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

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.

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

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

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

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.