Alternative Data and Its Impact on Modern Investing

And the way that these markets work is it's true market dynamics. In order to buy a yes contract, there must be a seller of a no contract. There must be a buyer of a no contract. Sorry, try that again. For every yes, there's someone that's taking the no. And so that's where it gets interesting for these quantitative hedge funds, is their market making on bad bets. This is Data Driven today. Prediction markets, KPI trading, and the new wild west of retail finance.

Hello and welcome back to Data Driven, the podcast where we explore the emerging industry of AI, data science, and of course, data engineering, which is really the underlying infrastructure to it all. However, my most favorite data engineer in the world, Andy Leonard, is not here today, but. But my most curious favorite person in the world is here today. And I mean that curious like in a good way. Not like curious like strange. This kind of our tagline for Impact Quantum, our sister podcast,

which is doing really well. So if you're not subscribed to that, check it out. We talk about quantum computing and in a way that's not scary, at least for most normal mortals. So thanks for joining me today, Candace. Andy couldn't make it. My pleasure, my pleasure, Frank. Today we're talking to Andrew Levos, who is a SVP of data licensing at Benzinga, not Buzzinga. And welcome to the show, Andrew. Thank you for having me. Cool, cool.

So I'll have to keep in mind Mercedes Benz, when I say your company's name and the big bang theory kind of all at once. Right? Kind of like mash it up. So you're coming to us from sunny Miami and you work at a financial, I would say a fintech company. Is that a good way to say it? Kind of fintechy or fintech supplier? Fintech, yeah, fintech vendor, financial media company. Tow both lines. Right. Which Miami is now like, no pun intended, like one of

the hot places for it. Right. There's obviously Wall street, there's y' all street they have in Dallas, I heard on Bloomberg the other day. But obviously Miami's become a focal point for a lot of financial services. So what exactly does Benzinga do? And kind of like, how'd you end up there? Yeah, so Benzinga, we started as a financial media company strictly the thesis by our founder was that Wall street had a massive edge on Main street in terms of information. That thesis still

lives true today, but we're trying to democratize it. Many companies have joined the mission in 2009, the High Flying tech stocks that we all love and know today were impossible to read or understand unless you had a Bloomberg terminal or another institutional resource. And so our founders set out to cover these stocks in a way that was understandable by everyone. Right. You didn't have to have a financial background, you didn't have to have a finance degree to invest.

That was his thesis and it rang true. It got very popular very fast.

And then in 2011, thinkorswim joined the democratization of finance mission and wanted the news piped directly into their platform for their retail users. We built an API, we became a vendor at that time. And then we slowly but surely realized that a lot of the data that we were producing and aggregating was of value outside of just news. So we started delivering earnings calendars and dividends and analyst ratings

and people would display it on their platform. You know, if you think about your 401k provider or your self directed investing platform, a lot of the data that you see on the page for Apple is from Benzinga or one of our competitors. And so we've, we've kind of transitioned to being that we're still a breaking news outlet and that's what most people know us for. But we take the data and content that we produce and deliver it for wider use across fintechs, across the globe.

Interesting. Which is obviously very crucial. And I don't think anyone who's not. I started my career in New York and on Wall street and things like that. Bloomberg terminals, at least in the 90s, early 90s, particularly before there was the Internet and all that, were very much status symbols I think like, you know, you knew somebody was a player if they had a corner office and a Bloomberg terminal, right. Or they had a, you know,

they had a private office. But I think it was really Bloomberg that really kind of pioneered the whole notion of getting information to the people. And I wouldn't say they were certainly not the first like financial information services company, but they're the one I think everybody knows. I still watch Bloomberg, I have a TV

over there. Lord knows I have a lot of monitors in my office, but One of the TVs is always tuned to Bloomberg because I always like kind of knowing what's on and things like that. It seems like, it seems like I have a lot of questions, right? So one of them is Bloomberg is probably 800 pound gorilla in this space that you're in. How do you, as a startup or smaller firm, how do you, how do you work around that? Right. And it's

not saying that you can't do that. Right. Because clearly you know, at one point Microsoft was the 800 pound gorilla in the PC space, right? Apple still exists, shockingly. And as I think I have a check today, haven't watched Bloomberg today, may have an evaluation greater than Microsoft. So clearly, you know, having an 800 pound gorilla in a room doesn't mean anyone else can compete. It's just how do you, you obviously have to work with it like an ecosystem.

So what's Beenzinga's kind of like angle on that? It's a great question and similar to the Apple Microsoft analogy, there's a niche in every industry that needs to be filled. And so just as an aside, there's this funny narrative going around with AI saying the Bloomberg killer, this platform is the Bloomberg killer. I never see a world, at least while I'm alive that that happens. Bloomberg is the first mover, it is the cream

of the crop of the industry. But our news is in the Bloomberg terminal, so we coexist. Our news is quite popular to the investors in the Bloomberg terminal. It's not the deep analytical 50 page report news, it's 500 to a thousand words, it's what happened, why is it important what happens next? There's a demand for that across institutional investors and retail investors. There's a demand for the 50

page reports too. That's where a lot of people generate their alpha. But there's a demand for breaking news news in an easy to consume way. And so we've, we've kind of made that our brand identity and build our teams around delivering that across our news and all of our data sets. And so Bloomberg is the 800 pound gorilla. I, I use the Bloomberg app

for my news. I also use Benzinga for my news. I think that there's enough room in the space and with, I mean I, so I joined Benzinga in 2019 and then in 2020, 2021, the retail trading boom happened. Everyone wanted to invest on their own. Everyone wanted to build a trading app. There was a trading app for every region of the country, every demographic, every interest, every type of

investing. It just exploded. And everyone has the ability to invest now in a way that is interesting to them and everyone needs content to power those platforms. So coexisting, in short, how do you build trust with an audience that's used to institutional authority like Bloomberg, but might be quietly craving something more human or interpretive?

That was an uphill battle for many years. I, I think I got lucky. Joining in 2019, we had, we already had like 6 million monthly active or monthly. Monthly uniques at the time. But I, I'm sure the, the first million was the hardest, right? We, we kind of got first mover advantage in the retail news space covering stocks that didn't have a lot of traffic or a lot of insight in a way that was

easy to understand. So you know, for example, if, if Apple announces something, a new product, the foldable phone I just saw the other day, everyone's going to cover that. But a small to mid size company that announces a new product or a new partnership, we try to get there first, we try to break that news and then we went on SEO, we went on

distribution on the platforms. If someone's searching that symbol on a fidelity or a public, they'll see our news first because a lot of the outlets don't care to cover the little guys and we've kind of taken the opposite approach. And so that's how we've, we've scaled it. Of course we cover the Apple updates as well. Everybody has to, our users need to know that. But we cover the smaller guys and we've also been a little bit, I need

to say this compliantly. How do I say this compliantly? We've been flexible and open minded about new markets as they enter the space. So we were one of the first financial media companies to cover Cannabis back in 201716 when, when everything went bonkers. We covered psychedelics. That didn't really go anywhere from a public company perspective, but it was interesting

nonetheless. We, we foresee of course, AI blockchain, crypto, but we foresee ourselves as like our duty is to share with our users any and all investable opportunities. They come to us to understand how to build their wealth and we present it in an objective way. And so we've, we've kind of, we've been able to win from an SEO and a readership perspective and built a loyal following by not being afraid to push the status quo and share what's

going on. That makes sense because you know, cannabis now is kind of very mainstream but like psychedelics is probably not very mainstream. I can't imagine them talking about that seriously on Bloomberg, right? Bloomberg is very straight laced. But now I can kind of see like you know, that that's one interesting niche. I also looked at your website and I think it's cool, like one of your item headers is APIs. So we'll talk about that next. But yeah, that's

an interesting point. It looks like I cut Candace off. Sorry Candace. Well, I was just thinking because you know, Bloomberg's strange strength is their speed and their breath. Right. I wonder if that creates blind spots in the stories that they're covering. Yeah, I mean, they're breaking the biggest stories in the world. They'll get there first. They have their relationships and so they're focused on those,

those larger moving items. They need outlets like us to cover the smaller stuff, the, the stuff that we're chasing and digging for. It's not worth the resources to do that. We've built those relationships over the last 16 years and so it's like a 17 now. So it's, it's, it's, it's kind of, it's a good place to sit. As, as a media provider and considering retail investing for the long term, our users want to know about those smaller companies that are emerging, the smaller markets. One

example, and we could talk about it in depth if you'd like. I'm super interested in the prediction markets, developments across the industry. This would be like Poly base, Poly market and all that. Yeah, I'm curious about that too because I see that and I'm like, how is this different than betting? And then I know there's a lot of pressure to regulate this and I don't want to put you on the spot or anything like that, but I'm

just, how did this come about? Because it just seems like how come this wasn't always a thing and how come it's just recently become a big thing? Yeah, it's. So Kelsey, we just announced a partnership with Kelsey today. Actually we're working with Fiscal AI. It's another really impressive data vendor in the space. Benzinga earnings plus fiscal AIs company KPI data is helping to power new company KPI markets on Kalshi. So imagine you're

a trader. I like to think of it as trading. It's not investing, it's not

betting. It's trading. Some of it is betting. But for this specifically, this is trick. Imagine you feel that Spotify users will increase this quarter and you want to invest in Spotify, but with the macroeconomic trends and general market trends, you don't know that the price will respond positively to the news that you are confident in. Now you can invest in that specific company, KPI on Kelsey instead of investing in Spotify as a single equity

and you take out all that variability. And so this is above my head, but imagine you're a quantitative trader or an institutional firm and you have a bunch of long call options on something. You can start using those different markets to hedge your positions in structured ways. I think that this is the first step towards true financial systems and strategies that combine traditional equities or options futures contracts with single company performance. I think

that from here it's. The opportunities are endless. That's pretty wild. So if I heard you right, it's, you can pick one KPI and kind of invest, slash, bet, slash, trade. You know, those verbs are very, the lines between those are very blurry in my opinion. And, and then just kind of invest in that. That's an interesting concept. I remember hearing something, and this goes way back probably, probably way

before. I think I'm a bit older than you, but I remember the rise of these new financial products that were like coming out of like the quant world. Right. Where it was kind of like one of the ones

I heard was Snapple at one point was not a public company. Right. But you could buy something called an Elk and it was like an equity linked something. And I'm like, I always was fascinated by this. And what's interesting was most of the quants when I was at Merrill lynch were on the 24th floor and they kind of

had their own separate space there. And like, it was kind of like they didn't talk about what they did in there, but if you could talk to them and they would kind of explain things in ways that made no sense and simultaneously made a lot of sense. That. And, but what you're describing seems to be very much a 21st century edition of what we used to call quants. Yeah. And there's, I mean there's still. The quants do very well. The quants beat

the market last quarter. Right. They're, they're outperforming. They either really outperform or really underperform. Like there's no, there's no middle with them. They, some of them are getting involved in the prediction markets, their market making some of that. Like, I mean, Charles Schwab yesterday on CNBC expressed interest in the prediction markets. Of course, the Charles Schwab CEO wouldn't say yes or no explicitly, but he said something like, there's a world where we could have it on our

platform. It wouldn't be too hard to add. Interactive Brokers has a, has a company that is building markets. They spoke at our event last year. All these brokerages that are allowing for investing in equities are looking at this as well. And we foresee it as, as an industry. We foresee it as a new tool that opens

up opportunities. And so anybody trading, whether it's the quantitative PhD at Citadel or the retail investor like Myself, the odds and I know I'm kind of all over the place on this idea, but consider also the implied odds from public opinion and what that can provide. So all these analysts that all these sell side banks are saying there's a 58% chance that the Fed is going to increase rates

on X date. Now you can go on Kelshi or Polymarket and see that public opinion says it's actually a 68% chance and you can invest accordingly. And so not only does it provide new tools to ways to invest, but it also provides new publicly sourced insights on traditional investing. It's like another signal that you can read into and get. But how does that work though? Like how does that work when we use the current events of the Strait of Hormuz, right. There

was all these bets leading up that will there be. Will it be closed by X number of dates? Right. And people, how do you invest in that? Because there's no, as far as I could tell, what are the assets behind that? I don't get. That's the thing I don't get. Like with the stock, it's pretty obvious, right? You get a slice of a company, right? The future. You get a slice of a future trade or whatever. I don't understand like, so if I don't want to, I don't want to say like a sports like who's going

to win the Super Bowl? Because that's kind of betting. But I mean we're. I get. Maybe it's the same thing. I don't know, like where's the money for this? Is it just people putting money down? Like, hey, you know, what's the river by. By Montreal? St. Lawrence river, right. Who's going to close the Straits of St. Lawrence, right. I don't want to try not to like get involved in any geopolitical things

that are going on. Right. Although who knows, like, you know, what are the odds of the straight, you know, the St. Lawrence river being blocked up by ice in April, Right. Like, you know, which does. We're going to have flooding then, right? Like right, right, right, right. Like flooding. Where's the asset for that? Right. That's good. Scandals. Because that's a natural thing. It's not tied to any geopolitical drama because the world has enough of that.

Like what's. Or, you know, hurricanes in Miami or you know, flooding on the Chesapeake Bay or I don't know, like what is it just like who puts up the money? Who would forces those contracts? Like how does that work? Like I, I feel like I completely have no idea what's going on here. Yeah, so I, I'm no,

I'm no professional on this. I, or, or you know, but I, I've done some research and the way that these markets work is it's true market dynamics, in order to buy a yes contract, there must be a seller of a no contract. There must be a buyer of a no contract. Sorry, try that again. For every yes, there's someone that's taking the no. And so that's where it gets interesting for these quantitative hedge funds is they're market making on bad bets and there's even

retail investors that are market making on bad bets. And so you know, one thing, not bets, trades. One thing that I think is interesting is a multi outcome event like the presidential election for example. There is

a list of 30 candidates and one candidate is at a 35 chance. Similar to horse, horse racing where some people, you can either take the, the preferred or you can, or you can play the field and there's all these different ways to do it or you can bet no against specific winners and take a 4% return, take a about 6% return. But if you do it at scale then

it makes it worth market making. And so the Kelsey or the platform Polymarket will create the market and they'll settle the market based on a defined outcome, you know, based on the Fed notes of this, you know, however they announce it and then the market will determine the odds and determine the yes or no. And it also, it's, it's, it's driven by liquidity. So if there's no one taking no, then you can't buy a yes. So it's almost self regulating or self, not self balancing. Self equilibrium

would be a good way to put that. Okay, that makes a little more sense. But these Polymorph, I don't want to call anyone by name but a lot of these quote unquote, you know, it will. The river flood type things, those are not regulated like an exchange as of today at least. Right. The CFTC regulates these markets now. Oh they do. Okay. But that's pretty recent. Like within the last few months. The date, I'm not sure but since, since Kelsey has been live in the US and legal. Okay. The

CFTC has been on it. So which makes it very interesting as well because it does add some structure. I think this is still the golden age of it. I think this is still first innings but there is some structure of what markets can and can't be what you can and can't bet on. Or trade on. I'm fascinated by this new market. Benzinga just produced a newsfeed around prediction markets, how it can affect equities, what's happening in the market. It's getting a lot of

traffic on our site. We, we try to be ahead of the curve on that type of stuff. So. And it does seem to be, at least with some of the macro events in the world, it does seem to be fairly accurate from the ones now, I don't know, maybe those are the ones that are just cherry picked, right. We don't, we hear about the winners, we don't necessarily about the user but

losers but like the whole, you know, will there be action taken against. I know with Venezuela, the, these prediction markets got that nailed. It got, you know, what's currently going on in Iran and that part of the world. It got that correct. Alarmingly so. So clearly when it works, it works really well. But have there been examples where it really wasn't on point or is it really just so plugged into. I also

wonder too, like how does that. I'm sorry, I don't want to follow. I had back on the monster energy drink today, so my brain's kind of on fire, but I just can't imagine like, I mean there's got to be some kind of insider trading risk, right? Like if you work at, you know, a government agency and you know, like we're going to, we're going to start wrecking this part of the world, right? Like, let me, let me go into polymarket, right? There's probably got to be some kind of. That's probably

illegal. It's illegal. They, all of

the platforms have controls around it and you'll see headlines about XYZ getting caught, insider trading on these things. The what I'll say, I don't know of examples where it is not correct, but there's a bunch of. I studied econ in college and there's a bunch of studies around how public opinion is the most accurate opinion. And so when you crowdsource an opinion, it's, it's often truer than any single researcher can, can create.

So I think as a general rule the insights, as long as there's enough liquidity, as long as there's enough activity on the platform, these insights are pretty accurate. And that just opens up a lot of, I mean the more markets that are available on the platform with high liquidity, the more insights we can get on what may happen in the future. It's like a prediction tool for researchers and traders. Whether you're Using the platform or not, you can use it as a reference point.

Point. Interesting. Yeah, that, that's cool. I hadn't thought about that. It's another signal to pull in from. Interesting. Candace looks like she's itching to ask questions. Sorry. So do prediction markets actually forecast outcomes or are they mostly. They mostly reflect the confidence of whoever is paying the most attention at the moment. That's a very

good question. I'm not sure. There probably is some, some bias involved because if you are willing to pony up your personal money towards something, you probably have a bit of bias that I'm not sure. So let me ask you this. Where do prediction markets break down? What kind of events or conditions make them unreliable? Unreliable. These are good questions. I'm going to do some research on this.

I, I think that now that there's better controls for insider trading, there's probably less accuracy, actually, because the people that know for sure aren't able to invest or trade. But with that comes a fair market for participants. So that could be considered a breakdown in some respects. There was the, the, there's rules that the CFTC has where you can't have contracts on certain outcomes like death or war. There are also rules from the cftc, and I'm, I'm no

professional on this, so this is not legal advice, it's not investment advice. This is just my, you know, nightly research that I, I've been doing on this. There's rules around like everyone. Yeah, this is just, this is my first, my personal opinion. Don't bet the farm on anything you hear today. Yeah,

I, I've read that there's certain CFTC regulations where there can't be contracts around specific revenue figures for companies. And so that's where the c, the, the KPI thing comes into play where it's like you can't bet or trade on earnings to be this amount or total revenue, top line, bottom line, this amount. But you can trade on how many iPads will be sold, how many cyber trucks will be delivered. So I think that with any new market, it's slowly through trial and error and through

new scenarios that we haven't seen before. The, the details will, will get ironed out further and further to be an efficient market. Interesting. I, I find it fascinating that this is real. I think the regulation here is relatively new. I remember this was, you know, and I, you know, I hear on the radio that, you know, that Congress is looking at more regulations than this. I just think it's fascinating because you said this is the golden age. It's also

the wild, wild West. And I think it's always interesting how those two tend to go together. Right.

And I would imagine, I guess with the individual KPIs, it would be like more people are going to listen to podcasts next month on Spotify than they would on Apple. Would be like one of the things you kind of bet for or against. And I guess that's a way, if I'm willing to pony up the money, as you would assume, rational actors would go with what they're thinking. And then that kind of explains, I guess, the wisdom of the crowd. Right. I remember this was a thing when

it was. Might have been one of those famous bloggers from the mid 2000s had this whole. Mini book on who wants to be a Millionaire and they discovered that the most accurate answer was the crowd, which was really kind of where I first heard the notion of crowdsourcing and wisdom of the crowd. And it seems to be still kind of be true. Right. And these prediction markets tend to let that happen. That's really interesting. That is interesting. I mean, I, and anybody can build their own thesis,

right. I'm in Miami. It's flooded with cyber trucks and Ferraris everywhere. If I see a decrease in cyber trucks at the turn of the year, the new model, then I might make a thesis on deliveries for cybertrucks myself. That's true. There's a lot of these little signals people don't, like, take seriously. And I think one of the ones I heard was that there was somebody did a project where predicting local congressional district election outcomes based on car types.

So if they suddenly notice a particular type of car showed up on Google Street Maps of all places, right. They. They would basically low, like, you know, suddenly, you know, if it's a swing district, obviously, if it's. If it's a stable district and it's really not, that's not a good signal. But if it's like a swing district where it really could go either way, like if they saw more Priuses versus more, you know, pickup trucks, right. Like, it was. It was an interesting signal.

Interesting, yeah. The signal that people use baffles me. It's. It's incredible what the smartest people in the world, frankly, the quantitative investors, the, the hedge funds, I mean, satellite imagery, phone usage, app downloads, credit card history. It's like the, the signals that they put together in order to produce alpha. It just blows my mind. And you mentioned satellite imagery, because that was

the one I first heard of. This was basically on Black Friday. They would have either Satellites or people like in planes taking aerial photography of shopping mall parking lots and based on how full or not full they were, they could predict kind of that wasn't an elegant signal, but it was still a signal.

That was the one that blew my mind because like I was talking to somebody who claimed his brother or his cousin was like a, like a commercial pilot that would take aerial photography and like the busiest day of the year for him was Black Friday. That's crazy. Yeah, the, anything that's statistically significant. I, I think the alt data space is so interesting and no matter how good AI gets the ideas that humans have that link together to produce alpha

will forever be dynamic. We, we work with a lot of the quant funds and they're always willing to test everything and anything they want to see if there's correlation between two variables. And it's so amazing what they find in order to produce alpha. Maybe in a different life I'll do my PhD in mathematics and put numbers together to produce

alpha. So is that what alternate data is? Because I was looking at the API products that you guys have on your site and there's the obvious news, there's corporate actions, but there was also something called alternative data. And I was like what does that mean? Alternative music? No, but what is alternative data? I guess these are kind of, would be non traditional kind of stuff like number of cyber trucks you see on Miami street versus let's just say if the economy tanks

people will be driving more modest. Maybe Honda Civics. Right, like that sort of thing. Yeah, I think in Miami they'll still rent the Lambos. I don't think it's. Yeah, yeah, I'm still gonna see the Lambos on my street. Um, but it's the old data space is super interesting because the data has to be extremely structured and consistent and there has to be a back, is a back testable history available of at least three years

usually. So one example, so how, how our alt data business came along and we actually have someone on our team that focuses on it. He was a trader for 15 years and he speaks the language and understands what people are looking for. We as Benzinga have a really deep network with fintechs across the space. We host an annual fintech awards day where all the brokerages trade tech data providers big and small come together

and share what they're, they're working on. And so because of that we've built this, this really deep network and people come to us and say hey, we have this new data set that might be interesting we have the relationships with the quants and the brokerages and if something rings interesting from our qualification, then we'll present it to who we think it

fits with. So it's kind of like a data brokerage. It's not a. The majority of our business is our internal data sets, our proprietary data sets, but we do this as well. It helps us keep a pulse on what's going on. And so it could be anything from like one partner we're working with now. They've found a way to provide real time short interest data, which is extremely difficult because a lot of short interest filings

is on a delayed basis. We have a partner who has deep institutional holdings data and trends from it.

We know people that do advanced options chain analytics. We have different news sources that are unique and abnormal, specific niches that they fill. And so if we ever come across something that's interesting and unique, that is delivered in a structured, systematic way, present it to the quants and they, they always test it. And if they find that it fits in a model, then they move forward with it. If it doesn't produce alpha, then we try the next one. And I think it's just

like friend to friend on this podcast and everyone listening. It's very interesting to me because in my career it's always been, you have a product and then you sell and try to, you, you go and search and try to source leads and then you sell them on the value proposition and you help them visualize how it will fit into their platform. On the alt data side, there's. There's no selling. It's actually

buyers. It's like just buyers and producers. Essentially all of these buyers are looking for new data sets and they'll test everything. There's no sale. It's like, hey, there's people at these companies that their whole role is to know what's going on in the market and test each of the data sets. So it's really, if you can, flea market, isn't it? It's almost, I mean, I get the vibe

that it's like a flea market where people are looking for the, I don't know, some ridiculous tacky thing or not tacky that sounds, but like something that has no value to anyone else right now. Right. Like, you know, that, that vintage, you know, we'll go back about 10, 15 years. Vinyl, like people weren't really in the vinyl. You know, there was a core set, but, but like now, now that's a premium offering, right? You see a lot of companies offering kind of new

Vinyl, old vinyl, that sort of thing. That is interesting. That makes sense, right? Because if I'm a, if I'm a quant and, or I'm a, you know, wannabe quant, right. I'm going to be like, you know, hey, maybe the, the wind pattern is going to alter. Like, you know, you know how the birds fly around my house and then that's going to impact crop yields down the line. So I'm gonna buy more. I don't know, my neighbor grows corn, so I'll say corn, right? I'll buy more corn. You know, or.

That's interesting. That would make a lot of sense because that's kind of like you have these people. I would imagine it runs the gamut from very, very, very serious kind of PhD types to kind of these wild eyed scientist types and you know, Mythbuster type folks. I only remember this because I remember talking to Someone. This was 30 years ago, Candace. Oh, that's painful to say. Where I guess SAP had OLAP cubes and things like that. This was still

relatively new. And somebody was saying, he goes, no, no, you don't understand. Like, you know, the population of kangaroos in Australia could have an impact on demand for rubber prices in this market because the way that the weather hits Australia might hit Indonesia a different way or something like that. Like, it was just kind of like, it was very much like, you know, if a butterfly flaps its wings in Singapore, you're going to

have a hurricane in Miami or something. It was kind of like there's a chain of causality. Yes, I can kind of grasp that. But like, how valuable is that chain of causality? I think is the. Yeah, it was just, I remember hearing that and I'm thinking like, this person's either really brilliant or are really insane. This, the cross, the cross linking between data sets to produce alpha. Like I said, it blows my mind every single day. And one of the frustrating things about working with quants

is that they don't share a thing. They don't share what? No, zero. Like you said, 24th floor, silent, locked. They don't want to let. On the left was the server room. Like, you know, this is way before the cloud kids. There was a server room and then there was the copy room on the left side of the building and the right side of the building. It was them. You, you needed badge access to get into the server room and you needed special badge edges to get to

their, their, their offices. Yeah, no, they don't share that. Cause it's like, I guess if they Figured something out before anyone else. Like that's the secret formula. Yeah. And if too many people buy into it or start using that same strategy, then it. Then it dilute. Right. Yeah. This has always been a fascinating thing because the most interesting people when I worked on Wall street certainly weren't the investment bankers at all or the traders. They were characters, for sure.

But it was the FX traders, the foreign currency people, and the quants. Quants never talked to anyone outside of their circle. But the foreign exchange people, the exchange currency people did tend to be a lot more rambunctious. That's all I'll say. I would love to hear some stories of these. Lord have mercy. But yeah, one time. Sorry, go ahead, Candace. No, no, let's tell your story, Frank. Tell your story. No, I, I remember I was, I was, I was in it, right?

And I got. One of my tasks was to support the. With the foreign. The currency exchange people. And they were characters. I mean, it was just really weird. Like, I remember my first day, I walk in there and this lady comes walking by. Apparently she's famous in those circles in full on cow, like Roy Rogers style cowboy cowgirl attire. And I said to the guy who was now working for me, I'm like, who is that? He goes, oh, that's so and so. She's really cool, dude. That's not where

I was going with that. It's like, why are we like, you know, you know, in. In like, you know, this old stodgy bank and somebody's walking around like. Like, this is the wild west. And then I come to find out that she was very successful. And part of the, part of the. The lore of that. That world is like, the more outlandish you can be. The more successful you are, the more outlandish you can be. Because no one cares because you made X millions of dollars that morning. Right?

So like, it's almost like a status symbol of how weird you could be. Interesting. That was my first day there. I was like, I don't know how prevalent that was. Or was it just this one department in this one company or is that a thing? I don't know. Sorry, Candace, I cut you off. But the sight of seeing somebody, like, dressed like Roy Rogers walking down the hallway, like in a cubicle, but if she's making the money, then she can wear whatever

the hell she wants to wear. I'm not gonna say. I'm gonna say. Yeah, right. Yeah, exactly, right. Like, you know, somebody said, like, you know, if you made enough money, you can come in here With a clown suit. And no one will say words to you. No one's gonna say a thing. They're gonna say, where do I get mine? Right? That's gonna make me better at what I better. It's almost a flex. It's almost a flex. It's almost a flex.

I can walk in with a clown suit or something like that. Like it was just like this was like 30 something years ago and I'm still like, holy crap, that actually happened. Sorry Candice, I cut you off. No, no, I'm just thinking about the idea of incentives shaping truth. And if people can profit from being right, does that sharpen accuracy or does that introduce new distortions?

I think both. I think that's the whole, that's, that's the yin and yang of investing for retail investors, for institutional investors. We're all trying to be right, we're all trying to find that edge. And we, the, the data we produce day in and day out and deliver to these brokerages is to help users find an edge. Of course they have to take that data and create their own thesis. Where it gets dicey is when people

try too hard or get immoral about it. It's, it truly is. The market truly is an aggregation of humanity and there's good actors and there's bad actors and there's immoral and moral beings in the space and it's a net zero game. So someone's going to win and someone's going to lose and people do some really shady stuff across history. Right. Like we've seen the Bernie Madoffs of the world and smaller cases of it every

year. There's a small case of it. I think as long as people maintain their humanity and they use the tools that are legal and moral to find alpha, I. E. Be correct, then it makes the market better. But once people try too hard and get too dicey about it, that's when people lose jobs and Enron closes and those sort of things. Yeah, there's always that. I mean it is a mirror. Markets are a mirror to

humanity, aren't they? Right. Like bad people are going to be bad, good people are going to be good. Most people are going to bounce between those two extremes. Good, bad, the ugly. Right, right, right. Back to the western theme. So if we fast forward a couple years, do we see prediction markets becoming a trusted decision making tools or just another signal people learn to question?

I don't know where it's going to go. That's what I'm excited to see, where it's going to go. I keep posting on my LinkedIn with that question and no one's answering it. I'm waiting for someone. If anybody has the answer, please go to my LinkedIn and tell me where this is actually where this is going to end up. Is it going to be in every brokerage? Are we going to look on our 401k and have the odds next to the S P, you know, the spy, whatever you're averaging into, in your, in your account?

Or is it going to be a secondary resource? Or are these lawsuits of. This is gambling. You know, there's a lot of pressure from specific jurisdictions and also from the fanduels and the draftkings of the world to kind of nip this at the bud. Where. Where is it going to go? I think that's, I think that's one of the reasons why I'm so interested in this space is because it's extremely disruptive for traditional finance, for the gambling industry, for researchers, I mean, for politicians.

And so when that happens, there's. There's people on both sides. It's polarizing. You know, this is like my, this is my drama that I'm following. This is my reality tv. No, that's true. Prediction markets have a finger in a lot of pies. Politics, sports, finance. It's fascinating because you have this many people it touches. Very rarely do you see something. I think the last time the financial world saw something this crazy in this out of left field

was probably crypto. And again, crypto was very rebellious, very, almost anarchistic at first. And then to your point, I don't quite see it on the same page or the same panel when I log into my 401k and I don't see it next to precious metals. But the way people kind of refer to bitcoin prices and things like that has a feel of like. Well, we're kind of talking about

ounces of gold, Right. It's not exact. You know what I mean? Right. It's not exactly the same, but it went from kind of being this crazy, crazy weird thing that only hackers and criminals use and super nerds to now it's kind of just a. It's just an element or two on a dashboard. Right. That's fascinating. And you're right. Like, will this do the same thing? Right. You know, bitcoin had a lot of. And all the cryptocurrencies kind of had a very shady birth process. Right? Not

necessarily shady in the bad way, but kind of sketchy. How about that? That's. That's a better Word. Right. But now you see these prediction markets as they kind of grow, will they be. Will they become kind of legitimized, like. Like crypto did, or will they kind of, you know, will they not be as successful? I don't know. Like, that's, That's a good point. I don't know either. And even if your brokerage doesn't allow you to buy Bitcoin directly,

I'm sure you have access to IBIT and the other ETFs. It can be in your 401k no matter where you're investing. And so 10 years ago, did we foresee a world where I could have crypto in my 401k alongside my VU or whatever my holding is? That was not the outcome that I thought it would be. I thought it was either going to be anarchy, new world order, Bitcoin only, or zero. And the market found a middle ground, which is really cool. Yeah, it kind of adapted around it, grew around it.

No, it's true. Because there was a point when might have been on Bloomberg actually, they were talking about, will crypto ever be. This is like 10 years ago. Will crypto ever be respected? And then everybody was like, no, that's the third rail. These brokerage companies will never touch that because it has a stain of or stench of criminality to it. And here we are. Right.

Like you said, you can either buy it directly through your brokerage or you can get it indirectly through your brokerage. Right? Yeah, there's an old line and about. I don't know, it's kind of not safe for work, but basically saying that I'll clean it up, I'll put some PC words to it. It was basically talking about how when a building goes up. It was an architecture critic. It basically said, even if it's considered ugly when it's made, as it. As it ages, it still

becomes respectable. The original quote's a little more salty, so I'll leave it at that. But it's basically like, you know, older sex workers and old buildings still get respect no matter how they originally were treated. Something to that effect. Okay. Yeah, interesting. I guess the same applies to financial products, right? Yeah, I guess so. I mean, build it in no comm. They say. Right, right. Everyone wants to know what the next big thing is. It's part of human nature.

It's a good opportunity to produce wealth for yourself. And this is dominating the news cycle. Who knows how long that'll last? But man, it's interesting. That's cool. I'm fascinated by the API stuff. I'm like, what's the fun? Because I'm a big sucker for data, obviously, this podcast, but I'm like, oh, what are sort of the cool things you could do with this data? I'm going to definitely poke around your API keys and stuff like that. Amazing.

You can. You can sign up for a free trial on there. Right, right. I definitely will. If you prefer a web hook, I can. I can hook you up with a key as well. People are doing some really cool stuff with it. I mean, especially with the rise of, you know, AI has really enabled folks to build faster and smarter. Yep. And so we're seeing a lot of interesting dashboards. People are building their own dashboards for their investment strategies. We are working with some

of the AI companies direct as well. It's been a huge growth lever for us, these AI companies. I mean, the output is only as good as the input. And so some of our more proprietary data sets are being consumed by the perplexities and their competitors of the world. Interesting. No, because, like, you know, I think everybody can be a builder now. Right. And that's. That's, you know. You know, Candice and I are building actually four products right now because, you know, ADHD and all. Right.

But the moat

used to be you have an idea you have on the back of a napkin or whatever or on a whiteboard behind you, and then you build it someday. Someday never happens. But now the building of the code is really just a matter of how do you get the AI to put what's on your head into the computer. Now the next challenge we're facing is there's a lot more to launching a Sass than code. Right? It's not idea plus Sass.

Idea plus code equals sass. No, no, no. There's idea plus Sass plus X, and it's probably more than one variable equals sas. So we're kind of learning that now. Right. Because Candice and I, before this call, we had a conversation. We're like, hey, it looks like somebody else is building something like what we're talking about. Like, yeah, I'm not surprised, because good ideas do not happen in isolation. Exactly, exactly. So where can folks find out more about you and Benzinga?

Benzinga.com, where you can read our news. Benzinga.com APIs where you can find the product offerings. We build a new product every quarter, so. Oh, cool. Join our newsletter list and we'll keep you updated. And then keep an eye out. You'd be surprised. Your brokerage may have little inklings of Benzinga around it. Now that you've heard the name, I will look for it. Give us a nod with your preferred brokerage. There you go. Very cool. And with that, we'll end the show.