Speaker 1: Look ahead, imagine more. Gain insight for your industry with
Speaker 1: forward thinking advice from the professionals at Cone Resnick. Is
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Speaker 1: Cone Resnick dot com Slash Breakthrough. This is Master's in
Speaker 1: Business with Barry Ridholts on Bloomberg Radio. This week on
Speaker 1: Masters in Business, we have a very special guest. His
Speaker 1: name is Jeff de Graff and he is known as
Speaker 1: a technicians technician. He has a storied career, most notably
Speaker 1: his time as the chief technician at Lehman Brothers, where
Speaker 1: he famously resigned pretty much the day of Lehman's all
Speaker 1: time high. Jeff is now the founder and presidents and
Speaker 1: chief technical strategist of Renaissance Macro, better known as ren Mack,
Speaker 1: which is really an interesting shop that come binds both
Speaker 1: macro analysis and technical analysis. In fact, one of the
Speaker 1: things that makes Jeff so unique is the fact that
Speaker 1: he has both a c f A and a CMT,
Speaker 1: which means that he is very schooled in both fundamental
Speaker 1: and technical analysis of of equities, and I think you'll
Speaker 1: find his approach to be somewhat unique. The way ren
Speaker 1: Mack was built to create its own unique database is
Speaker 1: something that not a lot of companies can can lay
Speaker 1: claim to UH, and it's part of the reason that
Speaker 1: for the past decade or so he's been named one
Speaker 1: of the top and and in fact has been ranked
Speaker 1: number one by Institutional Investor for the space he covers. So,
Speaker 1: without any further ado, here is my conversation with Jeff
Speaker 1: de Graff this Masters in Business with Barry Ridholts on
Speaker 1: Bloomberg Radio. My special guest this week is Jeff Degraff.
Speaker 1: He is the chairman and head technical analyst at Renaissance Macro.
Speaker 1: He has quite the storied background. Started out at Merrill Lynch,
Speaker 1: was at Lehman Brothers for a number of years, where
Speaker 1: he was not only chief technician but also on the
Speaker 1: firm's investment policy committee as a managing director. Moved to
Speaker 1: I s I in two thousand and seven before launching
Speaker 1: his own firm in two thousand and eleven. UH. He
Speaker 1: is both a c f A and a CMT charterholder,
Speaker 1: a member of the New York Society of Securities Analysts
Speaker 1: and the m T A UH. He has been number
Speaker 1: one ranked in Institutional Investor magazine for the last twelve years.
Speaker 1: Ranked his number one technol analysts for the last eleven years.
Speaker 1: And we know he's a great technician because he resigned
Speaker 1: Lehman Brothers literally the day of the stocks all time high.
Speaker 1: Jeff de Ra, Welcome to Bloomberg. Thank you for having me.
Speaker 1: So I've been following your work for a number of years.
Speaker 1: I have a lot of friends who are technicians, who
Speaker 1: who have nothing but good things to say about you.
Speaker 1: So let's jump right in to your background and talk
Speaker 1: a little bit about what makes what you do a
Speaker 1: little different than the average technicians. You describe yourself as
Speaker 1: a macro analyst. What does that mean? Well, we um,
Speaker 1: you know, we we really pride ourselves on looking at
Speaker 1: the big picture and within that what I mean is
Speaker 1: currencies and and bond markets and commodity markets and then
Speaker 1: trying to put all the pieces together. I mean, I
Speaker 1: think the world's always appolosible. That's why I love this business.
Speaker 1: It's a it's a chess match, you know, and it's
Speaker 1: never different. It's never the same thing the same right,
Speaker 1: and so it's really it's it's you know, it's it's
Speaker 1: upon us. Um. You know. This weekend, great example, I
Speaker 1: go through about a thousand charts on the weekend, right,
Speaker 1: and I put a pile of charts, UM in the
Speaker 1: I need to figure this out pile, right, And there's
Speaker 1: usually you know, five to ten Why do Chinese steel
Speaker 1: stocks look good while the rest of the world doesn't, right,
Speaker 1: And so you know, and then we we then start
Speaker 1: to backtrack and figure out what's going on. So I think,
Speaker 1: you know what what we do that's different is we
Speaker 1: believe in fundamentals, but we start with the charts, and
Speaker 1: I think that's the that's the difference. So that raises
Speaker 1: an interesting question. You're both a c f A, which
Speaker 1: stands for Chartered Financial Analysts, essentially the key to looking
Speaker 1: at stocks on a fundamental basis, officially a c f
Speaker 1: A charter holder which means you've gone per distance right
Speaker 1: three tests, and a CMT Chartered Market technician. So that's
Speaker 1: relatively unusual, having both fundamental abilities and technicals. What what
Speaker 1: motivated you to go for both accreditation? Well, my my
Speaker 1: my background is formal education is in finance, so obviously
Speaker 1: that's more fundamental than technical. And and like everybody who
Speaker 1: comes through any business school, it was you know, relatively
Speaker 1: pooh pooed, uh, the art of technical analysis, UM, and
Speaker 1: so I bought into that as I you know, was
Speaker 1: searching for grades more than anything else. And UM, you know,
Speaker 1: once I um got into the business, uh, it just
Speaker 1: found um that the technicians who I appreciated, Bob Farrell,
Speaker 1: who I grew up under, Steve Schaubin, who was my
Speaker 1: mentor at at Lehman Brothers, and just a fantastic individual
Speaker 1: and great technician. Um, I just I found that there
Speaker 1: was something to what they were saying. In fact, it
Speaker 1: was usually more prescient than what you're seeing out of
Speaker 1: the out of the fundamental side. So I picked up
Speaker 1: the Edwards and McGee book. I read it. Um, it
Speaker 1: was interesting. I didn't you know, I didn't buy into
Speaker 1: it wholeheartedly, but certainly there were you know, parts of
Speaker 1: it that I appreciated and could see the light with. UM.
Speaker 1: I thought the the books, the Wiser books UM or
Speaker 1: the I think Schweizer, Swigger, UM, the Right Market Wizard books.
Speaker 1: So I thought those were fantastic. And what that did
Speaker 1: for me really solidified it was UM and I've always
Speaker 1: been this type of person. It was about probability, right,
Speaker 1: and the best way for me to manage risk and
Speaker 1: thinking about it, whether it's at the poker table, the
Speaker 1: blackjack table, or in the markets was through technical analysis,
Speaker 1: and that just really hit me over the head. As
Speaker 1: as to the type of discipline essentially counting cards in
Speaker 1: the market, um is the last You start with the
Speaker 1: evidence in the data, you lay out what's most likely,
Speaker 1: least likely in everything in between, and that colors how
Speaker 1: you see the markets. Yeah. Look, I I described a
Speaker 1: little differently the difference between the pot odds and the
Speaker 1: odds in my hand. Right, there's a certain probability of
Speaker 1: pulling a card to complete an inside flush or an
Speaker 1: inside straight. Pardon me, Um, if the opportunity to stay
Speaker 1: in the pot is low enough and the the reward
Speaker 1: is high enough. Absolutely those even though it might be
Speaker 1: a very slim chance of pulling that straight, the chance
Speaker 1: to stay in makes an awful lot of sense. And
Speaker 1: that's how we think about You know, I took the
Speaker 1: m T A course with Ralph Acampora, and one of
Speaker 1: the lines that have stayed with me all these years
Speaker 1: has been fundamentals tell you what to buy, Technicals tell
Speaker 1: you when to buy. There's there's some truth to that.
Speaker 1: I would I would add to that though, too. Um.
Speaker 1: In fact, you know, it's just talking to somebody about this.
Speaker 1: With gold, UM, oftentimes the technicals will tell you, um
Speaker 1: what to buy, and maybe you don't know the fundamental story, right.
Speaker 1: I mean, if you think about when Apple first broke
Speaker 1: out of this huge base formation, nobody had a clue
Speaker 1: about the iPhone, and I mean it just was unbelievable,
Speaker 1: you know, sort of the the the the the ramp
Speaker 1: and the product and changing the world. Same thing with
Speaker 1: gold today. You know, the gold trends have changed, UM,
Speaker 1: and they changed in the first quarter for US. But
Speaker 1: you know, some me asked me, well, is it uh? Currencies?
Speaker 1: Is it uh? You know, negative interest rates. I don't
Speaker 1: know officially what the answer is, but the charts are
Speaker 1: telling you that something is out there that has a
Speaker 1: high probability of continuing. Let me ask you a simple question.
Speaker 1: What do most people misunderstand about technical analysis? I think,
Speaker 1: and this will you know, This will uh send shivers
Speaker 1: down to some people's spines. I think people believe that
Speaker 1: technical analysis can predict the future, and I really don't
Speaker 1: see it as that. I see technical analysis as identifying trends,
Speaker 1: identifying opportunities within those trends, and taking advantage of them.
Speaker 1: So to say it's predicting the future. I think is
Speaker 1: is a little a little misguided. I'm very Rihults. You're
Speaker 1: listening to Masters in Business on Bloomberg Radio. My special
Speaker 1: guest today is Jeff Degraff. He is the chairman and
Speaker 1: head technical analyst. Is that your your property title? CEO
Speaker 1: and chairman? And yeah. Renaissance macro a uh, pretty much
Speaker 1: a global research shop that supports institutions, edge funds, commutual funds,
Speaker 1: et cetera. Let's jump right in. Let's jump right in
Speaker 1: why technicals work. And I think it's it's pretty interesting
Speaker 1: for the lay person, for the average investor who might
Speaker 1: be listening to this or some student in an NBA
Speaker 1: course where they tell you this stuff doesn't work, Explain
Speaker 1: what is technical analysis and why does it work? Well?
Speaker 1: That there are definitely elements within technical analysis that I
Speaker 1: would even say probably don't work, and I want to
Speaker 1: be careful with some of those, and and and Elliott
Speaker 1: wave Fibonacci, some of the more fringe stuff, or just
Speaker 1: generally the patterns that some people there there are oscillations
Speaker 1: that people sort of believe must mean revert. And that's
Speaker 1: really you know, we've done a lot of work on that,
Speaker 1: and that doesn't prove to be true. There there are
Speaker 1: certain conditions that you can overlay to help create better
Speaker 1: probabilities or opportunities. But really when it comes down to
Speaker 1: for us is is technical analysis works because it's about
Speaker 1: trend analysis. And if you think about just the world
Speaker 1: in which we live, um, you know there are trends
Speaker 1: in place everywhere, right, I mean earnings are generally trending,
Speaker 1: um Uh, And so you know to expect that there's
Speaker 1: sort of this randomness and earnings there there isn't right,
Speaker 1: there generally is a trend. Now, there might be missed
Speaker 1: opportunities in those earnings trends here and there, but for
Speaker 1: the most part, uh, you know, a company's fundamental trajectory
Speaker 1: will be a trend, and we're capturing that through price.
Speaker 1: And the idea is that the markets are efficient and
Speaker 1: so what you know, what I know from a fundamental
Speaker 1: sense is probably already embedded in that price. And what
Speaker 1: we're doing is we're just simply measuring that price, taking
Speaker 1: that temperature and understanding or trying to understand whether or
Speaker 1: not the probabilities are for good continuation in that price
Speaker 1: or for a reversal in that price. So so the
Speaker 1: baseline assumption is that a trend in place, that momentum
Speaker 1: is going to continue until such time as something acts
Speaker 1: to stop it. The probabilities, overwhelmingly, whether it's academic research
Speaker 1: our own research, are that there's a persistence and trends
Speaker 1: in the market. It's called momentum in a lot of
Speaker 1: in a lot of academic studies. Um. And it drives
Speaker 1: people nuts because quote unquote shouldn't work, right, But the
Speaker 1: reality is is that it does and um, and that's
Speaker 1: what we exploit. Well, why shouldn't it work. Let's let's
Speaker 1: step back, because you're a big macro guy and you
Speaker 1: look at things from both the fundamental technical quant an
Speaker 1: economic perspective. Hey, every day people are earning money. That
Speaker 1: money gets shoveled into their four oh one case and elsewhere. Ultimately,
Speaker 1: there's only so many stocks in the universe that a
Speaker 1: fund manager with a given uh sector or topic or
Speaker 1: charge is going to buy. And so he's gonna go
Speaker 1: back and keep buying his favorite names over and over.
Speaker 1: I mean, that's it's a great point that the academics
Speaker 1: would say. Um, there's the efficient market hypothesis, which says
Speaker 1: that the um. You know, the the weak form, the
Speaker 1: strong form, that that information should already be discounted in
Speaker 1: the market price. The reality is, is it just it
Speaker 1: just isn't right. It's sort of kind of eventually more
Speaker 1: or less efficient, but it's not instantly efficient. You have
Speaker 1: there are too many people who have been consistently beating
Speaker 1: the markets. I know the academics like to just shrug
Speaker 1: it off and say outlawyers run off, but there are
Speaker 1: just too many Howard marks and too many Warren buffets,
Speaker 1: even though we're talking, you know, a few dozen, but
Speaker 1: they shouldn't exist, and they do, and and that that
Speaker 1: sort of begets that perfectly efficient thing. So what do
Speaker 1: you think is more important? Trends or mean reversion without
Speaker 1: question trend um If you look at mean reversion without
Speaker 1: the presence of trend in other words, trying to identify
Speaker 1: mean reversion without looking at first what the underlying trend
Speaker 1: is um, it is quickly a recipe and a system
Speaker 1: for losses um. The trends are historically um and this
Speaker 1: is a crossed assets it's not just equities, but the
Speaker 1: trends are historically prescient in giving you some foresight into
Speaker 1: the next move higher and that's that can be anything
Speaker 1: from intra day to to you know, long term, multi
Speaker 1: multi year. You know what we find the sweet spot um,
Speaker 1: And this isn't you know, I'm not I'm not breaking
Speaker 1: any rules here or breaking any new ground. But we
Speaker 1: find that from three months, uh, three months in other words,
Speaker 1: one month, two months, three months, uh, the returns of
Speaker 1: of equities over that period um tend to me mean reverting.
Speaker 1: In other words, if I have strong one month performance,
Speaker 1: the probability of me having another outperformance the next month
Speaker 1: is actually pretty low. UM. If I start getting into
Speaker 1: six month twelve month time frames and look out for
Speaker 1: the next six to twelve months, that probability actually shifts
Speaker 1: to being more momentum oriented. Right, So you want to
Speaker 1: be careful when people talk about, well, I'm not a
Speaker 1: trend foller, I'm not a momentum player. You know, you
Speaker 1: really have to define what your time frame is because
Speaker 1: if you're a swing trader, if you're a short term player,
Speaker 1: then you can be anti momentum. But I wouldn't suggest that,
Speaker 1: you know, you use twelve month or nine month momentum
Speaker 1: and try to fade that. Historically that doesn't work out
Speaker 1: for so long. How does valuation fit into into your analysis? Well,
Speaker 1: let's let's take valuation and lump it with fundamental analysis.
Speaker 1: And and we would look at UM fundamental analysis as
Speaker 1: UM one silo in what we call conditional factors. These
Speaker 1: are things that tend to support a bull phase or
Speaker 1: tend to support a bear phase. So you have these conditions,
Speaker 1: valuation being one, UM that certainly would be more supportive
Speaker 1: of a bull phase, presuming there's uh, there's good valuation.
Speaker 1: I would put things like credit, sentiment, seasonality. All these
Speaker 1: would be conditions that that support a bull or bear phase. UM.
Speaker 1: Think about it. If you will like the amount of
Speaker 1: gas in the tank, it sort of tells you how
Speaker 1: far you can go. UM. The other side of that
Speaker 1: is momentum and trend, and we think about that is
Speaker 1: how hot the spark is in the engine. Each one
Speaker 1: of these independently is useless, right, But it's the combination
Speaker 1: of both that's important. So if I've got strong conditions,
Speaker 1: if I've got a lot of barishness, I've got good valuation,
Speaker 1: I've got seasonality, credit conditions are good, and I've got
Speaker 1: that hot spark, I've got momentum, I've got trend. That's
Speaker 1: a great combination. So for us, that's about position sizing, right,
Speaker 1: that's a bigger call. That's something that we're more comfortable in,
Speaker 1: will make a bigger bet with. If I've got the
Speaker 1: market today, if I've got a hot spark, in other words,
Speaker 1: we've got good trend, we've got good momentum, but the
Speaker 1: way that we see the fuel in the tank is
Speaker 1: being maybe a quarter full. I'll still play, but I
Speaker 1: have to understand that the probabilities of this being an
Speaker 1: O nine type of trend change or an OH three
Speaker 1: type of trend change really are are are low. How
Speaker 1: does sector work figure into your macro approach? Do you
Speaker 1: look at specific market sectors technology, healthcare, energy? Absolutely? We
Speaker 1: think you know, we're known for market calls. I mean,
Speaker 1: that's sort of what people want to hear. But the
Speaker 1: reality is the way that we really make money air
Speaker 1: through sectors. And uh. We we look at sector relative performance,
Speaker 1: we global relative performance. So we bring it all together
Speaker 1: and find that there's a huge uh correlation between between
Speaker 1: regional markets and the sectors um and so we'll we'll
Speaker 1: use all that to identify where the best and where
Speaker 1: the worst sectors are, and we quantify the process. We
Speaker 1: have ways in which we've quantified, so it's not Jeff
Speaker 1: de graph We can got, you know, in a bad
Speaker 1: mood someday and saying everything looks terrible. Um, we haven't quantified,
Speaker 1: so we can back test it, and we can give
Speaker 1: people the confidence and assuredness that hey, if you follow
Speaker 1: this system, here's what you're looking at in terms of probabilities.
Speaker 1: I'm Barry Rihults. You're listening to Masters in Business on
Speaker 1: Bloomberg Radio. My special guests this week is Jeff DeGraf.
Speaker 1: He is a technician extraordinaire and and I jokingly started
Speaker 1: the show by saying he resigned Lehman Brothers pretty much
Speaker 1: to the day of it's all time high. That's how
Speaker 1: we know he's a really good technician. But that actually
Speaker 1: is a true anecdote. You did move to I s
Speaker 1: I pretty much early two oh seven thousand seven, when
Speaker 1: February oh seven was my resignation, and that's pretty much
Speaker 1: the top sick and it was the it was my
Speaker 1: origination letter was the day after the high in the
Speaker 1: stock price. So that's lucky, not good, But that is
Speaker 1: a true story. I love that story that I've said
Speaker 1: that to people and They're like, no, that can't be him,
Speaker 1: Like no, no, he's a really good technician. He saw
Speaker 1: that that trend break and he said that sad, I'm
Speaker 1: out of here. Um. But it's kind of interesting because
Speaker 1: you left for I s A. You were there for
Speaker 1: a couple of years. Ed him and another guy who
Speaker 1: thirty plush years number one ranked. We found him on
Speaker 1: the show. He's great. But at a time when when
Speaker 1: commission dollars are plumbering, when research budgets are really being constrained,
Speaker 1: you decide to launch a new research farm, right, what
Speaker 1: was the thinking like making that leap? Well, you know, look,
Speaker 1: the research budgets are contracting, but when you're when you're
Speaker 1: bloated and have you know, too much capacity, that's a
Speaker 1: bigger problem. When you're starting with eight people, which we
Speaker 1: did uh and are now up to um. You know,
Speaker 1: that's a that's a different that's a different game. And
Speaker 1: so you know, focusing on one of the keys to
Speaker 1: starting ren MAC was, uh, we wanted to build a
Speaker 1: world class database and you know, you just have to
Speaker 1: do that yourself. You can't do it under another another
Speaker 1: entity or you're basically building it for somebody else. And
Speaker 1: so the idea was build a world class database, quantify
Speaker 1: approach this in a much different way to work into
Speaker 1: people's process so that they have another overlay look of
Speaker 1: the street, spend its time and I don't falls them
Speaker 1: for this on fundamental research and the nitty gritty the
Speaker 1: quote unquote knowing the company is better than anybody else.
Speaker 1: But the reality is is not enough time is spent
Speaker 1: in the process of just understanding what the macro environment is,
Speaker 1: what the trends are. And so from our standpoint, we
Speaker 1: want to be able to quantify that for people so
Speaker 1: that they didn't have to become technicians, but they could
Speaker 1: look at it and say, okay, I understand that the
Speaker 1: risks are high in technology, that the opportunity set is
Speaker 1: actually high and in adustrials and have some quantification around that.
Speaker 1: And that's really what we provide. So n MAC is
Speaker 1: creating a dimensional analysis that simply isn't available to from
Speaker 1: other researches. Is that what sets you guys apart from
Speaker 1: everyone else. Absolutely, I think that's that's that's a huge
Speaker 1: part of it. And and how does one combine economics,
Speaker 1: quant fundamentals and technicals in one package. Well, we we
Speaker 1: don't do the fundamental side per se UM. We have
Speaker 1: Neil Datta who does our our economic side, and that's Look,
Speaker 1: there's a lot of high frequency data in economics and
Speaker 1: and even more so when you think about the globe
Speaker 1: UH and those are important data points. So what we
Speaker 1: do is we use those data points UM, we test
Speaker 1: those data points. We look at them within the context
Speaker 1: of what's happening to trends to see if they're useful. Again,
Speaker 1: some of those conditional factors that I spoke about in
Speaker 1: the earlier segment UM and that's how we we we
Speaker 1: marry it together in terms of this UM conditional elements.
Speaker 1: One of the things that you're known for is changing
Speaker 1: the weight of certain indicators depending on whether or not
Speaker 1: we're in a bullish or bearish market. Few people managed
Speaker 1: to do this. Well, how do you go about approaching that?
Speaker 1: You have to quantify it. You can't do it by
Speaker 1: the seat of your pants. You have to have UM,
Speaker 1: a quantification of the discipline, and you have to test
Speaker 1: that over time. And we've done that. And so a
Speaker 1: big one for us is our trend model UM, where
Speaker 1: we have basically a bullish bearish trend UM. It can
Speaker 1: go neutral, but we don't really have a neutral state.
Speaker 1: We'd like to have either black or white. And what
Speaker 1: we find is that other indicators that if you looked
Speaker 1: at over the entire spectrum of bullish and bearish might
Speaker 1: not be worth a damn. But when you break it
Speaker 1: down between bearish and bullish, UM, some indicators work very
Speaker 1: very well in a bear state. Other indicators work very
Speaker 1: very well in a bull state, but they don't work
Speaker 1: well across those different states. So for us, the quantification
Speaker 1: trend is a big one. The quantification of trend and
Speaker 1: then understanding what conditions work within that trend are a
Speaker 1: huge part of what we do. So what do you
Speaker 1: do in a crisis? We saw the oh eight o
Speaker 1: nine crisis ramping up. Essentially all the correlations went to
Speaker 1: one and it seemed like you were either in bonds
Speaker 1: or equity like products and there was nothing in between.
Speaker 1: How do you analyze as those sort of circumstances. Well,
Speaker 1: we we have ways to measure sentiment, which obviously was
Speaker 1: a disaster. I mean people were apocalyptic as we like
Speaker 1: to call it at the time. UM, we have ways
Speaker 1: to measure the UM, the severity of the downtrend, the
Speaker 1: risk adjusted returns UM, and we look at those and
Speaker 1: when they're they're so bad, um believe it or not,
Speaker 1: our system flags it. So we have an understanding that
Speaker 1: there's probably some capitulation taking place. And then we look
Speaker 1: at the credit markets. Credit markets are a huge part
Speaker 1: of our input that I don't think a lot of
Speaker 1: people pay as much attention to as they should. And look,
Speaker 1: the credit markets made their low UH in November two
Speaker 1: thousand and eight, and we're healing for a good three
Speaker 1: months prior to the equity low. Right, So when we
Speaker 1: looked at that that combination of things going on, saying, boy,
Speaker 1: credits getting better, but the equity markets are turning in
Speaker 1: a new low. There some opportunity here. And while we
Speaker 1: were warming up to equities again, we needed that spark.
Speaker 1: We needed to see that that engine spark. And that's
Speaker 1: what we saw in the early part of March of
Speaker 1: that year with these big breath days in this thrust.
Speaker 1: That's the that's the spark that we needed to say, Hey,
Speaker 1: these conditions are in place for what should be um
Speaker 1: a pretty impressive rally. I'm Barry Ridholtz. You're listening to
Speaker 1: Masters in Business on Bloomberg Radio. My special guest today
Speaker 1: is Jeff DeGraf. He is the founder and CEO of
Speaker 1: and head to technician at Renaissance Macro Analysis. Am I
Speaker 1: pronouncing that right? We'll make it easy rend mac. Jeff
Speaker 1: has been number one ranked by Institutional Investor magazine for
Speaker 1: the past twelve years as both a technical and macro analyst,
Speaker 1: probably best known for his years as the chief technician
Speaker 1: at Lehman Brothers. Let's talk a little bit about the macro,
Speaker 1: which is something that has been fascinating. It drives a
Speaker 1: lot of new stories. It makes a great narrative. You know,
Speaker 1: in my office we call certain people macro tourists. The
Speaker 1: folks who dabble in macro. They have gotten killed over
Speaker 1: the past few years. What what is that about? Well,
Speaker 1: it's about opportunity and thinking that you know, you can
Speaker 1: you can use the news environment to make money, which
Speaker 1: is usually pretty difficult to the party. Yeah, getting back
Speaker 1: to the discounting mechanism, right, so, um, you know, I
Speaker 1: think that's one that's one area of of of trouble
Speaker 1: or or this problematic Uh, you know, look, the macro.
Speaker 1: The reason that we specialize in macro is because of
Speaker 1: the street pays attention to their industry. They pay attention
Speaker 1: to their individual stocks, and they pay attention to their models.
Speaker 1: They don't really incorporate what's going on in the globe
Speaker 1: and whether or not the central bank assets are expanding
Speaker 1: or contracting, or you know, negative rates and the potential
Speaker 1: impact of that. So what we're trying to do is
Speaker 1: really cut out that niche and give the opportunity to
Speaker 1: look for somebody who's got expertise and that who does
Speaker 1: this on a daily basis, so that they can incorporate
Speaker 1: that into their small little world which is really industry focused.
Speaker 1: So we've seen a number of hedge fund players the
Speaker 1: past few years really struggle. Warren Buffett just came out
Speaker 1: at the annual seen Berkshire shareholder meeting in response to
Speaker 1: a question said to people, Hey, it's a lot of
Speaker 1: underperformance and it's a lot of excess fees. Uh, he's
Speaker 1: not a fan. Why have hedge funds been having so
Speaker 1: much difficulty in the present environment. Well, I think it's
Speaker 1: been policy related. And if you look at the excess
Speaker 1: returns on a volatility adjusted basis for for the S
Speaker 1: and P right the pure index um, they've been one
Speaker 1: of the five best periods that we've had since the
Speaker 1: nineteen twenties. It's a generational rally. People afford it the
Speaker 1: whole way up two hundred plus percent over six years.
Speaker 1: That's a monster. You're also putting people into these index
Speaker 1: products where they're looking at these returns, right, and they're saying, again,
Speaker 1: why should I pay active management forget hedge funds, but
Speaker 1: just active management when I can buy an index product
Speaker 1: for fifteen basis points and called today and I'm actually
Speaker 1: outperforming most people. And that's fine, that happens, But that
Speaker 1: also happened at the end of right. That also happened
Speaker 1: at the end of two thousand and seven. And so
Speaker 1: when we look at our metrics of how much fuels
Speaker 1: in the tank, this actually isn't the point where you
Speaker 1: want to start endorsing indexes. This is the point where
Speaker 1: you want to start endorsing active management hedge funds to
Speaker 1: look for an opportunity set um that will produce something
Speaker 1: that's better than what we think is is the the
Speaker 1: excess returns on a volatility adjusted basis going forward. So,
Speaker 1: so you mentioned some of the signals that were coming
Speaker 1: from the credit market and elsewhere in oh eight oh nine,
Speaker 1: you know what did how did you analyze the financial crisis.
Speaker 1: What really stood out from that period that you're unique
Speaker 1: way of looking at markets UH was insightful. I think
Speaker 1: there are two things. The first was, if you remember
Speaker 1: the UH, the internal hedge fund of bear Sterns blew up,
Speaker 1: and we were seeing that summer of oh seventh exactly,
Speaker 1: we're seeing that stress in the credit markets and the
Speaker 1: swap markets, particularly ahead of time, and UM, you know,
Speaker 1: it just worked its way down from tens to five
Speaker 1: statoos and and then sort of went away and said, well,
Speaker 1: what that's weird, Like there's always some you know, something
Speaker 1: goes kaboom here and then two weeks later we you know,
Speaker 1: we yeah, right right, and then boom, you know, it
Speaker 1: happens UM. And then you have the continued deterioration UM
Speaker 1: in these in these financials on the way down. So
Speaker 1: you know, talking about big top formations and the things
Speaker 1: that you know, sort of traditional technical analysis looks at
Speaker 1: those were in place in a lot of these financials. UH.
Speaker 1: In the in the mid part of two thousand and
Speaker 1: seven and obviously extending into two thousand and eight, UM,
Speaker 1: you had what was considered at the time the whale
Speaker 1: of of bear Stern we rallied off of that into
Speaker 1: the summer of oh eight, and then just you know,
Speaker 1: with this lethargy started to roll over again, which was
Speaker 1: the moment that you know, not all is well and
Speaker 1: then there may be some other fish to come up
Speaker 1: to the surface here as well. I recall August oh eight,
Speaker 1: and you could just smell something was coming. It was.
Speaker 1: It was one of those things where, gee, this just
Speaker 1: I know that you're an evidence based guy. I like
Speaker 1: to think I'm an evidence based guy. But it was
Speaker 1: one of those moments over the past twenty years where
Speaker 1: you could say, see something wicked this way comes. You
Speaker 1: couldn't put a finger on it, but you knew it
Speaker 1: was comment. And remember intra bank lending rates were spiking,
Speaker 1: the library ois spread was spiking, the euro basis swaps,
Speaker 1: so there were a lot of things that just said
Speaker 1: the mechanism was having trouble, that there was there was
Speaker 1: distrust amongst counterparties. Uh. And that's actually a much different
Speaker 1: scenario than we have today. While the European banks don't
Speaker 1: look good to us, the internal mechanism of that that
Speaker 1: counterparty risk is actually in pretty good shape. You don't
Speaker 1: have the same and in the gears that you had
Speaker 1: in O eight oh nine. Now this just seems to
Speaker 1: be almost more I don't want to use the word systemic,
Speaker 1: but more sort of generational in terms of what's happening
Speaker 1: to banks that the you know, the banking business has
Speaker 1: just become a bad business. It's a secular change that
Speaker 1: some of its technology, some of it's the new generation
Speaker 1: coming up that is distrustful. But it doesn't seem to
Speaker 1: be the same set sector that it was ten years ago, right, right,
Speaker 1: And we actually think that that's one of the reasons
Speaker 1: why we we looked at the starting Rendmack. We think
Speaker 1: that there's still opportunity for good research. Um, you know,
Speaker 1: particularly if you're willing to invest in it. The big
Speaker 1: banks just don't have that much interest in doing that here,
Speaker 1: not willing to put money and effort into into the research.
Speaker 1: You would think that that's a potential cash cow for them,
Speaker 1: or has the industry changed so much that it no
Speaker 1: longer is well you know, Look, research was forever a
Speaker 1: byproduct of banking, right, and the settlement in early two
Speaker 1: thousand sort of drove a wedge between the official link
Speaker 1: between those two. So Ever, since then, research has always
Speaker 1: been considered a cost center. Right, So there's been this
Speaker 1: juniorization of research taking place where people are swapping out
Speaker 1: senior analysts for junior analysts just to have the coverage
Speaker 1: helps the bank, but they don't have to pay for it.
Speaker 1: You know, look, we we we still believe in good
Speaker 1: old fashioned research and think that there's a premium to
Speaker 1: be had for that. And you know, our business is
Speaker 1: proving that that's true. Had a conversation with someone who
Speaker 1: talked about how middle market and merchant banking has been
Speaker 1: abandoned by the large banks if they've moved upstream, and
Speaker 1: these guys are screaming for any sort of coverage uh,
Speaker 1: transactional bankers and and there's a dearth there. I wonder
Speaker 1: how much of an opportunity exists for either boutique or
Speaker 1: purpose specific research shops like your own that can help
Speaker 1: fill in the void. But we certainly hope. So so
Speaker 1: let's talk a little bit about I. I where you've
Speaker 1: been ranked twelve years running? Is that right? I think
Speaker 1: that's right. That's an incredible track record tool mass to
Speaker 1: what do you And for people who may not be
Speaker 1: familiar with institutional investor, people, UH vote and they actually
Speaker 1: vote based to some degree on their assets under management
Speaker 1: and the commissions they spend. And they specifically say this
Speaker 1: is our favorite economists. That what's been ed Hyman for
Speaker 1: thirty five years running, the joke being he's actually not
Speaker 1: an economist. Um, just play one on TV and you've
Speaker 1: been numbered one for twelve years running as a macro
Speaker 1: analysts and eleven years as a technolonalyst. Is that right?
Speaker 1: That that's quite a track record to what do you
Speaker 1: to blame or credit that? Yeah? I guess what we
Speaker 1: try to do is we try to be as intellectually
Speaker 1: honest as we possibly can. Um. We are very very
Speaker 1: committed to making people money. UM. That is I mean
Speaker 1: that is job one as we see it, UM. And uh,
Speaker 1: I think you know the other important part of it
Speaker 1: is we we try to quantify the process. We try
Speaker 1: to demystify the technical process. And so you know, if
Speaker 1: you don't have a lot of technical experience, UM, we
Speaker 1: don't try to use the jargon e words. We try
Speaker 1: to say, hey, here's you know, here are the probabilities
Speaker 1: of this taking place based on these these certain factors
Speaker 1: of which they are technical. And so I think a
Speaker 1: lot of that has to do with the quantification, the
Speaker 1: demystification of the of the process. So I went out
Speaker 1: on Twitter over the weekend and said, hey, I'm interviewing
Speaker 1: Jeff degraph. Any questions and a few interesting things popped
Speaker 1: up from from some technicians on Twitter. One of the
Speaker 1: ones I liked was, how do you, as an analyst
Speaker 1: put a new and intriguing lens on the macro review
Speaker 1: when so much of it is is will trod uh Land,
Speaker 1: So many people have have our covering macro. How do
Speaker 1: you keep it fresh and interesting and valuable. Yeah, well,
Speaker 1: we we rely on our database, and we rely on
Speaker 1: our computer programmers, and um, we rely on the uh
Speaker 1: quantification of the data. Um. I mean, I'll give you
Speaker 1: a great example. We you know, our single stock database
Speaker 1: goes back to the existence of the SMP, back to
Speaker 1: the early nineteen sixties. So when we go through and
Speaker 1: look out, hey, do do breakouts work? Do breakdowns work?
Speaker 1: How does this, you know, play itself out? We're not
Speaker 1: talking about the next or last ten years or fifteen years.
Speaker 1: We're really talking about, you know, over longer than my
Speaker 1: lifespan so far. Um, you know, the the beginning of
Speaker 1: the SMP some fifty five plus years and so, Um,
Speaker 1: you know, I think that's one of the things that
Speaker 1: that differentiates us and puts a different spin on things,
Speaker 1: is that when you get the work from us, you've
Speaker 1: got the totality of work, and you know, we'll lay
Speaker 1: it out and say, hey, this works or this doesn't work,
Speaker 1: or this works, but only in these conditions, and um,
Speaker 1: you know, not many people are doing that. We've been
Speaker 1: speaking with Jeff DeGraf of ren Mack. Uh. Jeff, where
Speaker 1: can people find your work if they want to read
Speaker 1: more about what you guys do? Our website ww dot
Speaker 1: ren mac dot com. If you enjoy this conversation, be
Speaker 1: sure and check out our podcast extras, where we keep
Speaker 1: the tape rolling and continue chatting about all things market related. Uh,
Speaker 1: be sure and check out all of our previous conversations.
Speaker 1: You can find them on Apple iTunes, SoundCloud and on
Speaker 1: Bloomberg dot com. Check out my daily column on Bloomberg
Speaker 1: View dot com or follow me on Twitter at rit Halts.
Speaker 1: I'm Barry Hults. You've been listening to Masters and Business
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Speaker 1: Welcome to the podcast portion of our conversation, Jeff, thank
Speaker 1: you so much for doing this. Now I get to
Speaker 1: take off my headphones. I normally have these little headphones
Speaker 1: that are very unobtrusive, but um, I wasn't in the
Speaker 1: office Friday. I forgot to bring them in, so I'm
Speaker 1: a little bit of a mess today. Um, really, thank
Speaker 1: you so much for doing this. I have a few
Speaker 1: people who are serious uh technicians. I think J. C.
Speaker 1: Perett's how do you speak at an m T A
Speaker 1: event might have been been here. He was like, dude,
Speaker 1: so exciting to listen to Jeff. I'm like, all right,
Speaker 1: give me a couple of questions. So some of those
Speaker 1: questions were his, Um, you studied finance in college. Did
Speaker 1: you know from day one you wanted to go right
Speaker 1: into uh, right onto Wall Street? Yeah? Yeah, it was.
Speaker 1: It was pretty easy. I like the I mean look,
Speaker 1: I was trying to get out of Michigan so at
Speaker 1: a kalamazoo kalamazoo. Um. But you know, I liked the
Speaker 1: intellectual challenge. I like the lifestyle. I remember the first interview.
Speaker 1: I was in Chicago looking at an opportunity and the
Speaker 1: first interview, Um, the guy said, Uh, you'll never meet
Speaker 1: an industry where there's the funniest and smartest people at
Speaker 1: the same time. That's interesting. I said, sign me up.
Speaker 1: You're right. So I enjoyed that. That that's really interesting.
Speaker 1: There are a number of hilarious people in this industry.
Speaker 1: Most people are not familiar with them. Um, but they're
Speaker 1: out there and they definitely have a uh, there's some
Speaker 1: sense of games. My my partner, uh, Josh Brown. People
Speaker 1: don't realize this guy is hilarious, and people simply have
Speaker 1: no idea how funny is although I think on Twitter
Speaker 1: people have finally, uh finally figured that out. So you
Speaker 1: go straight to Wall Street. You were Merrill Lynch in
Speaker 1: the early days, is that right? Yea early days, and
Speaker 1: then I moved over to Lehman Brothers under Steve Schaubin,
Speaker 1: who had been at Meryl. So I knew Steve from
Speaker 1: my Merril days. Uh started out doing international work at
Speaker 1: Lehman Brothers and then moved into the hot seat in
Speaker 1: in two thousand there as chief chief technician at Lehman.
Speaker 1: So what were the golden days of Lehman Brothers? Like, Oh,
Speaker 1: it was you know, I was too young to know better. Um, yeah,
Speaker 1: I mean the eight to two thousand was just unbelievable.
Speaker 1: It was it was. It was so much fun. It
Speaker 1: was so fun to come into the to the office.
Speaker 1: Lehman Brothers had a great culture. Um. So that was yeah, yeah, yeah,
Speaker 1: I mean it was just it was and it was
Speaker 1: the little train who thought they could right and so
Speaker 1: just people were you know, hungry, and uh, it was
Speaker 1: it was just it was fun. We were all climbing
Speaker 1: in the right direction. Um, little train. There were the
Speaker 1: fourth fourth largest investment bank. They dominated mortgage underwriting. They
Speaker 1: were a substantial force for a long time. But remember
Speaker 1: that wasn't a big deal until the mid offs, right,
Speaker 1: so nobody realized until a little there were there were
Speaker 1: early signs that there were issues there. Oh two oh
Speaker 1: three things just got talk about looking at at data.
Speaker 1: One of my favorite charts has always been UM meeting
Speaker 1: income to Meetian home price. And I was looking at
Speaker 1: this long before the collapse, and you could see you
Speaker 1: were three standard deviations away from the norm. So either
Speaker 1: everybody's going to get a raise or something bad is
Speaker 1: going to happen. It was pretty much one or the other. Um.
Speaker 1: Did you ever spend much time under Dick fold And
Speaker 1: and meet meet him, work with him or was he
Speaker 1: off in the corner office? I mean I meant him
Speaker 1: a few times and it wasn't the big place. There wasn't. Yeah,
Speaker 1: there wasn't daily interaction. Tell us about the research process there?
Speaker 1: How How was that was pretty much traditional Wall Street
Speaker 1: research at at Lehman, Yeah it was, but it was
Speaker 1: you know, they were good, hungry young analysts. Um my
Speaker 1: president now Steve hash who's president of of Ren mack Um,
Speaker 1: actually ran the research department there. Um, we invested in
Speaker 1: up in commerce. I mean we just believe in you know,
Speaker 1: good smart young thinkers. And uh is another one was
Speaker 1: was that Meryl Lordly and you brought him along as well? Absolutely,
Speaker 1: So that's you know, that's how we think about the world.
Speaker 1: Where where's the rest of your team from? Oh, it's
Speaker 1: all over the map. Uh Some I s I sales
Speaker 1: people a lot of people that have been just from
Speaker 1: different parts of the of the business. Um, yeah, all
Speaker 1: all different walks of life. So what's the plan for
Speaker 1: a relatively you know, you're five years old just about
Speaker 1: is that right? Relatively young, fast growing company. How do
Speaker 1: you see this playing at for someone who's not yet fifty?
Speaker 1: What do you want to do with this company? Uh? Look,
Speaker 1: I'm I'm a big believer in the research process and
Speaker 1: while others are sort of moving away from it, you know,
Speaker 1: call it straw hats in January. I think that there's
Speaker 1: opportunity there for the right people. It's not just plug
Speaker 1: and play and you know, hope for the best. I
Speaker 1: think you have to get the right people in there.
Speaker 1: But there's still I mean, we see it in the business.
Speaker 1: There's still a demand and for good, um, thoughtful analysts, right,
Speaker 1: not just people that do stock research, but people that
Speaker 1: think differently, do the hard work, roll up their sleeves,
Speaker 1: you know, understand the company. There's there's there's interest there. Now,
Speaker 1: what we're what we want to do and make sure
Speaker 1: that we do with this is that it ties into
Speaker 1: the macro play, right, So it's not just covering semiconductors,
Speaker 1: but the semiconductors from a broader standpoint, and how and
Speaker 1: what that means for the macro world. You know, there's
Speaker 1: there's a thesis kicking around that following the early two
Speaker 1: thousand analysts settlement with the New York State Attorney General.
Speaker 1: Part of the settlement was a mandate that large banks
Speaker 1: funds independent third party research, and you and that that
Speaker 1: mandate has now ended. So you had this huge boom
Speaker 1: throughout the aughts of independent research, some of which was
Speaker 1: pretty good, some of which was of dubious value, but hey,
Speaker 1: there was a mandate and we had money to spend,
Speaker 1: go spend it. That has run its course, and that
Speaker 1: seems to be at least in part behind some of
Speaker 1: the shakeout that's happened in the research space. But what's
Speaker 1: left are the companies that people are sending research dollars to,
Speaker 1: whether they have to or not. They're the companies they
Speaker 1: find value at and want to buy purchase their research
Speaker 1: U I s I. There's a run of them that
Speaker 1: have have been around for a while and are likely
Speaker 1: to continue being around. Which is a long winded way
Speaker 1: to get to the question of how do you see
Speaker 1: the rest of the shakeout in research playing out. I mean,
Speaker 1: it's a it's a great question. I think you're gonna
Speaker 1: end up with um with the traditional banks again moving
Speaker 1: towards that juniorization and meaning they'll they'll swap out a
Speaker 1: high paid senior analyst with a junior guy without a
Speaker 1: lot of experience but doesn't demand a big check, and
Speaker 1: so they still have coverage. But you know, it's not
Speaker 1: it's not. Uh. I'm trying to think of a classic
Speaker 1: example of an analyst who who was the axe on
Speaker 1: a particular stock or in a particular sector. But Rick
Speaker 1: Sherlan's on on Microsoft or Charlie Wolf on Apple. They're
Speaker 1: handful of guys who knew it better than anybody. That
Speaker 1: era seems to be coming to an end. Yeah, I
Speaker 1: think so for the big banks, but there's still that
Speaker 1: opportunity set for the independence right now, a number of
Speaker 1: firms forget the macro space that that that we focus on.
Speaker 1: But um, you've got it for media, You've got it
Speaker 1: for industrials, you you've had it for financials. So you know,
Speaker 1: even these silos, Um, Dana Telsey came out of Bear Sterns.
Speaker 1: She's tag right on housing, Dana is on retail. So
Speaker 1: people who have an expertise in the space that becomes
Speaker 1: their area. That's right, That's right, that's that's kind of
Speaker 1: that's kind of fascinating that that's we didn't really see
Speaker 1: that twenty or so years ago, or did we UM
Speaker 1: my letter writers and things. But I think there's there's
Speaker 1: a few things there. One is that the the execution business, right,
Speaker 1: having a broker dealing the execution business through technology has
Speaker 1: gotten much simpler. Right, So this whole best execution I
Speaker 1: mean Ren Mack, little old Renmac can provide UM the
Speaker 1: best execution because we we basically use UM. The other
Speaker 1: big banks al goes, right, so we we come in
Speaker 1: and and and and uh sort of you know, from
Speaker 1: a from a from a darker perspective from the outside,
Speaker 1: people don't know exactly who's trading what, but you know,
Speaker 1: we know from our desk, the you know. The The
Speaker 1: other part of that is the the technology has allowed
Speaker 1: distribution UM to be a lot cheaper than it was.
Speaker 1: I mean, I remember when I started UM. We would
Speaker 1: send faxes, you know, and it was priced per sheet,
Speaker 1: per per recipient, right, So I mean there was a
Speaker 1: there was a half a million dollars. I'm serious, there
Speaker 1: was a half a million dollar cost and distributing our
Speaker 1: research because we had to pay the long distance fee
Speaker 1: and the facts fees. And you know, once the proliferation
Speaker 1: of email came about, writing a program to just convert
Speaker 1: that to a PDF and sending it out was simple,
Speaker 1: so facts as you're really talking late eighties, early nineties.
Speaker 1: By the mid nineties email was starting to pick up
Speaker 1: a bit. It was but to have research done, you
Speaker 1: know in a way that um, you know we're sending
Speaker 1: big PDFs over That's exactly right, that's exactly right. That
Speaker 1: was a bandwidth issue which wasn't solved bill after global
Speaker 1: crossing in Metromedia, fiber collapsed and left all this dark
Speaker 1: fibers that are so expensive to build free and or
Speaker 1: at least cheap for everybody else to pick up on
Speaker 1: on their bones. Except supply will create demand. And well
Speaker 1: that's the story of every major technology boom is after
Speaker 1: the bus, you have all this in expensive infrastructure. So
Speaker 1: that leads to the obvious question, which you alluded to previously,
Speaker 1: how has tech anology change the way you do business? Well? Uh,
Speaker 1: doing business or doing analysis? I think there are two
Speaker 1: different things, right, Um, you know, look, business has done
Speaker 1: you know, in the same in the same way. I mean,
Speaker 1: obviously it's relationships and you're you know, you understand what
Speaker 1: the clients are looking for. And UM, I mean I
Speaker 1: don't think that that will ever go aware certainly shouldn't UM.
Speaker 1: In terms of the analysis, UM. You know, I think
Speaker 1: one of the problems that you end up with is UM.
Speaker 1: You know, you give people the opportunity to sort of
Speaker 1: do things, and they think they can do it right,
Speaker 1: and they don't have the background or the understanding, UM
Speaker 1: to fully take advantage of what some of the technology
Speaker 1: can do. UM. And so for instance, let me interrupt
Speaker 1: you there. So in the mid to late nineties and
Speaker 1: early two thousands, you could get all manner of charts
Speaker 1: for free everywhere online, right, and everyone fancied themselves a technician.
Speaker 1: Most were not. Right. So is that democratization by technology? UM?
Speaker 1: Is that a problem that people actually think they could
Speaker 1: do things when there's a handful of technicians who came
Speaker 1: out of that era who are really good and a
Speaker 1: number of people who you know, they they think they're technicians,
Speaker 1: but they're just you know, exhibiting confirmation biased I have this.
Speaker 1: Let me go find a chart that I own this,
Speaker 1: let me find something that that confirms my prior position.
Speaker 1: I think, I think, but I think that happens with
Speaker 1: almost anything that's out there, right, I mean, I think
Speaker 1: I can retile my bathroom. I can't retie my bathroom, right,
Speaker 1: I mean that's there are YouTube videos that will show
Speaker 1: you how to do it, but it's still not going
Speaker 1: to look as good as if I pay the guy
Speaker 1: to do it, right, And that's why you hire a problem,
Speaker 1: right exactly. So it's the you know, it's really the
Speaker 1: same thing in any in any business, and uh um,
Speaker 1: you know, we we find we find similar you know,
Speaker 1: similar situations. But you know what we're doing which is
Speaker 1: so unique is again we're quantifying that process. So instead
Speaker 1: of drawing a trend line or um, you know, saying
Speaker 1: it's overbater over sold, we contextualize that and we show
Speaker 1: you know, what that really means in terms of the
Speaker 1: history and whether or not it's valuable. And that's what
Speaker 1: you know, that's what the amateurs and frankly a lot
Speaker 1: of the pros don't even do. And so um, that's
Speaker 1: one thing that really sets us apart. So you're using technology,
Speaker 1: um in a very significant way. You've built this database.
Speaker 1: What did you use for sources to put that together?
Speaker 1: How long did it take to clean up that database
Speaker 1: to get it to do what you want? How many
Speaker 1: different components are you tracking in that? Tell us a
Speaker 1: little bit about the secret sauce um as much as
Speaker 1: you're willing to write keeping it secret um. Look, it's
Speaker 1: you know, we use great we use we use CRISP data,
Speaker 1: CRISP price data um. And we've got that again going back,
Speaker 1: you know, s and P ninety going back to the
Speaker 1: mid the mid nineteen twenties and for people don't understand
Speaker 1: Chris but comes out of the University of Chicago, if
Speaker 1: memory serves, and really a deep and fairly clean database,
Speaker 1: uh of of market information. I think it goes all
Speaker 1: the way back to the twenties. Something thinking of the
Speaker 1: SMP ninety back to the twenties, which is, whenever you
Speaker 1: see the SMP five hundred quoted beyond it's it's the predecessor,
Speaker 1: which was in the SNP five. Even the SMP five
Speaker 1: hundred was in the SMP fire two. Sometime in the latent,
Speaker 1: I'm trying to remember when they changed the waiting sector
Speaker 1: that all went away in the eighties. Sometimes ye so
Speaker 1: changes and and has certainly look at that, and we
Speaker 1: look at the various waitings over time. UM. We use
Speaker 1: option data UM for a big part of our sentiment work. UM.
Speaker 1: We incorporate fundamental data UM from various various sources UM.
Speaker 1: And then UM we also, which I think uniquely, we
Speaker 1: bring in economic data so that we can see what
Speaker 1: that looks like in relation to these other things that
Speaker 1: we're looking at. Technically four stocks, Right, So does p
Speaker 1: M I work cure does the UM you know, do
Speaker 1: the UH the H four data from the FED? Does
Speaker 1: that have any influence? And so UM always looking, always adding,
Speaker 1: always building, and uh CFTC data we use that as well. So,
Speaker 1: so let's talk about economic data. UM. What is actually
Speaker 1: going on in terms of I'm not looking for a
Speaker 1: forecast to the future historically, what is the correlation between
Speaker 1: changes in the overall economy, either for the better or
Speaker 1: wars and markets. I've always looked at markets leading economic data,
Speaker 1: although not by as much as some people imagine. Well
Speaker 1: that's true. I mean, look, economic data is certainly UM
Speaker 1: less noisy believe it or not, UM, but it also lags.
Speaker 1: I mean, there's a reason they are leading indicators coincidental
Speaker 1: indicators and lagging indicators right and meaning leading the cycle
Speaker 1: or lagging the cycle. And look, the reason that business
Speaker 1: is so hard. If you can just look at economic
Speaker 1: data and forecast the US in p correctly, it'd be easy.
Speaker 1: It just it doesn't happen. Everybody's going to be rich,
Speaker 1: right exactly. So you know what we look at is
Speaker 1: historically the market has sniffed things out. Now, it's gotten
Speaker 1: it wrong before. But as I like to say that,
Speaker 1: you know, the market will fib but it won't be
Speaker 1: a chronic liar, right, And so you know, it's a
Speaker 1: great line. You have to be careful of that. But
Speaker 1: the reality is that the market gets it right, and
Speaker 1: the market gets it right better than the p m
Speaker 1: I gets it right. It gets it right better than
Speaker 1: the employment data gets it right, etcetera. So that's why
Speaker 1: it's really important from our standpoint to you know, put
Speaker 1: your ear on the track, understand or try to understand
Speaker 1: you know what's coming down then the pipe. Um. But
Speaker 1: you know, from our advantage point, it's a very difficult
Speaker 1: and challenging environment trying to do that with just economic data.
Speaker 1: And that's probably why so many people, uh always go
Speaker 1: to the quote by Samuelson, which is, marketing indices have
Speaker 1: forecast nine of the past four recessions markets will swing wildly.
Speaker 1: They're noisy, but they're going to do a better job
Speaker 1: than the average person scratching their chin and saying, here's
Speaker 1: here's what this this month's non farm payer all means. Yeah.
Speaker 1: But and let's you know, let's take it to the
Speaker 1: next step to what do I really care about the
Speaker 1: GDP number? If I'm invested in the SMP, I'm not right,
Speaker 1: I'm not I'm not invested in I don't have a
Speaker 1: GDP swap, right. In other words, GDP up over three
Speaker 1: percent and I make money that has nothing to do
Speaker 1: with that. I want to know what's going to happen
Speaker 1: to the SMP, right, And so you know, maybe we're
Speaker 1: not in recession, but you still have a correction or
Speaker 1: bear market in the STP. That's important, right, And so
Speaker 1: from our standpoint, you know, the work on uh, getting
Speaker 1: the economy right. I get it from the perspective of
Speaker 1: the nation, and certainly I appreciate that. But from the
Speaker 1: perspective of the investor, what I'm really trying to do
Speaker 1: is get the SNP right. You know, and the what
Speaker 1: I can tell you is getting the economy right has
Speaker 1: very little to do with getting the S P right historically.
Speaker 1: That that is a theme that I've heard from guests
Speaker 1: on the show for the past couple of years is well,
Speaker 1: the economy is interesting and the market is interesting, and
Speaker 1: on occasion they seem to be insane, but most of
Speaker 1: the time one goes one way and the other is
Speaker 1: just off uh in its own path, and and trying
Speaker 1: to use the economy to forecast the market is just
Speaker 1: a fool's Errand it certainly seems that way. We want
Speaker 1: to know what's going on, there's no doubt about it,
Speaker 1: but to to draw the link between the economy and
Speaker 1: saying that that that's gonna mandate the S and P
Speaker 1: does X good luck. So before I go to my
Speaker 1: favorite questions, I asked all my guests one last Twitter question.
Speaker 1: Someone had asked, so, why not manage a fund? Why
Speaker 1: not run money or put together e t F Y
Speaker 1: be an analyst? So I do this question all the time.
Speaker 1: That's one of the reasons why we started run Back,
Speaker 1: to be honest with you. So we we have a
Speaker 1: small albeit small um. We have a rend Mack Capital Um,
Speaker 1: where we haven't actively raised money, we have a ongoing
Speaker 1: stress of you that's in that mostly partner money right now. Um,
Speaker 1: but that's that's definitely uh, you know stage Renmack two
Speaker 1: point oh, that's in that. In that zone, there are
Speaker 1: people who left big firms to launch their own research shop.
Speaker 1: Rich Bernstein probably most notable, who's now running you know,
Speaker 1: three or four billion dollars. There's there's definitely a path
Speaker 1: to that. And I love the idea of having that
Speaker 1: pile of money which generates revenue which then can be
Speaker 1: plowed right back into making the research faster, sexy, or
Speaker 1: more interesting. There's a lot of stuff you can do
Speaker 1: when you have that much a u M with a
Speaker 1: fee on it. It just lets you plout right back
Speaker 1: into the business. And we want to be careful. I mean,
Speaker 1: obviously we don't want to have conflicts there. But what
Speaker 1: we do is, you know, we eat our own cooking.
Speaker 1: And um, it's a quantitative process. We think about it
Speaker 1: very quantitatively. It's not you know, hey, I like that
Speaker 1: idea or that, it's it's what is the system spit out?
Speaker 1: How does that overlay with these things? And then here's
Speaker 1: how we're managing that portfolio. So the question that always
Speaker 1: used to come up on the old UM research desks
Speaker 1: was idea generation. Hey, what's what's the idea of generation?
Speaker 1: Machine looked like, you guys don't really do that. It's
Speaker 1: it's pretty much spitting out from that database. Well, it's
Speaker 1: idea generation is just not you know, it's just not
Speaker 1: a noodling over it every single day and saying, hey,
Speaker 1: you know, what are the what are this? What's this?
Speaker 1: And that um it's looking at it now. It's important though,
Speaker 1: is that you know, we we understand through our research
Speaker 1: that there are points where UM, certain things will perform
Speaker 1: better UM in certain environments. Right, So a great example, UM,
Speaker 1: you know, shorts right here in this environment are not
Speaker 1: performing well, and we actually track that on a daily
Speaker 1: basis to see, hey, if you were to to be
Speaker 1: a seller of a breakdown, what's the performance. I mean,
Speaker 1: they're just they're just getting steamrolled. And that's actually an
Speaker 1: important becomes an important market indicator. But it also gives
Speaker 1: us some idea that the breakdowns in this environment have
Speaker 1: actually been a source of alpha UM, that breakouts are working,
Speaker 1: that overbought conditions aren't a place to be selling UM,
Speaker 1: they're actually a reflection of the momentum. So our idea
Speaker 1: generation is a combination of using some traditional and nontraditional
Speaker 1: techniques frankly, but then overlaying those and understanding how those
Speaker 1: work throughout history and where we should be at any
Speaker 1: given point in time. So, I know, I say, the
Speaker 1: show's UH tagline is no forecast, no stock picks. So
Speaker 1: I'm gonna ask this question slightly differently. I've been hearing
Speaker 1: for I don't know, five six years, this rally is overboard,
Speaker 1: it's artificial, it's fed induced. It's gonna end any day now,
Speaker 1: or so I've heard every day for the past five years.
Speaker 1: So where do you see us within the overall market cycle?
Speaker 1: And where does this end? Or can this just continue
Speaker 1: into such point as something comes along to stop it? Well, look,
Speaker 1: I I view the world as this ever expanding UH
Speaker 1: sample of the population, right, So you know the reality
Speaker 1: is as well, we have really good data as good
Speaker 1: or data is as good as anyone else is. You know,
Speaker 1: the markets and rough rice back in the you know,
Speaker 1: the Chinese in the fifteenth century. I don't have that data.
Speaker 1: So maybe something happened that was completely different that you know,
Speaker 1: would skew other things. But what I can tell you
Speaker 1: is if you look over the last nine years UH,
Speaker 1: and you look at risk adjusted returns for the SMP
Speaker 1: versus the risk free rate, and you measure those, we
Speaker 1: are in UM, you know, the ninety percentile of what
Speaker 1: you'd expect for excess returns. If you look at those
Speaker 1: other periods of time, the forward returns are not something
Speaker 1: that you want to write home about. In fact, you'd
Speaker 1: want to steer yourself towards that that active management, not
Speaker 1: towards passive management. So I, you know, I view this
Speaker 1: as the fuel in the tank is relatively slight UM.
Speaker 1: But within that context, it's important to recognize that momentum
Speaker 1: has been good. The trends for equities are positive UM.
Speaker 1: And so while I think the path at least resistance
Speaker 1: in the near term is higher by near term I
Speaker 1: mean three to six, maybe twelve months UM, the amount
Speaker 1: of fuel we have to really propel it at this
Speaker 1: stage still seems to be relatively lacking. So this is
Speaker 1: not in our view. This turn was not some historic
Speaker 1: low that's going to provide UM, you know, very good
Speaker 1: UH risk adjusted returns going forward. I think it's enough
Speaker 1: to probably catch people off sides get people to reposition
Speaker 1: and then you know, come back and uh and give
Speaker 1: us a tougher environment. In two thousand and seventeen, what
Speaker 1: is additional fuel that could keep the momentum going because
Speaker 1: because it's we've seen profits sort of top out and
Speaker 1: start to roll over a bit. Um. Energy prices never
Speaker 1: low energy prices never really provided the too consumers that
Speaker 1: they normally do. In theory, it help them pay down
Speaker 1: some debt, a little cash in their pocket. But we
Speaker 1: didn't see a surgeon retail spending UM. And we have
Speaker 1: an election coming up in November. What could change the
Speaker 1: dynamic that says, hey, this could go on for years,
Speaker 1: not quarters, no great question. It's usually something in the
Speaker 1: credit cycle, right so it could be QUEI four. I
Speaker 1: don't think that's likely, but that's you know, let's let's
Speaker 1: keep our our minds open. It could be fiscal stimulus UM,
Speaker 1: which both sides have been talking about fairly uh consistently.
Speaker 1: Right now, we have the credit cycle is flat that
Speaker 1: you know if you look at global central bank balance sheets, UM.
Speaker 1: So we don't concern ourselves as much with the rates
Speaker 1: as we do. What's happening to the composition of the
Speaker 1: balance sheet, right, So an expanding balance sheet is obviously
Speaker 1: credit creation. A contracting balance sheet is credit deterioration or destruction. UM.
Speaker 1: Global balance sheets as we measure them are about flat
Speaker 1: year over year, and that's actually one of the lowest
Speaker 1: levels that we've seen in the last fifteen years. So
Speaker 1: you know, changing that dynamic would be important. The Chinese
Speaker 1: with the FX reserves stabilizing would be one part. UM.
Speaker 1: Sovereign wealth funds not pulling UH their their wealth out
Speaker 1: of of the U S asset markets UM, that would
Speaker 1: be another point. UM. So you know, there's a lot
Speaker 1: of different dynamics that take place with this, but credit
Speaker 1: is usually at the forefront of it, and i'd say
Speaker 1: non financial leverage that we as we look at it,
Speaker 1: which is flattened here. If we can start to see
Speaker 1: that uptick would be would be helpful as well. Last
Speaker 1: politically related question, UM, we keep hearing and again both
Speaker 1: sides talking about a tax holiday to repatriate some of
Speaker 1: the tens of trillions of corporate dollars that are overseas.
Speaker 1: UM does at least two trillion just out of the
Speaker 1: SNP five and I've seen estimates as high as ten trillion.
Speaker 1: If whoever gets elected in November passes something like that.
Speaker 1: Is that a temporary blip. Does that have the potential
Speaker 1: to stimulate the economy here? Does that hurt Europe and
Speaker 1: Asia where the money might be sitting. What's the impact
Speaker 1: of that big repatriation assuming it actually happens. Yeah, I mean, look,
Speaker 1: when you when you withdraw UM money from one system
Speaker 1: to another, there usually as a transfer there, right, And
Speaker 1: so you're talking about tighter credit conditions and looser credit conditions.
Speaker 1: And by the way, the thinking behind this just to
Speaker 1: you mentioned infrastructure before the deal is the Democrats want
Speaker 1: to big infrastructure bill, bridges, roads, electrical grid, etcetera. The
Speaker 1: Republicans want to change the corporate tax rate and or
Speaker 1: repatriate the overseas dollar, but temporary tax holiday, maybe you
Speaker 1: take tax at at six percent, five percent, something like that.
Speaker 1: So if there's a deal struck that that's where I
Speaker 1: was leading from with that. I mean, that's you know,
Speaker 1: is that a positive? Is that a negative? Is it
Speaker 1: globally neutral viewed as a positive for the US? I
Speaker 1: mean this is not my area of expertise, but any means,
Speaker 1: but I would I would it as a positive for
Speaker 1: the US. UM and then the question is is how
Speaker 1: is that capital utilized? Right? Is it? You know, is
Speaker 1: it really going into property, plant, equipment, R and D spending? Look,
Speaker 1: I think the reality is the trajectory is the trajectory.
Speaker 1: I don't think of a boon. Uh if if companies
Speaker 1: thought that they could earn positive returns on projects, they
Speaker 1: do it. I mean, for God's sakes, interest rates are
Speaker 1: you know, next to nothing, So it's not it's not
Speaker 1: a huge hurdle here. You don't see a lot of
Speaker 1: CAPEX spending, although some people have have said that's misleading
Speaker 1: when you look at it as a percentage of GDP
Speaker 1: or as a percentage of other activity, it's actually at
Speaker 1: a fairly high rate. I think you'd probably go to
Speaker 1: corporate bybex really more so than than Capex. Really that
Speaker 1: that would be interesting. Let's in the last fifteen minutes
Speaker 1: or so, we have get to our standard questions. We
Speaker 1: we talked about what you did before UH Wall Street,
Speaker 1: which was college. Who are your early mentors Bob Ferrell,
Speaker 1: uh Steve Shoubin. Let's talk about Bob Farrell a little
Speaker 1: bit because Dave Rosenberg is a friend another guy who
Speaker 1: has him as a mentor. I've had heard his name
Speaker 1: come up from Ralph Akimpora has mentioned him. A number
Speaker 1: of people have mentioned, well he was the first. Remember
Speaker 1: he was the first one to actually um had a
Speaker 1: technical analysis department and Marylands right back in the fifties
Speaker 1: and sixties. Yeah. Um. And just a sweetheart of a
Speaker 1: guy and very intuitive, a great amount of experience and
Speaker 1: just understanding of the business. And what I really appreciated
Speaker 1: about Bob's perspective is he lived and you know, didn't
Speaker 1: grow up in but lived through um, you know, the
Speaker 1: tumultuous times of the late sixties, the seventies and the
Speaker 1: you know, I mean horrendous markets almost as bad as
Speaker 1: though I don't know people risk adjusted. Absolutely it was right, um,
Speaker 1: no doubt about it. So when you know, when you
Speaker 1: have somebody who's gone through that, there's a perspective that
Speaker 1: they bring. You know, I can read about it all
Speaker 1: I want, but when you're living it, it's completely different. Right.
Speaker 1: So this just a very unique perspective that um, you
Speaker 1: know that I really appreciated and and found found useful.
Speaker 1: Steve Schobin, who was started in the in the Mary
Speaker 1: Lynch Technical Analysis Department, then left for Lehman brothers in
Speaker 1: the mid nineties, who I eventually joined in the late
Speaker 1: nineties at Lehman. UM was equally as um as intuitive
Speaker 1: and Uh well he started a little later. I think
Speaker 1: he started in sixty eight. UM had a very very
Speaker 1: good perspective, and I worked more closely with Steve Um.
Speaker 1: His ability to um understand and really synthesized things qualitatively
Speaker 1: was unmatched from anybody I've worked with since. UM. He
Speaker 1: just had a very good intuition about the market. And
Speaker 1: I was far more quantitative than Steve, but his intuition.
Speaker 1: I certainly learned a lot from uh in Uh in
Speaker 1: my years working with him, and a great guy. So
Speaker 1: beyond Steve, if you're out there beyond beyond mentors, what
Speaker 1: other investors influenced your approach to the markets? Well, you know,
Speaker 1: without being specific about people, I think, what's what's interesting
Speaker 1: about the business, and you know, at whether it was
Speaker 1: at Meryl or Lehman or even at Rehnmac now UM,
Speaker 1: what I find is and very refreshing is it's the
Speaker 1: people that UM are very very successful, who are interested
Speaker 1: in our work. Right. In other words, it's not the
Speaker 1: hotshot m b A who you know learned the same
Speaker 1: thing that everybody does, that technical analysis is just a
Speaker 1: bunch of bunk. You know, their quote unquote smarter than
Speaker 1: the market, and they'll get it all figured out. It's
Speaker 1: the season professional with the scars and the battle wounds
Speaker 1: who are always interested in our perspective because they've seen
Speaker 1: it before, right, they understand that there's something more to
Speaker 1: the business. And you know, you can get into this
Speaker 1: debate between art and science, and I get it, and
Speaker 1: I do think that technical analysis probably relies too much
Speaker 1: on art, fundamental analysis relies probably too much on science. Um.
Speaker 1: We try to blend the two, right, taking the I
Speaker 1: understand there's something here, let's try to quantify it and
Speaker 1: do something around that. So um and look, even in
Speaker 1: fundamental analysis, there's an art to understanding where the kink
Speaker 1: in the hockey stick of growth is right, or what
Speaker 1: the difference between K and G in terms of the
Speaker 1: cost of capital and and the growth rate is. You know,
Speaker 1: so there's there's an art to everything that that's done.
Speaker 1: We just try to quantify it to the extent that
Speaker 1: we can. Um And so you know, when I look
Speaker 1: at the people that read our research and and that
Speaker 1: I'm good friends with in the business. Um, you know,
Speaker 1: there are people that I'm proud to have his clients.
Speaker 1: I mean, they're they're they're successful people. And I think
Speaker 1: you go back to the you know, to the Wizards
Speaker 1: of Wall Street books, and you know, I learned a
Speaker 1: lot from Richard Dennis and his Turtle system and just
Speaker 1: the way that they think about things right and stand
Speaker 1: people on it. It means it's quantitative and it's not
Speaker 1: purely in art. There has to be rules you can
Speaker 1: teach me. Yeah, And I think look, as as much
Speaker 1: as anything, what we try to do is we try
Speaker 1: to remain disciplined, right, And I think discipline is and
Speaker 1: people in the business understand that, but it's underrated amongst
Speaker 1: the investing public. I think, without question it's I think
Speaker 1: that I think it's underrated amongst the entire street. Is
Speaker 1: how how important and underutilized discipline is, right, And the
Speaker 1: problem being is that when you quantify it, you also
Speaker 1: quantify what your loss is going to be right, and
Speaker 1: so you know that you're not always going to be right,
Speaker 1: but you have to be willing to be wrong by
Speaker 1: this much. And most people say, I don't want to
Speaker 1: be wrong by this much right, And so instead of
Speaker 1: quantifying it. They'll just do it by the seat of
Speaker 1: their pants. So I can do it successfully, some can't.
Speaker 1: I'd rather quantify it and say, hey, here's where I am,
Speaker 1: here's my risk profile. Now what can I do to
Speaker 1: maybe further mitigate that, or how do you know, how
Speaker 1: can I position it so that I'm I'm willing to
Speaker 1: accept that and move on knowing that what I call
Speaker 1: terminal wealth is going to be far better than if
Speaker 1: I were to just index or something along those lines.
Speaker 1: The quote I read this week, and I don't remember where,
Speaker 1: what book or what publication I read this was we
Speaker 1: learned nothing from our winners. It's our losers that teach us.
Speaker 1: And there's those battle scars. You don't get those. The
Speaker 1: worst thing that can happen to a nubie investor is
Speaker 1: a winning streak. They learned nothing from it, and they
Speaker 1: start to think they're they're brilliant. You mentioned Turtle Traders
Speaker 1: and and market Wizards. That's the perfect transition to the
Speaker 1: next question. By the way, we've had Schwager on he's fantastic,
Speaker 1: and I don't know if you know Mike Koval's book
Speaker 1: Total Traders. He was really interesting. He's been entranced by
Speaker 1: Dennis's concept of let's raise them the way they raise
Speaker 1: turtles in these farms in Singapore which are used as
Speaker 1: a as a food source. If we can raise turtles,
Speaker 1: we can raise traders. And and let's so let's talk
Speaker 1: about some of your favorite books. The first book I
Speaker 1: read in when I got into the business was Market Wizards,
Speaker 1: and it was absolutely fascinating. You imply, um, you enjoyed
Speaker 1: the book as well. Yeah, at least two of them.
Speaker 1: I think there's three in order read to Market Wizards,
Speaker 1: New Market Wizards, and head Fun Wizards. Think yet, but
Speaker 1: so be it? Um, you know that that to me,
Speaker 1: I thought was sort of bringing theoretical to reality. Right,
Speaker 1: there's always the difference of you know, up on the chalkboard,
Speaker 1: it looks nice, but you know, in the trenches, how
Speaker 1: does this really play out? And that was you know,
Speaker 1: using both you had fundamental traders there, you had technical
Speaker 1: traders there get some that did a combination. Uh, and
Speaker 1: obviously all did it disciplined. By the way, what you
Speaker 1: mentioned is a theme that runs throughout the whids to
Speaker 1: every you absolutely have to have it without question. What
Speaker 1: what other books are standouts to you that either were influential,
Speaker 1: or just that you really enjoyed a great deal. I mean,
Speaker 1: this is probably a little bit more controversial, but I
Speaker 1: will say that i've i've certainly um internalized the thought
Speaker 1: process of the Austrian cycle of economics. UM. Not that
Speaker 1: it's always right, I wouldn't, I wouldn't think about it
Speaker 1: that way, but in terms of sort of grounding yourself
Speaker 1: and understanding that trees don't grow to the sky. You
Speaker 1: can't dig your way to China no matter how hard
Speaker 1: you try. I think it's just a good understanding not
Speaker 1: only of credit of money UH and the influence on
Speaker 1: the economy over time and the business cycle. No, no
Speaker 1: doubt about that. UM any other books before we move
Speaker 1: on to our two favorite questions, I think any book
Speaker 1: on market history is fantastic, just to again try to internalize,
Speaker 1: you know, and understand what Bob Ferrell knew from living it.
Speaker 1: The more you can understand the history of the markets,
Speaker 1: the more you'll find that things aren't aren't changing, they're
Speaker 1: staying the same. Give me a few I have a
Speaker 1: few favorites of my own, and the reminiscence of a
Speaker 1: stock operators classic the same around the same period that
Speaker 1: came out. You would appreciate this if you haven't read this.
Speaker 1: I'm fond of talking about Richard Wykoff's How I Trade
Speaker 1: Stocks and Bonds. If you swap out telephone wire for Internet,
Speaker 1: It's like it was written yesterday. Absolutely, it's amazing more
Speaker 1: and changed the question. I've recently started, um actually fondly
Speaker 1: reading the minutes from Federal Reserve meetings, really because the
Speaker 1: same thing right back, way back, way back to the thirties, right,
Speaker 1: no kidding, because you'll find that they're you know, we
Speaker 1: like to think that they're they're driving silly cars and
Speaker 1: wearing wool suits in the summer, and they don't have
Speaker 1: a clue. I mean, they're very thoughtful there as as
Speaker 1: of course they are, right. The Lords of Banking really
Speaker 1: makes that clear that book. Really, if you thought these
Speaker 1: are just a bunch of idiots flailing about, that will
Speaker 1: disabuse you of those notes. And and remember at the time,
Speaker 1: their technology that they had was superior to anything that
Speaker 1: they had thirty years prior. Right, So it's not like
Speaker 1: we're suddenly so much smarter because of all this stuff.
Speaker 1: It's just, you know, there are certain things that are
Speaker 1: just unknowable and and you find that in the business,
Speaker 1: So I think that's interesting. Um there's a good book
Speaker 1: called UMU, A Nation of Deadbeats, which which is a
Speaker 1: just a very good history. I'm not a fan of
Speaker 1: the title, but it's a very good history of the
Speaker 1: US economic cycles boom busts, and takes us through with
Speaker 1: a lot of interesting anecdotes about the you know, how
Speaker 1: the green bag became the green back, and and just
Speaker 1: you know, some interesting anecdotes about the US specifically. That
Speaker 1: title reminded me of a book I used for research
Speaker 1: some years ago about the nineteenth century banking in the
Speaker 1: United States called a Nation of counterfeiters, and all these
Speaker 1: banks would issue these notes wildcatting and eventually walk away
Speaker 1: from him. Eventually, that's why we ended up with a
Speaker 1: federal reserve. So our last two questions my favorite two
Speaker 1: questions I asked all of my guests. So a millennial
Speaker 1: or a recent college graduate comes to you and says, hey, Jeff,
Speaker 1: I'm thinking about going into finance. What sort of advice
Speaker 1: would you give them? Just get experience, get your feet wet,
Speaker 1: get your feet wet, get your feet wet. The second,
Speaker 1: and from from my perspective, UM I really don't hire
Speaker 1: people unless you're programmers. You have to have just a
Speaker 1: solid understanding of programming because that's really where the power is,
Speaker 1: you know. Um. So you know, if you're coming out
Speaker 1: and you're you're committed to the business and you want
Speaker 1: to show the commitment to the business as a you know,
Speaker 1: as a young fresh graduate, I'd say getting rolled in
Speaker 1: the c f A program as soon as you possibly
Speaker 1: can show that this is where you want to be.
Speaker 1: Obviously it's more specific than than an NBA program. Um.
Speaker 1: In fact of my my alma mater I um uh,
Speaker 1: you know, I really encouraged the students to to get
Speaker 1: their feet wet with the cf A program while they're
Speaker 1: in college and then you know, just gives them a
Speaker 1: leg up as they get out. Um to understand, um,
Speaker 1: you know to prospective employers that hey, I'm serious about
Speaker 1: this business and I've invested my resources and time to
Speaker 1: do this. Um. But programming history and just you know, commitment,
Speaker 1: get involved. And our final question, what is it that
Speaker 1: you know about investing today? You wish you knew twenty
Speaker 1: something years ago when you began. That's a great question,
Speaker 1: I think, um, instead of I knew about this, but
Speaker 1: how about the appreciation of this. I think it is
Speaker 1: probably a better word way to think about it is
Speaker 1: the absolute power of compound interest, right. I mean, you know,
Speaker 1: you can look at the tables, you can do all
Speaker 1: the forward valuation calculations you want and see how you
Speaker 1: can tune a thousand dollars into something you know, extraordinary.
Speaker 1: But the power of living for twenty years and seeing
Speaker 1: that work is astounding, and I think it's underappreciated by
Speaker 1: the masses. Humans have a hard time conceptualizing long periods
Speaker 1: of time. And I'm not talking eons and billions of
Speaker 1: years on an astronomical level, just your own lifetime. Hey,
Speaker 1: if I do this for thirty years, here's the net.
Speaker 1: My father in law was in town this weekend. He
Speaker 1: showed me a picture of his his Mustang that was
Speaker 1: brand new when he bought it in ninety five, and
Speaker 1: he said, I just saw it an eBay for a
Speaker 1: little under a hundred thousand dollars and so, I you know,
Speaker 1: I did the quick math on it, and uh, it
Speaker 1: worked out to about a seven and a half annualized
Speaker 1: rate of return. It would have done better in the market,
Speaker 1: just right. But you know, but now that it seem
Speaker 1: like a little better, but it seems like a big number,
Speaker 1: and you know that's the beauty of compounding. You just
Speaker 1: don't realize what, Hey, sixty five mustang, you're talking almost
Speaker 1: fifty years ago, more than fifty years ago. That that's
Speaker 1: a fascinating thing. Well, Jeff, thank you so much for
Speaker 1: doing this experisode. Generous with your time. I'm sure people,
Speaker 1: especially the technicians out there, are going to be fascinated
Speaker 1: by this. Uh. If you've enjoyed this conversation, be sure
Speaker 1: and look up an Inch or down an Inch on
Speaker 1: Apple iTunes and you can see the other ninety or
Speaker 1: so um conversations we've had with various notables in the
Speaker 1: financial industry. I would be remiss if I did not
Speaker 1: thank my booker and audio engineer, Taylor Riggs for helping
Speaker 1: to organize this. Uh. My head of research is Michael
Speaker 1: bat Nick, and Charlie Vollmer is our producer. You've been
Speaker 1: listening to Masters in Business on Bloomberg Radio look Ahead,
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