Speaker 1: Hello, and welcome to What Goes Up a weekly markets podcast.
Speaker 1: My name is Mike Reagan. I'm a senior editor at
Speaker 1: Bloomberg and I'm Boldana Higher, across asset reporter with Bloomberg
Speaker 1: at this week on the show, well, is the proverbial
Speaker 1: fed put dead or is the strike price just so
Speaker 1: low that it may as well be? That's the question
Speaker 1: on everyone's mind this week after Jerome pal signaled that
Speaker 1: the recent boltility in the stock market will not be
Speaker 1: enough to force the Central Bank to amend its plans
Speaker 1: to raise interest rates and shrink its balance sheet. What
Speaker 1: does it mean for markets? We'll get into it with
Speaker 1: the chief investment officer of a firm that focuses on
Speaker 1: artificial intelligence. But first, the two things I have to
Speaker 1: tell you, um. First of all, my crazy thing this
Speaker 1: week is custom made for you, so I okay, I
Speaker 1: expect big things from you on this Secondly, condolences UH
Speaker 1: to you and Jeffrey Gunlock and all the other Buffalo
Speaker 1: Bills fans out there. I know this is this is
Speaker 1: a bad week, so bad that it's Veldona's turn to
Speaker 1: hide under a blanket during the podcast this week. And Vildonna,
Speaker 1: I think if there were like a pure play company
Speaker 1: that makes folding tables, I would assorted them this week.
Speaker 1: What do you think? Uh, yeah, it's it's a bad
Speaker 1: time for Buffalo Bills fans for all of Western New York.
Speaker 1: I was depressed on Sunday on Monday. I'm depressed today.
Speaker 1: I don't know how I'm going to get through this answer,
Speaker 1: but thank you. I appreciate it. At least at least
Speaker 1: everybody watched the game was like record numbers of people
Speaker 1: who watched it. And now everybody's discussing overtime rules for
Speaker 1: the NFL, which is which is kind of cool. Yeah,
Speaker 1: but by everyone, you mean that the team that lost,
Speaker 1: the fans of the team that lost because of the
Speaker 1: Hey I saw, I saw Larry David was talking about
Speaker 1: it too. It is they've already amended it once. So
Speaker 1: we'll see. We'll see. One can hope maybe they'll they'll
Speaker 1: let them play that game over. But I'm excited about
Speaker 1: this guest. Uh this week. We haven't talked to him
Speaker 1: in a while. He's got a new firm he's involved with.
Speaker 1: Tell us about him. Bring him into the show here,
Speaker 1: let's get this going. Yeah, it's Max Kachman. He's the
Speaker 1: chief investment officer at Alpha. Trey, and Max, I want
Speaker 1: to welcome you back to the show. Thanks so much
Speaker 1: for having me. It's awesome to be back. Max. It's
Speaker 1: it's been a while, and I don't think i've talked
Speaker 1: to you since you've started this new gig. And I'm
Speaker 1: gonna I'm gonna confess something here. Max. Whenever I hear
Speaker 1: someone talk about artificial investing or part of me artificial
Speaker 1: intelligence in the investing world, you know what I do
Speaker 1: is I kind of nod my head and I stroked
Speaker 1: my chin as if I know what's going on. But
Speaker 1: just between us, don't let this get out. I really
Speaker 1: have no idea what they're talking about. I'm hoping you
Speaker 1: can give us all your takes on the market in
Speaker 1: the show. But but first let's get into that notion.
Speaker 1: What are you guys up to. What is sort of
Speaker 1: um going on with AI focused investing at the moment,
Speaker 1: What are the applications and where do you see it
Speaker 1: going uh in the future? And if you don't mind
Speaker 1: the for dummies version, I think it would probably be
Speaker 1: best for at least for me. I don't know about Baldonna. Sure, well,
Speaker 1: I'm sure. I'm sure e Donna would understand the intricacies
Speaker 1: of things like recursive neural networks and you know, transformers.
Speaker 1: But Mike, for you, I'll dumb it down. Yeah, thank you.
Speaker 1: I appreciate that. So, first of all, it's really important
Speaker 1: to differentiate artificial intelligence from the broader quant ecosystem because
Speaker 1: a lot of folks know about quant fund Systematic funds
Speaker 1: have trillions of dollars um you know, a stematic strategies
Speaker 1: have trillions of dollars under management. AI as in true
Speaker 1: artificial intelligence is very rare, and in fact, that's why
Speaker 1: I left a pretty strong position to to join this
Speaker 1: plucky startup to lead the new frontier. True artificial intelligence
Speaker 1: is really based on the concept of a neural network,
Speaker 1: and a neural network is kind of what it sounds like.
Speaker 1: It consists of neurons, just like your brain, and those
Speaker 1: neurons fire in different ways to process information, kind of
Speaker 1: the way human mind process it, but very differently from
Speaker 1: how a traditional systematic strategy process it. The best way
Speaker 1: to think about it is your typical quantitative strategy, even
Speaker 1: if it uses machine learning, which is kind of part
Speaker 1: of that AI phrase geology, but it's not quite what
Speaker 1: we consider authentic AI. It has a formula, and that
Speaker 1: formulas designed to systematize a way of thinking or an
Speaker 1: economic theory. And then that formula has you know, a
Speaker 1: bunch of factors, and those factors have coefficients, and basically
Speaker 1: the machine learning part will at a high level kind
Speaker 1: of adjust to coefficient so that we think that value
Speaker 1: is going to do well, it will be a positive coefficient.
Speaker 1: We think value is going to do not so well,
Speaker 1: that could be in that g of coefficient, right, but
Speaker 1: you're still basically making a decision. In that example of
Speaker 1: that we go longer short value factor. A unsupervised deep
Speaker 1: learning matterwork can actually create its own features. It can
Speaker 1: create its own view on what a factor is. It
Speaker 1: does not have to be this preconceived notion of value, large, momentum, quality, etcetera.
Speaker 1: And so that's a key thing about true AI strategies
Speaker 1: is they can adapt on their own without human intervention.
Speaker 1: They're also going to be unbiased. And and this is
Speaker 1: something that I think a lot of times when people
Speaker 1: think about quant funds, they say, well, quant funds don't
Speaker 1: have bias, and that's not quite true. They don't have
Speaker 1: emotion as in a formula. As a formula, it doesn't
Speaker 1: really care if the markets down fifty or up, you know,
Speaker 1: but it will have a bias because it's based on
Speaker 1: again systematizing a way of thinking. That thinking is inherently biased.
Speaker 1: As as I said, it was created by a human.
Speaker 1: An AI model actually does not have that bias in
Speaker 1: it if it's an authentic a A model. And that's
Speaker 1: something that I think is going to be even more
Speaker 1: important as we get into these markets, which will of
Speaker 1: course discuss where things are changing quite rapidly and we're
Speaker 1: going to see patterns emerge that we haven't seen before.
Speaker 1: You're gonna need something that can adapt on its own
Speaker 1: and adapt quite quickly, and that is to me a
Speaker 1: key hallmark of authentic artificial intelligence. So before we get
Speaker 1: to talk about the market, Max, I really like always
Speaker 1: talking with you because you're up for talking about lots
Speaker 1: of different things, including cryptocurrencies, and I believe you guys
Speaker 1: are working on an AI program for a crypto fund
Speaker 1: if you can tell us a little bit about that. Yeah,
Speaker 1: So this is currently kind of our cutting edge R
Speaker 1: and D efforts that we are working on. We're we
Speaker 1: think that AI and digital assets and I want to
Speaker 1: go beyond just saying cryptocurrency, because I think that actually
Speaker 1: is a arroware universe. So and I know you like
Speaker 1: things like pudgy penguins, um, you know, and n f
Speaker 1: t s. So those are all tradeable assets within the
Speaker 1: digital asset ecosystem, and we think that AI is a
Speaker 1: natural way to analyze those assets and trade them, in
Speaker 1: part because it's a brand new asset class. This is
Speaker 1: something that a lot of folks don't realize. I've seen
Speaker 1: a lot of traders who were good in currencies, are
Speaker 1: good in cross asset kind of jump into the crypto world.
Speaker 1: But they bring in those same concepts and they don't
Speaker 1: necessarily work in crypto space. Like, for instance, a lot
Speaker 1: of resistance and support bands in the currency markets are
Speaker 1: based on actually gentle bank purchasers or you know, companies
Speaker 1: that are hedging their their cost of goods. That doesn't
Speaker 1: exist in in crypto. So when you see our supported
Speaker 1: resistance level, it's actually driven by different factors. When we
Speaker 1: think about AI as as well, it really feeds on
Speaker 1: data of course, Like that's that's a something pbably should
Speaker 1: have said earlier, right, aies source of brain food is data.
Speaker 1: The higher quality of a data a smarter b AI
Speaker 1: will be able to be and data on the blockchain
Speaker 1: is very clean and therefore highly nutritious to an artificial
Speaker 1: intelligence engine. And addition to that, you have really low
Speaker 1: efficiencies in the market, so high quality data, low efficiency,
Speaker 1: and then sprinkling top about a really high volatility that
Speaker 1: is kind of the most fertile you know, a sybal
Speaker 1: if you will, for for AI to drive alpha from UM.
Speaker 1: In addition to that, you've got really unique parts within
Speaker 1: the crypto space, such as the actual code basis that UM.
Speaker 1: A lot of these protocols are developed in and those
Speaker 1: are things where you know, one bit of code, reading
Speaker 1: another bit of code and making a decision on it
Speaker 1: and analyzing it is actually something that opens up even
Speaker 1: more doors. So we think there's a lot of really
Speaker 1: amazing up tunities. I can't talk about too much on
Speaker 1: the specifics, but next time I'm on I hopefully we'll
Speaker 1: be able to share a lot more. But we do
Speaker 1: think that AI and digital assets are a perfect marriage. Max.
Speaker 1: Let's bring it into the present tense a little bit
Speaker 1: with what we saw this week in the markets, and
Speaker 1: I'm curious how AI would work with sort of an
Speaker 1: event risk type of situation like we saw this week
Speaker 1: with the fit. I mean, I know there's been a
Speaker 1: lot of work done on sort of natural language processing
Speaker 1: and try to you know, have computers listen or or
Speaker 1: read text and and and make a decision based on that.
Speaker 1: Where is that in in sort of the big scheme
Speaker 1: of things with with Aiyes, it's still you know, is
Speaker 1: that still a little too tricky to to do? Is
Speaker 1: it something that they need sort of the uh, you know,
Speaker 1: the the organic intelligence of a guy like you to
Speaker 1: handle that end of it. I mean, you know, can
Speaker 1: a I listened to Jerome palell and and pick up
Speaker 1: the nuances and and that or is it just you know,
Speaker 1: a matter of reacting to the market signals as he's speaking.
Speaker 1: It's a great question. There's going to be different answers
Speaker 1: depending on who you talk to. I know, on on
Speaker 1: one end, there's one fund that thinks they can actually
Speaker 1: train a camera. Well, they basically put a camera on
Speaker 1: Powell live and they try to to construct the nuance
Speaker 1: of his physical body language and the nu once of
Speaker 1: his speech inflections to figure out what he's doing. Yeah, now,
Speaker 1: I they when I asked him how well about work?
Speaker 1: They kind of got quiet, so I'll just leave it
Speaker 1: at that. Well, if Pal's got a pretty good poker face,
Speaker 1: so he might not be the best, he's he's gotten
Speaker 1: better since let's let's let's let's let's let's put it there.
Speaker 1: I think I think Marrio track he might have been
Speaker 1: a better test case so that you know a little
Speaker 1: more out of me, Yeah, a little more. You know
Speaker 1: his Italian. So there's there's that. But I do think
Speaker 1: when it comes to things like n LP, it's a
Speaker 1: question of the decay and what I mean by decays
Speaker 1: between when the word is uttered and transcripted to when
Speaker 1: the market reacts. What's the lag and can you actually
Speaker 1: capture that? A lot of times the answer is no,
Speaker 1: So we actually haven't found a lot of utility and
Speaker 1: kind of real time n LP because a real trader,
Speaker 1: who is you know, able to hit buy or sell
Speaker 1: as soon as they here even like half of the
Speaker 1: word is going to be a little bit quicker than
Speaker 1: you know a program will be. It's fascinating area of
Speaker 1: research because I feel like, you know, you could read
Speaker 1: the text of a speech and think one thing where
Speaker 1: you could see someone recite the same speech with different
Speaker 1: inflection and sort of different emotions and and come away
Speaker 1: with something something different. So it's a it's a fascinating
Speaker 1: area of recent I think, yeah, and and I think
Speaker 1: there's a lot of words that especially central bankers use
Speaker 1: were almost dead of vocabulary is not a normal person's vocabulary.
Speaker 1: And as FED watchers, like as economists, we kind of
Speaker 1: know what they mean when they say words um, like
Speaker 1: you know, we're gonna be humble um, or we're gonna
Speaker 1: be um, you know, like persistent for for instance, like
Speaker 1: different contexts that could be very hawkish are very dubbish.
Speaker 1: And a traditional n LP model is just gonna say
Speaker 1: this is positive or negative sentiment. It's not gonna be
Speaker 1: quite as good unless you train And this is this
Speaker 1: is actually where we get into some interesting stuff. And
Speaker 1: I have seen this work where you train a model
Speaker 1: on a specific person. You can do that of central bankers.
Speaker 1: I actually had this idea originally back in I think,
Speaker 1: and at the time it wasn't able to really figure
Speaker 1: out how to do that. But I actually wasn't going
Speaker 1: to train a model back then on Bernanky and uh
Speaker 1: and and draggy and say okay, can we figure out
Speaker 1: based on ner specific vocabulary they're specific mannerisms if they're
Speaker 1: you know, being hawkish or dubbish. But back then it
Speaker 1: definitely didn't work. Perhaps in the future, as compute increases,
Speaker 1: we can you know, really isolate that and and that
Speaker 1: will be a very interesting situation where you have actually
Speaker 1: algorithms making those split second decisions. But we're not quite
Speaker 1: there yet. So speaking about this week, I was hoping
Speaker 1: you could sort of just go over briefly and very
Speaker 1: quickly your takeaways from the FED meeting, and I wanted
Speaker 1: to ask you if you think the market is correctly
Speaker 1: interpreting what happened with Paul this week. I think the
Speaker 1: market is been having a really hard time get getting
Speaker 1: its sea legs this January, right. I mean, just look
Speaker 1: at the action we experienced kind of right after the meeting,
Speaker 1: we had the really big drop, then overnight we started
Speaker 1: dropping further and then came back up. I don't think
Speaker 1: Powell said anything really dramatically new. In fact, you and
Speaker 1: I were talking to about that um right right after
Speaker 1: the meeting. To me, it seemed like just the hope
Speaker 1: is gone, right, that was the initial reaction, like, okay,
Speaker 1: but the Powell put is out of the money. It
Speaker 1: may be completely off the table. And that was that
Speaker 1: Initially like oh crap, like we're the training wheels are
Speaker 1: off uh situation for for investors. But then overnight, all
Speaker 1: of a sudden, you know, we got some some I
Speaker 1: guess newfound hope or newfound um confidence that the markets
Speaker 1: can do well on their own. So if you think
Speaker 1: of like again with the training wheels example, it almost
Speaker 1: seemed like you know, you can take your your kid.
Speaker 1: You kind of sent them down the hill and they
Speaker 1: start really wobbly and they think they're going to fall,
Speaker 1: and then they eventually they start peddling and they're like, oh,
Speaker 1: look at me, I'm going But at no point that
Speaker 1: pow will say anything to me. That was different. That
Speaker 1: was you know, unexpected. They've done a really good jap
Speaker 1: of telegraphing what they were going to do. And the
Speaker 1: thing that I always watched for is kind of the
Speaker 1: speed speakers score on the fringes either the most hawkish
Speaker 1: or the most ubblish, and see if do they start
Speaker 1: changing their tune, And they did the most dubbish. Fet
Speaker 1: speakers UM and FMC members got a lot more hawkish
Speaker 1: in the you know kind of weeks coming up to
Speaker 1: this meeting, So it shouldn't have been a surprise that
Speaker 1: the Fed said, Yep, we're gonna hike in March, we're
Speaker 1: gonna end QE, and we're gonna look at tightening. That's
Speaker 1: pretty much what I think everyone should have expected. Yeah,
Speaker 1: and maybe that's you know, maybe they did, and that's
Speaker 1: why we saw such such altility before the meeting, even
Speaker 1: you know, kind of priced it in. But Maxell, well,
Speaker 1: how are you thinking about the rest of the year now, um,
Speaker 1: especially in context of well, if if treasuries and stocks
Speaker 1: are selling off together, you know, uh, that's sixty forty
Speaker 1: portfolio maybe is not as diversified as it once was.
Speaker 1: You know, I think this is a issue with people
Speaker 1: have been talking about for a year, year or more now,
Speaker 1: but it certainly seems to be an urgent topic now,
Speaker 1: you know. Or is it possible we'll see sort of
Speaker 1: assimule tenious weakness in both the bond and the stock
Speaker 1: market And how do you how do you play that? Yeah, So,
Speaker 1: first of all, the answer is yes, I think that's likely.
Speaker 1: That's actually my base cases that we will see weakness
Speaker 1: in stocks for at least some part of this year.
Speaker 1: I do think we'll um, eventually be a little bit
Speaker 1: higher than where we started, but we will likely see
Speaker 1: a bowl correction and we'll also see rates go up.
Speaker 1: And you know, the last time when rates were in
Speaker 1: a secular uptrend, I think Bill, Donna and I weren't
Speaker 1: even born yet. So Mike, Mike had been around for
Speaker 1: you for decades. But full disclosure, I was asked to
Speaker 1: uh to give Mike some some singers before this show started.
Speaker 1: I'll try to get him in where where I can.
Speaker 1: I remember putting my money in the bank and earning
Speaker 1: something on it that was for the Those were the days.
Speaker 1: What what's such bank? Is that like like like a
Speaker 1: physical ethereum wallet. I would I would roll up the
Speaker 1: quarters and nickels and dimes in the little paper wrappers
Speaker 1: from my paper routing and ride my bike down and
Speaker 1: on a little paper to deposit slip and the interest
Speaker 1: was good. Those were the days. Bring back bring back
Speaker 1: those you know, five percent savings deposit accounts. Max's he's
Speaker 1: talking about the early Yeah, I I think it's kind
Speaker 1: of turn up the sanctuary, you know, yeah, novel there
Speaker 1: that that Mike was was spinning a little little Oliver twist. Yeah,
Speaker 1: artificial intelligence back then was like if you got the
Speaker 1: cheap code to Donkey Kong. You know that that was
Speaker 1: that was about as far as it went. I I
Speaker 1: do think with that you may be careful what you
Speaker 1: wish for, because I think we could get those five
Speaker 1: percent interest rates, but that also, you know, I believe
Speaker 1: came with like a twelve percent mortgage. That's fair, so
Speaker 1: you know, fair point. Those of us who locked in
Speaker 1: you know, low mortgages are are pretty happy. Probably at
Speaker 1: this point, I do think we are going to see
Speaker 1: this secular rising rate environment come back, and that really
Speaker 1: posts the challenge not only for sixty forty, but the
Speaker 1: thing that kind of supplanted sixty four for a lot
Speaker 1: of institutional portfolis, which is risk parity. And while you
Speaker 1: know risk parity folks will tell you about it's very sophisticated.
Speaker 1: Um having run risparity strategies before, I can tell you
Speaker 1: that generally speaking, it still relies on the crucial concept
Speaker 1: of bonds go up when stocks go down, and duration
Speaker 1: risk diversifies equity risk. If that no longer is the case,
Speaker 1: you need to create something different. I think it's gonna
Speaker 1: be really important to be more dynamic. It's gonna be
Speaker 1: what I mean about its dynamic in terms of asset classes.
Speaker 1: So the concept of a balanced portfolio is really important.
Speaker 1: I think if we break it down to its really
Speaker 1: building blocks, it's a risk asset that can go up
Speaker 1: and produce capital gains, and then a diversifying outset that
Speaker 1: maybe produces a little bit of income and steady returns,
Speaker 1: but primarily is there to hedge the risky asset. So
Speaker 1: what those two components are. I think that's gonna be
Speaker 1: more dynamic going forward, and the new old Weather strategies
Speaker 1: are going to be playing with those concepts. So they
Speaker 1: may hold equities and bonds like current strategies do. They
Speaker 1: may also hold some amount of um commodities like some
Speaker 1: resperity strategies, but they may at various points hold totally
Speaker 1: different things. They may actually hold some amount of crypto
Speaker 1: and some amount of you know, loans, and some amount
Speaker 1: of stocks, and those assequences will have to keep varying.
Speaker 1: It's gonna be a bit of a musical chair strategy.
Speaker 1: And I know it sounds a lot more complex than
Speaker 1: it is, but the unfortunate byproduct of our reality is
Speaker 1: things do get more complex with time, and if you
Speaker 1: stick to you know your traditional approaches, I think you're
Speaker 1: more liable to actually suffer long term and not achieve
Speaker 1: your objectives as an institutional investor. Do you do, uh,
Speaker 1: commodities play a role in in diversification these days, there's
Speaker 1: that chip already say out of it, you already missed
Speaker 1: that boat. I I think they do. But again it's tricky.
Speaker 1: You know. I think a lot of times people say, oh,
Speaker 1: commodities are a good inflation hedge, and in my research
Speaker 1: I found that commodities are good as a hedge against
Speaker 1: inflation shocks, but there not necessarily a hedge against steady
Speaker 1: rising inflation. And there's a lot of factors that figure
Speaker 1: into commodities, especially once you started actively trading around them,
Speaker 1: that are very idiosyncratic. So you know, OPEC doesn't necessarily
Speaker 1: care about your inflation hedge, your your income story when
Speaker 1: they decide, however, to raise or lower supplies. And you know,
Speaker 1: when people in OPEC cheat and actually ignore the supply constraints,
Speaker 1: then you know, it creates a whole different situation. And
Speaker 1: you know, then we have things like, well, if we
Speaker 1: get the infrastructure bill pass, that will certainly send some
Speaker 1: commodities up higher. But if Conversely, people stops, you know,
Speaker 1: spending as much on restaurants, that will send other commodities down.
Speaker 1: So so it's a more complex ecosystem, and I think
Speaker 1: looking at it at a very high level, like as
Speaker 1: just a single as a class, is not a good idea.
Speaker 1: I think commodities are pretty idiosyncratic. So talking about the
Speaker 1: high level, I wanted to ask you about some maybe
Speaker 1: positive catalysts for the stock market, because the idea is, UH,
Speaker 1: sort of the Powell and the FED can move sooner
Speaker 1: and quicker in terms of hikes this year because the
Speaker 1: economic backgroup backdrop is strong, right. And then the second
Speaker 1: part of this is, and I've heard Gina Martin Adams
Speaker 1: talking about this on different interviews that she was giving
Speaker 1: this week, is earnings and how that might sort of
Speaker 1: help support stocks at least in the near term. Yeah,
Speaker 1: I think that the FED starting earlier is good. There's
Speaker 1: obviously some folks who think that OFF is starting late,
Speaker 1: and I I personally don't think they're starting late. I
Speaker 1: think they're starting at the right time, and I think
Speaker 1: they're signaling like signaling it well, So kudos to UH
Speaker 1: to share Powell on I think navigating this about as
Speaker 1: well as possible. I do think that earnings are also
Speaker 1: going to be a very important catalyst, and it's a
Speaker 1: question of not so much what the street expects, but
Speaker 1: what investors expected. We've seen a bit of a divergence there.
Speaker 1: So if we look at the most recent kind of
Speaker 1: you know, Q four earnings that have been released so far,
Speaker 1: I think um generally speaking, beats were punished a little
Speaker 1: bit and losses were punished severely. And that's an important concept, right.
Speaker 1: So that means even the beats on average or not
Speaker 1: quite what investors expected. And that was my fear going
Speaker 1: into this reporting season, is that the actual investor expectations
Speaker 1: were higher than what we were going to see. So
Speaker 1: then the question is, as we go further and as
Speaker 1: we get into you know, like April, are Q one
Speaker 1: expectations going to be more in line. That's gonna be
Speaker 1: again using that training Wovels analogy, the market has to
Speaker 1: peddle on its own. Now the fat is not going
Speaker 1: to come in. I also think it's important to note
Speaker 1: that fate works both ways, and I'm talking about the
Speaker 1: flexible inflation targeting. So just as the fat was comfortable
Speaker 1: with inflation running over the two percent line for a
Speaker 1: while there will be actually be comfortable with inflation running
Speaker 1: below that. So Powell made it very clear when he
Speaker 1: spoke this week that he cares about the labor market
Speaker 1: and not as surprises, asset prices inflating upwards a byproduct
Speaker 1: of the stimulus that needed to be done to help
Speaker 1: the labor market. And I think investors need to really
Speaker 1: internalize that because because I don't think that's a blood
Speaker 1: all right, Max, you know, Valdanna has a blanket on
Speaker 1: her head for this podcast. I'm gonna put my tinfoil
Speaker 1: hat on my head for a minute and uh and
Speaker 1: tell me what you think of this, uh conspiracy theory
Speaker 1: of mine. Actually it's not really a conspiracy theory. I
Speaker 1: don't really believe this is a conspiracy, but I could
Speaker 1: see sort of the monetary and political outcomes uh coming
Speaker 1: out like this, and that is Um. Jerome pal comes
Speaker 1: out this week. He's very hawkish. Um. We've obviously had
Speaker 1: this correction in the stock market. The year goes on,
Speaker 1: we get into the summer, we start lapping the comparisons
Speaker 1: to last year, and we see that maybe inflation has
Speaker 1: cooled off, at least come off the boil off the
Speaker 1: seven percent. That allows pal to get a little more dubbish,
Speaker 1: you know, a little less hawkish perhaps. Uh. In the
Speaker 1: summer early fall, markets rallying again. Uh. By the time
Speaker 1: the mid term election comes around, everyone's forgotten about this
Speaker 1: ugly spell in the markets, and politically it's beneficial to
Speaker 1: Biden and the Democrats. In theory. Again, I don't really
Speaker 1: believe that's a conspiracy theory, but I could see it
Speaker 1: playing out along those lines. But I'm just curious, you know,
Speaker 1: what do you think of that scenario, and what do
Speaker 1: you think about the mid terms in general? I know
Speaker 1: they're traditionally uh, kind of a weak year for equities. Um,
Speaker 1: you know, is that going to be the case this year?
Speaker 1: Is there is there political risk that we're gonna have
Speaker 1: to deal with later in the year or what? Well,
Speaker 1: I think the second part of your question is the easiest. Yes, well,
Speaker 1: you will have to deal with political risk with midterms around.
Speaker 1: They are very important mid terms. I don't want to
Speaker 1: be that guy who comes on you know every time
Speaker 1: versus elections, save this it's the most important election of
Speaker 1: our time, because you know, it's always easy to make
Speaker 1: that comment. I don't think this is this is the
Speaker 1: most important midterm election of our time. I do think
Speaker 1: it's an interesting one as a someone you know who's
Speaker 1: a bit of a political wonk and also market participant
Speaker 1: who trades on that political information. I think there's some
Speaker 1: unique features which are well known, which is one, you
Speaker 1: obviously have a very tight margin and that margin needs
Speaker 1: to be maintained by the Democrats. And I think with
Speaker 1: that you also have these you know, two outliers in
Speaker 1: the Senate who need to come in line at some point,
Speaker 1: and I think they will because I think at the
Speaker 1: end of the day, there are going to choose their
Speaker 1: party and they're gonna want to keep that majority because
Speaker 1: they know if they don't have friends on the other side,
Speaker 1: even though they've skewed pretty close to it, and so
Speaker 1: you know, I think Mansion and Cinema are going to
Speaker 1: eventually support build Back Better, and I think the timing
Speaker 1: of that is going to be important. We know that
Speaker 1: in Washington a lot of times the theatrics are geared
Speaker 1: towards giving you that like last minute conclusion. I think
Speaker 1: that's probably what's gonna happen. And I actually still think
Speaker 1: build Back Better passes that does, by the way, create
Speaker 1: a little bit of a fist put in the markets
Speaker 1: that I don't think it's totally priced in yet, but
Speaker 1: just how much that gives us is a bit of
Speaker 1: an open question. I think there we do want to
Speaker 1: be careful, you know, I wouldn't start overweighing on industrials
Speaker 1: and materials and financials just yet, but I do think
Speaker 1: those are v sectors that can do better from from that,
Speaker 1: and and beyond that, you know, there will be other
Speaker 1: related midterm theatrics that are are going to start happening.
Speaker 1: I think there we're going to start seeing that more
Speaker 1: towards you know, kind of early third quarter UM is
Speaker 1: when things will really start kind of getting interesting from
Speaker 1: a political standpoint, the drama builds, the drama bills. Max.
Speaker 1: I wanted to ask you about some geopolitical risks that
Speaker 1: you're thinking about, because obviously we have a bunch of
Speaker 1: stuff going around Russia and Ukraine, and so how should
Speaker 1: investors be thinking about that. Do you think that some
Speaker 1: of those risks are properly priced in? And what potentially
Speaker 1: would would an escalation mean for the price of oil
Speaker 1: and inflation and so on. Sure, So, so, one thing
Speaker 1: that we know about Russias, they tend to be the
Speaker 1: most aggressive in winter times because they control the heating
Speaker 1: power for Europe and when Putin goes on, and you know,
Speaker 1: this is one one area where it's nice to have
Speaker 1: been born and raised in the country because I can
Speaker 1: actually listen to Putin in Russian speak to Russian Russian public,
Speaker 1: and he uses very colorful language. Let me just put
Speaker 1: it that way. One that I I'm not going to
Speaker 1: say on the podcast, but but he does talk about
Speaker 1: how he can basically freeze all of the people in Europe,
Speaker 1: and there's some truth about it. That's why you never
Speaker 1: see very meaningful sanctions come out. Now. The biggest concern
Speaker 1: for Putin, of course, is that Ukraine somehow becomes part
Speaker 1: of NATO. So that's the that's really the gamble and
Speaker 1: the risk. I do think that a conflict there is likely,
Speaker 1: unfortunately in terms of a kinetic conflict, because you just
Speaker 1: have this powder keg on both sides, and even though
Speaker 1: it's cold, it's very dry, and in the sense that
Speaker 1: anything could spark it off. I think for the markets
Speaker 1: that's not going to be as big of a risk
Speaker 1: as what's going on further out east um and there
Speaker 1: I'm really thinking about China and Taiwan. So last time
Speaker 1: China flew their jets times over Taiwanese airspace definitely a
Speaker 1: very strong signal. I do think Taiwan has perhaps the
Speaker 1: best defense forces of any small nation, and that defense
Speaker 1: force is called t SMC. Taiwanese Semiconductor Company. Is probably
Speaker 1: the best deterrent because it is so vital to all
Speaker 1: other nations around the world that no one can actually
Speaker 1: afford to risk China taking over t SMC. And for
Speaker 1: that reason, you know, even as there kind of saber
Speaker 1: rattling gets louder, I still think it's a big tail risk,
Speaker 1: but it is also a tail risk that I don't
Speaker 1: think we can fully discounts. So that to me is
Speaker 1: kind of the biggest geopolitical risk. But to take your
Speaker 1: question and look at it a little higher level, but
Speaker 1: I think is driving a lot of geopolitical risk. And
Speaker 1: the last i'd say, like five years or so is
Speaker 1: de globalization. And that's a trend that's been pretty secular.
Speaker 1: We've seen a lot of businesses move from just in
Speaker 1: case inventor sorry, from just in time inventory to just
Speaker 1: in case inventory. And what I mean by that is
Speaker 1: it used to be that um, you could realize much
Speaker 1: better margins if you just ordered whatever you needed. You
Speaker 1: had want typically one plant, usually in China or you know,
Speaker 1: another kind of low labor cost country that you'd get
Speaker 1: all of your goods from, and that made for good
Speaker 1: margins and it made for quick um inventory is talking,
Speaker 1: so you didn't need to build up a lot. Well, now,
Speaker 1: since tradewards really began and this deglobalization movement began, you've
Speaker 1: to just in case inventory where you have a factory
Speaker 1: in China, for instance, and then maybe a second factory
Speaker 1: in Vietnam that's able to take on additional capacity necessary.
Speaker 1: So that means companies are no longer as dependent on
Speaker 1: a specific country. And while that can sound good, it
Speaker 1: also lends a political or a politicians more leeway to
Speaker 1: create more strenuous ties with those countries. And that's where
Speaker 1: you know, trade wars as they progress can actually um
Speaker 1: exacerbate because companies have created hedges, if you will, against
Speaker 1: those situations. And and that to me is a more
Speaker 1: concerning secular trend. Fascinating stuff, Max, you know, I it's
Speaker 1: such a great point about Taiwan semiconductor, especially given the
Speaker 1: state of the chip supply chain these days. And also
Speaker 1: I didn't realize Pewton, you know, said they said the
Speaker 1: quiet stuff out loud like that. I thought, you know,
Speaker 1: I know, it's always assumed he could freeze everyone out
Speaker 1: if he wanted to. I didn't realize he actually talked
Speaker 1: about that. That's pretty that's such Tiden up your straight jackets.
Speaker 1: It's time for the craziest things we saw in markets
Speaker 1: this week. I think it's that time. It is that time.
Speaker 1: As I said, I've Telor made my craziest thing for
Speaker 1: the one in a evil Danta Hirich. But I want
Speaker 1: to hear yours first. What's here. I appreciate that after
Speaker 1: my tough bill's loss, but I want to first say
Speaker 1: you and I never explained the blanket thing to our listeners.
Speaker 1: So I want to give a shout out to our
Speaker 1: producer Laura, who makes me and you hide under blankets
Speaker 1: sometimes for better sound quality. So that's that's what we're
Speaker 1: talking about here. I have a bunch of blankets over
Speaker 1: my head. Yeah sometimes I just tied under them. You know. Yeah,
Speaker 1: I know you did, because I'm feeling it, you know. Yeah,
Speaker 1: that's that's fine, that's fine. I think that's okay. Well, okay,
Speaker 1: so first or I guess second. After my my little
Speaker 1: blanket thing, I want to give a second shout out
Speaker 1: to Ben Emmons of Medley Global Advisors. He's a frequent
Speaker 1: guest of the podcast, and he actually wrote something into
Speaker 1: me that I wanted to read out loud. It's not
Speaker 1: exactly markets related, but it's money related, so I'm gonna
Speaker 1: allow it. He sent a USA Today story in the
Speaker 1: headline is a woman finds out she won three million
Speaker 1: dollar lottery prize after checking her email spam folder. So
Speaker 1: thank you Ben for sending that in. I love that,
Speaker 1: and I think it is markets related. I think lottery
Speaker 1: tickets are a fine investment choice, you know. Yeah, sure,
Speaker 1: it's kind of a tail risk fund. I'll all out,
Speaker 1: all out. Yeah. And so that's just a reminder that
Speaker 1: if anybody else has seen anything weird and wants us
Speaker 1: to know about it, you can give us a call
Speaker 1: on the Crazy Things hotline. That's six four six three
Speaker 1: two four three nine zero, leave us a voicemail, hit
Speaker 1: us up on Twitter, and maybe we'll play or talk
Speaker 1: about your weird thing or crazy thing on the show.
Speaker 1: And then for mine, I have a story courtesy of
Speaker 1: another pod friend. It's Crystal Kim. She was on a
Speaker 1: couple of weeks ago and she wrote about the FOMO
Speaker 1: E t F the Fear of missing out E t F.
Speaker 1: I don't know if you saw this story, but this
Speaker 1: fund buys meme names and other sort of popular high
Speaker 1: flying stocks except except right now, it has so many
Speaker 1: dull names in it. But its own manager said the
Speaker 1: strategy puts him to sleep. And the PHONEO et F
Speaker 1: right now is almost in cash. It's the biggest holding
Speaker 1: is Chevron. It has Campbell Soup in there. And then
Speaker 1: I was checking it out and I look for Game
Speaker 1: Stop in AMC and neither one are part of this
Speaker 1: fund anymore. That is pretty fascinating. Well, they're they're not.
Speaker 1: No fear of missing out on the drops in those stocks.
Speaker 1: I guess that's that's pretty good. Yeah, fear of missing
Speaker 1: out on capital preservation, I guess is the theme this week.
Speaker 1: All right, Max, that's pretty good. What do you got first?
Speaker 1: Have you seen anything crazy? I mean, so whenever I
Speaker 1: look for something crazy on on short notice, I tend
Speaker 1: to go to the metaverse. Now and uh, you know,
Speaker 1: you'll you'll never stopped short of kind of fun figures.
Speaker 1: So I'll start, I'll sort of that and then I'll
Speaker 1: drill down to the actual thing that I thought was crazy.
Speaker 1: They just released the data for the fourth quarter of
Speaker 1: virtual land sales in metaverse three million dollars. So that
Speaker 1: was interesting. And you know, we we we know about
Speaker 1: how seeing inflation has been going on in the real world.
Speaker 1: But Sandbox virtual real estate one last month, two lands
Speaker 1: in the center land went for over two point three
Speaker 1: million dollars. So um, I I don't know if that
Speaker 1: means and that's just for the land or you you
Speaker 1: build on them, and if you have to hire like
Speaker 1: virtual developers to you know, come in and build stuff.
Speaker 1: But it seems expensive to me. But but but the
Speaker 1: thing that really got me was someone bought a yacht
Speaker 1: in Sandbox. So it's not land, it's just really a
Speaker 1: virtual yacht that guess you can sail around this virtual world.
Speaker 1: You guys have any guests for how much they paid
Speaker 1: for his virtual yacht? Oh? Well, I think I saw this.
Speaker 1: I want to say half a billion. Well, if if
Speaker 1: that's Mike's guests, I'll go with that too, because I
Speaker 1: did not see this story, and I'm notoriously about at
Speaker 1: guessing did you say half a billion. Yeah, it was
Speaker 1: well that that that would be a lot um No,
Speaker 1: it was half a half a million. It would be
Speaker 1: closer six or so. Yeah, that's by a few zeros there. Yeah,
Speaker 1: so pretty affordable then, uh you know, I guess and yeah,
Speaker 1: and that's like a bargain now actually cheaper than I
Speaker 1: guess a real yacht. So relative to you know, buying
Speaker 1: two point four million dollars for a plot of land,
Speaker 1: maybe that's what's that's what we should be doing now,
Speaker 1: is buying U n F T yachts in uh the metaverse? Max?
Speaker 1: Are you locking in low rates in the metaverse? Buying
Speaker 1: purchasing land over there? I don't know. I mean, I
Speaker 1: I kind of feel like someone does need to do.
Speaker 1: But I'm going to train the AI to figure out
Speaker 1: how to arbitrage different land plots and maybe we can
Speaker 1: become just a virtual landlord, you know. Um, I don't know.
Speaker 1: Didn't someone pay up, pay up big to be like
Speaker 1: Snoop Dogg's neighbor or something like that? There was there
Speaker 1: was a couple of stories about that last year. Um
Speaker 1: so so yeah, and you know it's funny to me.
Speaker 1: So when I was just starting out like writing code.
Speaker 1: It was one of this thing around this is this
Speaker 1: will now date me, Mike, so I'll join you the
Speaker 1: old guy camp. There's a thing called vermal or virtual
Speaker 1: reality markup language. It was. It was kind of started
Speaker 1: like in the mid nineties, and it looked a lot
Speaker 1: like the metaverse. It never took off. No one cared
Speaker 1: about it. It was kind of silly, but you could
Speaker 1: create these three dimensional virtual worlds by just writing like
Speaker 1: kind of very basic code. Well, I mean, maybe you
Speaker 1: know that should have been something I pursued further. I
Speaker 1: don't know, but yeah, yeah, I get that dust off
Speaker 1: those old ploppy disks. I guess. I see kids in
Speaker 1: the in the coffee shops now and they're all wearing
Speaker 1: like nineties clothes, and I feel like, hey, that's my generation.
Speaker 1: You can't wear rape jeans like that and band shirts
Speaker 1: that you know weren't around, uh or haven't been around
Speaker 1: for like twenty years. That's pretty good. Well, the only
Speaker 1: coating I ever did was as a kid. It was basic,
Speaker 1: and it would be like line ten print Mike is cool,
Speaker 1: and then line twenty go to ten and it would
Speaker 1: just scroll rout and then I'd save it on too
Speaker 1: literally a cassette tape on my there's a radio shack.
Speaker 1: I think computer ride. Anyway, I've really dated myself there, boy.
Speaker 1: All right, as loyal listeners will know you're you're what's
Speaker 1: known as a potter Head, not a pothead. I do
Speaker 1: know some potheads, but a potter Head. I love Harry Potter.
Speaker 1: A big fan of Harry Potter. So J. K. Rowling's
Speaker 1: first book, Harry Potter and the Philosopher's Stone, is heading
Speaker 1: to auction. It's a very special edition, one of just
Speaker 1: five hardbacks printed in so it's are you rare gem
Speaker 1: In fact, her name is listed, I believe is Joanne Rolands,
Speaker 1: not even j K. So that's going up for sale.
Speaker 1: Now I want to put you two to the test.
Speaker 1: There's something else going up for sale or went up
Speaker 1: for sale, actually, and that is the hat Milannia Trump
Speaker 1: wore to her first state dinner when her in President
Speaker 1: Trump had the macrons from France over for dinner. That
Speaker 1: sold at auction. Unfortunately, it's sold in soul the Salona
Speaker 1: blockchain currency that that's not doing so well. So so
Speaker 1: here's the prices right for you. Vill Donna, which had
Speaker 1: a higher value the expected value of the Harry Potter
Speaker 1: hard back hardcover or Milannia Trump's big floppy hat that
Speaker 1: she wore to a state dinner UH with with the
Speaker 1: leaders of France UH and his wife. Give me a
Speaker 1: value on each. Okay, you know I told you I've
Speaker 1: been I've been watching Antiques Brow Show recently because I'm
Speaker 1: so bad at guessing this, so it's like preparation for me.
Speaker 1: And they see all the things that come up on
Speaker 1: the show, and I try to guess and I'm always
Speaker 1: way off. Anyway, I'm going with Harry Potter. I have
Speaker 1: to I know what the hat was supposed to go for.
Speaker 1: I believe I think it was something like five hundred
Speaker 1: thousand dollars. I honestly could be misremembering that, but it
Speaker 1: was part of an n f T collection, which you
Speaker 1: forgot to mention. It was like all a big package,
Speaker 1: I believe. But I'm going with Harry Potter. Okay, I'm
Speaker 1: gonna I'm gonna keep a poker face here. Max. As
Speaker 1: a a student of political culture, what do you think
Speaker 1: Philosopher's stone or Melani's hat? Great question, Um, so you're
Speaker 1: gonna get some AI. I want an AI model on
Speaker 1: this stuff. If you can get an AI model on
Speaker 1: my alternative assets, then we're going to be billionaires. There
Speaker 1: is a way to do that again when when you
Speaker 1: guys have me on next time, I might be able
Speaker 1: to share a few more insights. So I'll just leave
Speaker 1: it as a foreshouting with for now. I'll keep my
Speaker 1: you know, human brain working. So I think that if
Speaker 1: we're not hedging for the fact that it was sold
Speaker 1: on Soul, then I would echo what val Donna said
Speaker 1: and go with Harry Potter. I would think that you
Speaker 1: can get seven figures. There's enough Potter heads out there
Speaker 1: who've done well, and I think they could build that up. Conversely,
Speaker 1: despite how successful Trump's spack was initially, I don't think
Speaker 1: there's as many folks who would want the hat and
Speaker 1: also not on n F T S. Yeah, it's it's tricky.
Speaker 1: You have to sort of uh, you know, engauge the
Speaker 1: enthusiasm of Harry Potter fans versus fans of the Trump
Speaker 1: both very enthusiastic fan basis. I would say, um, so
Speaker 1: I will say that Milania's hat was was a disappointment.
Speaker 1: She wanted to think in Soul. Of course, Soul crashed.
Speaker 1: She only got a hundred and seventy thousand dollars for
Speaker 1: the hat, but the Harry Potter book is only expected
Speaker 1: to sell for thirty thousand pounds, so about forty dollars.
Speaker 1: So so, but I kind of agree with both of you.
Speaker 1: I think the Potter heads uh will show up in force.
Speaker 1: And that's just you know, the hat already sold, the
Speaker 1: book has not sold so very well. Could be could
Speaker 1: be a push, but us as far as expected value,
Speaker 1: L I think you should bid on that one, uh
Speaker 1: and see how it goes. Yeah, it's time for me too. Yep.
Speaker 1: All right with that said, I think that is all
Speaker 1: the time we have. Max. Always a pleasure to catch
Speaker 1: up with you, and good luck with the new venture.
Speaker 1: We definitely are gonna have to catch up again and
Speaker 1: have you back on and see how all how it's
Speaker 1: all going. Thanks so much, guys. Always great to catch
Speaker 1: up with you as well. Thank you, Max. What Goes
Speaker 1: Up will be back next week. Until then, you can
Speaker 1: find us on the Bloomberg Terminal website and app or
Speaker 1: wherever you get your podcasts. We'd love it if you
Speaker 1: took the time to rate and review the show on
Speaker 1: Apple Podcasts so more listeners can find us and you
Speaker 1: can find us on Twitter, follow me at Reaganonymous, Wildonta
Speaker 1: Hirich is at Wildonta. Hirich also followed Bloomberg Podcasts at
Speaker 1: Podcasts and thank you to Charlie Pelletta. Bloomberg Radio What
Speaker 1: Goes Up is produced by Laura Carlson. The head of
Speaker 1: Bloomberg Podcast is francesco Leavie. Thanks for listening, See you
Speaker 1: next time, um,