Latest / Masters in Business / Dr. Raife Giovinazzo Discusses Research on Investors' Mistakes

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Dr. Raife Giovinazzo Discusses Research on Investors' Mistakes · Masters in Business

0:02
Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio.
0:09
Speaker 1: This week on the podcast, I have an extra special guest.
0:13
Speaker 1: I'm gonna bet you haven't heard of this money manager,
0:16
Speaker 1: but you should. His name is Dr Raife Jovinazzo. He
0:20
Speaker 1: runs the very interesting behavioral small cap equity strategy at
0:27
Speaker 1: Fuller and Thaylor. For the past five years, the fund
0:30
Speaker 1: has compounded and it has beaten of all its peers,
0:36
Speaker 1: so they are doing something right there. Uh. He has
0:39
Speaker 1: a fascinating background, and you'll hear about both his academic
0:44
Speaker 1: background at Princeton and the University of Chicago working for
0:49
Speaker 1: two of the giants in the world of behavioral economics,
0:53
Speaker 1: Danny Kahneman and Richard Thaylor. How's that for a pair
0:57
Speaker 1: of advisors. Uh. And he spent his entire your career
1:01
Speaker 1: working in that space, trying to figure out how to
1:05
Speaker 1: apply the knowledge and the wisdom that those gentlemen and
1:09
Speaker 1: others have created in the field of of behavioral finance
1:13
Speaker 1: to the world of investing. I think you will find
1:16
Speaker 1: this to be an absolutely fascinating conversation. I know I
1:20
Speaker 1: enjoyed it a great deal. So with no further ado,
1:23
Speaker 1: my conversation with Raife Jovinazzo. I'm Barry Ridhults. You're listening
1:32
Speaker 1: to Masters in Business on Bloomberg Radio. My special guest
1:36
Speaker 1: today is Dr Raith Jovinazzo. He is responsible for managing
1:42
Speaker 1: the Fuller and Failor behavioral small cap equity strategy at
1:47
Speaker 1: the firm Fuller and Failor. He has a fascinating background. Previously,
1:53
Speaker 1: he was researcher and co portfolio manager with black Rocks
1:58
Speaker 1: Scientific Active Equity Group. He has a BA in sociology
2:03
Speaker 1: from Princeton and an m b a PhD from the
2:06
Speaker 1: Booth School of Business at University of Chicago. But his
2:10
Speaker 1: advisors were Danny Khanoman at Princeton and Richard Taylor at Chicago.
2:16
Speaker 1: So I expect this to be a fascinating conversation. Dr
2:21
Speaker 1: Raef Gina Venazzo, welcome to Bloomberg. Thank you very much.
2:25
Speaker 1: So let's start with your advisors. That's pretty elite group
2:31
Speaker 1: of people to work within your career. Kneman is your
2:35
Speaker 1: undergraduate advisor and Failor as your m b A and
2:38
Speaker 1: PhD advisor. That's some serious intellectual firepower. They are smart folks.
2:44
Speaker 1: I was lucky, you know, I took a class by
2:48
Speaker 1: Knoman on decision making. I loved it, asked him to
2:51
Speaker 1: be my thesis advisor. The funny thing is, at that
2:54
Speaker 1: point in time, I didn't understand that he was a
2:56
Speaker 1: giant in his field. I knew he was very smart. Obviously,
3:00
Speaker 1: in the course of doing my research, I realized I'm
3:02
Speaker 1: talking to the number one expert in this subject matter. Uh.
3:07
Speaker 1: And then he actually connected me ultimately with Taylor. He said,
3:11
Speaker 1: I called him up about five years after I've been
3:13
Speaker 1: working as a strategy consultant and said, I want to
3:15
Speaker 1: go back and I want to combine study of business
3:18
Speaker 1: with the study of psychology. And he said, well, you
3:21
Speaker 1: need to go study under my best friend, Dick Taylor
3:23
Speaker 1: the University of Chicago. How crazy is that? Well so, so,
3:27
Speaker 1: during the time these folks were advising you, you had
3:30
Speaker 1: an appreciation of how unbelievably fortunate you are. I did,
3:35
Speaker 1: you know. And that's a nice thing, you know, it's
3:37
Speaker 1: a great thing. Let me talk up my alma made
3:40
Speaker 1: to the University of Chicago. There's so many noble prize
3:42
Speaker 1: winners there, you know, I mean, ironically, I don't know
3:45
Speaker 1: if you knew this fact. On my dissertation committee were
3:48
Speaker 1: both Taylor and Fama, which is the only time that's
3:51
Speaker 1: ever happened. And you know that, to my knowledge, that
3:53
Speaker 1: those two have been on the same and they're golfing buddies. Yeah,
3:57
Speaker 1: they get along much much better than people think they
3:59
Speaker 1: do well. Philosophically, they're completely the opposite sides of the universe.
4:04
Speaker 1: And yet I would disagree actually, and that they both
4:07
Speaker 1: strongly believe in paying attention to evidence. Let's look at
4:11
Speaker 1: the data, and that is it's actually a big unifying
4:15
Speaker 1: approach as opposed to we'll just look, we'll have a
4:18
Speaker 1: theory about what should work, if we don't actually care
4:20
Speaker 1: if it actually happens in the real world. So they
4:22
Speaker 1: start with the data, but they end up in very
4:25
Speaker 1: different places. They have different interpretations of the data. That's
4:28
Speaker 1: certainly true to say the least. So the other question
4:32
Speaker 1: that comes to mind is how do you go from sociology,
4:35
Speaker 1: which is definitely not a moneyed um economic slash business
4:42
Speaker 1: oriented coursework to write in the mix of finance and
4:47
Speaker 1: asset management. What made you decide sociology leads to NBA.
4:53
Speaker 1: So it happens that at Princeton the most flexible major
4:57
Speaker 1: was sociology and I actually only took five sociology classes
5:01
Speaker 1: as a quote sociology major. Uh. To be honest, I'm
5:05
Speaker 1: was never were very well trained in the discipline of sociology,
5:09
Speaker 1: but it allowed me to take all sorts of social
5:11
Speaker 1: science classes. And I think at the time I was
5:14
Speaker 1: really searching for this understanding that it's more than just economics.
5:19
Speaker 1: There is something that matters about how people think, how
5:21
Speaker 1: people behave, what are norms? And so I think it
5:24
Speaker 1: was a very natural transition to where I ultimately ended
5:27
Speaker 1: up even at Princeton, to really being focused on this
5:29
Speaker 1: decision making, which is an intersection of psychology and economics.
5:33
Speaker 1: So so you come out of Princeton, you spend five
5:35
Speaker 1: years doing some consulting work. Uh, you end up going
5:39
Speaker 1: to Chicago. What was that four years NBA PhD? I
5:43
Speaker 1: wish it was only four. So the NBA is two years,
5:46
Speaker 1: and then it's another three or four years on top
5:48
Speaker 1: of that. You know what's ironic is I told my
5:51
Speaker 1: wife when I joined the PhD program, Oh, I think
5:55
Speaker 1: I'll be able to do it in three years. It
5:57
Speaker 1: turns out nobody does it in three years, and almost
6:00
Speaker 1: nobody does it in four years. And so I was
6:03
Speaker 1: the norm. I did it in five years. It's kind
6:06
Speaker 1: of funny that meets the standard planning biases that I
6:09
Speaker 1: was about to bring that up exactly. The planning talks
6:12
Speaker 1: about that all the time. When they when they started
6:14
Speaker 1: working on an economics textbook, he said, well, you know,
6:18
Speaker 1: we're smarter than most of those other guys. This will
6:20
Speaker 1: only take us. And he said we were off by
6:22
Speaker 1: a factor of ten x, which is exactly I did
6:25
Speaker 1: the same thing. You know, what he says is people
6:27
Speaker 1: use an internal model the forecast. They think about their
6:31
Speaker 1: own personal situation, and they downweight the external model of forecasting,
6:36
Speaker 1: which would be what happened to everybody else. So I
6:38
Speaker 1: felt like, look, I've been here two years, I've taken
6:41
Speaker 1: some PhD classes. I know what I'm doing. I have
6:43
Speaker 1: a focused area. I should be able to do it quickly. Yeah,
6:46
Speaker 1: I mean, listen, how hard is a trade war? It's not.
6:50
Speaker 1: It's not that difficult. That is the classic planning fallacy
6:54
Speaker 1: right there. It is. So, so you get your PhD
6:57
Speaker 1: and your m b A. And what's your first job
7:00
Speaker 1: out of out of B school slash PhD school. Yeah,
7:04
Speaker 1: so the PhD program is trying to train researchers fundamentally UH,
7:10
Speaker 1: and at the time I actually thought I wanted to,
7:13
Speaker 1: if possible, go into an academic position, but it was
7:18
Speaker 1: fascinated by predicting stock returns. I did always wonder a
7:22
Speaker 1: little bit, if you really want to predict stock returns,
7:25
Speaker 1: should you be just studying it? Why not actually try
7:27
Speaker 1: to put it in practice? But primarily I interviewed for
7:30
Speaker 1: academic positions, but as well as a few UH positions
7:34
Speaker 1: in industry as well. I was fortunately I did get
7:37
Speaker 1: a number of job offers. My wife is a Harvard
7:40
Speaker 1: Business School graduate. She's a successful executive, and it was
7:43
Speaker 1: very hard to to match some of the locations. I
7:46
Speaker 1: had an offer at a Dartmouth actually with Ken French,
7:49
Speaker 1: which was great, but there's no there's that as a
7:51
Speaker 1: tiny town. There's no real positions for no positions for
7:55
Speaker 1: my wife. And I also realized, you know again, I'd
7:58
Speaker 1: like to be closer to actually amending this, so I
8:01
Speaker 1: actually had a conversation with Dick. I had a few
8:03
Speaker 1: offers in industry. One of them was at Barkley's Global
8:07
Speaker 1: Investors in the Scientific Act of Equity that eventually became
8:09
Speaker 1: Black Rock, which eventually became Black Rock and I've also
8:12
Speaker 1: had an offer, fortunately from Fuller and Failure and Dick said, look,
8:17
Speaker 1: if what you want to do is learn all about
8:21
Speaker 1: the investment process and be involved in everything with that,
8:24
Speaker 1: join our firm. We're a small firm. You will do everything.
8:27
Speaker 1: If what you want to do is just focus on research, well,
8:30
Speaker 1: if you join a twenty PhD uh staffed research group
8:35
Speaker 1: at Barkley's Global Investors, you can focus on research and
8:38
Speaker 1: since at the time I had been struggling with academia
8:41
Speaker 1: or industry, that seemed like a happy medium. But by
8:44
Speaker 1: the end of my time there, I had already moved
8:46
Speaker 1: over into more of a portfolio management role and realized
8:50
Speaker 1: that's what I wanted to do. So it was a
8:51
Speaker 1: great opportunity to come to Fuller and Taylor five years later.
8:54
Speaker 1: That's fascinating. Let's let's talk a little bit about behavioral finance.
9:00
Speaker 1: So you you leave Princeton under Danny Kahneman's tutelage and
9:05
Speaker 1: end up with Richard Thaylor, widely known at the University
9:08
Speaker 1: of Chicago, widely known as the father of behavioral finance.
9:12
Speaker 1: What was it like learning at the knee of the master.
9:17
Speaker 1: It's great, you know, one thing that impresses me about
9:20
Speaker 1: both of them is their willingness to actually be challenged
9:26
Speaker 1: and change their minds. I think they both like me
9:29
Speaker 1: because I was willing to disagree with them, and that's
9:32
Speaker 1: good because if they didn't like that, then things could
9:35
Speaker 1: have been a little bit rocky. I saw you do
9:37
Speaker 1: an interview of Dr Khaman not too long ago, um,
9:42
Speaker 1: and you talk to him about the role of money
9:44
Speaker 1: buying happiness, how much it can and his perspective on
9:49
Speaker 1: that has swung around. Tell us a little bit about
9:51
Speaker 1: that conversation, because I thought you're back and forth with
9:54
Speaker 1: charming well well in college. He at that point time,
10:00
Speaker 1: back in the late nineties, he was doing a lot
10:02
Speaker 1: of research about experienced happiness as opposed to predicted happiness,
10:08
Speaker 1: and part of that study was an analysis of how
10:11
Speaker 1: happy does money really make us. We all think it
10:13
Speaker 1: makes us tremendously happy, doesn't make us as happy as
10:16
Speaker 1: we think, And one of his conclusions at the time
10:19
Speaker 1: was that there is a kink in the amount of
10:22
Speaker 1: happiness we experience from money happening defined that kink sorry,
10:26
Speaker 1: meaning that the amount of happiness goes up up up
10:29
Speaker 1: with money up until at the time he said about
10:32
Speaker 1: twenty thousand dollars of income, which then thirty years ago
10:35
Speaker 1: meant economic security. You're paying for healthcare, and we even
10:40
Speaker 1: even then, you know twenty you know, in a lot
10:42
Speaker 1: of mid nineties, twenty thousand is not a whole lot um.
10:46
Speaker 1: And he set up till twenty thousand, it increases, your
10:48
Speaker 1: happiness increases with money, but after that it's flat. And
10:52
Speaker 1: I was joking with him, actually talked to him about
10:54
Speaker 1: five years after college working in New York making fortunately
10:58
Speaker 1: more than twenty thousand dollars, but not a whole lot more.
11:01
Speaker 1: And I recalled when I got my first raise, made
11:04
Speaker 1: me a lot happier. That was quite useful. I said,
11:06
Speaker 1: I gotta tell you, this does not match my experience
11:10
Speaker 1: of the idea that money beyond twenty dollars doesn't do
11:13
Speaker 1: anything more for my happiness. And he at the time said, oh, rafe,
11:17
Speaker 1: we got it wrong. Actually, it's not kinked. It's log linear,
11:21
Speaker 1: meaning it gets more and more gradual. How much happiness
11:26
Speaker 1: you get from money, it starts the plateau. The rule
11:29
Speaker 1: of diminishing returns kicks in. It's but to be precise,
11:32
Speaker 1: a plateau is literally a flat point whereas diminishing returns
11:36
Speaker 1: is the slope is going down. So his point was
11:39
Speaker 1: just it still goes up, but much more slowly goes up,
11:41
Speaker 1: much more slowly, exactly. And so I was just struck
11:44
Speaker 1: by this is a giant in his field. What giant
11:46
Speaker 1: in their field? Have you ever heard say, oh I
11:48
Speaker 1: made a mistake. Oh I'm changing my mind. Although then
11:51
Speaker 1: in our interview which you witnessed, he said, Rafe, I've
11:55
Speaker 1: now gone back to thinking that it is in fact
11:57
Speaker 1: kinked and there's a permanent plateau where it doesn't get higher.
12:00
Speaker 1: I wonder if that's just a function of longevity and
12:03
Speaker 1: seeing the world from your seventies and eighties as opposed
12:06
Speaker 1: to your thirties and forties, that sort of smile of happiness,
12:10
Speaker 1: you're you're really happy as a young in and then
12:13
Speaker 1: it sort of drops and then peaks again in your
12:15
Speaker 1: later years. I wonder if that that's relevant, could be.
12:18
Speaker 1: But knowing Dr conom and I bet it's based on
12:20
Speaker 1: some very hard data which I just haven't seen now.
12:23
Speaker 1: The other data on this one point, which I find fascinating.
12:26
Speaker 1: It turns out that once you control for life events
12:30
Speaker 1: such as divorce, the numbers skew much higher. And if
12:34
Speaker 1: there's a divorce in there, no matter how much money
12:37
Speaker 1: you have, it ends up being miserable or so some
12:41
Speaker 1: economists have have referenced, you know, uh, Dick Taylor has
12:46
Speaker 1: a phrase which is your happiness is the minimum of
12:49
Speaker 1: yours and your spouses happiness. So that makes Amie accordingly
12:54
Speaker 1: that that makes that makes perfect sense. So you're at
12:58
Speaker 1: the University of Chicago with Sailor. Did you ever participate
13:02
Speaker 1: in any of his studies as a subject. I don't
13:06
Speaker 1: think I did. Actually, you know, the standard psychological experiments
13:11
Speaker 1: usually use a little bit of misdirection, and if they
13:14
Speaker 1: say it's about one thing, but it's really about something
13:17
Speaker 1: slightly different, it makes it a little bit tricky. If
13:20
Speaker 1: you have people who know too much of the psychology
13:22
Speaker 1: to be able to see through what are you really
13:24
Speaker 1: asking about? You would be the ringer at the table
13:26
Speaker 1: that was wo That would throw it off. And um,
13:29
Speaker 1: let's talk a little bit about blind spot bias, the
13:33
Speaker 1: people's own failure to recognize their own biases, even if
13:37
Speaker 1: they're knowledgeable about biases and other people. That was also
13:41
Speaker 1: discussed with Professor Khaneman. Part of it is our biases
13:45
Speaker 1: are hardwired. They really come deep innately from how we
13:50
Speaker 1: think about the world. You know, It's funny as the
13:53
Speaker 1: conversation I recently had with Danny that you witnessed, he
13:57
Speaker 1: pointed out, I was making a joke at the research
14:01
Speaker 1: that he started uses this complicated word heuristics that people
14:05
Speaker 1: use a heuristic which is really just a rule of thumb,
14:08
Speaker 1: and I tease them about why don't you call it
14:10
Speaker 1: a rule of thumb, which is an English phrase that
14:12
Speaker 1: people understand. He he reacted very strongly to that. He
14:16
Speaker 1: also reacted brilliantly to point out that a rule of
14:20
Speaker 1: thumb is a deliberately chosen approximation, but in fact our
14:25
Speaker 1: biases come from unconscious rules of thumb. In fact, he said,
14:29
Speaker 1: rules of thumb is therefore the wrong word because it's
14:32
Speaker 1: it's an unconscious process that makes us quickly jumped to
14:35
Speaker 1: conclusions that are in fact incorrect. And it's precisely because
14:39
Speaker 1: it is these unconscious processes that make us do this,
14:44
Speaker 1: that make it so hard to overcome our biases, even
14:46
Speaker 1: if we're aware that we should be looking out for them.
14:49
Speaker 1: Let's jump right into that and describe what it's like
14:53
Speaker 1: to build a firm based on known behavioral biases. How
14:58
Speaker 1: is the firm structured and how does it take advantage
15:01
Speaker 1: of all of these eras that investors make. Yeah, everything
15:05
Speaker 1: we do is based on the study of investor mistakes,
15:09
Speaker 1: and we try to invest on the opposite side of
15:12
Speaker 1: where we think other investors are making those mistakes. Broadly,
15:17
Speaker 1: psychologists have documented dozens of mistakes, but you can group
15:21
Speaker 1: them in two categories. Sometimes people overreact, sometimes people underreact.
15:26
Speaker 1: The trick, of course, is knowing when they're likely to
15:28
Speaker 1: do one versus the other, and then we try to
15:30
Speaker 1: buy when people have overreacted to bad news, to panicking,
15:34
Speaker 1: or when they're underreacting to good news, and we think
15:37
Speaker 1: that prices are going to go up even further and
15:39
Speaker 1: faster than they realize. So if if you were managing
15:43
Speaker 1: a portfolio at the current portfolio you're running at a
15:47
Speaker 1: different firm, I would say, oh, it looks like Rape
15:50
Speaker 1: is managing those small cap value tilted FAMA French factor portfolio.
15:57
Speaker 1: But that's not exactly what you're doing, is it. No? Oh,
16:00
Speaker 1: so I would say that the overreaction to bad news
16:04
Speaker 1: is naturally going to find stocks that have bad news.
16:07
Speaker 1: They're gonna be guess what we're likely value strategies value companies,
16:13
Speaker 1: And in fact we run a strategy that is a
16:16
Speaker 1: pure overreaction strategy, and that does look like small value.
16:21
Speaker 1: Of course, uh by by construction, the strategy that I
16:24
Speaker 1: run is actually a small cap core because it includes
16:28
Speaker 1: this examination of do we think people are under reacting
16:31
Speaker 1: to good news? And therefore it sort of removes the value.
16:34
Speaker 1: Tilton ends up being core portfolio because of that reason,
16:38
Speaker 1: and I just have to reference that. At the failure
16:41
Speaker 1: economent event, I was sitting at the overreaction table and
16:45
Speaker 1: all the tables had cognitive biases. Instead of table one,
16:49
Speaker 1: table two, table three, it was table confirmation bias, table um, overreaction,
16:54
Speaker 1: et cetera. I found that terribly amusing. So so let's
16:59
Speaker 1: talk a little bit about small cap um. The argument
17:02
Speaker 1: could easily be made that small caps outperform over time
17:08
Speaker 1: because you're taking more risk, you have liquidity risks, they're
17:12
Speaker 1: much less followed by analysts, they're much less known, and
17:16
Speaker 1: and therefore that out performances on a risk adjusted basis
17:20
Speaker 1: goes away or or does it? What? What are you?
17:24
Speaker 1: What are your thoughts on the so called UH small
17:26
Speaker 1: cap premium? So I think the reality is that some
17:29
Speaker 1: of the small cap premium is truly risk and most
17:34
Speaker 1: of the small cap premium is not risk. But it's both.
17:38
Speaker 1: On a side note, you know, academics often write papers
17:42
Speaker 1: that are either everything's a mistake or everything is rational,
17:45
Speaker 1: but if you talk to them, almost all of them
17:47
Speaker 1: agree it's both. So specifically, let me talk about the
17:51
Speaker 1: small cap premium. You mentioned liquidity risk. I think that
17:56
Speaker 1: there is some risk of owning things that have less liquidity,
17:59
Speaker 1: that if you need to sell them, they're going to
18:02
Speaker 1: perform worse. Although interesting note, in general, stocks that have
18:06
Speaker 1: lower liquidity actually have a lower beta, they have lower
18:09
Speaker 1: exposure to the market. It appears that when the market panics,
18:13
Speaker 1: people tend to sell their most liquid names. Not exactly
18:19
Speaker 1: so the intuition of oh, when people are desperate, the
18:22
Speaker 1: least liquid will be terrible. It doesn't do bad on
18:25
Speaker 1: a price scent. In terms of prices. It is of
18:28
Speaker 1: course a challenge if you really do need to sell it, though,
18:31
Speaker 1: makes a lot of sense. So if it's not all risk,
18:35
Speaker 1: where does the rest of the return come from? In
18:37
Speaker 1: small caps? So you mentioned the other issues that there's
18:41
Speaker 1: less followed not a lot of analysts not well known
18:45
Speaker 1: and not well known. So to me, none of those
18:49
Speaker 1: actually are truly risk. They're sort of a lack of comfort,
18:53
Speaker 1: and I think that's where a lot of the return
18:56
Speaker 1: can come from, in that people don't know about them,
19:00
Speaker 1: and so they're willing, they're unwilling perhaps to to take
19:04
Speaker 1: a gamble on them and invest as much in them.
19:06
Speaker 1: But that really truly isn't risk in the sense of
19:09
Speaker 1: risk to your money. It's just perhaps risk to your psyche.
19:12
Speaker 1: And I would call that kind of risk to your
19:13
Speaker 1: psyche something that is really more behavioral. And I should
19:17
Speaker 1: add there's there's one other element that I do think
19:19
Speaker 1: really matters, and this is a little bit technical, but
19:23
Speaker 1: if you think about it, once you assume that there
19:26
Speaker 1: are errors in the prices of companies, Naturally, if a
19:31
Speaker 1: company is overvalued, it will be a little bit bigger,
19:35
Speaker 1: if a vent company is undervalued, it will be a
19:38
Speaker 1: little bit smaller. So as soon as you think that
19:41
Speaker 1: there are any errors, sorting on size is not going
19:44
Speaker 1: to be a very direct way of finding those errors,
19:46
Speaker 1: but it will be correlated with the errors. And so
19:49
Speaker 1: I do think that matters as well, that just beaten
19:51
Speaker 1: up stocks are more likely to be small, just because
19:54
Speaker 1: any any mistake people made would automatically make them a
19:58
Speaker 1: little bit smaller than they really should have been. The
20:00
Speaker 1: description of of the psychological risk of not being familiar
20:04
Speaker 1: with the names reminds me a little bit of the
20:06
Speaker 1: home country bias that people tend to be wildly overweighted
20:10
Speaker 1: around the world. Wherever you live, you own the companies,
20:13
Speaker 1: you're familiar with, the CEOs, you've seen on local television,
20:17
Speaker 1: and it creates a very distorted portfolio. You're quite right,
20:20
Speaker 1: And of course, the United States is such a large
20:23
Speaker 1: economy and it's so well diversified, having a home bias
20:26
Speaker 1: in the United States is probably fine. Furthermore, a lot
20:29
Speaker 1: of the largest companies in the United States nowadays they
20:32
Speaker 1: have international operations. You actually are getting exposure. But what's
20:35
Speaker 1: fascinating to me is always you take a small company
20:37
Speaker 1: in Norway, and Norwegian investors are more likely to invest
20:41
Speaker 1: a predominant amount of their investments in Norwegian stocks. That
20:45
Speaker 1: really doesn't make sense overall, other than the fact that
20:47
Speaker 1: they're so familiar with those It does give them, It
20:50
Speaker 1: does give them psychological comfort, and you know there might
20:53
Speaker 1: be a value to that. But if from purely rational.
20:56
Speaker 1: All I care about is my money and my return standpoint.
21:00
Speaker 1: We're taking a lot of risk with the homebias. It
21:02
Speaker 1: seems that things that investors do that give them comfort
21:07
Speaker 1: don't seem to work to their advantage in the markets.
21:10
Speaker 1: Is that a fair statement. I think that's a very
21:14
Speaker 1: fair broad statement. It matters a little bit exactly how
21:20
Speaker 1: you implement it, of course. But but the idea is,
21:23
Speaker 1: if people are going to pile into something because it
21:25
Speaker 1: makes them feel good, it should cause the returns on
21:29
Speaker 1: that particular feel good strategy to be a little bit lower.
21:32
Speaker 1: So here's the key question I have about the portfolio
21:35
Speaker 1: you manage. When stocks get thrown out by a large
21:40
Speaker 1: group of investors and they become a little smaller and
21:43
Speaker 1: the price becomes a little lower, how can you identify
21:48
Speaker 1: when it is either a behavioral issue of people overreacting
21:53
Speaker 1: or genuinely decaying fundamentals. So a lot of the Reeds
21:59
Speaker 1: that own malls and and other things they've gotten shell act.
22:05
Speaker 1: Is this a permanent change in society or people over reacting?
22:08
Speaker 1: Maybe that's not the best example. We could use steam
22:11
Speaker 1: engines and leather belt companies back in the early days
22:14
Speaker 1: of the DAO. But the key question is how can
22:16
Speaker 1: you tell the difference between when something is fundamentally deteriorating
22:21
Speaker 1: on a long term, secular basis versus investors overreaction. Yeah,
22:26
Speaker 1: that of course is the key question. And you know,
22:30
Speaker 1: naturally I could talk for hours and hours about the
22:33
Speaker 1: details of how we implement stuff and just touch the
22:35
Speaker 1: surface of how we approach it. But here's the broad outline.
22:39
Speaker 1: Our approach is to try to look at queues where
22:42
Speaker 1: we think and other investors are likely to make mistakes here.
22:46
Speaker 1: Some of the cues we use, for example, in the
22:49
Speaker 1: retail space, because we see a lot of overreaction to
22:52
Speaker 1: problems in retail right now, are to say an individual
22:56
Speaker 1: company basis, what are the insiders doing, What is the
22:59
Speaker 1: manage meant doing? Are they buying back shares of their company?
23:02
Speaker 1: Are they selling shares? That's an entry point to say
23:06
Speaker 1: is there a real problem here? Then we're gonna look
23:08
Speaker 1: at how the investors reacted to the news. In this case,
23:11
Speaker 1: it's pretty easy to understand there's a lot of negative
23:13
Speaker 1: news out there about retail. But then we do also
23:16
Speaker 1: have to do the hard work of digging in and saying, Okay,
23:19
Speaker 1: what is the real opportunities of this individual firm. Part
23:23
Speaker 1: of our approach is to try to not make an
23:25
Speaker 1: overall description, overall analysis of hair are people overreacting to,
23:30
Speaker 1: you know, mall reads, but instead really look at individual
23:33
Speaker 1: companies and say, how about this particular read. And when
23:36
Speaker 1: you dig into individual companies, of course they have individual
23:39
Speaker 1: nuances that can make a real difference. Let's talk a
23:42
Speaker 1: little bit about the success your funds has had over
23:46
Speaker 1: the past a half decade prior five years, you've compounded
23:51
Speaker 1: at seventeen percent a year, beating of other small cap funds.
23:57
Speaker 1: So what do you owe this success too, and what
24:01
Speaker 1: are your expectations about this fun going forward. The success
24:05
Speaker 1: is due to our process and that's the key to
24:09
Speaker 1: how we invest. We are trying to spot where other
24:12
Speaker 1: investors might be biased. Make no doubt, I'm biased, just
24:16
Speaker 1: like every other portfolio manager at Fuller and Taylor, just
24:19
Speaker 1: like you, just like everyone. And it's our process that
24:22
Speaker 1: lets us overcome those biases and find opportunities. And we
24:26
Speaker 1: think that's going to continue working. Obviously, no guarantees. My
24:30
Speaker 1: compliance person would get very mad if I made any
24:32
Speaker 1: kind of guarantees. But what we continue to have very
24:35
Speaker 1: comfortable with the process. Yeah, we think it makes sense
24:40
Speaker 1: when investing to try to figure out where are other
24:43
Speaker 1: people making a mistake. So, so here's the key arbitrage
24:47
Speaker 1: a way, the alpha question. You guys have carved out
24:51
Speaker 1: a niche in behavior investing, and obviously when you have
24:54
Speaker 1: people like Richard Taylor and Danny Kahneman involved, that gives
24:59
Speaker 1: you a big edge. But what about other firms recognizing
25:03
Speaker 1: this and coming into the same space and saying, hey,
25:06
Speaker 1: we want to catch some of that behavioral alpha as well.
25:10
Speaker 1: Do you see any are there any competitors and do
25:13
Speaker 1: you see any competitors coming in eventually? Yeah, we see
25:16
Speaker 1: a lot of folks talk about behavioral finance. It's a
25:19
Speaker 1: fun topic. People like to use it to justify what
25:22
Speaker 1: they're doing. But honestly, we have never seen really anybody
25:26
Speaker 1: who's doing exactly what we do. And there's a few
25:29
Speaker 1: reasons for that. I think one is doing what we
25:34
Speaker 1: do requires not doing a lot of the traditional things
25:38
Speaker 1: that cause bias that makes people uncomfortable. We talked about
25:41
Speaker 1: how people like to do things that leave them comfortable.
25:44
Speaker 1: Omitting some of the steps that people typically do will
25:48
Speaker 1: make people uncomfortable, and really focusing are the way we
25:51
Speaker 1: do just on the mistakes often can make other folks
25:54
Speaker 1: uncomfortable and so they don't do it for that reason.
25:56
Speaker 1: And as you know, as we talked about in the beginning,
25:59
Speaker 1: these biases are hardwired. So it's not that the investor
26:01
Speaker 1: mistakes are going to go away, but you really need
26:05
Speaker 1: to have a process that's laser focused on finding them
26:08
Speaker 1: to work in the long term. So we we discussed earlier.
26:11
Speaker 1: Um Fama and Failure play golf together their buddies. Um,
26:17
Speaker 1: there's clearly inefficiencies in the market over the short term.
26:22
Speaker 1: Our markets mostly kind of eventually sort of efficient. Like,
26:27
Speaker 1: how do you think about markets over longer periods of time? Yeah,
26:32
Speaker 1: you know, Fisher Black had a rule that he said
26:35
Speaker 1: markets are efficient probably do a factor of two that
26:38
Speaker 1: prices are within plus or minus two times the correct price.
26:42
Speaker 1: Now you tell me, it's actually pretty reasonable in the
26:45
Speaker 1: scale of things to say that's reasonably efficient. Okay, they're
26:48
Speaker 1: not ten times what they should be. On the other hand,
26:51
Speaker 1: that leads a lot of room for is a giant swing. Yeah,
26:54
Speaker 1: that's a big swing. So I think it depends on
26:57
Speaker 1: how you think about in defining what would efficiency be
27:01
Speaker 1: the idea that all prices are perfect. I think it
27:04
Speaker 1: is about as ridiculous as thinking all people are perfect,
27:06
Speaker 1: But the idea that they're pretty good it's about as
27:10
Speaker 1: reasonable as thinking that most people are pretty good. But
27:13
Speaker 1: there's a lot of rooms still to find improvements that
27:16
Speaker 1: that we look out for. So if I had to
27:19
Speaker 1: define the era following the financial crisis, I think most
27:23
Speaker 1: people would look at it as the era of indexing
27:26
Speaker 1: and simultaneously the era of e t f s. The
27:29
Speaker 1: question that comes up over and over again is what
27:32
Speaker 1: does indexing due to price discovery? How does that affect
27:36
Speaker 1: the ability to identify miss pricing. Yeah, so I think
27:40
Speaker 1: that e t f s and indexing have a variety
27:44
Speaker 1: of impacts. One impact is that there's a bunch of
27:48
Speaker 1: people who used to be analyzing individual securities that aren't anymore.
27:52
Speaker 1: That's gonna make individual prices, as you can imagine, a
27:55
Speaker 1: little bit less efficient. On some level. That makes our
27:58
Speaker 1: job as an active man, you're a little bit easier
28:01
Speaker 1: because you've taken some of the people who used to
28:03
Speaker 1: be analyzing things out of the out of the game.
28:06
Speaker 1: At the same time, I think there are increasingly more
28:10
Speaker 1: swings that happen because people are moving into a utility
28:14
Speaker 1: z et F, and now they're moving into a financials
28:16
Speaker 1: et F, and now they're moving into a smart bay
28:19
Speaker 1: to e t F. And there are a lot of
28:20
Speaker 1: movements that are happening more at the macro level in
28:23
Speaker 1: terms of individual E t F decision making. And you know,
28:29
Speaker 1: the funny thing is, I mean, I've heard one phrase
28:31
Speaker 1: is a sort of an extreme phrase, that that indexing
28:35
Speaker 1: is communist in the sense of you've trusted everybody else
28:39
Speaker 1: to set the price. You really do have to have
28:40
Speaker 1: confidence that the market is reasonably efficient, that the price
28:43
Speaker 1: that you're buying things is right, And that's not a
28:46
Speaker 1: bad approximation. But I think I do think you can
28:48
Speaker 1: do a little bit better. I'm I'm biased, of course,
28:50
Speaker 1: because I'm an active manager. I'm pulling this from memory.
28:53
Speaker 1: I believe it was Alliance Bernstein called indexing Marxist, but
28:58
Speaker 1: I'm not positive that was my search piece. Um, but
29:01
Speaker 1: but the same the same issue applies. So here's the
29:04
Speaker 1: counter argument about indexing, and it's a behavioral argument. Uh,
29:09
Speaker 1: humans are irrational. We're not especially good at stock picking,
29:13
Speaker 1: we're not especially disciplined at staying on even if we
29:17
Speaker 1: come up with a quantitative method, we have a tendency
29:20
Speaker 1: to get caught by narratives and stories. You know, if
29:25
Speaker 1: I just index and forget about it for forty years,
29:27
Speaker 1: I'm better off than getting in my own way. What's
29:30
Speaker 1: the counter to that? From a behavioral perspective, I think
29:33
Speaker 1: you're right that people get in their own way all
29:36
Speaker 1: the time. You know, Dick Taylor's got a phrase. Instead
29:40
Speaker 1: of watching CNBC, you should be watching ESPN. The idea
29:44
Speaker 1: being that tracking how you're doing every day is going
29:48
Speaker 1: to cause tremendous unhappiness and it's gonna lead to more biases. Actually,
29:53
Speaker 1: we worked with separate note. We worked with one of
29:55
Speaker 1: our academic advisors, Professor Joey Engelberg, who's that U see
30:00
Speaker 1: you c s D. And he's done research that when
30:05
Speaker 1: the market goes down there's more admittances for heart attacks
30:09
Speaker 1: to hospitals around the country. Not surprised it really, it
30:12
Speaker 1: really makes people unhappy. So the set it and forget
30:15
Speaker 1: it I think actually is right. At the individual investor level,
30:18
Speaker 1: people should set it and forget it. I think there's
30:20
Speaker 1: a role for picking the right active manager as part
30:24
Speaker 1: of your set it and forget it strategy, But it's
30:26
Speaker 1: certainly true that trying to make those individual timing decisions,
30:30
Speaker 1: you're going to be very subject to biases. The The
30:32
Speaker 1: other um favorite example, and I'm trying to remember who
30:36
Speaker 1: brought this up recently, is imagine if you've got your
30:39
Speaker 1: home price quoted every single day, and it would make
30:43
Speaker 1: people crazy. You wouldn't you wouldn't be able to deal
30:45
Speaker 1: with it. You get a price when either you put
30:48
Speaker 1: up your house for sale or one of your neighbor's
30:50
Speaker 1: house cells, and even then we redid our kitchen, they didn't, etcetera.
30:54
Speaker 1: So what what does the daily price action tell us
30:58
Speaker 1: about investor psychology? Yeah, you know, I'm sure you're aware
31:04
Speaker 1: that no matter what happens in the market, people are
31:08
Speaker 1: always on the news spinning here's why it did what
31:11
Speaker 1: it did. But the reality is, I gotta tell you,
31:14
Speaker 1: as as an academic, we see a lot of movements
31:17
Speaker 1: that we don't really know why it moved. Here's here's
31:19
Speaker 1: a different way, more technical way of phrasing it. Uh.
31:22
Speaker 1: The academic perspective, more broadly is that most of the
31:25
Speaker 1: price movements that happened in the market are changes in
31:29
Speaker 1: the required return, not changes in cash flows. What that
31:33
Speaker 1: means is it's not that people have a new, updated
31:36
Speaker 1: vision generally about how well the core business is going
31:41
Speaker 1: to perform. Rather, they've changed their mind and said, oh,
31:45
Speaker 1: I'll accept a little bit lower return, and therefore the
31:47
Speaker 1: price went up, or oh, I'll accept a little bit
31:50
Speaker 1: higher return, so that I demand a little bit higher
31:52
Speaker 1: returns to the price went down. But for you and me,
31:55
Speaker 1: that's equal to the same thing as there's just noise.
31:57
Speaker 1: It just moved for kind of no reason, and as
32:00
Speaker 1: long as you brought up noise, I understand. Professor Khneman
32:03
Speaker 1: is working on a new book on noise. I'm absolutely
32:06
Speaker 1: fascinated by that. Why is it that we're so compelled
32:10
Speaker 1: to take what appears to be to the educated eye
32:15
Speaker 1: random noise and impose a narrative storyline on that drunkards walk?
32:22
Speaker 1: That ability to very quickly find patterns is crucial to learning.
32:28
Speaker 1: Think about how quickly toddlers learn new words. Think about
32:32
Speaker 1: how quickly kids figure out what the rules of social
32:36
Speaker 1: interaction are. And they do it all by just watching
32:39
Speaker 1: a few times. Sometimes I'm sure you've seen toddlers might
32:42
Speaker 1: hear a word once and then they start being able
32:44
Speaker 1: to use it. Why because yeah, exactly, of course they
32:47
Speaker 1: figure that out. And why because we're experts at quickly
32:52
Speaker 1: identifying patterns, and that's of course useful from an evolutionary standpoint,
32:57
Speaker 1: but then it trips us up on things that truly
33:00
Speaker 1: are random. We start to see patterns that don't exist,
33:03
Speaker 1: and we interpret that in ways that then can cause bias.
33:07
Speaker 1: So a big part of the way you manage the
33:10
Speaker 1: portfolio is capitalizing on overreactions. What do we see more
33:15
Speaker 1: of overreactions to the upside based on green and enthusiasm,
33:20
Speaker 1: or overreactions to the downside based on risk aversion and panic.
33:25
Speaker 1: You see both. I think you see a little bit
33:28
Speaker 1: more overreactions to the down side. Now I say that,
33:32
Speaker 1: but I may be biased because we're focused on overreactions
33:35
Speaker 1: to the downside. That's when we buy. If there's a
33:37
Speaker 1: company that's overhyped, we're not going to buy it, and
33:41
Speaker 1: we do a little bit of long short investing, but
33:44
Speaker 1: for the most part, we're not going to pay attention
33:46
Speaker 1: to those super hype stocks. And so maybe that's why
33:48
Speaker 1: I'm giving a biased answer that it seems people more
33:51
Speaker 1: likely overreact to the downside because that's what we focus on.
33:53
Speaker 1: Can you stick around a little bit. I have a
33:55
Speaker 1: few more questions to ask you. We have been chatting
33:58
Speaker 1: with Dr rap Jovinazzo of Fuller and Thailor, where he
34:02
Speaker 1: manages the behavioral small cap equity portfolio. If you enjoy
34:07
Speaker 1: this conversation, be sure and check out our podcast extras,
34:10
Speaker 1: where we keep the tape rolling continue to discussing all
34:13
Speaker 1: things behavioral. You can find that at iTunes, overcast, Bloomberg
34:18
Speaker 1: dot com, wherever funer podcasts are sold. We love your comments,
34:22
Speaker 1: feedback and suggestions right to us at m IB podcast
34:26
Speaker 1: at Bloomberg dot net. You can check out my daily
34:29
Speaker 1: column on Bloomberg View dot com. Follow me on Twitter
34:32
Speaker 1: at rid Halts. I'm Barry rid Halts. You're listening to
34:36
Speaker 1: Masters in Business on Bloomberg Radio. Welcome to the podcast, Ray,
34:53
Speaker 1: Thank you so much for doing this. This is really
34:55
Speaker 1: a fascinating topic that I am, you know, have been
34:59
Speaker 1: enamored for or decades about and offline, we were talking
35:04
Speaker 1: about the problem with our cognitive issues is we evolved
35:11
Speaker 1: for very different purpose. It's it's I give a presentation
35:15
Speaker 1: where I use via Gra as an example. It's off label. Originally,
35:20
Speaker 1: Viagra was a hypertension and heart disease um products, And
35:26
Speaker 1: as they do when they do these studies, they ask
35:28
Speaker 1: the the subjects any side effects. Yeah, my wife has
35:32
Speaker 1: locked herself in the bathroom and she won't come out. Um. Oh,
35:36
Speaker 1: maybe we have a different use for this product. So um.
35:40
Speaker 1: The question that comes up time and again with all
35:43
Speaker 1: these biases and all these cognitive issues was the human
35:48
Speaker 1: mind or has the human mind evolved for very different
35:52
Speaker 1: purposes than we we are currently using them? Yeah? We
35:56
Speaker 1: were evolved in an environment where there were is not
36:00
Speaker 1: a news media that were not graphs and charts that
36:05
Speaker 1: we had to interpret, where there was no Excel, no
36:08
Speaker 1: financial statements. We were designed for very rapid decisions of
36:12
Speaker 1: you here rustling in the bushes, You better get out
36:14
Speaker 1: of the way quickly because it might be a linn Not.
36:17
Speaker 1: How do I plan a twenty year investment in a
36:20
Speaker 1: power plant? That's not what we're designed for. And so
36:24
Speaker 1: we end up applying our cognitive skill set to a
36:30
Speaker 1: bunch of issues that we really are not built for. Yeah,
36:35
Speaker 1: let me let me give you an example which I
36:37
Speaker 1: think will be illustrative. Maybe I'm biased because it was
36:41
Speaker 1: the research I did with Dr Khneman at Princeton. I
36:44
Speaker 1: began trying to do research on how do we come
36:47
Speaker 1: up with the shortlist from which we make a decision,
36:50
Speaker 1: because the research on decision making is all about choices,
36:55
Speaker 1: and in the process of trying to answer this question
36:58
Speaker 1: of how do we come up with the shortlist, realize
37:01
Speaker 1: the answer is we don't come up with a short list.
37:03
Speaker 1: In fact, we're sort of hardwired to instantly jump to
37:06
Speaker 1: the answer that what we're doing is something which in
37:10
Speaker 1: cognitive psychology is often called problem solving as opposed to choosing.
37:14
Speaker 1: But it's precisely because we want to instantly get to
37:16
Speaker 1: the final answer that we're very lousy at making choices
37:20
Speaker 1: when we have a range of choices that we need
37:22
Speaker 1: to think carefully about. You know, it's funny funny you
37:25
Speaker 1: say that. I um years ago on a trading desk,
37:29
Speaker 1: someone would bring an idea to me and very often
37:33
Speaker 1: that piece of junk. And I eventually learned that that
37:37
Speaker 1: reaction is, hey, maybe there's an overreaction on everybody's perspective,
37:42
Speaker 1: because when someone brings you I was a fan of Apple.
37:45
Speaker 1: When the iPod not iPhone iPod first came out, every
37:50
Speaker 1: person I showed that stock to same reaction a piece
37:53
Speaker 1: of junk company going out of business, the stock a
37:57
Speaker 1: six for one split ago on a two for one
37:59
Speaker 1: split of for that I want to say it was
38:01
Speaker 1: fifteen with thirteen in cash, and that reaction of junk.
38:07
Speaker 1: That's that immediate response. As opposed to Professor Koneman, we
38:12
Speaker 1: call its system to where you're actually thinking through. You know,
38:15
Speaker 1: here's a funny fact related to that mediate emotional reaction.
38:20
Speaker 1: Our ability to know whether we like someone operates far
38:25
Speaker 1: faster than our ability to remember any fact about them.
38:29
Speaker 1: We know whether we like that person before we can
38:31
Speaker 1: remember their name, because that is what, if you think
38:35
Speaker 1: about it, we're built to be able to make very
38:37
Speaker 1: rapid is that person a friend? Or do I need
38:39
Speaker 1: to run away decisions? But it can really trip us
38:42
Speaker 1: up when analyzing something abstract like a stock that we've
38:45
Speaker 1: got decades to invest in or not invest in. That's
38:49
Speaker 1: not a good system to be able to make us
38:51
Speaker 1: a decision in milliseconds, even though from a evolutionary standpoint
38:55
Speaker 1: was quite useful back when we were cavemen cave women.
38:59
Speaker 1: That that same here's an instantaneous reaction which has a
39:03
Speaker 1: purpose in in keeping you alive. Ps. The people who
39:06
Speaker 1: did not have that, that's that particular hard wire, well
39:10
Speaker 1: none of their progeny around think they got eaten by
39:13
Speaker 1: the right. They were literally people's lunch, all right, So
39:15
Speaker 1: I only have you for a limited amount of time. Uh,
39:18
Speaker 1: let's jump to some of our favorite questions that we
39:21
Speaker 1: ask all of our guests. What's the most important thing
39:25
Speaker 1: people don't know about you or your background? I think
39:29
Speaker 1: the important thing to me that maybe people don't know
39:34
Speaker 1: given the focus on behavioral finance that we have, is
39:37
Speaker 1: my father is a retired professor of accounting, so I'm
39:41
Speaker 1: actually one of those geeks who likes analyzing financial statements
39:44
Speaker 1: as well. It's not pure psychology. Sometimes people think it's
39:47
Speaker 1: all about psychology, but what we do is a combination
39:51
Speaker 1: of finance and psychology. And honestly, it's the finance that's
39:53
Speaker 1: more important than the psychology. But the psychological combination and
39:58
Speaker 1: addition sort of changes the flavor of everything, gives it
40:01
Speaker 1: a different dimension. Dimension around now is when I ask
40:04
Speaker 1: people who they're early mentors were. But we know at
40:08
Speaker 1: least two of your mentors, Danny Khneman and Richard Faylor.
40:12
Speaker 1: Any other mentors you want to share. That's those are
40:16
Speaker 1: two pretty good names to drop. They're pretty good. They're
40:18
Speaker 1: pretty good. My father was a mentor. Of course, I
40:21
Speaker 1: did a lot of consulting work work for him in
40:24
Speaker 1: his consulting business when I was in high school and college,
40:27
Speaker 1: and that was some useful training as well. So let's
40:30
Speaker 1: talk about investors who influenced your approach to put in
40:34
Speaker 1: capital at risk. Yeah, I've been obviously tremendously influenced by
40:40
Speaker 1: all of the research and behavioral finance. There are patterns
40:44
Speaker 1: to people's mistakes and therefore their patterns for investing that
40:47
Speaker 1: make a difference. Uh. And if you follow those patterns,
40:50
Speaker 1: you can earn higher returns. And uh, let's talk about books.
40:54
Speaker 1: This is everybody's favorite question. What are some of your
40:56
Speaker 1: favorite books, be they fiction, nonfiction, investing, add or not.
41:01
Speaker 1: That's a hard one. I've got a lot of favorite books. Um,
41:05
Speaker 1: I do think you know. I have to give a
41:06
Speaker 1: plug for Thinking Fast and Slow by Daniel Conoman. It's
41:11
Speaker 1: incredibly comprehensive and that can also read is a little
41:15
Speaker 1: bit slow and dense, but you really learn a tremendous
41:18
Speaker 1: amount from reading it. I learned a lot of that
41:21
Speaker 1: at the Feet of the Master. But I think for
41:23
Speaker 1: people who haven't had that lucky experience, it's it's a
41:26
Speaker 1: great book for learning. It's wonderful, and if you read
41:29
Speaker 1: the whole thing once sitting, it's dense. The first half
41:32
Speaker 1: of it really flies. Yeah, you know other other books
41:35
Speaker 1: that I have enjoyed. I'm a big science fiction and
41:38
Speaker 1: fantasy fan. Um. I don't mean to tell us some
41:41
Speaker 1: of your favorite you know. I've got a bunch of
41:43
Speaker 1: The King Killer Chronicles are one. I'm really hoping Patrick
41:47
Speaker 1: Rothlist will hurry up and write that third book. I
41:49
Speaker 1: don't know if you've read that. Yeah, I loved the
41:52
Speaker 1: books the Game of Thrones. Obviously that's quite popular now.
41:56
Speaker 1: I wish George R. R. Martin would go ahead and
41:59
Speaker 1: finish those book as well. Uh, those are something, you know.
42:03
Speaker 1: I like a lot of those, uh classics in the
42:06
Speaker 1: in that in that realm, if they're kind of fun.
42:09
Speaker 1: Any other science fiction authors float your boat? You know?
42:12
Speaker 1: I really like Werner Vinge. I don't know if you're
42:15
Speaker 1: familiar with him, the science fiction author. He's got a
42:18
Speaker 1: neat book called Rainbows End, which is trying to imagine
42:22
Speaker 1: sort of a near future where there's a tremendous use
42:25
Speaker 1: of artificial intelligence, and what does the economy look like?
42:28
Speaker 1: Which I think is pretty smart. It's got some other
42:30
Speaker 1: good books fire on the Deep that deals with artificial intelligence.
42:34
Speaker 1: I think it's kind of neat, quite interesting. That's a
42:37
Speaker 1: good list. Tell us what you're most excited about today,
42:40
Speaker 1: like these days? What what really do you find fascinating?
42:44
Speaker 1: You know, I never stopped being fascinated by investing and
42:49
Speaker 1: by behavioral finance. I know it seems odd, but that's
42:53
Speaker 1: part of what makes it so easy to do what
42:55
Speaker 1: I'm doing, is that there's always new wrinkles in the
43:00
Speaker 1: kinds of mistakes that people make. I also like to
43:03
Speaker 1: apply it to myself and say, what which of these
43:06
Speaker 1: mistakes am I making? And how can I try to
43:08
Speaker 1: correct that? So it's a perpetual passion. It's endlessly fascinating,
43:13
Speaker 1: there's no there's no doubt about that. Given that you
43:16
Speaker 1: work in portfolio management, what do you see as the
43:18
Speaker 1: next major shifts that are going to take place? Yeah? Well,
43:22
Speaker 1: one shift clearly is increasing use of passive investments, and
43:28
Speaker 1: how does that fit with active you know, I think
43:30
Speaker 1: it's no surprise there's some reasonable arguments in more efficient spaces,
43:36
Speaker 1: maybe in large cap to to consider passive. We think
43:39
Speaker 1: in inefficient spaces like small cap, really doesn't make sense
43:43
Speaker 1: to be passive. But but that continual trend is clearly
43:46
Speaker 1: going to be happening. I think a second trend that's
43:49
Speaker 1: going on is how do we incorporate all of the
43:52
Speaker 1: information and what's the role of artificial intelligence in trying
43:56
Speaker 1: to use be used for predicting returns. On that note,
44:00
Speaker 1: I have a little bit of a different perspective than
44:01
Speaker 1: a lot of people people. I think artificial intelligence is
44:04
Speaker 1: obviously incredibly powerful, but it needs a tremendous amount of feedback.
44:09
Speaker 1: If you think about it, if you want to build
44:10
Speaker 1: an AI system to do minute to minute or second
44:13
Speaker 1: to second trading, there's a tremendous amount of feedback that's
44:17
Speaker 1: going to be very powerful. If you're trying to predict
44:19
Speaker 1: five year returns, well over a twenty five year period,
44:22
Speaker 1: you only have five data points. There is no way
44:25
Speaker 1: to build an artificial intelligence just feed it the data
44:27
Speaker 1: and let it figure things out. That's not gonna work.
44:30
Speaker 1: But I'm sure that a lot a lot of people
44:32
Speaker 1: are gonna try. So tell us about a time you
44:35
Speaker 1: failed and what you learned from the experience. Well, I
44:38
Speaker 1: have what I think is a rather amusing investment failure story.
44:43
Speaker 1: Um So, during the original Internet bubble around late late nineties,
44:49
Speaker 1: you know, there was somebody put out a report that
44:52
Speaker 1: said Amazon dot Com is going to double in the
44:55
Speaker 1: next year. And I just said, this is ridiculous. No,
44:57
Speaker 1: you can't predict that a stock is going to double. This,
45:00
Speaker 1: this is crazy. Henry Blodget. That was a very famous
45:03
Speaker 1: piece he put out at Oppenheimer, I want to say,
45:07
Speaker 1: and then eventually moved over to Merrill Lynch and things
45:10
Speaker 1: won't arrive from them exactly. So I decided, you know
45:14
Speaker 1: what I'm gonna I'm gonna short this in my personal portfolio.
45:17
Speaker 1: At the time, I had about twenty five thousand dollars
45:21
Speaker 1: in savings, and I decided I was going to put
45:23
Speaker 1: on a five thousand dollar position on the theory of well,
45:26
Speaker 1: if this actually does double in a year and I
45:28
Speaker 1: lose five thousand dollars, I can handle that in the
45:31
Speaker 1: in the short term, and in the long term, I
45:33
Speaker 1: hope that I'm going to have a lot more savings.
45:35
Speaker 1: And you know, this won't this won't break my lifetime earnings.
45:38
Speaker 1: I'm not gonna be bankrupt forever. Well, first of all,
45:41
Speaker 1: I couldn't borrow the shares for three weeks because lots
45:45
Speaker 1: of people were trying to short the Internet stocks at
45:47
Speaker 1: that point in time, during which time the price went up.
45:51
Speaker 1: Brilliant me said, oh this is great, even better, even
45:55
Speaker 1: better time to short to short this stock. Finally I
45:59
Speaker 1: put on the position, and by the way, instead of
46:02
Speaker 1: doubling in one year, the price then went to double
46:05
Speaker 1: at that original call in another two weeks. It was
46:09
Speaker 1: like a month and a half or two months. It
46:10
Speaker 1: was crazy fast. At which point in time, now I
46:14
Speaker 1: have a position which is closer to ten thousand dollars short, uh,
46:18
Speaker 1: in which case, now if this doubles again and I
46:20
Speaker 1: lose ten thousand dollars, now I'm starting to have some problems. Unsurprisingly,
46:25
Speaker 1: I was working as a strategy consultant at that time,
46:27
Speaker 1: but I was spending a lot of time watching the
46:30
Speaker 1: daily that minute to minute price movements of Amazon dot Com.
46:34
Speaker 1: While I got to feel emotionally what it feels like
46:38
Speaker 1: to be losing money and worried about things. UH. At
46:41
Speaker 1: one point in time, I decided, as it keep kept
46:44
Speaker 1: going the wrong, wake up, going up, up, up, g
46:47
Speaker 1: I need to reduce this position. I did something complicated
46:50
Speaker 1: just because it had taken three weeks to borrow the shares,
46:53
Speaker 1: and that I shorted against the box, so I actually
46:55
Speaker 1: bought seven I bought seventy five shares while still being
46:59
Speaker 1: short hundred and fifty shares. This was the massive amounts
47:02
Speaker 1: of money. I was covered half of the covered half
47:04
Speaker 1: of the position, and I think this is really an
47:08
Speaker 1: impressive accomplishment. Frankly, because I was doing this sort of
47:13
Speaker 1: panicked decision during the day, I managed to close this position.
47:18
Speaker 1: I e by the seventy five shares at literally the
47:22
Speaker 1: high point of the day, and then as during the day,
47:26
Speaker 1: it then started to drop for the first time, and
47:28
Speaker 1: I thought, what am I doing? This is crazy. I'm
47:31
Speaker 1: not supposed to be. This was my whole thesis and
47:33
Speaker 1: now it's not working. So I undid a portion of
47:36
Speaker 1: that uh at and I managed to both buy at
47:41
Speaker 1: the high of the day and sell at the low
47:44
Speaker 1: of the day in the same day, which I think
47:46
Speaker 1: is a rare accomplishment. And I learned an important little fact.
47:49
Speaker 1: By the way, the published prices are only four round
47:52
Speaker 1: lots of hundred shares. And because I was trading at
47:56
Speaker 1: seventy five shares they're not quoted prices, and in fact
48:00
Speaker 1: managed to sell below the low of the days for
48:03
Speaker 1: my seventy five shares. You know, eventually I held onto
48:07
Speaker 1: the position for years, and eventually the position kind of
48:10
Speaker 1: came positive and consistent with every behavioral bias. Once I
48:13
Speaker 1: was able to declare victory of okay, I've no longer
48:16
Speaker 1: lost money, then I closed out the position. But longer term,
48:19
Speaker 1: look how well Amazon has done. I would the better
48:21
Speaker 1: trade was close out the position and then go long
48:25
Speaker 1: exactly if you term, If you look longer term, they've
48:29
Speaker 1: been one of the successful ones. There was a lot
48:31
Speaker 1: of insanity during during the financial crisis, but I, in
48:37
Speaker 1: my naivete at that time twenty plus years ago, picked
48:42
Speaker 1: one of the wrong things to bet against. So that
48:44
Speaker 1: bet was fundamentally wrong. But but I'll tell you I
48:48
Speaker 1: felt at the time I did have the wisdom to
48:50
Speaker 1: know I'm gonna learn something here. I've learned a lot.
48:54
Speaker 1: That is one of the formative investment experiences for me
48:57
Speaker 1: about knowing about proper position sizing, knowing when to take risks.
49:01
Speaker 1: And one of the lessons that I have too is
49:03
Speaker 1: when you see something that looks crazy. I'll tell you,
49:05
Speaker 1: I think bitcoin looks crazy. You're very, very wary of
49:09
Speaker 1: shorting it. I think the Canes quote was the market
49:12
Speaker 1: can remain irrational a lot longer than you can remain solvent,
49:15
Speaker 1: to say the to say the very least. Um, what
49:19
Speaker 1: do you do for fun? What do you do outside
49:21
Speaker 1: of the office, either to relax, or to stay physically fit,
49:24
Speaker 1: or or just for left Yeah. The two of the
49:27
Speaker 1: hobbies of mine is one I coach my kids in sports,
49:31
Speaker 1: which is one nice thing actually about being on the
49:35
Speaker 1: West Coast is because and being on market hours actually
49:39
Speaker 1: get out of work, start at some insane hour in
49:42
Speaker 1: the morning, but get out of work in time to
49:44
Speaker 1: actually go coach a baseball practice or soccer practice. Markets
49:47
Speaker 1: close at one o'clock. You can be home by the
49:49
Speaker 1: time they're back from so I'm not leaving at one o'clock,
49:51
Speaker 1: but but I can. I can make a five thirty
49:53
Speaker 1: baseball practice, so that's good. Uh. Second thing that I
49:56
Speaker 1: do is I love board games. I mean, I'm a
49:58
Speaker 1: super geek, so UH play a lot of board games.
50:02
Speaker 1: Actually make tried making some board games for my friends.
50:05
Speaker 1: I mean, I'm I'm I'm ultra geek. What what board
50:08
Speaker 1: games do you like? Uh, you know, I like a
50:11
Speaker 1: lot of the board games that have been quite popular. Um.
50:15
Speaker 1: I like a game, you know, Ticket to Ride is
50:17
Speaker 1: a simple game, but it's pretty good. Another game that
50:20
Speaker 1: we have played a bunch this is is something called
50:24
Speaker 1: Scithe that's a little bit of a war game. It's
50:26
Speaker 1: a little bit stranger. Um. Just to give you an idea,
50:30
Speaker 1: I owned about two hundred board games. So asking me
50:34
Speaker 1: to pick my favorite, that's that's kind of tough. See,
50:36
Speaker 1: that's the most important thing. People don't know about your background. Uh.
50:39
Speaker 1: And I assume you've seen the game Night the movie
50:44
Speaker 1: you know, it's funny, it's my wife and exactly. So
50:46
Speaker 1: my wife and I try to go to that on
50:49
Speaker 1: a date a couple of weeks ago after it's been out,
50:52
Speaker 1: I think a month, and every movie theater we went
50:55
Speaker 1: to had been sold out, so we up watching a
50:57
Speaker 1: different movie. So it's still on our list. The weird
51:00
Speaker 1: thing is these movies come and go so quickly these days,
51:03
Speaker 1: in theaters for two weeks and then and then they're going.
51:05
Speaker 1: But the good news is now we can watch any
51:06
Speaker 1: of them on demand. Right. You might want to think
51:09
Speaker 1: about shorting Netflix, which continues to go higher. That that
51:12
Speaker 1: would be the other side of ill be honest, I
51:15
Speaker 1: don't understand Netflix. They're hemorrhage in cash. They just did
51:18
Speaker 1: a billion and a half dollar financing to acquire more content. Yeah, exactly,
51:22
Speaker 1: I don't get them, but I have learned. Yeah, I'm
51:25
Speaker 1: not going to short that right. Yeah that sometimes you
51:28
Speaker 1: don't want to get in front of the runaway locomotive.
51:31
Speaker 1: Let let somebody else be the hero. And and our
51:34
Speaker 1: last two questions, what sort of career advice would you
51:37
Speaker 1: give a millennial or recent college graduate who came to
51:40
Speaker 1: you and said, I'm thinking about a career in asset management.
51:44
Speaker 1: So let me give you some general career advice that
51:47
Speaker 1: I think is very important for young people, and then
51:50
Speaker 1: I'll give some specific advice for asset management. My general
51:53
Speaker 1: advice to people is, you hear these phrases do what
51:57
Speaker 1: you love, and I think the correct phrasing is do
52:01
Speaker 1: something you love, the distinction being don't ask yourself what's
52:06
Speaker 1: the thing I love the most of all in life,
52:09
Speaker 1: because it's gonna be probably something that has no commercial value.
52:13
Speaker 1: I love playing video games the most in life, or
52:15
Speaker 1: for me, it's seriously considered. Because I love board games,
52:18
Speaker 1: maybe I should become a board game designer. And one
52:21
Speaker 1: of the best decisions I ever made was, I'll have
52:24
Speaker 1: that be a hobby. I can spend some time doing
52:26
Speaker 1: this for fun, but I should actually pick a job
52:29
Speaker 1: that I also love, but not try to figure out
52:32
Speaker 1: what's the thing that's absolute most fun. So that's that's
52:35
Speaker 1: my advice. To pick something you love and enjoy, but
52:38
Speaker 1: don't try to pick the thing you love the most, uh,
52:41
Speaker 1: unless you're lucky enough to have it be something that's
52:43
Speaker 1: highly lucrative. The second advice is specific to asset management,
52:47
Speaker 1: is I just think there's a tremendous power and maybe
52:51
Speaker 1: this is my bias from having come from uh some
52:55
Speaker 1: affirm that specializes in behavioral finance, there's tremendous power to understanding.
53:01
Speaker 1: Are you in a realm where you need to sort
53:04
Speaker 1: of figure out where other people are making mistakes, which
53:07
Speaker 1: I would say is true in markets like the stock market,
53:10
Speaker 1: or are you in a realm where what matters is
53:12
Speaker 1: are you making the mistake, in which case you've got
53:15
Speaker 1: to do the financial analysis. Well, So the distinction I
53:17
Speaker 1: would sort of make is I've never heard of behavioral
53:20
Speaker 1: private equity. If you're the only person bidding, if you're
53:23
Speaker 1: the only person bidding on a company, you just got
53:25
Speaker 1: to do the analysis right. You want to focus on
53:28
Speaker 1: financial knowledge. If you're competing with lots and lots of
53:32
Speaker 1: other folks, then I think being an expert on what
53:35
Speaker 1: are the mistakes other people are gonna make that's going
53:37
Speaker 1: to be more important. So it's good to go which
53:39
Speaker 1: area you're trying to focus on and get an expertise
53:42
Speaker 1: that matches that area. And a final question, tell us
53:45
Speaker 1: something you know about investing today that you wish you
53:48
Speaker 1: knew twenty years ago. Well, I already told you that
53:52
Speaker 1: story I wish I knew, don't know. It's it's be
53:58
Speaker 1: aware of betting against extreme hype because it can go
54:04
Speaker 1: It can go the wrong way much longer than you
54:06
Speaker 1: would expect. We have been speaking with Dr Raife Jovinazzo
54:12
Speaker 1: of Fuller and Thailor. If you enjoy this conversation, be
54:15
Speaker 1: sure and look up an Inch or down an Inch
54:17
Speaker 1: on Apple iTunes when you can see any of the
54:20
Speaker 1: other two hundred such conversations we've had previously. We love
54:25
Speaker 1: your comments, feedback and suggestions right to us at m
54:29
Speaker 1: IB podcast at Bloomberg dot Net. I would be remiss
54:33
Speaker 1: if I did not thank our crack staff who helps
54:35
Speaker 1: put together these conversations each week. Taylor Riggs is our producer,
54:40
Speaker 1: Booker m Medina Parwanner is our audio engineer. Slash producer
54:45
Speaker 1: Michael Batnick is our head of research. I'm Barry Ritolts.
54:49
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