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.