of Cards, for example,
Speaker 1: the you know, the TV I'm going to call it
Speaker 1: a melodrama with that's very compelling, with Kevin Spacey and
Speaker 1: Robin Wright, House of Cards, House of Games, House of Cards, um,
Speaker 1: you know, in that show, over and over again, you
Speaker 1: see these journalists at a newspaper clearly modeled after the
Speaker 1: Washington Post doing things that are so unscrupulous that if
Speaker 1: you did them once at the Wall Street Journal, you
Speaker 1: would be summarily fired. And it's it now just goes
Speaker 1: without passing, without mention. I think the American public sort
Speaker 1: of takes it for granted that journalists are sloppy creeps who,
Speaker 1: you know, invade people's privacy and lie to their sources regularly,
Speaker 1: and in fact, believe it or not, journalists in a
Speaker 1: traditional newsroom environment are phenomenally ethical people who who would
Speaker 1: you could put most journalists thumb in a screw and
Speaker 1: tighten it before you would get them to tell a lie.
Speaker 1: That I don't disagree with that it's always the bed
Speaker 1: eggs that that spoil everybody's perception. But I want to
Speaker 1: mention something you just said earlier, that anybody with a
Speaker 1: cell phone can can broadcast and and literally, I'm gonna
Speaker 1: do this. I'm gonna do this right now. I'm gonna
Speaker 1: use periscope and broadcast a few seconds of our interview
Speaker 1: off of a phone. That this is fascinating technology that
Speaker 1: did not exist forget twenty five years ago, this didn't
Speaker 1: exist eight months ago. Exactly. It's amazing that the technology
Speaker 1: for this exists today. And so how do you compete
Speaker 1: with that? How do you build a television station and
Speaker 1: go through the training of reporters and journalists when everyone
Speaker 1: and anyone can be a citizen journalist. What happens to
Speaker 1: that business model that digital technology is challenging. It's amazing. Well,
Speaker 1: first of all, Barry, thank you for not pointing the
Speaker 1: camera at your feet. Um. And secondly, I said, can't
Speaker 1: off of shoes and get comfortable, and uh, literally, that's
Speaker 1: what we did. And secondly, I'm you know, look, you're
Speaker 1: raising an incredibly troubling question and we don't yet know
Speaker 1: the answer because we don't how this is going to
Speaker 1: play out. I think ultimately the better emerging news organizations.
Speaker 1: And you know, we could all think of you know,
Speaker 1: some of the candidates right like, you know, maybe Vice
Speaker 1: or some some outfit like that. Um, we'll get the
Speaker 1: capital and the experience and the professionalism that they need
Speaker 1: to build something that competes with the traditional newsroom like
Speaker 1: the Wall Street Journal or Bloomberg, and um, that could
Speaker 1: take a long time now, and ultimately those organizations are
Speaker 1: going to have to cannibalize the existing great news organizations
Speaker 1: to staff themselves up with people who have the experience
Speaker 1: and the ethical background to run uh, proper news organization.
Speaker 1: I'm running, I'm running out of battery here, so I'm
Speaker 1: gonna kill periscope and I think that that's done. But um,
Speaker 1: that was just thirty of that. UM, I think you're
Speaker 1: onto something with that, which which leads me to a
Speaker 1: question I wanted to get to earlier, um, and didn't.
Speaker 1: It's actually two related questions. The first is this comes
Speaker 1: right from you, from your money and your brain. People
Speaker 1: who received frequent news updates on their investments earn lower
Speaker 1: returns than those who get no news whatsoever. Discuss Yeah,
Speaker 1: this is based on a series of fascinating experiments done
Speaker 1: by a psychologist named Paul Andreas and in the nineteen
Speaker 1: eighties he was at Columbia for a while and Harvard,
Speaker 1: and he took UH. He took experimental subjects and divided
Speaker 1: them into two groups. Some got essentially no no updated
Speaker 1: information on their chosen investment portfolios, and others got frequent,
Speaker 1: in fact, almost constant news updates. And then he tracked
Speaker 1: their investment performance. And he found that the more often
Speaker 1: people got news, the more often they traded. And we
Speaker 1: know what the net outcome of that is for the
Speaker 1: average invest The more you trade, the less you learn.
Speaker 1: And it's a direct relationship. It's just if A then B.
Speaker 1: If you get more news information, more updates, you will
Speaker 1: act on it because it will feel informative to you,
Speaker 1: even if it's just even if the news is just noise,
Speaker 1: you will feel you have to act on it because
Speaker 1: it seems like news and it seems significant. I call
Speaker 1: a lot of what gets reported falls into the recency effects. Look,
Speaker 1: we get a non farm payroll every month. It doesn't
Speaker 1: mean that it changes the value of what your investment is.
Speaker 1: And half of the time when it's an aberration to
Speaker 1: the upisode of the downside, it's still within the statistical
Speaker 1: range of probabilities that reflect nothing other than oh, something
Speaker 1: is slightly often this reporting, and so it's a little
Speaker 1: more were a little less than people were expecting, and
Speaker 1: yet everybody reacts and overreacts to it. Yeah, I mean
Speaker 1: we're you know, everyone sort of comes with a default
Speaker 1: hair trigger mechanism. I mean, this example has been used
Speaker 1: so many times it's it's almost dull at this point.
Speaker 1: But you know, in evolutionary time, when our ancestors were
Speaker 1: evolving on the you know, the planes of the African savannah,
Speaker 1: you know, if you thought you might see a lion
Speaker 1: and you overreacted to what you thought was the lion,
Speaker 1: well you lived to you know, pass on, and if
Speaker 1: person was blase about that, not a whole lot of progeny. Right.
Speaker 1: The thing is, most of the time it wasn't a lion.
Speaker 1: Most of the time it was just the wind, you know,
Speaker 1: waving a patch of grass. But that one time it
Speaker 1: was a lion. If you overreacted, you survived and you
Speaker 1: passed your jeans on. And if you underreacted, you were
Speaker 1: lion food. That that makes perfect sense. So I've used
Speaker 1: the phrase behavioral economics repeatedly your behavioral finance. But the
Speaker 1: book Your Your Money, or Your Brain, which you talked
Speaker 1: about the New Science of Neuroeconomics, describe the difference between
Speaker 1: behavioral economics and neurofinance. How do you how do you
Speaker 1: define that? Yeah, it's really I think it's a I
Speaker 1: think it's a very simple distinction. In neuroeconomics or or
Speaker 1: neurofinance simply uses the tools and techniques of neuroscience. Two
Speaker 1: extend existing research and findings in psychology and economics, and
Speaker 1: by those tools and techniques, it's primarily methods of measuring
Speaker 1: brain activity m R. Yeah, like a functional MRI I,
Speaker 1: a pet scan, a cat scan, um. It could also
Speaker 1: be uh various um um uh tools for monitoring brain
Speaker 1: waves or electromagnetic activity in the brain. So so the
Speaker 1: way I like to define that behavioral economics is you
Speaker 1: can see the results of this issue in someone's actual behavior.
Speaker 1: They did this, they bought that, they sold that, whereas
Speaker 1: neuro you're actually looking inside their brain in some way
Speaker 1: and seeing what's going on organically as opposed to behaviorally. Yeah,
Speaker 1: And if you think about it, uh, there's there's not
Speaker 1: much difference between the two in a way behavioral economics
Speaker 1: is telling you what minds do, and neuroeconomics is telling
Speaker 1: you what brains do. It's we already a great distinction.
Speaker 1: We can already observe the behavior. Because somebody buys high
Speaker 1: and sells low. They made a decision in their mind
Speaker 1: to do this. We see, we see their action, we
Speaker 1: see what they did, so we know what happened. What
Speaker 1: neuroeconomics does is it says, these are the specific circuits
Speaker 1: in the brain that generated the behavior you've observed in
Speaker 1: in your psychological experiments. Let me shift gears on you,
Speaker 1: and and let's talk a little bit about the problem
Speaker 1: with predictions. What's the problem? So we all make forecasts. Everybody,
Speaker 1: everybody in will state has a Here's where the d
Speaker 1: will be in a year. Here's what I think these
Speaker 1: earnings are gonna be. What's the problem with predictions. Well,
Speaker 1: I think that there's a there's many problems with them, Barry.
Speaker 1: I think the first problem is that people are people
Speaker 1: are very poor at learning from their predictive errors, particularly
Speaker 1: when the consequences aren't high or the feedback is noisy.
Speaker 1: To define that, what do you mean by that? Well,
Speaker 1: think about it this way. I'm you know. Uh, think
Speaker 1: of the quarterfinal match in the US Open between the
Speaker 1: Williams sisters. You know, Venus and Serena are playing. Every
Speaker 1: stroke has three characteristics. The feedback their feedback of every stroke.
Speaker 1: So if Venus hits the ball, it's in or it's out,
Speaker 1: and she knows that immediately. So the feedback is prompt
Speaker 1: and it's unambiguous. Secondly, every stroke matters. It's consequential if
Speaker 1: if you miss too many shots, you lose, and you
Speaker 1: lose millions of dollars in front of millions of people.
Speaker 1: Other than that, though, really it's just a game. Other
Speaker 1: than that, it's just a game. So in in a
Speaker 1: sport like professional tennis, feedback is extremely reliable, in a
Speaker 1: very powerful way of learning from your mistakes. If you
Speaker 1: take it seriously and you practice, you will get good
Speaker 1: at it. You'll get a lot better. The financial markets
Speaker 1: are different. The feedback is not prompt out nor isn't unambiguous.
Speaker 1: I mean, let's say you and I decide today Netflix
Speaker 1: is going up, so we buy Netflix. Well, on the
Speaker 1: next tick, Netflix goes up, so we're right. But the
Speaker 1: next ticket goes down and now we're wrong, so we
Speaker 1: get up. We go to the bathroom. We come back,
Speaker 1: it's up. We're right. We go out for lunch, we
Speaker 1: come back, it's down. Now we're wrong. What is the
Speaker 1: feedback telling us? It's really noisy. The feedback is noise.
Speaker 1: Prices fluctuated, that's what it's telling you. So there is
Speaker 1: useful feedback in market prices, but it takes a long
Speaker 1: time to unfold, and you have to develop a real
Speaker 1: skill in interpreting the feedback, and a lot of people
Speaker 1: can't do that. And the task at the same time
Speaker 1: manage the money or uh, you know, pick the particular
Speaker 1: securities and the consequences. The consequences for a lot of
Speaker 1: people are enormous. It depends how much skin you have
Speaker 1: in the game, right, how much of your reputation, your
Speaker 1: personal reputation is riding on the line. If you're an employee,
Speaker 1: just a face in a crowd at a giant asset
Speaker 1: management firm, uh, consequences might not be all that great.
Speaker 1: The consequences for you aren't in being right or wrong.
Speaker 1: It's whether you're right or wrong relative to the crowd.
Speaker 1: And so you're not concerned with your absolute performance, whether
Speaker 1: what you did is right or wrong. You're concerned whether
Speaker 1: you're gonna stand out for doing something different that might
Speaker 1: make you or the firm look foolish. Career risk is
Speaker 1: that is that what you're It's career risk. And so
Speaker 1: if avoiding career risk steers you toward making timid or
Speaker 1: sub optimal decisions, you can't learn from normal feedback because
Speaker 1: the feedback you care about is am I increasing or
Speaker 1: decreasing my career risk as opposed to am I doing
Speaker 1: better or worse? As an investor invest investments. That's quite fascinating.
Speaker 1: So so when we look at predictions in general, you're
Speaker 1: looking at them with that three pronged analysis, similar to
Speaker 1: the way you would look at a sporting event, only
Speaker 1: the results, the timeline, and the all three things are
Speaker 1: totally different. Yeah, and you know there's I think the
Speaker 1: other thing that makes all of this baffling is we
Speaker 1: in in daily life, we have a general belief and
Speaker 1: it's been popularized as sort of the ten thousand hours rule,
Speaker 1: you know, outlawyer rule, Mountain Glass exactly if you if
Speaker 1: you just practice anything long enough and hard enough, you'll
Speaker 1: get good at it. If that was true, wouldn't all
Speaker 1: the best fund managers be the guys who've been around
Speaker 1: the longest. Yes. And also if that were true, everyone
Speaker 1: would be the Beatles. Everyone who's ever everyone who's ever
Speaker 1: spent a lot of time plucking on and get are
Speaker 1: would would be Eric Clapton. And it's not really true
Speaker 1: because the second essential criterion, the other thing you have
Speaker 1: to have, is good feedback. I mean, if you you
Speaker 1: could spend thirty hours playing guitar, but if you're tone
Speaker 1: deaf and you don't know you stink and nobody will
Speaker 1: tell you stink, you'll never get good. Well, you'll figure
Speaker 1: it out when they're not buying your albums or going
Speaker 1: to your concerts, or when they're paying or when they're
Speaker 1: paying you not to play. That's a whole different Uh,
Speaker 1: that's a whole different issue. Um. Another random question. Does
Speaker 1: money by happiness or is it the anticipation of money
Speaker 1: that leads to happiness? Well, yeah, I talked about this
Speaker 1: quite a bit in in my earlier book Your Money
Speaker 1: in Your Brain and anticipation based on the on the
Speaker 1: research that's been done, I think is more of what
Speaker 1: I would call a hot state than I'm actually receiving
Speaker 1: a gain. So thinking about or imagining or contemplating the money,
Speaker 1: you'll make if you turn out to be right, is
Speaker 1: probably more at least as rewarding as getting the money is.
Speaker 1: I've used that analysis as an explanation for sell the News,
Speaker 1: and you you kind of imply that in the book
Speaker 1: as well. Ye. So, so put it into context of investing.
Speaker 1: Why do stock prices run up to a quarterly earning
Speaker 1: then you get a good earnings number and the stock
Speaker 1: goes down? Yeah, there's there's There was a fascinating study
Speaker 1: published in Science magazine, which, as many of our listeners know,
Speaker 1: is the is the pre eminent journal of science in
Speaker 1: the US, and it it looked at monkey brains and
Speaker 1: they recorded from single neurons deep in the dopamine centers
Speaker 1: of the monkey's brains how they responded. And essentially, when
Speaker 1: the monkey receives an expected reward, the dopamine generation at
Speaker 1: the time the reward is received goes down, So the
Speaker 1: dopamine activity ramps up as the monkey recognizes the predictive queue.
Speaker 1: Here comes the banana. Here comes the banana. In this
Speaker 1: case it was it was sugar water, but same idea.
Speaker 1: Here comes here comes the banana. I'm going to get
Speaker 1: the banana. The bananas coming, and that's when the dopamine peaks,
Speaker 1: then the monkey actually gets the banana and he's like, oh,
Speaker 1: I got the banana. I've been wanting all along. And
Speaker 1: so that activity peaks and then it drops. And I
Speaker 1: think that's why so often in the stock market you
Speaker 1: see the price of you see the company's stock price
Speaker 1: just ramp up and and go parabolic when people are
Speaker 1: expecting a positive earning surprise, the company is going to
Speaker 1: exceed analysts expectations. Then the actual learnings come out and
Speaker 1: exactly what people thought they would be just as good,
Speaker 1: and it goes down. It's a disappointment. There's a Spock
Speaker 1: quote from Star Trek which I won't even attempt, but
Speaker 1: it's the same concept of wanting generating more satisfaction than
Speaker 1: actually having. And I find that that fascinating so related
Speaker 1: to some of um these cognitive issues. Um, what was
Speaker 1: it like working with Danny Kahneman on thinking fast and Slow? What?
Speaker 1: What were your contributions, uh to the book? He I'm
Speaker 1: trying to remember if he thanked you in his Nobel
Speaker 1: speech or not, but I didn't, But I I I
Speaker 1: read the book, or I read the first three quarters
Speaker 1: of the book on a beach some years ago and
Speaker 1: found it just absolutely fascinating stuff. Well, we're you know,
Speaker 1: working with Danny was one of the was one of
Speaker 1: the great experiences of of my life. Um, certainly one
Speaker 1: of the great learning experiences. UM. You know. He he's
Speaker 1: got a remarkable mind and um, he questions everything, and
Speaker 1: he has he has that wonderful ability that most of
Speaker 1: us losing our intellectual lifetime of putting ourselves almost into
Speaker 1: the shoes of a child and saying just asking why
Speaker 1: why is that? And he's often completely baffled by things
Speaker 1: that everyone takes for granted as an as an accepted truth,
Speaker 1: and he he just sort of scratches his head in
Speaker 1: front of it, says, well why do people think that?
Speaker 1: And it's not that he's doubting it, he just genuinely
Speaker 1: doesn't know. And part of that is because he has
Speaker 1: the most perfectly calibrated sense of what he knows. I
Speaker 1: think of anybody I've ever certainly anybody I've ever worked with,
Speaker 1: no Dunning Kruger effect. They're very, very very little. I
Speaker 1: only saw it once, which was the first day we
Speaker 1: worked physically together on the book in his apartment, when
Speaker 1: he talked about the planning fallacy which I know you're
Speaker 1: familiar with, Barry, but I'll explain it for for our listeners. Uh.
Speaker 1: He likes to tell a famous a story that's become
Speaker 1: famous about one of the first major projects that he
Speaker 1: undertook when he was a young psychologist on the rise
Speaker 1: in Israel at the Hebrew University in Jerusalem. And um,
Speaker 1: he and some of his colleagues were working on rewriting
Speaker 1: the standard high school psychology textbook for students in Israel.
Speaker 1: And that's a big undertaking because it's a you know,
Speaker 1: it's it's basically a core part of the curriculum. You
Speaker 1: have to start the textbook from scratch and um. So
Speaker 1: they asked each other, well, how long we should this take?
Speaker 1: And so one of them said, oh, I mean, how
Speaker 1: could it take more than seven or eight months? Another
Speaker 1: one said maybe a year? And somebody else said, I
Speaker 1: don't know, a year and a half or something. And
Speaker 1: Danny's just sitting there listening, puzzled the same way I
Speaker 1: just described. And then he so he turned, he gets
Speaker 1: a lightbulb and he over his head and he turns
Speaker 1: to the dean of education at the at the school
Speaker 1: they were affiliated with, the Humor University, and says to him,
Speaker 1: you know, are you aware of other teams, other groups
Speaker 1: that have done similar projects like this one? And the
Speaker 1: dean says, well, yeah, you know now that you mention it,
Speaker 1: I am, And that didn't occur to me before because
Speaker 1: he was one of the people who had given this
Speaker 1: low estimate of ten months or something like that. So
Speaker 1: Danny says, oh, so, of those groups, what what was
Speaker 1: the average length of time took them to complete the textbook?
Speaker 1: So the dean sort of pulls his chin for a while,
Speaker 1: and everyone in the room is sort of shifting uneasily
Speaker 1: in their seats, and after a long pause, he says, well,
Speaker 1: I guess of those who completed a similar project, I
Speaker 1: think it took on average about four years, not counting
Speaker 1: the guys who were still working and having closed the
Speaker 1: and so and so. Then Danny says, oh, okay, and
Speaker 1: what about the ones and how many how many of
Speaker 1: these teams would you say never completed it? And he said, oh,
Speaker 1: I guess forty or fifty percent, And so the room
Speaker 1: goes dead silent. And so the corollary to this is
Speaker 1: that they finally did finish the textbook, it took either
Speaker 1: seven or nine years, and if I think there's a
Speaker 1: second correla, I think I'm remembering this right was never
Speaker 1: actually used and yeah, it was out of it. And
Speaker 1: so so the first day Danny and I are working
Speaker 1: on the book, he says to me, I really want
Speaker 1: to avoid the planning fallacy. And by the way, I
Speaker 1: forgot Barry the just to sort of take this the
Speaker 1: final turn. The reason the planning fallacy is relevant because
Speaker 1: it brings out a basic flaw in human cognition, which is,
Speaker 1: when we're faced with any challenge or any set of data,
Speaker 1: what we tend to do is we think in very
Speaker 1: narrow framing. So you and I are going to write
Speaker 1: this textbook. So we think about and we talked to
Speaker 1: each other and we and you say, well, you know,
Speaker 1: I'm good at this, and I say, well you're good
Speaker 1: at it, I'm better. And we think about how qualified
Speaker 1: we are to do this, how excited we are about
Speaker 1: performing this task, and all we can really focus on
Speaker 1: is how we're going to do it better, faster and
Speaker 1: um and more perfectly than anybody who's ever done it before.
Speaker 1: But we don't ask ourselves what's the success rate of
Speaker 1: people who have tried this. There's a database of all
Speaker 1: the other people who've tried it, what is it? What's
Speaker 1: in the data? And so we don't look at the
Speaker 1: base rate. And that's Danny Kahneman is all about base rates.
Speaker 1: And so the wonderful line he gave me that I
Speaker 1: use all the time in my thinking and in my
Speaker 1: writing is he once said to me, the single most
Speaker 1: important question is what is the base rate? It's so
Speaker 1: funny you you bring this up today. This is absolutely true.
Speaker 1: I was having a discussion on the train on the
Speaker 1: way in about a woman I work with work. A
Speaker 1: woman I commute with is in fashion, and she's she's
Speaker 1: on the train. She's always having these angry like she
Speaker 1: pulls out her her phone so annoyed and she sends
Speaker 1: nasty emails to people, and I go, what's today? She goes,
Speaker 1: I get this email from somebody saying that they were
Speaker 1: so they do these long. I won't mention the brand,
Speaker 1: but one of us is wearing it, and it's um
Speaker 1: it's a very well known, famous brand. And she'll get
Speaker 1: this run off of a production line and three of
Speaker 1: them were terrible. Oh we have three, and she I go, so,
Speaker 1: why are you angry? She goes, three out of what
Speaker 1: three out of fifty three a fifty thousand. I don't
Speaker 1: know what this means. And I said to her that's
Speaker 1: called numerator blindness or denominator Basically, they're giving you the
Speaker 1: numerator and ignoring the context of how many of this? So,
Speaker 1: so the denominator blindness is So, if you want to
Speaker 1: impress the person who's sending you this adiotic there were
Speaker 1: three bad units out of the production run, tell them
Speaker 1: you have denominator blindness. You're not aware of the context
Speaker 1: from the lower You're only giving me the top number
Speaker 1: with no frame of reference. Correct. But but that that
Speaker 1: reminds me very similar to what is the basics? What
Speaker 1: is what is the base rate? Exactly? So you know.
Speaker 1: So Danny says to me that first day, of all people,
Speaker 1: I don't want to be the one who commits the
Speaker 1: planning fallacy. I don't want us in a book on
Speaker 1: cognitive bias, in a book that is going to talk
Speaker 1: about the planning house. So, uh, I want us to
Speaker 1: figure out together how long this is likely to take,
Speaker 1: so that we know what we're in for. And so
Speaker 1: we had a long conversation and he has a method
Speaker 1: for d biasing the planning fallacy, and we went through
Speaker 1: really perfectly, and at the end we concluded it should
Speaker 1: take a year and a half to two years, two years,
Speaker 1: and so I worked on the project with him for
Speaker 1: two years until you know, I had other things that
Speaker 1: were demanding my attention. Um, but for those two years
Speaker 1: it was pretty much a full time job for me
Speaker 1: and for him for that matter. And so at the
Speaker 1: end to those two years, he said, I'm about a
Speaker 1: third done, I think. And it took another I think
Speaker 1: three or four years after that, no kidding. So so
Speaker 1: he was right when he when he said he was
Speaker 1: a third done. Uh yeah, except he was wrong in
Speaker 1: the beginning when we when we decided it would take
Speaker 1: two years. So you know, when I said that, he
Speaker 1: he he has a remarkable sense of his own limitations.
Speaker 1: That was one issue where I think, but even there,
Speaker 1: he was aware of the fact that that was a problem.
Speaker 1: He knew it was a problem. He it's just the
Speaker 1: d biasing method didn't work well. And it's very difficult
Speaker 1: for most people to the bias, especially considering so many
Speaker 1: people are so unaware of their own biases. How can
Speaker 1: you protect yourself if you simply have no conception that hey,
Speaker 1: I have a cognitive bias he or or I have
Speaker 1: some aside from the fact that most many of these
Speaker 1: are already hardwired into you. If you're unaware of your
Speaker 1: confirmation bias, how are you going to avoid it? I
Speaker 1: tell people the reason we study this is so at
Speaker 1: least you have a fighting chance to be biasues. That
Speaker 1: is key. I mean, the biggest problem with the findings
Speaker 1: of behavioral economics is that most of the biases it
Speaker 1: identifies are unconscious, and by definition, you don't know you
Speaker 1: have this bias. So the single most powerful thing that
Speaker 1: you can do as an investor or for that manner,
Speaker 1: a consumer of information, or just an intelligent citizen is
Speaker 1: to use techniques to try to surface those biases in
Speaker 1: your own mind, at least make yourself aware of them.
Speaker 1: You know, It's funny because coming out of a legal background,
Speaker 1: where the mood court exercises, basically, you prepare a case
Speaker 1: and at any point in time you may be forced
Speaker 1: to argue the other side of the case, and it
Speaker 1: really gives you some degree of objectivity as to the
Speaker 1: strength and weaknesses of your arguments. And I started as
Speaker 1: a trader, and this was always something that was drilled
Speaker 1: into me. Hey, it doesn't matter if you're long or short.
Speaker 1: You have to be ready when the circumstances change to
Speaker 1: get out of that position to take the other position.
Speaker 1: I think a lot of people don't go through those
Speaker 1: sort of processes of saying because we have this whole
Speaker 1: conversation all the time, Hey, are you a bull or
Speaker 1: a bear? Uh? You know, I'm whatever makes sense at
Speaker 1: the moment, and don't feel the need to declare a
Speaker 1: major and stick to that regardless of what what the
Speaker 1: evidence says. Yeah, and it isn't an interesting barrier that,
Speaker 1: despite how badly reviled, the legal profession is almost as
Speaker 1: badly as financial journalism. When people are trying to figure
Speaker 1: out whether there's a conflict of interest at hand, they
Speaker 1: do call in lawyers because lawyers are better at evaluating
Speaker 1: that than most other profession. Doctors are not good at it.
Speaker 1: People on Wall Street are not good at it, and
Speaker 1: a lot of financial journalists, for that matter, are not
Speaker 1: good at it. You have to be able to step
Speaker 1: back and look at both sides of the argument, and
Speaker 1: that's a bigger challenge. That's that's a skill set that
Speaker 1: you have to learn. It doesn't necessarily come easy. Once
Speaker 1: you kind of get into a groove of it, it
Speaker 1: becomes something that can be done. All right, I know
Speaker 1: I don't have you all day, so let me get
Speaker 1: to some of my favorite questions that I ask everybody. UM.
Speaker 1: In the last ten or fifteen minutes we have, UM,
Speaker 1: you've mentioned some of your mentors. Who are your earliest mentors,
Speaker 1: either as a journalist or a UM neuroeconomic neuro economists,
Speaker 1: neuro finances as a journalist who your early mentioned I'm
Speaker 1: gonna I think I'm just going to mention one people,
Speaker 1: one person out of all the people I could mention.
Speaker 1: UM my beloved editor at Forbes, jim My Coles, who
Speaker 1: was the long time editor of the magazine and far
Speaker 1: and away one of the most brilliant editors I or
Speaker 1: anyone else I have ever encountered. And in when I
Speaker 1: was a young reporter at Forbes, Jim uh decided that
Speaker 1: I would be the mutual funds editor, and I'm uh.
Speaker 1: The one thing I remembered in the nick of time
Speaker 1: was that that had been his first major job when
Speaker 1: he came to the magazine in the nineteen fifties. So
Speaker 1: I knew better than to show disappointment on my face
Speaker 1: at having been handed such a boring assignment. So I
Speaker 1: said to him, do you have any advice for me?
Speaker 1: You did this job once, and he thought about it
Speaker 1: for a second. He looked at me and he sort
Speaker 1: of half smiled, and he said, don't get anybody's blood
Speaker 1: on your hands. And I never forgot it, and I
Speaker 1: know exactly what he meant by it, which was, you know,
Speaker 1: don't do your best not to give people advice. You
Speaker 1: wouldn't take yourself the hypocritic first, do first, do no harm,
Speaker 1: not not a bad thing. We've been talking a lot
Speaker 1: about books and investors, and you mentioned The Intelligent Investor
Speaker 1: by Benjamin Graham. What other books really stood out to
Speaker 1: you as you developed your your your your BS Detector,
Speaker 1: your your journalism chops, and your finance jops. Yeah, there's
Speaker 1: a couple of books I really love. I mean, we
Speaker 1: talked about Richard Feynman before. I think anybody can pick
Speaker 1: up any of the oral history books. You just Mr
Speaker 1: fineman or um, what do you care what other people think?
Speaker 1: Is another wonderful one. Uh, those books are fabulous even
Speaker 1: for someone with no background in science. They can teach
Speaker 1: you a little bit about how to think like a scientist,
Speaker 1: and that's critical. There's a wonderful little book called um
Speaker 1: How to Lie with Statistics by Darryl Hoff. It's literally
Speaker 1: sitting on my night tap, which is such a fabulous book.
Speaker 1: You know that came in out and I want to
Speaker 1: say the late fifties. Yeah, it came out in the
Speaker 1: fifties as a wonderful book. It doesn't seem dated at all.
Speaker 1: It's it's not, it's not. It will never go out
Speaker 1: of style. And where are the customers? Yachts? By Fred
Speaker 1: Schwade Jr. Which was published in and I've never read that,
Speaker 1: have the book, and I've been dying to get the
Speaker 1: free time. I can't believe I came on your show
Speaker 1: and you've never read that. I'm not I'm leaving right now.
Speaker 1: I'm not exaggerating that. I actually mentioned that to someone
Speaker 1: in the beginning of the summer, that that's my book
Speaker 1: to read the summer, and know you're going to read
Speaker 1: it tonight. It's I started the first chapter and really
Speaker 1: enjoyed it. What I want you to do is read
Speaker 1: it aloud. I want you to read it aloud to you.
Speaker 1: The second person who's mentioned that technique, we didn't allowed
Speaker 1: to yourself, all right, or to other people. You I'm
Speaker 1: walk in a room start reading aloud from it. People
Speaker 1: stop what they're doing, really, and now look at you. Well, normally,
Speaker 1: when you walk into a room and just start reading
Speaker 1: a lot from a book, people stop what they're doing.
Speaker 1: And yeah, but but after they listen for a while,
Speaker 1: they'll go back to what they're doing. They won't do
Speaker 1: that with this book. All right, I'm gonna I'm not
Speaker 1: exaggerating when I say, of all the Wall Street books
Speaker 1: I have not read, this is the one that I've
Speaker 1: been most looking forward to reading, not on my night table,
Speaker 1: on my dresser, but literally in the bedroom. It's it
Speaker 1: is easily one of the five best books ever written,
Speaker 1: so ahead of the Goldman sax Elevator book. But move
Speaker 1: move this up the queue. Okay, it's in the top three. Beforehand,
Speaker 1: I'm I'm finishing, had a lie with statistics and this
Speaker 1: was next in my You have to I'm embarrassed to
Speaker 1: admit that I've had this sitting waiting to be read
Speaker 1: for six months and I just haven't read it. It's
Speaker 1: a wonderful book. And uh what other investors influenced you? Uh?
Speaker 1: You know. Fairly early in my career, I was lucky
Speaker 1: enough to get to know a bunch of really great
Speaker 1: wise people, UM, Sir John Templeton, m Phil Coray, Irving Khan.
Speaker 1: These were all people who had lived through the crash
Speaker 1: of and had really benefited from it and developed sort
Speaker 1: of incredibly powerful long term perspective. UM. And I learned
Speaker 1: a lot from from those guys, Uh and UM, and
Speaker 1: also from some other people I was lucky to spend
Speaker 1: time with when it was easier to spend time with them,
Speaker 1: Michael Price, Bill Miller. UM. Folks like that who you know,
Speaker 1: sort of gone on to fame and fortune and in
Speaker 1: some cases some some misfortunes. I'm trying to get Templeton
Speaker 1: on the show, but as people never response, yeah, he's
Speaker 1: not returning calls anywhere. U. Miller is a guy who's
Speaker 1: actually enjoying a little bit of a resurgence. He would
Speaker 1: be interesting to have a conversation. UM. So we talked
Speaker 1: a little bit about the changing nature of financial journalism
Speaker 1: and and media. What do you see as the next
Speaker 1: major shifts that are that are coming in this space? Well,
Speaker 1: I think I think what is still desperately needed, UM
Speaker 1: is UM filters. Um. You know, Twitter does a lot
Speaker 1: of that, but if you set it upright, if you
Speaker 1: use it, you have to you have to approach Twitter
Speaker 1: very very deliberately and intelligently to make it work for
Speaker 1: you instead of against you. And I think the time
Speaker 1: is coming when there will be platforms or applications that
Speaker 1: will intelligently filter material for people and do a real service.
Speaker 1: I don't think we're there yet, and I don't know
Speaker 1: what it's going to look like, but I know it's
Speaker 1: coming and I hope it comes soon. That's that's that's
Speaker 1: really interesting. And I find that a handful of UM
Speaker 1: aggregators are are enormously helpful. I not only read a
Speaker 1: ton of stuff when I put together my morning reads,
Speaker 1: but I also look at a handful of other aggregators
Speaker 1: and see what they're looking at. And I don't want
Speaker 1: to have too much overlap. I want to look and
Speaker 1: find interesting. But but that's human driven, that's not robot driven. UM.
Speaker 1: Twitter is really something that I think has so much potential.
Speaker 1: So long as you mute the annoying and block the
Speaker 1: intellectually dishonest, that that eliminates a lot of the noises.
Speaker 1: And I think there's one other. There's one other tip,
Speaker 1: Barry and and I know you do this and I
Speaker 1: work very hard at it, which is you really want
Speaker 1: to use a service like Twitter. Two feed yourself as
Speaker 1: much disconfirmation as you can. You really want to follow
Speaker 1: people and try to be followed by people you don't
Speaker 1: agree with, people you think are wrong, but you think
Speaker 1: they're intelligently wrong. I have that cast has always had
Speaker 1: that role with me. We are frequently on the opposite
Speaker 1: side of the trade. And if I like a market,
Speaker 1: or if I'm long term bullish and Doug this short
Speaker 1: term bearish, he forces me to sharpen my argument. On
Speaker 1: the other hands, I've been negative on gold for about
Speaker 1: four or five years, and when someone challenges me and
Speaker 1: their Twitter handle has either the word gold or bullion
Speaker 1: in it, I know I'm not getting a honest, objective analysis.
Speaker 1: On the other side, I want someone to explain to
Speaker 1: me why I should own gold when I don't want
Speaker 1: to own gold. Um, in a way that's objective and
Speaker 1: neutral and dispassionate. Don't go looking for that on Twitter.
Speaker 1: You're not gonna find them. And UM my favorite two
Speaker 1: questions I asked of all my guests. First, what advice
Speaker 1: would you give to a millennial or recent college graduate
Speaker 1: who is just beginning their career in financial journalism? Well,
Speaker 1: I would First of all, I guess the first advice
Speaker 1: I would give you is to make sure you're in
Speaker 1: the right field. There are a lot of smart people
Speaker 1: who would tell you you're crazy for trying to be
Speaker 1: a financial journalist right now, and you might want to
Speaker 1: listen to them. They could be right. The second thing is,
Speaker 1: I'm I arrive earlier and leave later than everybody else.
Speaker 1: Every day I'm find the smartest people you can possibly
Speaker 1: find and learn everything you can from them. Ask everyone,
Speaker 1: what do you read? Whom do you admire? Who's the
Speaker 1: smartest person you know? Um? You know, when I started
Speaker 1: at Forbes in seven, every day I would I would
Speaker 1: read the Wall Street Journal and I would circle in
Speaker 1: red pen every quote from somebody who knew more about
Speaker 1: whatever it was than I did, and then I would
Speaker 1: call that person up, because in those days you had
Speaker 1: to call and I would say, I want to buy
Speaker 1: you breakfast, lunch, dinner, drinks, and then I would just
Speaker 1: download from the person's brain and then I you know,
Speaker 1: I learned something I didn't know before. That's quite fascinating,
Speaker 1: and that worked. You can pick up the phone and
Speaker 1: call somebody. It worked then, and I think it works
Speaker 1: now too, although email is easier obviously, to say the least.
Speaker 1: And and our last question, what is it that you
Speaker 1: know today about financial reporting, investing and journalism that you
Speaker 1: wish you knew thirty years ago? Well, my dad, who
Speaker 1: was a very wise man, had a wonderful expression, which
Speaker 1: was that, And I think I remember this verbatim. It's
Speaker 1: remarkable how much you have to learn about something in
Speaker 1: order to discover how little you need to know about it.
Speaker 1: He goes right back to Dunnan Krueger. There's the experts
Speaker 1: know their own skill set. Amateurs have no clue, right,
Speaker 1: And I think the other the other thing he was
Speaker 1: driving at is that in order to learn those few
Speaker 1: true things that are at the core of everything, you
Speaker 1: have to learn an enormous amount about them. And I
Speaker 1: guess the thing I most wish I had known at
Speaker 1: the beginning was where all this would come out, which
Speaker 1: is that ultimately success as an investor depends on one thing,
Speaker 1: really only depends on one thing self control. M hm.
Speaker 1: And you know when Benjamin Graham said, uh, the investor's
Speaker 1: worst enemy is himself. He wasn't kidding, And in a
Speaker 1: lot of ways, the entire book The Intelligent Investor boils
Speaker 1: down to that one sentence. And great investors have self control,
Speaker 1: and everyone else can't be a great investor. If you
Speaker 1: don't have self control, you don't belong in the game
Speaker 1: where you're not going to prevail at least. Hmm. That's
Speaker 1: quite fascinating. Jason, Thank you so much for spending so
Speaker 1: much time with us and being being so generous. If
Speaker 1: people want to find your work, the entire body of
Speaker 1: your work, I would be remiss if I didn't mention
Speaker 1: Jason's Wide dot com. For those of you who follow
Speaker 1: me on Twitter, and you will notice each morning around
Speaker 1: six ish, you occasionally will see a Today in seven
Speaker 1: and I will reference what happened that day, and I
Speaker 1: probably do that once or twice a week. That comes
Speaker 1: directly from this day in financial history, UM, which I
Speaker 1: then have to edit down to a hundred forty characters
Speaker 1: because it usually starts at about three or four hundred characters,
Speaker 1: and there is an art to getting a paragraph into
Speaker 1: a tweetable sentence. UM. But I find that fascinating. There's
Speaker 1: a lot of great quotes there, there's basically who you are,
Speaker 1: what you've done. Is it safe to say just about
Speaker 1: every column you've written is either there or linked to
Speaker 1: from there? That it can be gotten? Yeah, I mean,
Speaker 1: I'm plus your books plus everything. I like a good
Speaker 1: hedge fund manager. I'm backfilling. But it but it, but
Speaker 1: it takes time. I think I have everything back to
Speaker 1: two thousand thirteen and a lot of stuff back uh ten,
Speaker 1: fifteen or twenty years or more. In fact, I recently
Speaker 1: pulled something from your site that you had re added there.
Speaker 1: I'm trying to remember. It was was like fifteen years
Speaker 1: ago as a speech you had given, and I linked
Speaker 1: to it in the Weekend Reads because it was the
Speaker 1: longer form thing and it I love when I will
Speaker 1: find something that people haven't seen yet and then it
Speaker 1: starts just hanging around going viral, and I'm like, oh,
Speaker 1: I guess everybody else liked it. Also, it was I
Speaker 1: wasn't out on a limb. That was a speech you gave.
Speaker 1: Do you know what I'm referring to? I think it
Speaker 1: was a speech I gave that that I called fat
Speaker 1: tails thin ice. That the one and and that fifteen
Speaker 1: years not seen online for a long time and suddenly
Speaker 1: that goes viral. It's a speech I gave at the
Speaker 1: Morning Star Investment conferency and UH two thousand one, I think, UM,
Speaker 1: where I sort of talked about UH, I guess what
Speaker 1: would I say? A few risks that I'm materialized later
Speaker 1: and UH that I thought the financial advisor community was
Speaker 1: dangerously overlooking. Well, I'm We're out of time, and I
Speaker 1: just wanted to thank you again for spending so much time. UM,
Speaker 1: you've been listening to Masters in Business on Bloomberg Radio.
Speaker 1: If you enjoy this conversation, look up an Inch or
Speaker 1: down an inch on iTunes and you could see any
Speaker 1: of the other five dozen such podcasts we've had over
Speaker 1: the past year and change. UM, Jason's wife, thank you
Speaker 1: again for for coming by my pleasure. Parry, thanks for
Speaker 1: having me. You're listening to Masters in Business with Barry
Speaker 1: Ridholts on Bloomberg Radio.