Hello, and welcome to What Goes Up, a weekly markets podcast. My name is Mike Reagan. I'm a senior editor at Bloomberg, and I'm gonna higher across Acid reporter with Bloomberg and this week on the show. Well, if you've been anywhere near the Internet in the last few months, you've probably read a poem, or bits of a movie script, or maybe even some dad jokes that were written by a while a computer. Actually, the Experimental Chat Bought Chat GPT has taken the world by storm since its launched in November, sugaring a million questions about how this type of technology can disrupt various industries and fueling a fresh wave of interest in how artificial intelligence can be used by investors. We're gonna get into it with the head of research at a company that's been using AI for a few years now to pick stocks for an almost two billion dollar ETF. But uh, first, l donna I try to go to chat GPT. I've I've, like everyone else, I've fallen into the hype of this chat GPT, and I went on trying to get it to write us an intro to the podcast, but it's too busy. There are too many people using it that they just turn me down. I tried for you also, so that we can get a nice fun intro from from the robot. And it didn't work. And I even try to trick it. I said, I have a very simple request and I'm on deadline. Please can you help me out? No? Luck, No, robot doesn't like me. I wonder the robot must have a pr REP that maybe we could to complain. Yeah, it's probably a robot pr rep. I don't know. But on a pr rep who that is? Also? Yeah? Yeah, they'll just tell me to go to hell. So is that most of I'm sorry you some of them? Oh my gosh. All right, well you taught me which one. I'll get back to them. But I do think our guest is the perfect guest to unpack this, uh this topic. So why don't you bring him in? Yeah he is. It's Matt Bartolini. He's the head of Spider America's research at Stage Street Global Advisors. And Matt, thanks so much for joining us. Yeah, thank you for having me. So we'll get into one of your AI E t F s in a bit, but maybe just to start, you can give us sort of your journey into working with E t F and what you do. Yeah. Sure, So my journey in TTS is working at State Street Bank essentially since the middle of two thousand's and work my way up throughout the organization on the County team's portfolio management teams and then landed within the E t F teams helping to conduct some of the research on our products, different portfolio construction topics, investment theses, market outlooks, and market commentaries. Uh and that's really where my job is now at the of Spider America's research. You know, our job is to help makes sense of a complex world by using data driven insights, and we write market commentaries, market outlooks, provide some portfolio instruction discussions to end advisors and hopefully help them, you know, select the right investment choice for them. And if that's a Spider et F then I think that's all great, But in some cases it doesn't. And that's how we operate, trying to be fair and balanced. Yea, and uh Ai is obviously one of your areas of research. Match I'm curious, you know, this chat CHPT thing to me, and I think to a lot of people, just can't it seem to have come out of nowhere. You know, it launched in November, and you know, granted I don't follow the space that closely, but I think for a lot of people it was just sort of dumbfounding how good this thing is right at launched, you know it to me, I would have expected sort of a to see a cruder version of this that wasn't quite as impressive. But how did you see it like it was? Were you sort of as surprised as everyone else for the you're sort of research into AI? Had it led you to kind of know this type of thing was possible and in the pipeline? Yeah, So a lot of the AI work we've done is is within sort of portfolio construction and index selection on some of our funds, so we were aware of the ability to use things like natural language processing, predictive text, but also even just in our daily lives. I think some of the functions of Czech GP two we've probably just been benefiting from just in very small morsels, whether that is, you know, auto correcting your text, or the predictive text nature within your iPhone of what you might say next, like that's sort of the same idea, or even you know, when when we use the Bloomberg terminal and we asked the help desk, we sometimes get a very automated response back that's all sort of pieces of it. Uh. The first time I saw it, you know, we were sort of playing around with it of you know, write us a blog post about the benefits of ETFs and it got it probably eighty per correct, you know, how we would want to structure of the argument. And I think that's sort of where chat chypt is is that it kind of gives you about an eight. And now sort of joking with you know, some of my colleagues who have old their kids that you know, chet chypt would probably be be a B minus student if it only ever turned in its homework, because that's kind of the surface level it gets. And I have a friend who's a professor at a college and they've actually started to work on how to figure out you know, essays and reports that are written through AI. And the big thing is you've got to look at the nuance. And chat gypt doesn't really understand the complexity of nuances, particularly for topics like ets where there actually is a lot of operational nuance. You know, as a B bonus student, myself. That explains why I was so impressed. I think if you are a student right now, you could use it to help boost your grades a little bit. Yeah, well that's I think the fear of everyone has. I have a nine year old son who had to do a penguin project and he, instead of looking in a book, he yelled out to Alexa, you know how how fast you to penguin swim? And I had to tell them they can't do that. So the new reality that we're all living in, ask can penguins swim? I don't know what the the ask Alexa, No, don't ask Alexa. Well, no, my kids it's the same thing. They're sitting there doing their homework and I hear them, y'all, hey, Google, what's you know? Nine times thirty seven? And I mean, in some ways, it's just a calculator, and I think educators are gonna have to get used to it and allow it in some to some degree, I don't know, it's it's such a strange new world. But but Matt talked to us about the spider Ken show New Economy ZTF, which actually has been using AI to to pick stocks, you know, for for sort of the Layman among us South there. How how exactly does AI help in this, uh, this stock picking effort. Yeah, So the artificial intelligence behind it is natural language processing and this is run by the index provider S and P. To actually start it over the firm Ken Show there was a small startup that was incubated out of Goldman Sachs. UH SMP bought that firm and all of the I P along with it, and that's our index provider for the fund. And you know the NLP or natural natural Language process and what it does. Scans through UH perspectives and other regulatory filings from companies because you want to start with a strong source. Regulatory filings have to be quite prescriptive and if you, you know, make falsehoods about that, uh, there's penalties, right. UM. So the scans through UH regulatory documents searching for key terms to identify how these firms material operations correlate back to areas of innovation, whether it's like enterprise collaboration, clean energy, advanced transport systems, drones. So scan through all these UM regulatory documents looking for the frequency of a term used, but also the words around it, so you know if a company is saying that drow own technology is incredibly important for the future of growth of our business. That really shows some emphasis towards that type of innovation. So that would be scanned and recorded and classified appropriately into twenty five different areas of innovation, and then from their stocks are weighted and more of a modified equal weighted structure where core firms to a specific innovation are overweighted to non core firms. So basically, the you know, the way we sort of describe it is that the AI process selects the stocks and then there's a quantitative weighting methodology to weight the stocks. But the reason why we went down this path of using AI s that we wanted something forward looking, something dynamic, because you know, back in two thousand and eighteen, we understood that in the E t F world, there weren't a lot of strategies that were this forward looking innovative type paradigm. A lot of it was based on revenue, and revenue was what has already been realized that a backward looking approach, and we wanted something that was more dynamic and a ford looking approach in the AI process was able to deliver that for us. Okay, so before you tell us more about that I am interested in sort of the mechanics. So once the AI runs through and chooses these companies that it fits, that it thinks fits thinks I don't know I thinks is the right word, but that it chooses as fitting the right criteria, do you then have a human go through the results and say, okay, this actually sounds pretty good, or maybe we don't want to have X y Z company as part of this portfolio. So within the index methodology there is sort of a human control element to it, most like a quality control. So for instance, uh, if you know a company is classified as innovating within Clean Energy UM, they use the term your wind and solar are quite significantly that it said it's part of the material operations. But when it comes down to it, there's a check and balance from the index committee to say, okay, well, does firm x y Z offer a product and service in this category or they just some sort of you know, this is probably a bad term, but some sort of shell company that doesn't actually provide a product or service. They just yeah, this isn't what they do. They just say saying something that doesn't correlate back to their actual products and services. So that's where there's a little bit of a manual quality check to ensure that these firms are actually engaged in these areas of innovation and they are not just talking about it sort of you know, extemporaneously. And the other thing is too that helps in terms of you know, get let's say perfect you know, we have a champagne problem that this fund becomes a hundred and ninety billion dollars and someone wants to get into it and they just use the word drone a thousand times to game it. That helps, right, that sort of oat manual overrides sort of quality check. What I find fascinating about it something like five sixty holdings, you know, so it's not not a very concentrated fun and you know, when you're looking for innovative sort of startup type of companies, a lot of times that means really small even maybe microcap companies, uh, that you have to dig through, which are not typically very heavily followed by you know, the Wall Street analysts class just by definition, you know, if there's thousands of them, um, and this really surprised me. Uh. And you know what you say about forty eight percent of the holdings have less than ten analysts covering the stock. Is that almost a benefit for this type of strategy that it helps you sort of find these hidden gems that are maybe being completely overlooked by by the masses out there. Yeah, I mean, AI at its heart is to help increase efficient efficiencies and productivity. And what this does is allows us to cover the uncovered. So if you're using an analyst recommendations, analysts can only cover so many stocks within a given day. And there's candies some firms that are quite innovative, they're you know, performing and producing some really interesting things within our economy. You know, whether it's things within advanced healthcare like wearables that aren't really covered by Wall Street analysts because they might be smaller capitalization securities. And we sort of just know this even from like traditional finance, that the majority of analysts recommendations are in that large caps space um and then small caps and maycaps sort of do you not get as much notoriety or coverage. And AI is basically is one way to solve that problem, to give you a deeper breath of opportunities and really broaden your scope of companies that may be considered innovative. So I want to give a shout out to Katie Greifield and Sam Potter on the Cross has a team at Bloomberg, because they had this really fascinating story that said something like, we asked chat GPT to create an e t F for us, and here's the results, and and actually it had done a really good job putting something together. And you were part of this story. And Katie and I were chatting about it afterwards, and she said, Matt had all these insights into the composition aspect of because you guys have your own AI E t F. And I do wonder about that, like, is the power of the AI being able to create an E t F? Is the power? Does it lie in the sheer amount of work that it can do, whereas you might not be able to have like a team of humans combing through so many different things to the point where they get to an e t F that has five and sixty components. Yeah, it's it's all about creating efficiencies and being able to capture, you know, undiscovered or unrepresented areas within the equity markets. You know, even just looking in core portfolios, disruption happens further down that cap spectrum. And that's why using something that is able to explore data sets that are really unstructured because revenue profiles balances those more structured data sets. But using textual language processing to identify firms based on what their material operations are saying is one way to help classify them into these areas of innovation. And I think one of the things about this fund in particular is that we do understand that it is not innovation does not just benefit the pure place, is that the ecosystem around it can benefit. You know, the whole idea during the gold rush of the eighteen hundreds of it would rather mind for gold or sell the pick axes and the tents to go along with it. You probably had a pretty good business model if you're selling a lot of pick axes in the eighteen hundreds. And that's sort of the idea here is, you know, the ecosystem is also beneficial, and how do you identify that ecosystem? Uh? You know, affirm like Video for example, they make all of the sensory technology with an autonomous vehicles. That's a supplier to that ecosystem. And as autonomous vehicles take off, they're going to benefit as well, so using AI to to detect that can really help create a really targeted, but diversified portfolio of innovative stocks. And basically this e t F has many more components than it would if a team of humans was putting it together. Right, yeah, so the you know the statistic, they're over ten analysts. So let's just say we use that as an example, like we needsily at least be covered by ten ten analysts will right then and there we lose half the portfolio and tends not a big number. So if we were to take more of a human based approach to it, it would be far more concentrated with portfolio. And that's what we see with the other broad innovation e t f s out there, is that they're far more concentrated and they're also far more geared towards large cap security. So you do not get the differentiation that you would want in something that is supposed to be innovative and you know, not largely represented within core portfolio. Is right when this fund was launched, I guess it was three or four years ago. You know, growth stocks, innovative disruptive stocks were you know, the hottest things going in the market, and the funded great, you know, a few thousand and nineteen up thirty seven, two thousand twenty up sixty one percent, up about four twenty one. Then obviously last year was kind of the rug pole out from under growth and innovation down. So I'm wondering, you know, is there a way to layer AI on top of a fund like this to allow to sort of shift to a value strategy or to kind of sniff out the market cycle into what's kind of the the new hot factor to get to UM. I know that's not the goal of this fund, but I wonder if you think about that, you know, is there is there a way to not only pick the the individual stocks under a certain theme or strategy like this, but so also have that strategy sort of evolve over time and try to you know, isolate the upcoming market cycle and what's gonna what's the leadership is gonna be? Uh in case growth does have a down draft like this, So I mean, that's when that becomes just market timing, so to speak. Right, and you're now you're now doing some former factor rotation. You know, I think you could but perhaps create more of a style style neutral innovative portfolio, but that becomes much harder because then you're going to have in an optimization framework, the optimizer is gonna be working really hard to mitigate any of that small cap bias, so and then you're just gonna basically look like you know, a large cap growth tech exposure. So then it's always this trade off of like, do I want to mitigate some of these implicit style factors and get you know, sort of close up that tracking risk to traditional benchmarks, or maintain the purity of what we're trying to do of innovative exposures. So you always try to find that balance. And if you try to create more style neutral or or something that is, you know, less impacted by market cyclical factors, then you're gonna lose some of the purity of your intended focus. And I think when we are having discussion ground performance, we always just go back to attribution and we will use you know, UH fundamental risk models. And if we look at it, since inception, industry and stock selection effects relative to UH, you know, the like the SMP fIF for example, industry and stock selection effects have been positive to UH. The funds return has been a dative to performance. The industry party is interesting because there are some industries like semiconductor software, um you uh, sort of wearable technologies within healthcare, those industries are gonna be more innovative than say some firms within like staples and you're sort of consumer goods products. So industry effects byproduct of the folks of innovation. Stock selection effects is by product of the AI selection methodology and then the waiting um process. The detractors of returns have been style factors, namely higher volatility, lower quality, and high high growth you know, since inception. But those factors are are implicit because it's not what we're we're seeking to obtain. But they're also cyclical. So high volatility, low quality, high growth were being famously rewarded, uh star and through you know sort of mid right, So that was as a tail wind two returns back then. So that's how we always like to frame the performance conversation is breaking those three components out, noting that the style components are going to be cyclical and move in and out based on market directions. I'm always curious how E t F issuers decide on a theme or a topic or you know, putting an e T F together. So a couple of years ago. Was AI something that you guys when you got together, we're thinking was going to be a big deal in the coming years, or is it sort of which I think this happens a lot in the E T F space. Let's just put it out there, give it a try, and see what happens. So it's definitely not the ladder within our firm, We're definitely not that. Yeah, we're we're not gonna be like, hey, this is a hot dot, let's throw it out there and see if it works. You know, that's just not what we do UM with respect these funds. We have a pretty strong heritage within sector and industry investing, and we know that there are thematic investors out there. We see it all the time within our traditional industry suite. You know, someone that wants to play a rally and oil stocks will go by xop our Oil and Gas ETF and that's a thematic investor. And we knew that thematic investing was was going to be UM on the rise because there's some thematics like auntonomous vehicles or cybersecurity or clean energy that are hard to to to gain exposure to under a traditional GETS framework. Because some of these firms are are operate across gig sectors. You know, clean energy is a perfect example. You have firms within the legacy energy sector, the utility sector, industrial sector, technology sector, so you want to go across the sectors. So we were like, well, how do you go about doing this again? We wanted something that was forward looking. We knew that revenue was back with game. So this is how we landed on, you know, firm like Ken Show and then later obviously S and P Ken Show as a combined entity of having a really unique value proposition of using natural language processing to detect firms that are listing out these innovative UM services or innovative corporate designs as part of their material operations. UM. So that's that was really the impetus for it. And I think, you know, I sort of remember one instance. It was I think it was obviously before we launched, was probably time frame when we're really starting to kick the tires on this. The Pokemon vert augmented reality iPhone app was just really really popular. I remember playing softball and seeing a bunch of people like hanging out by the left field tree. We had no idea why, and someone put a Pokemon stay. I don't play this, so I have no idea, and I remember talking to folks and internally like you would be really interesting if we could have something that focused on these type of firms, you know, innovating within virtual reality and augmented reality coincided at the same time as we're kicking the tires on on this process. And that's kind of the idea now, owning twenty stocks and augmented reality, is that, you know, pure play investment thesis for the long term, probably not, but having it part of a more diversified innovative exposure probably is. And that's sort of where we ended up. They were looking for for for Pokey Balls, I think, right, yeah, some rare Pokemon character or something. I don't know. I've never played it either, But do you remember people wandering around turning out their phones, pumped into each other. It was, I think the kind of cave and went though, which is weird, you know, it's it's uh. I almost thought that type of gaming would have caught on more, you know that using that location element of your phone more. But who knows, maybe maybe something is coming. I'm curious just if you can give us kind of a thirty ft view of how you're thinking about AI. Now. Like I said at the beginning, you know this chat GPT does seem to to sort of us layman like a big innovation, Like suddenly the innovation in in AI has accelerated faster than I think UM people realized. UM tell me if you agree with that or disagree, But also UM, in general, where do you see AI? What industries do you see being most susceptible to disruption from AI going forward? Yeah, I mean I think for the most part, you know, AI investment I think is projected to increase something in respected like a fift percent over the next three years. That, like, the statistics around AI investment is astounding. You see it every day, big numbers, big percentages. I think from an industry perspective, something that like paralegal services could be something like that UM research documentation. We're able to scan something very quickly, and I think you can even see that and some of the McKenzie studies that you talk about, how you know upwards of the workforce we need to change jobs as a result of advances in the artificial intelligence. Legal requests are are likely to be one of those because you know, going and pulling all of the specific you know, court cases over the last fifty years. Really the one topic you know that could be done quite easily through natural language processing is you know, using predictive tax searching for tax I think that's just one one of those. Just even within my team, we're trying to use some form of AI to help, you know, right, weekly notes for us, it's something that you know, some I put out on our plans for this year is just you know, again creating more efficiencies and some of the weekly notes are more about you know, fun flows and market performance and you're having something easily done quicker that there's also can be helped from a compliance perspective too, because everything's rublespaced. But yeah, that's the legal one of always ones that comes to mind any sort of documents search, document retrieval, UM. Those that's where a I think is some of the more low hung fruits. It doesn't sound as flashy, but you know that's um that's one Well, if you're a law firm, you're certainly gonna save a boatload of money, uh if you can you know, hire a fewer paralegals to do all that. That's sort of leg work. But I think podcast hosts are totally fine, right, don't chinx us, Yeah, don't chin us. I don't know that chat JBT wrote wrote some pretty good dad jokes, So I'm feeling threatened you might be out of that job. Yeah, even kind of. I mean, who would have thought that, you know, they would could create a young Luke Skywalker and the most recent or last seasons of the Mandalorian. You know, all of a sudden they can use you know, AI and some of the other stuff to create different voice structures. Who knows. I think podcast has have a go, have a good chance of out last night for at least the next twenty years. Fun fun podcast hosts. Maybe just to bring it back to the market, I'm wondering, like which sectors maybe can stand to benefit the most from AI. That sort of tough because I think, you know, obviously within technology, a lot of firms for already starting to use AI and their processes. I would probably say within the industrial sector for supply chain logistics, um, other sort of you know, consumer oriented areas in terms of consumer service. So you can obviously already see it with Amazon and some of the way they interact with consumers and using AI. Um, I would say probably those three probably the biggest round industrials. You know, you can supply chain and then consumer and then tech is just going to benefit because they're the ones sort of creating the innovation. Yeah, yeah, mat I know. So we've been talking all out about AI, which is one of your focuses, but not not the only ones. So I'm curious if you can just give us kind of the state of play in the TF market as a whole. You know, what, what kind of flows are you seeing? Uh this year? You know, market obviously off to this super strong start, growth and innovation doing well again. Where are you seeing the flows? Are people chasing that sort of rebound in innovation and growth or they still going into value? What's uh? What do the flows look like? Yeah, so thematic ETFs last year in two actually had outflows, and they had outflows for the first time since two thousand and thirteen. Now k OMP actually had inflows. A little bit of a divergence there, um maybe speaking to our efforts, but a lot of it was for our performance related. Roughly of all thematic ETFs on the et F industry beat the SP five hundred last year. That's actually been different this year. This year we're around eighties. Six of thematic ets are beating the sp five hundred. Yet at the end of January flows we're still negative for the broader category. So ETF investors are still little skeptical, which I think is not too surprising given the dour performance results from last year UM. But you know, again within our suite we've actually seen influence which you know, perhaps speaks to the efficacy of the UM, the product type, the structure, the rationale on the investor motivation. Matt, we can't let you go without asking you about Spy, which is probably the best known at F out there, and it just turned thirty years old. So happy birthday, just SPI. I know you guys through it a couple of birthday parties, but can you maybe tell us about this like it's been around for thirty years ow I think we had a story on Bloomberg saying, you know, it's held the crown for so long, but can it continue to hold on to this sort of the crown of being the most prominent and well known e t F. So maybe just tell us about by a little bit, just because we have you here and you're the sort of pre eminent figure I'm talking about this. Yeah, so I mean Spy. Like I said, you know, without Spy, there's a lot there's no k MP, but there's not a lot of other e t f s out there. It started the industry. U. The infrastructure that it has is the reason why we do have ETFs, the ability to in kind creation redemption. UH. And it's been time tested throughout those past thirty years. And well, I think this year taught us it. Spy had a record amount of users come to that product in terms of it had nine and a half trillion dollars of trading volume. It had a record amount of overall shares traded and you know, roughly uh is of all trading volume in et fs was on it was on Spy. UM. So I think that's just really you know, a good indicator of UM how much usage it still gets even though it's thirty years after its inception. And it was interesting we were talking with jet Chat GPT earlier that when you do ask chat GPT what is the best et F, it does come back Spy. And I think it's with reason. You know, it's it's the biggest, it's the most liquid, it's the longest trajectory um and for that reason, chat GPT recognizes being one of the better ets out in the marketplace, bringing in full circle there. I like it. Oh, Matt Bartolini's the head of Spider's America's research at State Street Global Advisors. Great stuff. We really appreciate your time. We cannot let you go though, and so uh we hear the craziest thing you've seen in markets this week? Data as always, why don't you get us started? Okay, So mine is in crypto this week, and it's this report by chain Alis this which I don't know if you don't know about the analysis. They sort of do like forensics basically of the blockchain and within the crypto space. So it's interesting that such a report will come from a crypto company specifically, But basically, they found that thieves stole a record three point eight billion dollars worth of cryptocurrency last year, and at North Korea itself, it's estimated uh still one point seven billion dollars in up from four million the year prior, which is just crazy amounts of money. Because you know, it's people in crypto don't like to talk about this aspect of crypto, but then you have this crypto company actually coming out with this report talking about if that's that's at current market prices were at it Probably it's probably at the price of the assets when they were stolen, I would imagine, But I would think so, yeah, I would think so, But I mean, yeah, but even if you think about where bitcoin was yeah a couple of months ago versus not. Yes, And they probably don't answer for this in that report. But I wonder how much of that is sort of trapped you have. Can you steal some crypto and it's stuck in a while and everyone knows it's there, and it's it's sometimes hard to launder that. I'd be curious to see how much of that actually, you know, these thieves are enjoying the benefits of that at the Yeah, there are some companies, some crypto like researchers that look into when sizeable sums of coins are moved, or like nineteen thousand coins that hadn't moved in ten years or some which I really interested. That's when you never know where they're going with That's when the thirties always catch them. Two is the minute you try to move it, and the something else than the exactly the FBI is watching. That's a pretty good How about you, Matt, you see anything crazy recently? I mean, I actually one of the craziest things the market reaction to the most recent Federal Reserve great hike I didn't think would be that overwhelmingly positive. Powell was still pretty persistent on the need to hike rate um and right now you have a two year yield that is roughly fifty basis points below what the Fed funds is and that doesn't really happen. I think that's pretty crazy. Is that, you know, borrowing money two years out is cheaper than overnight rates at the Reserve. So I think that's I'd be interesting what happens in the ensuing days if that course corrects. Yeah, that is a It is a bizarre upside down world. And uh, I don't think the market reaction was anything what he hadn't sended. I've joked that Palp should probably have a Bloomberg terminal in front of him when he's giving the press conference to it to amend his answers to to have the desired effect, because I don't think I don't think that's what he was after that day. But we should send him. Yeah, I bet he. Well he I'm assuming he has one. I know, I think he has one. All right, we'll give you mine. Yeah, well do as i've You know, I'm not really a car guy. I'm more of a pedestrian. But I real. But what happened to those four portions? Yeah, they're they're still imaginary. They still are imaginary. I am into when people pay ridiculous prices for collectible items. As you know though, So the story's courtesy of CNN. So if you ever heard of the car company Bugatti, they make these like hot rods, supercars. They call them. Uh yeah, I heard you have two of them? Yes, yes, matchbox size. But so Bugatti apparently is transitioning to electric. They're gonna go hybrid first. Um, but they're done making uh strictly gas powered cars. So they recently produced the last pure gas line powered car they're ever gonna make. It's a um, I'm probably gonna butcher this pronunciation. The Bugatti cheron profably. I believe I didn't take French, but I have something like that. So when up for auction, they instead of just selling it, they put it up for auctions with Southern beas I believe. I'm just gonna tell you what it went for on auction. It's boring to to name the price. Uh, ten points ten point seven million. This car million, brand new car set a record for the highest priced new car sold at auction. But what I'm gonna make you guys square off against each other in our game show is what do you think the max speed is that this vehicle is capable of reaching the fastest it can go? Oh my gosh, in miles per hour for ten point seven million dollar car? How fast do you think you get to go in that car when you flo It's only fair if we can name it in kilometers. All feel free to do that, but you need to translate it to miles for me, like like, oh my gosh, um, I'm guessing it's not as high. But I really I know nothing about cars. Am I going first? There's not going first? I think you go first? Yeah, fine, I'm gonna go with two sixty two d and sixty miles an hour. I don't know. Is that a lot? That's a lot that's way too much? A lot that's like a plane here? I would say I would probably like too, Oh my gosh, I think we uh I think we have our first tie in the Prices Precise to thirty six. Wow, so you guys are pretty close. Although traditional rules she went over vill Donna's, I think we gotta give it some run over. It's fine, the guests can win. That's that's right here, Prices Precise rules. Don't get our lawyers involved. This is called the Prices Precise Yet. Here is the crazier thing, though, is that's not the fastest car got he's ever sold. The fastest could go three hundred miles an hour, they say, quote in theory, and I'm not sure everyone anyone's ever managed to get it up to three hundred. I don't know if you could. Tom Cruise would if you gave him a chance for one of his good It's probably has several of these, but I'm not sure if you could. Theoretically, if you could drive a car three hundred miles an hour, I feel like it would take off like a rocket ship at that point, like I would my heart would burst from it, like I'd be so scared. You definitely have to live. If you're driving that fast, you gotta listen to your podcasts at double speed. I think so if we have any boogotten drivers out there allow them to double speed us two x X. Yeah, pretty good, though you guys are both in the ballpark. I'm not sure what I would have I would have guessed. I'm not sure if I would have gone over two hundred. It just seems insane to drive over two hundred miles an hour. But anyway, you don't go. You don't go two hundred miles an hour in the New Jersey Turnpike. Well, New Jersey Transit I do. Yeah, that's the when we're late anyway, Matt Partalini from State Treet Global ADVISORSS just real honor to be able to pick your brain on all these topics. Uh, wish you all the best and hopefully you'll come back and talk to us again some day. Yeah, thanks, thanks Matt, what goes up? We'll be back next week. And so then you can find us on the Bloomberg Terminal website and app or wherever you get your podcasts. We love it if you took the time to rate and review the show on Apple Podcasts, so more listeners can find us, and you can find us on Twitter, follow me at reag Anonymous, Bill Donna hierarch Is at Bildonna Hirach. You can also follow Bloomberg Podcasts at Podcasts. What Goes Up is produced by Stacy Wang. Thanks for listening, See you next time.

Hello, and welcome to What Goes Up, a weekly markets podcast. My name is Mike Reagan. I'm a senior editor at Bloomberg, and I'm gonna higher across Acid reporter with Bloomberg and this week on the show. Well, if you've been anywhere near the Internet in the last few months, you've probably read a poem, or bits of a movie script, or maybe even some dad jokes that were written by a while a computer. Actually, the Experimental Chat Bought Chat GPT has taken the world by storm since its launched in November, sugaring a million questions about how this type of technology can disrupt various industries and fueling a fresh wave of interest in how artificial intelligence can be used by investors. We're gonna get into it with the head of research at a company that's been using AI for a few years now to pick stocks for an almost two billion dollar ETF. But uh, first, l donna I try to go to chat GPT. I've I've, like everyone else, I've fallen into the hype of this chat GPT, and I went on trying to get it to write us an intro to the podcast, but it's too busy. There are too many people using it that they just turn me down. I tried for you also, so that we can get a nice fun intro from from the robot. And it didn't work. And I even try to trick it. I said, I have a very simple request and I'm on deadline. Please can you help me out? No? Luck, No, robot doesn't like me. I wonder the robot must have a pr REP that maybe we could to complain. Yeah, it's probably a robot pr rep. I don't know. But on a pr rep who that is? Also? Yeah? Yeah, they'll just tell me to go to hell. So is that most of I'm sorry you some of them? Oh my gosh. All right, well you taught me which one. I'll get back to them. But I do think our guest is the perfect guest to unpack this, uh this topic. So why don't you bring him in? Yeah he is. It's Matt Bartolini. He's the head of Spider America's research at Stage Street Global Advisors. And Matt, thanks so much for joining us. Yeah, thank you for having me. So we'll get into one of your AI E t F s in a bit, but maybe just to start, you can give us sort of your journey into working with E t F and what you do. Yeah. Sure, So my journey in TTS is working at State Street Bank essentially since the middle of two thousand's and work my way up throughout the organization on the County team's portfolio management teams and then landed within the E t F teams helping to conduct some of the research on our products, different portfolio construction topics, investment theses, market outlooks, and market commentaries. Uh and that's really where my job is now at the of Spider America's research. You know, our job is to help makes sense of a complex world by using data driven insights, and we write market commentaries, market outlooks, provide some portfolio instruction discussions to end advisors and hopefully help them, you know, select the right investment choice for them. And if that's a Spider et F then I think that's all great, But in some cases it doesn't. And that's how we operate, trying to be fair and balanced. Yea, and uh Ai is obviously one of your areas of research. Match I'm curious, you know, this chat CHPT thing to me, and I think to a lot of people, just can't it seem to have come out of nowhere. You know, it launched in November, and you know, granted I don't follow the space that closely, but I think for a lot of people it was just sort of dumbfounding how good this thing is right at launched, you know it to me, I would have expected sort of a to see a cruder version of this that wasn't quite as impressive. But how did you see it like it was? Were you sort of as surprised as everyone else for the you're sort of research into AI? Had it led you to kind of know this type of thing was possible and in the pipeline? Yeah, So a lot of the AI work we've done is is within sort of portfolio construction and index selection on some of our funds, so we were aware of the ability to use things like natural language processing, predictive text, but also even just in our daily lives. I think some of the functions of Czech GP two we've probably just been benefiting from just in very small morsels, whether that is, you know, auto correcting your text, or the predictive text nature within your iPhone of what you might say next, like that's sort of the same idea, or even you know, when when we use the Bloomberg terminal and we asked the help desk, we sometimes get a very automated response back that's all sort of pieces of it. Uh. The first time I saw it, you know, we were sort of playing around with it of you know, write us a blog post about the benefits of ETFs and it got it probably eighty per correct, you know, how we would want to structure of the argument. And I think that's sort of where chat chypt is is that it kind of gives you about an eight. And now sort of joking with you know, some of my colleagues who have old their kids that you know, chet chypt would probably be be a B minus student if it only ever turned in its homework, because that's kind of the surface level it gets. And I have a friend who's a professor at a college and they've actually started to work on how to figure out you know, essays and reports that are written through AI. And the big thing is you've got to look at the nuance. And chat gypt doesn't really understand the complexity of nuances, particularly for topics like ets where there actually is a lot of operational nuance. You know, as a B bonus student, myself. That explains why I was so impressed. I think if you are a student right now, you could use it to help boost your grades a little bit. Yeah, well that's I think the fear of everyone has. I have a nine year old son who had to do a penguin project and he, instead of looking in a book, he yelled out to Alexa, you know how how fast you to penguin swim? And I had to tell them they can't do that. So the new reality that we're all living in, ask can penguins swim? I don't know what the the ask Alexa, No, don't ask Alexa. Well, no, my kids it's the same thing. They're sitting there doing their homework and I hear them, y'all, hey, Google, what's you know? Nine times thirty seven? And I mean, in some ways, it's just a calculator, and I think educators are gonna have to get used to it and allow it in some to some degree, I don't know, it's it's such a strange new world. But but Matt talked to us about the spider Ken show New Economy ZTF, which actually has been using AI to to pick stocks, you know, for for sort of the Layman among us South there. How how exactly does AI help in this, uh, this stock picking effort. Yeah, So the artificial intelligence behind it is natural language processing and this is run by the index provider S and P. To actually start it over the firm Ken Show there was a small startup that was incubated out of Goldman Sachs. UH SMP bought that firm and all of the I P along with it, and that's our index provider for the fund. And you know the NLP or natural natural Language process and what it does. Scans through UH perspectives and other regulatory filings from companies because you want to start with a strong source. Regulatory filings have to be quite prescriptive and if you, you know, make falsehoods about that, uh, there's penalties, right. UM. So the scans through UH regulatory documents searching for key terms to identify how these firms material operations correlate back to areas of innovation, whether it's like enterprise collaboration, clean energy, advanced transport systems, drones. So scan through all these UM regulatory documents looking for the frequency of a term used, but also the words around it, so you know if a company is saying that drow own technology is incredibly important for the future of growth of our business. That really shows some emphasis towards that type of innovation. So that would be scanned and recorded and classified appropriately into twenty five different areas of innovation, and then from their stocks are weighted and more of a modified equal weighted structure where core firms to a specific innovation are overweighted to non core firms. So basically, the you know, the way we sort of describe it is that the AI process selects the stocks and then there's a quantitative weighting methodology to weight the stocks. But the reason why we went down this path of using AI s that we wanted something forward looking, something dynamic, because you know, back in two thousand and eighteen, we understood that in the E t F world, there weren't a lot of strategies that were this forward looking innovative type paradigm. A lot of it was based on revenue, and revenue was what has already been realized that a backward looking approach, and we wanted something that was more dynamic and a ford looking approach in the AI process was able to deliver that for us. Okay, so before you tell us more about that I am interested in sort of the mechanics. So once the AI runs through and chooses these companies that it fits, that it thinks fits thinks I don't know I thinks is the right word, but that it chooses as fitting the right criteria, do you then have a human go through the results and say, okay, this actually sounds pretty good, or maybe we don't want to have X y Z company as part of this portfolio. So within the index methodology there is sort of a human control element to it, most like a quality control. So for instance, uh, if you know a company is classified as innovating within Clean Energy UM, they use the term your wind and solar are quite significantly that it said it's part of the material operations. But when it comes down to it, there's a check and balance from the index committee to say, okay, well, does firm x y Z offer a product and service in this category or they just some sort of you know, this is probably a bad term, but some sort of shell company that doesn't actually provide a product or service. They just yeah, this isn't what they do. They just say saying something that doesn't correlate back to their actual products and services. So that's where there's a little bit of a manual quality check to ensure that these firms are actually engaged in these areas of innovation and they are not just talking about it sort of you know, extemporaneously. And the other thing is too that helps in terms of you know, get let's say perfect you know, we have a champagne problem that this fund becomes a hundred and ninety billion dollars and someone wants to get into it and they just use the word drone a thousand times to game it. That helps, right, that sort of oat manual overrides sort of quality check. What I find fascinating about it something like five sixty holdings, you know, so it's not not a very concentrated fun and you know, when you're looking for innovative sort of startup type of companies, a lot of times that means really small even maybe microcap companies, uh, that you have to dig through, which are not typically very heavily followed by you know, the Wall Street analysts class just by definition, you know, if there's thousands of them, um, and this really surprised me. Uh. And you know what you say about forty eight percent of the holdings have less than ten analysts covering the stock. Is that almost a benefit for this type of strategy that it helps you sort of find these hidden gems that are maybe being completely overlooked by by the masses out there. Yeah, I mean, AI at its heart is to help increase efficient efficiencies and productivity. And what this does is allows us to cover the uncovered. So if you're using an analyst recommendations, analysts can only cover so many stocks within a given day. And there's candies some firms that are quite innovative, they're you know, performing and producing some really interesting things within our economy. You know, whether it's things within advanced healthcare like wearables that aren't really covered by Wall Street analysts because they might be smaller capitalization securities. And we sort of just know this even from like traditional finance, that the majority of analysts recommendations are in that large caps space um and then small caps and maycaps sort of do you not get as much notoriety or coverage. And AI is basically is one way to solve that problem, to give you a deeper breath of opportunities and really broaden your scope of companies that may be considered innovative. So I want to give a shout out to Katie Greifield and Sam Potter on the Cross has a team at Bloomberg, because they had this really fascinating story that said something like, we asked chat GPT to create an e t F for us, and here's the results, and and actually it had done a really good job putting something together. And you were part of this story. And Katie and I were chatting about it afterwards, and she said, Matt had all these insights into the composition aspect of because you guys have your own AI E t F. And I do wonder about that, like, is the power of the AI being able to create an E t F? Is the power? Does it lie in the sheer amount of work that it can do, whereas you might not be able to have like a team of humans combing through so many different things to the point where they get to an e t F that has five and sixty components. Yeah, it's it's all about creating efficiencies and being able to capture, you know, undiscovered or unrepresented areas within the equity markets. You know, even just looking in core portfolios, disruption happens further down that cap spectrum. And that's why using something that is able to explore data sets that are really unstructured because revenue profiles balances those more structured data sets. But using textual language processing to identify firms based on what their material operations are saying is one way to help classify them into these areas of innovation. And I think one of the things about this fund in particular is that we do understand that it is not innovation does not just benefit the pure place, is that the ecosystem around it can benefit. You know, the whole idea during the gold rush of the eighteen hundreds of it would rather mind for gold or sell the pick axes and the tents to go along with it. You probably had a pretty good business model if you're selling a lot of pick axes in the eighteen hundreds. And that's sort of the idea here is, you know, the ecosystem is also beneficial, and how do you identify that ecosystem? Uh? You know, affirm like Video for example, they make all of the sensory technology with an autonomous vehicles. That's a supplier to that ecosystem. And as autonomous vehicles take off, they're going to benefit as well, so using AI to to detect that can really help create a really targeted, but diversified portfolio of innovative stocks. And basically this e t F has many more components than it would if a team of humans was putting it together. Right, yeah, so the you know the statistic, they're over ten analysts. So let's just say we use that as an example, like we needsily at least be covered by ten ten analysts will right then and there we lose half the portfolio and tends not a big number. So if we were to take more of a human based approach to it, it would be far more concentrated with portfolio. And that's what we see with the other broad innovation e t f s out there, is that they're far more concentrated and they're also far more geared towards large cap security. So you do not get the differentiation that you would want in something that is supposed to be innovative and you know, not largely represented within core portfolio. Is right when this fund was launched, I guess it was three or four years ago. You know, growth stocks, innovative disruptive stocks were you know, the hottest things going in the market, and the funded great, you know, a few thousand and nineteen up thirty seven, two thousand twenty up sixty one percent, up about four twenty one. Then obviously last year was kind of the rug pole out from under growth and innovation down. So I'm wondering, you know, is there a way to layer AI on top of a fund like this to allow to sort of shift to a value strategy or to kind of sniff out the market cycle into what's kind of the the new hot factor to get to UM. I know that's not the goal of this fund, but I wonder if you think about that, you know, is there is there a way to not only pick the the individual stocks under a certain theme or strategy like this, but so also have that strategy sort of evolve over time and try to you know, isolate the upcoming market cycle and what's gonna what's the leadership is gonna be? Uh in case growth does have a down draft like this, So I mean, that's when that becomes just market timing, so to speak. Right, and you're now you're now doing some former factor rotation. You know, I think you could but perhaps create more of a style style neutral innovative portfolio, but that becomes much harder because then you're going to have in an optimization framework, the optimizer is gonna be working really hard to mitigate any of that small cap bias, so and then you're just gonna basically look like you know, a large cap growth tech exposure. So then it's always this trade off of like, do I want to mitigate some of these implicit style factors and get you know, sort of close up that tracking risk to traditional benchmarks, or maintain the purity of what we're trying to do of innovative exposures. So you always try to find that balance. And if you try to create more style neutral or or something that is, you know, less impacted by market cyclical factors, then you're gonna lose some of the purity of your intended focus. And I think when we are having discussion ground performance, we always just go back to attribution and we will use you know, UH fundamental risk models. And if we look at it, since inception, industry and stock selection effects relative to UH, you know, the like the SMP fIF for example, industry and stock selection effects have been positive to UH. The funds return has been a dative to performance. The industry party is interesting because there are some industries like semiconductor software, um you uh, sort of wearable technologies within healthcare, those industries are gonna be more innovative than say some firms within like staples and you're sort of consumer goods products. So industry effects byproduct of the folks of innovation. Stock selection effects is by product of the AI selection methodology and then the waiting um process. The detractors of returns have been style factors, namely higher volatility, lower quality, and high high growth you know, since inception. But those factors are are implicit because it's not what we're we're seeking to obtain. But they're also cyclical. So high volatility, low quality, high growth were being famously rewarded, uh star and through you know sort of mid right, So that was as a tail wind two returns back then. So that's how we always like to frame the performance conversation is breaking those three components out, noting that the style components are going to be cyclical and move in and out based on market directions. I'm always curious how E t F issuers decide on a theme or a topic or you know, putting an e T F together. So a couple of years ago. Was AI something that you guys when you got together, we're thinking was going to be a big deal in the coming years, or is it sort of which I think this happens a lot in the E T F space. Let's just put it out there, give it a try, and see what happens. So it's definitely not the ladder within our firm, We're definitely not that. Yeah, we're we're not gonna be like, hey, this is a hot dot, let's throw it out there and see if it works. You know, that's just not what we do UM with respect these funds. We have a pretty strong heritage within sector and industry investing, and we know that there are thematic investors out there. We see it all the time within our traditional industry suite. You know, someone that wants to play a rally and oil stocks will go by xop our Oil and Gas ETF and that's a thematic investor. And we knew that thematic investing was was going to be UM on the rise because there's some thematics like auntonomous vehicles or cybersecurity or clean energy that are hard to to to gain exposure to under a traditional GETS framework. Because some of these firms are are operate across gig sectors. You know, clean energy is a perfect example. You have firms within the legacy energy sector, the utility sector, industrial sector, technology sector, so you want to go across the sectors. So we were like, well, how do you go about doing this again? We wanted something that was forward looking. We knew that revenue was back with game. So this is how we landed on, you know, firm like Ken Show and then later obviously S and P Ken Show as a combined entity of having a really unique value proposition of using natural language processing to detect firms that are listing out these innovative UM services or innovative corporate designs as part of their material operations. UM. So that's that was really the impetus for it. And I think, you know, I sort of remember one instance. It was I think it was obviously before we launched, was probably time frame when we're really starting to kick the tires on this. The Pokemon vert augmented reality iPhone app was just really really popular. I remember playing softball and seeing a bunch of people like hanging out by the left field tree. We had no idea why, and someone put a Pokemon stay. I don't play this, so I have no idea, and I remember talking to folks and internally like you would be really interesting if we could have something that focused on these type of firms, you know, innovating within virtual reality and augmented reality coincided at the same time as we're kicking the tires on on this process. And that's kind of the idea now, owning twenty stocks and augmented reality, is that, you know, pure play investment thesis for the long term, probably not, but having it part of a more diversified innovative exposure probably is. And that's sort of where we ended up. They were looking for for for Pokey Balls, I think, right, yeah, some rare Pokemon character or something. I don't know. I've never played it either, But do you remember people wandering around turning out their phones, pumped into each other. It was, I think the kind of cave and went though, which is weird, you know, it's it's uh. I almost thought that type of gaming would have caught on more, you know that using that location element of your phone more. But who knows, maybe maybe something is coming. I'm curious just if you can give us kind of a thirty ft view of how you're thinking about AI. Now. Like I said at the beginning, you know this chat GPT does seem to to sort of us layman like a big innovation, Like suddenly the innovation in in AI has accelerated faster than I think UM people realized. UM tell me if you agree with that or disagree, But also UM, in general, where do you see AI? What industries do you see being most susceptible to disruption from AI going forward? Yeah, I mean I think for the most part, you know, AI investment I think is projected to increase something in respected like a fift percent over the next three years. That, like, the statistics around AI investment is astounding. You see it every day, big numbers, big percentages. I think from an industry perspective, something that like paralegal services could be something like that UM research documentation. We're able to scan something very quickly, and I think you can even see that and some of the McKenzie studies that you talk about, how you know upwards of the workforce we need to change jobs as a result of advances in the artificial intelligence. Legal requests are are likely to be one of those because you know, going and pulling all of the specific you know, court cases over the last fifty years. Really the one topic you know that could be done quite easily through natural language processing is you know, using predictive tax searching for tax I think that's just one one of those. Just even within my team, we're trying to use some form of AI to help, you know, right, weekly notes for us, it's something that you know, some I put out on our plans for this year is just you know, again creating more efficiencies and some of the weekly notes are more about you know, fun flows and market performance and you're having something easily done quicker that there's also can be helped from a compliance perspective too, because everything's rublespaced. But yeah, that's the legal one of always ones that comes to mind any sort of documents search, document retrieval, UM. Those that's where a I think is some of the more low hung fruits. It doesn't sound as flashy, but you know that's um that's one Well, if you're a law firm, you're certainly gonna save a boatload of money, uh if you can you know, hire a fewer paralegals to do all that. That's sort of leg work. But I think podcast hosts are totally fine, right, don't chinx us, Yeah, don't chin us. I don't know that chat JBT wrote wrote some pretty good dad jokes, So I'm feeling threatened you might be out of that job. Yeah, even kind of. I mean, who would have thought that, you know, they would could create a young Luke Skywalker and the most recent or last seasons of the Mandalorian. You know, all of a sudden they can use you know, AI and some of the other stuff to create different voice structures. Who knows. I think podcast has have a go, have a good chance of out last night for at least the next twenty years. Fun fun podcast hosts. Maybe just to bring it back to the market, I'm wondering, like which sectors maybe can stand to benefit the most from AI. That sort of tough because I think, you know, obviously within technology, a lot of firms for already starting to use AI and their processes. I would probably say within the industrial sector for supply chain logistics, um, other sort of you know, consumer oriented areas in terms of consumer service. So you can obviously already see it with Amazon and some of the way they interact with consumers and using AI. Um, I would say probably those three probably the biggest round industrials. You know, you can supply chain and then consumer and then tech is just going to benefit because they're the ones sort of creating the innovation. Yeah, yeah, mat I know. So we've been talking all out about AI, which is one of your focuses, but not not the only ones. So I'm curious if you can just give us kind of the state of play in the TF market as a whole. You know, what, what kind of flows are you seeing? Uh this year? You know, market obviously off to this super strong start, growth and innovation doing well again. Where are you seeing the flows? Are people chasing that sort of rebound in innovation and growth or they still going into value? What's uh? What do the flows look like? Yeah, so thematic ETFs last year in two actually had outflows, and they had outflows for the first time since two thousand and thirteen. Now k OMP actually had inflows. A little bit of a divergence there, um maybe speaking to our efforts, but a lot of it was for our performance related. Roughly of all thematic ETFs on the et F industry beat the SP five hundred last year. That's actually been different this year. This year we're around eighties. Six of thematic ets are beating the sp five hundred. Yet at the end of January flows we're still negative for the broader category. So ETF investors are still little skeptical, which I think is not too surprising given the dour performance results from last year UM. But you know, again within our suite we've actually seen influence which you know, perhaps speaks to the efficacy of the UM, the product type, the structure, the rationale on the investor motivation. Matt, we can't let you go without asking you about Spy, which is probably the best known at F out there, and it just turned thirty years old. So happy birthday, just SPI. I know you guys through it a couple of birthday parties, but can you maybe tell us about this like it's been around for thirty years ow I think we had a story on Bloomberg saying, you know, it's held the crown for so long, but can it continue to hold on to this sort of the crown of being the most prominent and well known e t F. So maybe just tell us about by a little bit, just because we have you here and you're the sort of pre eminent figure I'm talking about this. Yeah, so I mean Spy. Like I said, you know, without Spy, there's a lot there's no k MP, but there's not a lot of other e t f s out there. It started the industry. U. The infrastructure that it has is the reason why we do have ETFs, the ability to in kind creation redemption. UH. And it's been time tested throughout those past thirty years. And well, I think this year taught us it. Spy had a record amount of users come to that product in terms of it had nine and a half trillion dollars of trading volume. It had a record amount of overall shares traded and you know, roughly uh is of all trading volume in et fs was on it was on Spy. UM. So I think that's just really you know, a good indicator of UM how much usage it still gets even though it's thirty years after its inception. And it was interesting we were talking with jet Chat GPT earlier that when you do ask chat GPT what is the best et F, it does come back Spy. And I think it's with reason. You know, it's it's the biggest, it's the most liquid, it's the longest trajectory um and for that reason, chat GPT recognizes being one of the better ets out in the marketplace, bringing in full circle there. I like it. Oh, Matt Bartolini's the head of Spider's America's research at State Street Global Advisors. Great stuff. We really appreciate your time. We cannot let you go though, and so uh we hear the craziest thing you've seen in markets this week? Data as always, why don't you get us started? Okay, So mine is in crypto this week, and it's this report by chain Alis this which I don't know if you don't know about the analysis. They sort of do like forensics basically of the blockchain and within the crypto space. So it's interesting that such a report will come from a crypto company specifically, But basically, they found that thieves stole a record three point eight billion dollars worth of cryptocurrency last year, and at North Korea itself, it's estimated uh still one point seven billion dollars in up from four million the year prior, which is just crazy amounts of money. Because you know, it's people in crypto don't like to talk about this aspect of crypto, but then you have this crypto company actually coming out with this report talking about if that's that's at current market prices were at it Probably it's probably at the price of the assets when they were stolen, I would imagine, But I would think so, yeah, I would think so, But I mean, yeah, but even if you think about where bitcoin was yeah a couple of months ago versus not. Yes, And they probably don't answer for this in that report. But I wonder how much of that is sort of trapped you have. Can you steal some crypto and it's stuck in a while and everyone knows it's there, and it's it's sometimes hard to launder that. I'd be curious to see how much of that actually, you know, these thieves are enjoying the benefits of that at the Yeah, there are some companies, some crypto like researchers that look into when sizeable sums of coins are moved, or like nineteen thousand coins that hadn't moved in ten years or some which I really interested. That's when you never know where they're going with That's when the thirties always catch them. Two is the minute you try to move it, and the something else than the exactly the FBI is watching. That's a pretty good How about you, Matt, you see anything crazy recently? I mean, I actually one of the craziest things the market reaction to the most recent Federal Reserve great hike I didn't think would be that overwhelmingly positive. Powell was still pretty persistent on the need to hike rate um and right now you have a two year yield that is roughly fifty basis points below what the Fed funds is and that doesn't really happen. I think that's pretty crazy. Is that, you know, borrowing money two years out is cheaper than overnight rates at the Reserve. So I think that's I'd be interesting what happens in the ensuing days if that course corrects. Yeah, that is a It is a bizarre upside down world. And uh, I don't think the market reaction was anything what he hadn't sended. I've joked that Palp should probably have a Bloomberg terminal in front of him when he's giving the press conference to it to amend his answers to to have the desired effect, because I don't think I don't think that's what he was after that day. But we should send him. Yeah, I bet he. Well he I'm assuming he has one. I know, I think he has one. All right, we'll give you mine. Yeah, well do as i've You know, I'm not really a car guy. I'm more of a pedestrian. But I real. But what happened to those four portions? Yeah, they're they're still imaginary. They still are imaginary. I am into when people pay ridiculous prices for collectible items. As you know though, So the story's courtesy of CNN. So if you ever heard of the car company Bugatti, they make these like hot rods, supercars. They call them. Uh yeah, I heard you have two of them? Yes, yes, matchbox size. But so Bugatti apparently is transitioning to electric. They're gonna go hybrid first. Um, but they're done making uh strictly gas powered cars. So they recently produced the last pure gas line powered car they're ever gonna make. It's a um, I'm probably gonna butcher this pronunciation. The Bugatti cheron profably. I believe I didn't take French, but I have something like that. So when up for auction, they instead of just selling it, they put it up for auctions with Southern beas I believe. I'm just gonna tell you what it went for on auction. It's boring to to name the price. Uh, ten points ten point seven million. This car million, brand new car set a record for the highest priced new car sold at auction. But what I'm gonna make you guys square off against each other in our game show is what do you think the max speed is that this vehicle is capable of reaching the fastest it can go? Oh my gosh, in miles per hour for ten point seven million dollar car? How fast do you think you get to go in that car when you flo It's only fair if we can name it in kilometers. All feel free to do that, but you need to translate it to miles for me, like like, oh my gosh, um, I'm guessing it's not as high. But I really I know nothing about cars. Am I going first? There's not going first? I think you go first? Yeah, fine, I'm gonna go with two sixty two d and sixty miles an hour. I don't know. Is that a lot? That's a lot that's way too much? A lot that's like a plane here? I would say I would probably like too, Oh my gosh, I think we uh I think we have our first tie in the Prices Precise to thirty six. Wow, so you guys are pretty close. Although traditional rules she went over vill Donna's, I think we gotta give it some run over. It's fine, the guests can win. That's that's right here, Prices Precise rules. Don't get our lawyers involved. This is called the Prices Precise Yet. Here is the crazier thing, though, is that's not the fastest car got he's ever sold. The fastest could go three hundred miles an hour, they say, quote in theory, and I'm not sure everyone anyone's ever managed to get it up to three hundred. I don't know if you could. Tom Cruise would if you gave him a chance for one of his good It's probably has several of these, but I'm not sure if you could. Theoretically, if you could drive a car three hundred miles an hour, I feel like it would take off like a rocket ship at that point, like I would my heart would burst from it, like I'd be so scared. You definitely have to live. If you're driving that fast, you gotta listen to your podcasts at double speed. I think so if we have any boogotten drivers out there allow them to double speed us two x X. Yeah, pretty good, though you guys are both in the ballpark. I'm not sure what I would have I would have guessed. I'm not sure if I would have gone over two hundred. It just seems insane to drive over two hundred miles an hour. But anyway, you don't go. You don't go two hundred miles an hour in the New Jersey Turnpike. Well, New Jersey Transit I do. Yeah, that's the when we're late anyway, Matt Partalini from State Treet Global ADVISORSS just real honor to be able to pick your brain on all these topics. Uh, wish you all the best and hopefully you'll come back and talk to us again some day. Yeah, thanks, thanks Matt, what goes up? We'll be back next week. And so then you can find us on the Bloomberg Terminal website and app or wherever you get your podcasts. We love it if you took the time to rate and review the show on Apple Podcasts, so more listeners can find us, and you can find us on Twitter, follow me at reag Anonymous, Bill Donna hierarch Is at Bildonna Hirach. You can also follow Bloomberg Podcasts at Podcasts. What Goes Up is produced by Stacy Wang. Thanks for listening, See you next time.