October 30, 2024 • 45 mins
Earlier this election cycle, Nate and Maria appeared on Odd Lots to talk about prediction markets and election betting. It was a fun conversation -- and we're releasing it now for anyone hoping to get their final bets in.
Political prediction markets — where traders can make bets on election outcomes — have been around for years. But in this cycle in particular, we've seen an explosion of interest, with people constantly checking the odds on sites like Polymarket and PredictIt to assess the state of the US presidential race. But how accurate are these markets? How do people make money on them? What do they tell us beyond what traditional polling or modeling already indicates? On this episode, Odd Lots hosts Joe Weisenthal and Tracy Alloway speak with Nate Silver and Maria Konnikova, the co-hosts of the new podcast Risky Business. Silver is, of course, a famed election modeler, and both are serious poker players with good instincts for gambling and odds. We discuss how these markets work and what the markets and models are saying right now about the current US campaign.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:15):
Pushkin. Welcome back to Risky Business, a show about making
better decisions. I'm Maria Kannakova.
Speaker 2 (00:29):
And I'm Nate Silk.
Speaker 1 (00:30):
Today we're dropping into your feeds to share an episode
that Nate and I taped with The Odd Lots Podcast,
where we appeared to talk about prediction markets.
Speaker 3 (00:38):
Yeah, this is a really fun interview. The host Joe Wisenthal,
I know d you a little bit. We've hung out
in Vegas together actually, and Tracy Alloway, Uh ask the
great questions. They're kind of nerdy in the same ways
that we are. So it was a fun, fun crossover
eighties sitcom crossover episode.
Speaker 1 (00:55):
Basically, absolutely and if you enjoy the episode, you can
find more of Odd Lots wherever you're listening to this podcast.
Speaker 4 (01:16):
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 5 (01:32):
Hello and welcome to another episode of The Odd Lots Podcast.
I'm Joe Wisenthal and.
Speaker 6 (01:37):
I'm Tracy Alloway.
Speaker 5 (01:38):
Tracy, I have to say prediction markets have actually become
a really significant part of what I would call my
news consumption.
Speaker 6 (01:46):
I know you tweet about them a lot. In fact,
you have an ongoing joke that you keep repeating that
I would argue that novelty value has worn off. But
clearly I'm wrong because everyone on the platform finds it
very amusing.
Speaker 5 (01:59):
Yeah, and other people have stolen my joke.
Speaker 6 (02:01):
I've seen that.
Speaker 4 (02:02):
Yeah.
Speaker 2 (02:02):
So the joke is.
Speaker 5 (02:03):
That, you know, when people are really confident about something
and something is priced at seventy five cents on the dollar,
they're selling a dollar for seventy five cents right now
on polymarket. My joke is that when something is fifty
to fifty, I say, oh, they're selling dollars for fifty cents,
which of course sounds confident but can mean in both directions.
It's worked really well. I'm getting a lot of mileage
out that one. And you may be bored of it now,
(02:24):
but I think we're in the valley of humor where
if I'm still making the joke a year from now
at Tracy, You're gonna find it funny. We shall see.
Speaker 6 (02:33):
Okay. Prediction markets, Okay, prediction markets are interesting. I have
a lot of questions about them, And first of all,
I feel like I should caveat this entire conversation with
an admission that I'm pretty sure I have made on
this podcast before, but I intuitively do not understand probabilities.
(02:55):
I'm kind of serious, Like I understand rationally, why if
you flip a coin five times, the probability of having
five instances of heads is not fifty percent, but if
you flip it once, it's fifty percent. But like, on
an intuitive basis, I don't really feel that way, right,
(03:15):
And then the other thing I would say when I
see prediction markets. So one of the things that happened
recently was people were going like, oh, prediction markets are
so smart and so interesting because like on Predicted there
was a ten percent chance that Biden would drop out
of the race, and so people were going like, oh,
see the prediction market called it, and it was like, well,
(03:37):
a ten percent chance. That was higher maybe than some
other platforms or some pundits expected, but it happened, the
chance was one hundred percent.
Speaker 3 (03:46):
Like I just.
Speaker 6 (03:48):
Intuitively, I don't get it. I don't get I don't
get what the percentage actually means.
Speaker 5 (03:53):
Right, So, Tree, the way you think about the lottery,
for example, is that if you buy a lottery ticket,
your odds should be fifty to fifty because either you
win or you done right.
Speaker 6 (04:01):
Therefore it should be binary.
Speaker 5 (04:03):
No, So the way I think about them, and we'll
be talking very shortly to people who know a lot
more than me. Is not that like I find conversations
about the rightness or the wrongness of prediction markets or
a given contract on a market to be sort of
the wrong question. It's more like, to me where I
find it valuable. It's like, Okay, a lot of people
think that Biden might drop out, right, right, But is
(04:27):
that mean there's an eighty percent chance? Does that mean
there's a fifty five percent chance? And so what I
find interesting about prediction markets is not so much whether
going to be right or wrong, but that it seems
like they can put some sort of number on the
emerging conventional wisdom. Because look, even before the debate, some
people thought Biden still had a chance of dropping out,
and so it's interesting that the traders in those markets
(04:49):
assigned non negligible odds to that happening, and then of
course it all spiked after the debate and stuff like that.
So to me, you know, in thinking about the election,
we have polls, we have models, we have prediction markets.
Now we have punditry that appears on opinion pages of
various times. It's yet another tool to sort of consume
information and figure out where people's heads are at. And
(05:12):
I like it for that reason.
Speaker 6 (05:13):
Yeah, okay, but I still don't get the value of
putting a specific number on it. Like you could just
have an arrow that goes up or down that shows momentum.
And I'm being slightly facetious here, but like you could
look at Google trends or something, or you know, try
to gauge momentum that way. But okay, I have a
bunch of questions. I fully admit that this is something
that again on a sort of like instinctual level, I
(05:37):
do not quite understand. But we do, in fact have
the perfect guests to explain it all to us.
Speaker 5 (05:42):
Yeah, yeah, I'm very excited. We are going to be
speaking with Nate Silver and Maria Kanakova. They're the co
hosts of the fairly brand new Risky Business podcast, which
is all about questions like this. They're both poker players.
Speaker 3 (05:57):
They are both.
Speaker 5 (05:57):
Recently played in the World Series of Poker and have
made a lot of money over the years playing poker.
They are people with probability in gambling and odds and
making decisions with money on the line. Both in their
blood is the author of the forthcoming book on the Edge,
The Art of Risking Everything, And he's also an advisor
to Polymarket, which is one of the big prediction markets
(06:18):
that everyone has been quoting these days. So a couple
of great people to talk to about things like betting
on elections and how they think about all this stuff.
So Nate and Maria, thank you guys both for coming
on odd Laws.
Speaker 2 (06:30):
Thank you so much. Joe and Tracy, Yeah.
Speaker 1 (06:32):
Thanks for having us.
Speaker 5 (06:33):
Absolutely so. When we look at all these markets and
poly markets the hot one, but I forget the one
is predict It was also really big. Do I think
they're running into some they have some regulatory issues years
ago there used to be in trade. There's the Iowa
futures market, there's others. What is the value When people
look at all these numbers and say, like, what is
the value of markets like these?
Speaker 3 (06:55):
I think it's the same value as any type of
market where you have price discovery from participants who have
a rational incentive to make smart trades and be closer
to whatever the value the market resolves.
Speaker 2 (07:05):
To, you know.
Speaker 3 (07:06):
I mean Tracy asks some existential questions about the notion
of probability for things that are kind of seen as
one off events. But whether things are intrinsically uncertain or
not is kind of above my paid grade, right. The
fact is that we have uncertain information. We're trying to
make judgement space and complete data and complete information. And
I think it's better to quantify things than to be
(07:27):
totally subjective and use weasel words and not have any
accountability for you know, a twenty percent chance versus a
forty percent chance for example.
Speaker 1 (07:35):
Yeah, and I think that there is a huge difference
between the two and Tracy your existential questions make a
lot of sense to me as a psychologist, because you know,
the human mind really does not like probabilistic thinking. You're
not the only one, and we do want to think
in absolutes, right, We do like zero and one hundred
those are easy numbers for us, whereas twenty three percent
not so much. But this idea that if we actually
(07:59):
put our money where our mouth is, it will help
us calibrate those probabilities better, help us calibrate our intuitive
sense of how confident we are in something, how much
we actually believe in it. That's I think why prediction
markets in all sorts of literature and all sorts of
areas have gained momentum because you think differently. I bet
(08:22):
and I would put money on this tracy that if
I forced you to put money down on an opinion
or a thought, you would actually start homing in on
those instincts, on those decisions, and you would find that, Okay, well,
like you know, I'm probably less certain of this than
I thought I was, because I'm only willing to bet,
you know, ten dollars and not one hundred dollars. Asking
(08:43):
yourself questions like this, Actually putting down those bets really helps.
And what Nate was saying, when you have lots of people, right,
when you have hundreds and thousands of people doing this,
that's when the calibration becomes better. Because if we have
a thousand Tracs who might you know, not believe in
probabilities that much or not understand them, and yet they're
all putting their money down. The idea is that in
(09:06):
this particular case, the crowd actually knows something right, there
is some wisdom to the amount of money you're putting down,
because once again, actually betting with your wallet so that
it hurts, that's when you start to actually question your beliefs.
Speaker 6 (09:24):
Well, let me just say, off the bat, thank you
so much for trying to make me feel better. I
will just say, in my defense, I did do AP statistics,
and I did like I did okay, probably because back
then you had to draw charts by hand, and I
was really into drawing like neat charts. So I think
I got points for that.
Speaker 2 (09:41):
Okay.
Speaker 6 (09:41):
Let me ask a non existential question, which is, if
I go on to polymarket or predict it, and let's
just say I see an event and the probability is
something like forty percent, where is that forty percent coming from?
And what exactly is it telling me?
Speaker 3 (10:01):
It's saying that in the long run, if you took
one hundred similar events some reference class, that the event
would occur about already out of every one hundred times
and wouldn't occur the.
Speaker 2 (10:12):
Other sixty out of one hundred.
Speaker 3 (10:13):
I think what bothers people is that they question whether
it's something like an election falls into an appropriate larger
subset of some random distribution of data.
Speaker 2 (10:22):
Right. That bugs people.
Speaker 3 (10:23):
If you're playing poker, then there's one to fifty two
cards that might come next. It's technically not random, right.
The hand is actually dealt out once it's shuffled but
de facto random, right, Or if you're watching a basketball game,
you have some sense that a free throw may or
may not go in, or may bounce off the back rim,
et cetera, et cetera. With elections, I mean, parties always
tell people that, oh, this is the most important election
(10:44):
of all time, but there are like a lot of
like fairly random contingencies in this election. Or example, to
use a somewhat pointed example, if Donald Trump had not
turned to look at a billboard of immigration data, then
the bullet that was fired at him might have done
much more damage than Grayze's ear, for example. Or in
two thousand, the butterfly ballot. This is going back a ways.
(11:05):
A ballot design issue in Palm Beach County, Florida probably
costs al Gore the election and cause old people to
confusingly vote for pap you can and instead. So there
are these kind of near random circumstances even in elections.
But even then, you know, not everything is knowable or predictable.
And if you think it's locked in that Harris is
going to win or Trump is going to win, then okay,
well great, maybe you're right, but you can make a
(11:26):
lot of money by betting on that at polymarket or
predicted or whatever else.
Speaker 1 (11:30):
Yeah, I think one more time. You know, nothing in
life is certain ever, no matter how much we want
it to be, right, Like, I might die in the
next minute. I hope I don't, but I'm right.
Speaker 6 (11:41):
There's a non.
Speaker 5 (11:42):
Zero non zero jes exactly where my mind went when
you said nothing.
Speaker 1 (11:48):
Right. But it's so true. And if you actually think
of the election like a poker hand, except you know,
think about it in like multiverse terms. I'm going to
go back to existential terms, Tracy. You try to get
us out of existential terms, I'm going to bring us
right back there. So imagine, you know, the multiverse experiment
where we have, you know, a million possible versions of
(12:10):
our reality, and in one of them, we had different ballots. Right,
they weren't butterfly ballots. Al Gore won the election. We
would probably not be here right now, because you know,
it's funny that it's a butterfly Yeah, butterfly ballot, butterfly effect. Right,
those tiny things do matter, but you do have to
realize that those probabilities still matter, right, like the fact
(12:30):
that Hillary Clinton lost and that Nate got a lot
of for it. I defended Nate very publicly, as did
a lot of people, because his forecast was the single
best one. It gave her a good chance of winning,
but it gave Donald Trump the highest chance of winning.
But people don't like you know, you know, they don't
understand that over twenty percent is a hell of a
lot of a percent. You know. In my last book,
(12:53):
I compared Nate's percentage just to poker, and I said,
the chances of Donald Trump winning according to Nate's prediction
was the same chance of you flopping a pair in Texas.
Hold them now, Think how often you flop a pair
right that you pair up one of the two cards
that you're holding. That happens all the time.
Speaker 5 (13:11):
I really just like, sometimes I'm sitting there at the
poker table and I'm like, God, just give me a
set and then I could double up and walk away
for the night, and it never happens anyway. So I
have two quick thoughts. One is I always do find
it funny when people talk about, like our prediction markets
good or not, because a point that I've made many
times in writing, et cetera, is we actually do have
a very popular liquid prediction market that existed for a
(13:34):
long time, which is the short term treasury market, which
is explicitly a bet on what the you know, nine
members or whatever of the FMC are going to do
over the next And that's literally a prediction market. And
no one questions whether that market works. It does work,
and it exists, and there's a lot of money writing
on it, and it literally is not just metaphorically, it
is a prediction market.
Speaker 6 (13:54):
You know.
Speaker 5 (13:54):
It occurs to me though, when we talk about, okay,
what is a forty percent return? This must be easily testable, right,
Like if you take a thousand contracts that have existed
over the life of polymarket or the life of predicted
or intrade or whatever it was, and then say, like, okay,
one hundred days out from resolution, did the ones that
say forty percent? Did they resolve forty percent of the time?
Speaker 2 (14:16):
Like? Has that been tested?
Speaker 5 (14:17):
Like can we say that that is the case that
things with forty percent in the prediction market over some
timeframe do resolve forty percent towards the direction?
Speaker 2 (14:26):
There's been somewhat mixed literature on this. I do know.
Speaker 3 (14:29):
I guess this is just a not so humble brag right.
I do know historically that like the five point thirty
eight now Silver Bullet and election forecasts have been better
than prediction markets, which is unusual. Usually publicly available information
is not better than the market. However, they've been pretty
well calibrated according to most estimates.
Speaker 2 (14:45):
And also I think the markets.
Speaker 3 (14:47):
Are maturing a lot where Look, I've talked to a
lot of different types of businesses, investment banks and hedge
funds and things like that, and they understand that like
political risk is market risk when you have this bigure
difference between the two parties, that like whether Donald Trump
or Kamala Harris is the next president, has a lot
of implication for every sector of the economy or any
trades you want to make. And so you have seen
(15:09):
more institutional attempts to either bet directly through prediction markets
or bet on proxies. And again I'm an advisor to
poly market, but their volumes are meaningfully much higher than
in the past, their structures are good, so you don't
pay as much of a tax in essence, so I
kind of think they've turned a corner from being pretty
good to maybe verging on very good.
Speaker 1 (15:31):
Yeah, I think, Nate, you just head on a really
important point, which is volume. Right, prediction markets are only
as good as the traffic that they get, and so
for a long time, you know, there was no legal
prediction market in the United States, and so it's very
difficult when you're talking about betting on political events within
the United States to have a well calibrated market if
people within the United States can't actually bet on it. Right,
(15:53):
So I think that a lot of things are changing,
and hopefully we'll change for the better because volume is
essential in calibrating correctly, and you need people with expertise
doing it as well. But you also you just need
bodies to you need both of these things.
Speaker 3 (16:06):
The ratio of smart money to dumb money is really important. Yes,
in the Super Bowl, the literal actual chiefs versus forty
nine ers whatever, super Bowl, there is so much dumb
money being bet on the Super Bowl that the sharp
money can't consume all of it, and so therefore you
often have positive expective value bets by fading the public
in the Super Bowl. That's not true for a regular
season Hornet's Wizard's Game in the NBA or something, but
(16:29):
for very very big events like a big UFC fight
or the super Bowl, talk about some in the book
a little bit. Then those things potentially you have more
dumb money than sharp money. And so what you now
have happening, I think is like more of a professional
class of betters on politics, whether it is hedge funds
or whether it is just smart individuals who are betting
on the US election and elections around the world. You
(16:50):
see some sharp money coming into these markets.
Speaker 6 (17:10):
So just on this idea of like where the information
and the bets are actually coming from. Talk to us
a little bit about the difference between a book maker
versus a prediction market, because my impression of a bookie
is like they kind of set the odds and then
people decide whether or not they want to place money
on them, and then you know, they might calibrate those
(17:31):
odds depending on the response they are getting from people
placing the bets. But there's like a starting point that
the bookies have, and I guess it must be different
for prediction markets. Talk to us about like the difference
in establishing those probabilities.
Speaker 3 (17:46):
I mean, yeah, the classic act of bookmaking is where
you have some in essence prior. I guess it's an
advanced show, right, So like you have. You start out
with some number that you kind of probably comes out
of a model or some conversation. You have the initial
line that a sportsbook post on an NFL game is
actually probably often quite beatable. Right, it's just some like
nerd in a back room somewhere who's doing his best.
(18:08):
But then you look for action from sharp betters. Maybe
the book maker thinks that Maria is really good at
sports bidding and I'm a total hack whale.
Speaker 1 (18:16):
Definitely, definitely anyone listening that this is accurate.
Speaker 3 (18:20):
So Maria bets on the Chiefs, she bets five K
on the Chiefs, and they'll move the line toward the
Chiefs in Maria's direction. Right, So now it's more extensive
for me to about on the Chiefs. If I bet
I think I'm a whale, they to do about it, right,
because they think that's just dumb money they're trying to
make a profit from. So that's traditional book making, whereas
the prediction markets, it's all happening more organically, right, there's
(18:41):
no human at the switch who was deciding and evaluating
where to move their numbers.
Speaker 1 (18:46):
I think that the other important thing is that you,
I think suggested Nate but didn't say explicitly when you're
talking about sports books, when you're talking about bookmaking, this
all happens pretty much manually, where people actually look to
see who's placing the bets, and then they actually adjust
the lines, right like there is a human adjusting the
(19:06):
line and deciding, okay, this is what we need to do,
and that might happen hundreds of times a day, maybe
even more, and the line gets better and better. But
in prediction markets, those adjustments are just happening all the time.
Speaker 3 (19:18):
It's the invisible hand, the same as like the stock market,
for example.
Speaker 1 (19:21):
YEP.
Speaker 5 (19:22):
I could imagine that there are various types of betters
on prediction markets, and you broke it down into sharps
versus whales or whatever it is, or done money versus
smart money, but they're also different. Even within the category
of smart money, there are probably many different approaches. So
I could imagine that there are some people who are
very sophisticated in their political analysis, and they could say,
(19:43):
you know, this person is a better chance of winning,
you know, getting the vice presidential tap than someone else.
Someone else might just say, you know what, anytime the
model or the price diverges from the silver bulletin model.
I'm going to go either short or long that I imagine
that there are arbitrage traders who are just sort of
maybe looking at the price on one exchange versus the
(20:05):
price of another exchange and attempting to take advantage of discrepancy,
just like it exists in stock market. I assume maybe
there are momentum people. It's like this is hot right now,
even if I don't believe it. But talk to us
about some of the different strategies that the good betters
on prediction markets take.
Speaker 3 (20:22):
I mean, I think you identified most of them, Joe.
And you know, one thing you learned being in the
gambling world, playing poker and so forth, is that if
there is an arbitrage to have or an edge to
be had, someone's going to.
Speaker 2 (20:32):
Hoover it up. Right.
Speaker 3 (20:33):
There are actually people who go around and are professional
slot machine players, for example, because there are odd circumstances
where you might have a jackpod or a conditional probability
where playing a slot machine can don't do this at home,
do not do this at home, but there are cases
where race.
Speaker 2 (20:47):
Is going to do it.
Speaker 3 (20:49):
Yeah, Plus you need to play a slot machine. So
at the end of the day, something like the vice
presidential race. It's inherently somewhat subjective, but if you have practice,
I mean as a poker player. Poker players develop uncanny
intuitions for probabilities. They'll say, I need thirty one percent
to make this call profitable on the river, and it
(21:10):
was only getting thirty percent and so I folded, right.
I mean, they'll literally get to like one percent delta
versus the actual odds.
Speaker 1 (21:17):
Are good poker players. You need an adjective in there.
Speaker 3 (21:20):
Yeah, yeah, but you learn it kind of. I mean,
it's just it's muscle memory at some point.
Speaker 2 (21:24):
Yeah.
Speaker 1 (21:25):
Absolutely, And sometimes you don't even quite know what the
probabilities are. You just know that you have those odds
or you don't have those odds. You really do start
feeling them. So that is something that develops over time.
And I'm actually not sure though that it would develop
over time when you're doing something like prediction markets, right,
because slot machines are also something that is very experiential,
(21:47):
right where you actually kind of are doing this and
you're trying it over and over and over. And for
prediction markets, I think you often just place lots of
bets and it's not like you're sitting there actually watching
this and experiencing it and learning from it. So I
think you already. If you want to be a good better,
you need to learn those intuitions from something like poker
(22:08):
and then apply them to the prediction markets. I don't
think it works the other way around, because the way
that the brain works, you need that experience. You need
to sample those probabilities over and over and over. That's
why poker players know what one percent feels like, because
they've played tens of thousands, hundreds of thousands of hands
and they have seen the outcomes they've sampled correctly, right,
(22:29):
so they know exactly what that feels like. That doesn't
happen in prediction markets. So Nate can go into a
prediction market and he's going to crush, right, because he
has a good instinct for those probabilities. But someone who
doesn't already, I don't think that they're going to suddenly
develop it because they were betting in prediction markets.
Speaker 6 (22:47):
Joe, I can say with one hundred percent confidence that
I have failed to apply my poker intuitions to my
slot machines playing strategy. That is definitely true. Okay, Wait,
so I'm looking at polymarket right now, and I should
look at this more because this is actually kind of fun.
How are the particular events that people are betting on?
(23:09):
Are those chosen or selected? Because right now I am
looking at will the US confirm that aliens exist in
twenty twenty four? What will Trump say in August? I
mean really, I feel like that could be anything? And
then will Taylor Swift get engaged in twenty twenty four?
So the big questions of our time? But how are
those sort of like why those particular questions? Is it
(23:31):
just if anyone wants to start a market in a
particular event.
Speaker 3 (23:35):
Yeah, I'd say the polymarket guys who I know a
little bit, are very attuned to finance, Twitter and politics,
Twitter and crypto Twitter. Sometimes they're kind of jokes and
kind of troll is. I mean, they're trying to have
some fun, right, and so you'll see some questions that
are a little bit memified.
Speaker 2 (23:50):
For sure.
Speaker 1 (23:50):
I actually saw Nate and I'm not sure if this
was I don't remember if it was on polymarket or
one of the other prediction markets, but there was a
prediction market on our podcast, including you know, number of
f bombs that Nate will drop within the first ten minutes.
You know, things like.
Speaker 6 (24:05):
Wait, do you guys bet on that? Presumably you can
make a lot of money.
Speaker 3 (24:09):
I mean some sites say that that's okay, right if
you talked so. The other the big free money prediction
market site is Manifold, which has a s very dedicated
community traders. So even though as a polymarket advisor, now
I'd say I think real money is a way to go,
it's pretty good. I certainly have a lot of respect
for Manifold, But yeah, a Menifold is kind of radical
transparency where anyone can put up a market about anything
(24:31):
and they will even say yeah, as long as there's
no complict of interest, then inside information only makes the
market smarter.
Speaker 2 (24:38):
I'm a little bit worried about that.
Speaker 3 (24:39):
I mean, this is an issue in sports markets too,
where now you have ESPN bets might offer a market
on like the NFL draft or something. Right, well, if
you're an ESPN NFL beat reporter, you might have a
lot of knowledge about what the Atlanta Falcons are going
to do. And for politics markets, I mean something moved
the markets toward Tim Walls, Kamala Harris's VP pick aggressively
(25:00):
about fifteen minutes before that pick was confirmed.
Speaker 2 (25:04):
What is that? I don't know.
Speaker 3 (25:05):
Maybe it's that there were SUVs as there seemed to
be outside of Tim Wallas's resident Minnesota where we lives
in Minnesota. But inside information is I mean from a
user standpoint, it's all incorporated, so it's useful. But like
you do wonder a little bit about like are there
ulterior motives for people who have, you know, inside knowledge
about sports, politicst cetera, financial events to bet?
Speaker 1 (25:26):
Yeah, and then you know there's a thin line. I'm
working right now on my next book, which is about cheating,
and there's a thin line when you can use inside
information where you know everything is fair game between that
and cheating right and starting to throw games and starting
to actually do things where how you bet affects how
you act, and that's incredibly difficult to police. It's always
(25:46):
been difficult to police, and I think it's going to
become even more so. So I personally, and I'm not
involved with any prediction markets, I personally would like to
see there be some sort of penalties in it. Not
being quite as open to that sort of thing, just
because I think that there is a huge possibility for
abuse and for things that actually end up sabotaging the
(26:08):
integrity of especially things like sports games, but politics, you know,
all sorts of contests.
Speaker 5 (26:13):
Right, Tracy, and I I think it was last year
maybe twenty twenty two, we interviewed Roustin benham Oh, the
head of the CFTC, and they have not been friendly
towards prediction markets for some of these specific reasons which
you there are probably good reasons why you don't want
manipulation of actual political events to have money on the line.
And actually, while we're on this topic specifically, since you're here, Nate,
(26:37):
my understanding is that polymarket is not legally available to
people in the US, but as many people know, VPNs exist,
and because it uses stable coins to fund it, there
are ways around it. Is that an accurate characterization of
its state we look?
Speaker 3 (26:53):
Since I am in an especial capacity for them, I
las say is that you are not allowed to bet
on polymoticket if you're in.
Speaker 2 (26:57):
The United States. Got it?
Speaker 5 (26:58):
Okay, we know what it's going on here. You know,
you mentioned prediction markets on podcasts actually there and you
mentioned manifold at one point, Tracy, I don't know if
you saw it. This fellow who's like it used to
be a pro magic the gathering player and gambling's Vmashevitz.
He put up a contract and it said, well's Vmashevitz
get invited onto the Odd Lots podcast this year. And
(27:20):
I thought about going, Oh, I was.
Speaker 6 (27:21):
Like, I just got money on there.
Speaker 5 (27:22):
I'm gonna take all my I'm gonna take all my
fake manifold currency go along and then invite them on
the I didn't do that, but it is very amusing
to think of the various ways you could very easily
get Thank you.
Speaker 6 (27:34):
For protecting the integrity of the podcast and.
Speaker 2 (27:36):
The market, yes, and the market the most.
Speaker 6 (27:38):
The price discovery mechanism of prediction markets. Thank you.
Speaker 5 (27:41):
But I want to get back to actually get deeper
into this question of like you know, on polymarket, there's
a leader board or there's a top volume this week,
and I think you can see leaderboards just kind of
open so you can see talk to us more about
like what good traders are doing and why some people
seem to be better at this than others.
Speaker 3 (28:00):
I think good traders are good at kind of quick
slice intuition and working with limited information, and you know,
where's that skill come from. I mean, it's partly the
common nation of being both analytical and really competitive.
Speaker 2 (28:13):
Right.
Speaker 3 (28:13):
These are not people who are just in the abstract
building academic models, but they're people who have to use
the cliche and other author They have skin in the game,
They have a lot of practice, and they really want
to win, which is why gamifying these things and having
leaderboards and having discussion forums for people to explain the
rationales behind their bets.
Speaker 2 (28:33):
I mean, these are really.
Speaker 3 (28:34):
Really competitive people, which is true for the other fields
that Marie and I indulge in, and the cream rises
to the top over the long run, I suppose.
Speaker 6 (28:59):
So one thing I wanted to ask is we've obviously
been focused on prediction markets, but if I want to
express an opinion or bet money on something like who's
going to win the US election, putting a bet on
poly market or something like that is not my only avenue.
So we know that Trump has that spack DJT. I'm
(29:22):
looking at the share price right now. It's spiked, you know,
in sort of early July, I guess, post the assassination attempt,
but it's come back down dramatically. And there are also
things like I mean, I think at this point there
are a number of them, but Trump related cs and
tokens and things like that. So I could just buy
one of those if I think that Trump is going
(29:44):
to win in November. How are you seeing people sort
of evaluate the opportunity from prediction markets versus things like,
you know, a Trump spack or Trump token.
Speaker 3 (29:56):
I mean, look, if I were talking to the CFTC,
then one thing I'd say is that because there are
proxies for all these things anyway, that certain sectors of
the economy might be better off with the Harris versus
Trump administration, or interest trades treatments might be different.
Speaker 2 (30:11):
Or Bitcoin itself, yeah, which has sort of.
Speaker 6 (30:13):
Become yeah, which has become like a true administration.
Speaker 5 (30:16):
Become kind of a Trump proxy, given how suddenly Bitcoin
friendly has become yeah.
Speaker 2 (30:20):
Yeah.
Speaker 3 (30:21):
So you know, why have people bet on these noisy
proxies when they're trying to hedge political risk, which is
also economic risk. So that's me as I guess now,
as a paid spokes and for prediction market company talking
to the CFTC and saying you and we're all making
you all have to figure out this risk anyways, So
why not have prediction markets instead of having to bet
on DJT coins or whatever.
Speaker 1 (30:41):
Yeah. I think a really important point is that this
is what traders do all the time, right, This is
the job of a professional trader is to buy and
sell things and trade things based on what they think
is going to happen, especially if you're a macro trader. Right,
there are people so Nate and I this week on
the podcast had Bill Perkins, who is a very famous
(31:01):
energy trader who made millions of dollars trading on predicting
correctly what's going to happen to oil future prices too,
energy prices depending on certain global events. What was he doing.
He was betting on the likelihood that those events were
going to happen, right, and he thought that the market
was off, and then he was able to make those
trades accordingly. And so if you think about it in
(31:24):
those terms, I mean, we have prediction markets. That's what
the stock market is, that's what all of these different
commodities markets are. You're constantly, constantly betting on the future
and betting on these things that will happen. And the
best macro traders out there, the people who trade events,
are the ones who have those intuitions and who are
able to figure out, Okay, what do I do and
(31:46):
how do I pull the trigger? Right? These are also
people who have to have a high risk tolerance and
who need to understand risk taking. For someone like Bill Perkins,
he's also a poker player, right, So a lot of times,
once again, these things go hand in hand.
Speaker 5 (31:58):
I remember Tracy when I really was like into poker,
and I used to read these like biographies of poker
players and reading about like how much some of them
just like love to bet on literally everything was really fascinating,
Like they would like two guys would see like a
fly on the table and they're like, oh, I'll bet that.
I'll go that's right, one thousand dollars that that fly
is going to take off in the next ten seconds
(32:18):
from the felt or something like that. And I get
the impression, and it sort of speaks to what Maria
was saying about building up then intuition, like over thousands
and thousands of events. It almost read to me like
the great poker players see probability on something like the
way we see a color of something. It's like that
I see your sunglasses on the table, they're green. Someone
(32:40):
else looks at that sunglass and say, I see there's
some chance that Tracy's gonna pick up the sunglasses.
Speaker 6 (32:46):
But probability that they're gonna break or the.
Speaker 5 (32:48):
Products here they're gonna self combust. And it's just like
becomes the way they see the world. We have a
few minutes left, Nate, what's going to happen in the election?
Speaker 3 (32:57):
So we are actually pretty close to prediction markets. The
Silver Bullets and forecast as of this morning has Harris
with a fifty three percent chance and Trump at forty
seven percent. If you want to round that down to
fifty to fifty, a poker player would say it's not
quite the same, but fifty fifty more or less. I
think the question is like whether she so she clearly
has momentum now in the polls. We can debate what
momentum means exactly, whether that implies momentum will continue. But
(33:19):
there are a couple of downsides for Harris. One is
that the electoral college likely still favors Trump. It's a
very very close popular vote, and to us that she
could be at something of.
Speaker 2 (33:27):
A high water mark.
Speaker 3 (33:29):
There is enthusiasm among Democrats right now that verge is
almost up to being like rapidly excited for Kamala Harris,
but we still have three months to go.
Speaker 2 (33:38):
Cannot be sustained.
Speaker 5 (33:39):
We shall see and then, you know, looking across the
different markets, you know, as you mentioned, I'm looking at
poly Market right now. It's forty nine forty nine percent kamalas,
so they're a little bit tighter than what you haven't
like so far. I don't know, are there things that
you're watching for in the markets themselves. You know, we
did an episode on sports gambling with The Sports Better
(34:01):
and he was talking about, you know, sometimes there's edge
in very niche markets. So he was a tennis he
liked to bet on tennis, but he was saying, you know,
there's there's often opportunities where you can like bet like,
well so and so will win in two sets or
three sets instead of four or whatever it is. Are
there interesting things that you're seeing on the markets, whether
it's Polymarket or others that seem off or on or
(34:23):
interesting or things that we should watch perhaps besides that
headline Harris versus Trump contract.
Speaker 3 (34:30):
I mean you can bet on individual states. You can
bet on things like margins of victory and individual states.
And you know, if you have a model like mine,
then you have lots of opinions about that that you
can bet on potentially, However, the volumes tend to be
a lot smaller. There's also kind of a more macro question,
which is in recent elections, the markets have been a
little bit Republican leaning relative to what the models say.
(34:51):
Hum Partly that's because I think the demographics of who
trade on these markets, right, they are a little bit
crypto pilled, very literally, so in cas it's looking like polymarket,
So that affects things a little bit.
Speaker 2 (35:02):
But also, you know, poles have been off.
Speaker 3 (35:05):
By a little bit in favor, you know, the low
bulld Trump in twenty sixteen, twenty twenty, not in twenty
twenty two.
Speaker 2 (35:12):
But Trump wasn't on the ballot.
Speaker 3 (35:13):
So one way to read the delta between my forecast
in the markets is that the market is pricing in
just a little tiny bit of Trump beating his poles,
which you know, might not be entirely irrational.
Speaker 6 (35:26):
I'm glad you brought this up because the wisdom that
is being derived from this particular crowd, Like the crowd
is technically non American, but definitely you know, mostly male
from what we know, and maybe a little Republican leaning,
as you just mentioned. Are there like efforts underway or
(35:48):
is there a desirability to broaden out the number of
people who are using this in order to maybe like
up the size of the crowd and make sure that
you're getting the best sample that you could possibly get.
And again, if you look at the official polls, the
poles always attempt to get a slice of the American
(36:10):
population that is reflective of its actual makeup. That's not
really happening on these prediction markets. So is there anything
that you could do about that or is it a concern?
Speaker 1 (36:20):
I think that in an ideal world, of course we
would take all of these things into consideration and you
would have a more representative sample of betters. But we're
not living in an ideal world, and like we're not,
I can't affect the regulation, but I do think that
it's important to get a sort of sample that is
(36:42):
representative of the people who are going to be voting, right,
So it's not just representative of the population, but who's
actually going to be going to the polls, who's going
to be casting the ballots. Those are important questions to ask,
and sometimes the fact that things are skewed also reflects
like who's actually going to be walking? Who are we
actually going to be asking? So I think there's so
(37:04):
many different parts of this question. And yes, Nate, as
you correctly point out, I am worried about, yes said,
I am worried about all of these different things. But
some of them are just like a fact of existence,
and we need to account for them. But we need
to realize that, Okay, like if we try to make
it representative, we might actually be skewing things if the
vote isn't going to be representative. If that makes sense.
Speaker 5 (37:26):
Yeah, Actually that leads me to one more question, which
is that just thinking about the election itself, setting aside
betting markets. So there is reason to think that maybe
in twenty sixteen, perhaps the polls weren't capturing all of
Trump's support, and I guess it's sort of played out
like that, but right now it actually seems to cut
in both directions. So there is a view that, okay,
(37:47):
polls aren't good anymore, and that people don't pick up
the phone and they become much more expensive and less efficient,
and that there could be a skew in the type
of person who answers the phone On the other hand,
one thing that we've seen particularly emerging in midyear elections
is that Democrats just like they love to turn out
to vote, They loved the vote in any random election,
(38:08):
And there is the PERCEP shouldn' probably accurate that many
Trump voters are you know, less engaged and they might
support Trump, but whether that support actually translates into showing up,
registering to vote, finding the polling location, going there, and
voting is another question. How are you thinking about like
some of these sort of risks right now in twenty
(38:29):
twenty four, with some of the quality of data, and
you know, ways it could be biased right now.
Speaker 2 (38:35):
Yeah.
Speaker 3 (38:35):
Look, the model more or less assumes that although polls
can and probably will be biased some degree, that the
direction of the bias is unpredictable, which I Joe kind
of see as a spinoff from like efficient market hypothesis.
Speaker 2 (38:48):
The markets aren't always right. They do silly things.
Speaker 3 (38:50):
But if you think you know better than the market
what Nvidia should be priced at or something, then then
you can make a killing trading options or whatever else. Look,
pollsters have an incentive to get the right answer, And
we've also moved away from kind of like a purist
world where you call everybody in the phone book at
random and say can I speak to the person with
the next birthday? And they always answer. We moved away
(39:11):
from that to where like poles are basically models, so
my model is kind of like aggregating models into one
big meta model. And so therefore I think the market
incentives are pretty good, right, And when poles are biased
toward Democrats, the Republican leading polsters tend to get more
work the next cycle, so it's a little bit it's
fairly self correcting.
Speaker 2 (39:32):
I think, actually that's a.
Speaker 1 (39:33):
Very good way of looking at it. So I hope
you're right. Night.
Speaker 5 (39:37):
Nate and Maria, thank you so much both of you
for coming on the podcast. Good luck and congratulations on
the launch of the new podcast. Maybe a little competition,
who knows, but no really appreciate having you both on.
ODD loves to talk about something that's very timely and exciting.
Speaker 1 (39:51):
Thank you so much. It's been a pleasure.
Speaker 5 (40:06):
Tracy, that was a lot of fun. I'm a terrible gambler,
really bad, but I still like it. I don't like
losing money, but I still like in my mind, I
wish I were good, and I like talking about it, well, I.
Speaker 6 (40:18):
Thought Maria's point about when you actually have to put
money behind like your thought process about who is going
to win the election, it sort of sharpens your reasoning
and your thinking. I thought that was interesting. By the way, Joe,
I have good news for you and I have bad news.
Oh okay, So the bad news is there's a question
(40:40):
on poly market that is, will America bans in in
twenty twenty four. The good news is that the current
probability is seven percent. So I think you're okay, that's
all right.
Speaker 5 (40:51):
I have Zalt instead. There's one hundred other ones that,
as we learned in a recent episode, will probably get
through border security regardless of the regulatory environment. But no,
I thought it was fun. And look, it gets back
to two things that I still basically think, which is
that A, in the form of regular markets prediction market
have worked for a long time, and B they're just
(41:13):
from my perspective, I don't participate in betting markets, but
I find it interesting, is like, what is the conventional
wisdom right now on what's going to happen where people's
heads at And as a news consumer, I find them
additive in a way that just say tweets like I
think Kamala is going to win or has the momentum.
It's it's something helpful. On top of that, it's.
Speaker 6 (41:34):
Definitely something to talk about in the media and aout
that is true. I do think not to go all
existential again, but I do think it opens up really
interesting questions about the nature and the purpose of market.
So Nate talked in the beginning about, well, this is
a price discovery vehicle, and you know, I can see that.
(41:55):
But I guess if you were a market traditionalist, you know,
there might be people out there who think that markets
are about efficiently allocating capital, and so the question is like,
what are you really allocating capital too in this particular instance.
But then I guess the reverse argument would be like, well,
there is value in making a correct prediction, and so
(42:17):
you are rewarding that behavior.
Speaker 5 (42:19):
So I think that's a great point, And I think
I would say two things from my perspective, which is
Ny pointed out. For some of these bets, there is real.
Speaker 2 (42:27):
Economic issue at stake.
Speaker 5 (42:29):
So if you are interested in the future of electric
vehicles or oil or whatever it is, then it might
make a very big difference who wins the election. In
other words, like you like you already have skin in
the game and this becomes an instrument to hedging, or
I'm like a little bit more skeptical as like, okay,
so here is one of the things I see. What
will Trump say during his interview with Elon Musk. There's
(42:50):
a seventy two percent he says make America great again.
There's a forty nine percent chance he mentions crypto. There's
a fifty seven percent chance you mentioned censorship, et cetera.
Like for a market like that, that seems like pure
speculation because there are very few actual outside exogenists.
Speaker 6 (43:08):
Well crypto, but yeah, no, that's I take the point.
Speaker 5 (43:11):
Well, like so okay, like okay, so for maybe a
better one, will Taylor Swift get engaged?
Speaker 2 (43:15):
Right?
Speaker 5 (43:16):
Or you know the number here.
Speaker 6 (43:18):
That might that might actually mean something for inflation.
Speaker 5 (43:21):
Or the marriage market, right, because a lot of people
think that if Taylor Swift gets engaged, then a bunch
of people are like, it's time for us to tie
the knot and sort of do the same thing.
Speaker 6 (43:30):
Maybe we should just do this for a while and
just play a game where we go through all of
these particular events and questions come up with the real
world economic it come.
Speaker 5 (43:38):
Up with a j there's one. The number of Elon
Musk tweets between August second August nine, currently between eighty
and eighty nine is at one hundred percent, So people,
well to keep tweeting.
Speaker 6 (43:50):
Maybe Elon must tweets have an impact on the presidential election.
There has an impact on a bunch of real world stuff.
Speaker 5 (43:56):
Five percent that there's a doge coin etf in twenty
twenty four. That seems a little high to me, because
but you know, we don't even have anyway. We could
go on and on. It's very fun. It's just another
way for me to consume the news.
Speaker 6 (44:08):
All right, Well, I'm sure we'll probably end up doing
more prediction market episodes in the future, but for now,
shall we leave it there?
Speaker 2 (44:16):
Let's leave it there.
Speaker 6 (44:17):
This has been another episode of the Athlots podcast. I'm
Tracy Alloway. You can follow me at Tracy Alloway.
Speaker 5 (44:23):
And I'm joll Wisenthal. You can follow me at the Stalwart.
Follow our guest Nate Silver, He's at Nate Silver five
thirty eight. Maria Kanakova, She's at Mconnakova. Follow our producers
Carmen Rodriguez at Kerman armand Dashill Bennett at deshbot and
Kilbrooks at Kilbrooks. And thank you to our producer Moses Onam.
And for more Oddlots content, go to Bloomberg dot com
(44:43):
slash odd lots, where of transcripts, a blog and a
newsletter and you can chat about all of these topics
in our discord. In fact, there's a very active channel
where people are talking about this stuff all the time
in the elections channel and the pundit dunk take channel
where they people drop bad predictions or make fun of people.
Very entertaining subchannel, and there might be my favorite. Check
(45:03):
out our discord, Discord dot gg slash odlot.
Speaker 6 (45:07):
And if you enjoy all thoughts, if you like when
we talk about prediction markets and the nature of markets themselves,
then please leave us a positive review on your favorite
podcast platform. And remember, if you are a Bloomberg subscriber,
you can listen to all of our episodes absolutely ad free.
All you need to do is connect your Bloomberg subscription
with Apple Podcasts. In order to do that, just find
(45:28):
the Bloomberg channel on Apple Podcasts and follow the instructions there.
Thanks for listening.
Pushkin. Welcome back to Risky Business, a show about making
better decisions. I'm Maria Kannakova.
Speaker 2 (00:29):
And I'm Nate Silk.
Speaker 1 (00:30):
Today we're dropping into your feeds to share an episode
that Nate and I taped with The Odd Lots Podcast,
where we appeared to talk about prediction markets.
Speaker 3 (00:38):
Yeah, this is a really fun interview. The host Joe Wisenthal,
I know d you a little bit. We've hung out
in Vegas together actually, and Tracy Alloway, Uh ask the
great questions. They're kind of nerdy in the same ways
that we are. So it was a fun, fun crossover
eighties sitcom crossover episode.
Speaker 1 (00:55):
Basically, absolutely and if you enjoy the episode, you can
find more of Odd Lots wherever you're listening to this podcast.
Speaker 4 (01:16):
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 5 (01:32):
Hello and welcome to another episode of The Odd Lots Podcast.
I'm Joe Wisenthal and.
Speaker 6 (01:37):
I'm Tracy Alloway.
Speaker 5 (01:38):
Tracy, I have to say prediction markets have actually become
a really significant part of what I would call my
news consumption.
Speaker 6 (01:46):
I know you tweet about them a lot. In fact,
you have an ongoing joke that you keep repeating that
I would argue that novelty value has worn off. But
clearly I'm wrong because everyone on the platform finds it
very amusing.
Speaker 5 (01:59):
Yeah, and other people have stolen my joke.
Speaker 6 (02:01):
I've seen that.
Speaker 4 (02:02):
Yeah.
Speaker 2 (02:02):
So the joke is.
Speaker 5 (02:03):
That, you know, when people are really confident about something
and something is priced at seventy five cents on the dollar,
they're selling a dollar for seventy five cents right now
on polymarket. My joke is that when something is fifty
to fifty, I say, oh, they're selling dollars for fifty cents,
which of course sounds confident but can mean in both directions.
It's worked really well. I'm getting a lot of mileage
out that one. And you may be bored of it now,
(02:24):
but I think we're in the valley of humor where
if I'm still making the joke a year from now
at Tracy, You're gonna find it funny. We shall see.
Speaker 6 (02:33):
Okay. Prediction markets, Okay, prediction markets are interesting. I have
a lot of questions about them, And first of all,
I feel like I should caveat this entire conversation with
an admission that I'm pretty sure I have made on
this podcast before, but I intuitively do not understand probabilities.
(02:55):
I'm kind of serious, Like I understand rationally, why if
you flip a coin five times, the probability of having
five instances of heads is not fifty percent, but if
you flip it once, it's fifty percent. But like, on
an intuitive basis, I don't really feel that way, right,
(03:15):
And then the other thing I would say when I
see prediction markets. So one of the things that happened
recently was people were going like, oh, prediction markets are
so smart and so interesting because like on Predicted there
was a ten percent chance that Biden would drop out
of the race, and so people were going like, oh,
see the prediction market called it, and it was like, well,
(03:37):
a ten percent chance. That was higher maybe than some
other platforms or some pundits expected, but it happened, the
chance was one hundred percent.
Speaker 3 (03:46):
Like I just.
Speaker 6 (03:48):
Intuitively, I don't get it. I don't get I don't
get what the percentage actually means.
Speaker 5 (03:53):
Right, So, Tree, the way you think about the lottery,
for example, is that if you buy a lottery ticket,
your odds should be fifty to fifty because either you
win or you done right.
Speaker 6 (04:01):
Therefore it should be binary.
Speaker 5 (04:03):
No, So the way I think about them, and we'll
be talking very shortly to people who know a lot
more than me. Is not that like I find conversations
about the rightness or the wrongness of prediction markets or
a given contract on a market to be sort of
the wrong question. It's more like, to me where I
find it valuable. It's like, Okay, a lot of people
think that Biden might drop out, right, right, But is
(04:27):
that mean there's an eighty percent chance? Does that mean
there's a fifty five percent chance? And so what I
find interesting about prediction markets is not so much whether
going to be right or wrong, but that it seems
like they can put some sort of number on the
emerging conventional wisdom. Because look, even before the debate, some
people thought Biden still had a chance of dropping out,
and so it's interesting that the traders in those markets
(04:49):
assigned non negligible odds to that happening, and then of
course it all spiked after the debate and stuff like that.
So to me, you know, in thinking about the election,
we have polls, we have models, we have prediction markets.
Now we have punditry that appears on opinion pages of
various times. It's yet another tool to sort of consume
information and figure out where people's heads are at. And
(05:12):
I like it for that reason.
Speaker 6 (05:13):
Yeah, okay, but I still don't get the value of
putting a specific number on it. Like you could just
have an arrow that goes up or down that shows momentum.
And I'm being slightly facetious here, but like you could
look at Google trends or something, or you know, try
to gauge momentum that way. But okay, I have a
bunch of questions. I fully admit that this is something
that again on a sort of like instinctual level, I
(05:37):
do not quite understand. But we do, in fact have
the perfect guests to explain it all to us.
Speaker 5 (05:42):
Yeah, yeah, I'm very excited. We are going to be
speaking with Nate Silver and Maria Kanakova. They're the co
hosts of the fairly brand new Risky Business podcast, which
is all about questions like this. They're both poker players.
Speaker 3 (05:57):
They are both.
Speaker 5 (05:57):
Recently played in the World Series of Poker and have
made a lot of money over the years playing poker.
They are people with probability in gambling and odds and
making decisions with money on the line. Both in their
blood is the author of the forthcoming book on the Edge,
The Art of Risking Everything, And he's also an advisor
to Polymarket, which is one of the big prediction markets
(06:18):
that everyone has been quoting these days. So a couple
of great people to talk to about things like betting
on elections and how they think about all this stuff.
So Nate and Maria, thank you guys both for coming
on odd Laws.
Speaker 2 (06:30):
Thank you so much. Joe and Tracy, Yeah.
Speaker 1 (06:32):
Thanks for having us.
Speaker 5 (06:33):
Absolutely so. When we look at all these markets and
poly markets the hot one, but I forget the one
is predict It was also really big. Do I think
they're running into some they have some regulatory issues years
ago there used to be in trade. There's the Iowa
futures market, there's others. What is the value When people
look at all these numbers and say, like, what is
the value of markets like these?
Speaker 3 (06:55):
I think it's the same value as any type of
market where you have price discovery from participants who have
a rational incentive to make smart trades and be closer
to whatever the value the market resolves.
Speaker 2 (07:05):
To, you know.
Speaker 3 (07:06):
I mean Tracy asks some existential questions about the notion
of probability for things that are kind of seen as
one off events. But whether things are intrinsically uncertain or
not is kind of above my paid grade, right. The
fact is that we have uncertain information. We're trying to
make judgement space and complete data and complete information. And
I think it's better to quantify things than to be
(07:27):
totally subjective and use weasel words and not have any
accountability for you know, a twenty percent chance versus a
forty percent chance for example.
Speaker 1 (07:35):
Yeah, and I think that there is a huge difference
between the two and Tracy your existential questions make a
lot of sense to me as a psychologist, because you know,
the human mind really does not like probabilistic thinking. You're
not the only one, and we do want to think
in absolutes, right, We do like zero and one hundred
those are easy numbers for us, whereas twenty three percent
not so much. But this idea that if we actually
(07:59):
put our money where our mouth is, it will help
us calibrate those probabilities better, help us calibrate our intuitive
sense of how confident we are in something, how much
we actually believe in it. That's I think why prediction
markets in all sorts of literature and all sorts of
areas have gained momentum because you think differently. I bet
(08:22):
and I would put money on this tracy that if
I forced you to put money down on an opinion
or a thought, you would actually start homing in on
those instincts, on those decisions, and you would find that, Okay, well,
like you know, I'm probably less certain of this than
I thought I was, because I'm only willing to bet,
you know, ten dollars and not one hundred dollars. Asking
(08:43):
yourself questions like this, Actually putting down those bets really helps.
And what Nate was saying, when you have lots of people, right,
when you have hundreds and thousands of people doing this,
that's when the calibration becomes better. Because if we have
a thousand Tracs who might you know, not believe in
probabilities that much or not understand them, and yet they're
all putting their money down. The idea is that in
(09:06):
this particular case, the crowd actually knows something right, there
is some wisdom to the amount of money you're putting down,
because once again, actually betting with your wallet so that
it hurts, that's when you start to actually question your beliefs.
Speaker 6 (09:24):
Well, let me just say, off the bat, thank you
so much for trying to make me feel better. I
will just say, in my defense, I did do AP statistics,
and I did like I did okay, probably because back
then you had to draw charts by hand, and I
was really into drawing like neat charts. So I think
I got points for that.
Speaker 2 (09:41):
Okay.
Speaker 6 (09:41):
Let me ask a non existential question, which is, if
I go on to polymarket or predict it, and let's
just say I see an event and the probability is
something like forty percent, where is that forty percent coming from?
And what exactly is it telling me?
Speaker 3 (10:01):
It's saying that in the long run, if you took
one hundred similar events some reference class, that the event
would occur about already out of every one hundred times
and wouldn't occur the.
Speaker 2 (10:12):
Other sixty out of one hundred.
Speaker 3 (10:13):
I think what bothers people is that they question whether
it's something like an election falls into an appropriate larger
subset of some random distribution of data.
Speaker 2 (10:22):
Right. That bugs people.
Speaker 3 (10:23):
If you're playing poker, then there's one to fifty two
cards that might come next. It's technically not random, right.
The hand is actually dealt out once it's shuffled but
de facto random, right, Or if you're watching a basketball game,
you have some sense that a free throw may or
may not go in, or may bounce off the back rim,
et cetera, et cetera. With elections, I mean, parties always
tell people that, oh, this is the most important election
(10:44):
of all time, but there are like a lot of
like fairly random contingencies in this election. Or example, to
use a somewhat pointed example, if Donald Trump had not
turned to look at a billboard of immigration data, then
the bullet that was fired at him might have done
much more damage than Grayze's ear, for example. Or in
two thousand, the butterfly ballot. This is going back a ways.
(11:05):
A ballot design issue in Palm Beach County, Florida probably
costs al Gore the election and cause old people to
confusingly vote for pap you can and instead. So there
are these kind of near random circumstances even in elections.
But even then, you know, not everything is knowable or predictable.
And if you think it's locked in that Harris is
going to win or Trump is going to win, then okay,
well great, maybe you're right, but you can make a
(11:26):
lot of money by betting on that at polymarket or
predicted or whatever else.
Speaker 1 (11:30):
Yeah, I think one more time. You know, nothing in
life is certain ever, no matter how much we want
it to be, right, Like, I might die in the
next minute. I hope I don't, but I'm right.
Speaker 6 (11:41):
There's a non.
Speaker 5 (11:42):
Zero non zero jes exactly where my mind went when
you said nothing.
Speaker 1 (11:48):
Right. But it's so true. And if you actually think
of the election like a poker hand, except you know,
think about it in like multiverse terms. I'm going to
go back to existential terms, Tracy. You try to get
us out of existential terms, I'm going to bring us
right back there. So imagine, you know, the multiverse experiment
where we have, you know, a million possible versions of
(12:10):
our reality, and in one of them, we had different ballots. Right,
they weren't butterfly ballots. Al Gore won the election. We
would probably not be here right now, because you know,
it's funny that it's a butterfly Yeah, butterfly ballot, butterfly effect. Right,
those tiny things do matter, but you do have to
realize that those probabilities still matter, right, like the fact
(12:30):
that Hillary Clinton lost and that Nate got a lot
of for it. I defended Nate very publicly, as did
a lot of people, because his forecast was the single
best one. It gave her a good chance of winning,
but it gave Donald Trump the highest chance of winning.
But people don't like you know, you know, they don't
understand that over twenty percent is a hell of a
lot of a percent. You know. In my last book,
(12:53):
I compared Nate's percentage just to poker, and I said,
the chances of Donald Trump winning according to Nate's prediction
was the same chance of you flopping a pair in Texas.
Hold them now, Think how often you flop a pair
right that you pair up one of the two cards
that you're holding. That happens all the time.
Speaker 5 (13:11):
I really just like, sometimes I'm sitting there at the
poker table and I'm like, God, just give me a
set and then I could double up and walk away
for the night, and it never happens anyway. So I
have two quick thoughts. One is I always do find
it funny when people talk about, like our prediction markets
good or not, because a point that I've made many
times in writing, et cetera, is we actually do have
a very popular liquid prediction market that existed for a
(13:34):
long time, which is the short term treasury market, which
is explicitly a bet on what the you know, nine
members or whatever of the FMC are going to do
over the next And that's literally a prediction market. And
no one questions whether that market works. It does work,
and it exists, and there's a lot of money writing
on it, and it literally is not just metaphorically, it
is a prediction market.
Speaker 6 (13:54):
You know.
Speaker 5 (13:54):
It occurs to me though, when we talk about, okay,
what is a forty percent return? This must be easily testable, right,
Like if you take a thousand contracts that have existed
over the life of polymarket or the life of predicted
or intrade or whatever it was, and then say, like, okay,
one hundred days out from resolution, did the ones that
say forty percent? Did they resolve forty percent of the time?
Speaker 2 (14:16):
Like? Has that been tested?
Speaker 5 (14:17):
Like can we say that that is the case that
things with forty percent in the prediction market over some
timeframe do resolve forty percent towards the direction?
Speaker 2 (14:26):
There's been somewhat mixed literature on this. I do know.
Speaker 3 (14:29):
I guess this is just a not so humble brag right.
I do know historically that like the five point thirty
eight now Silver Bullet and election forecasts have been better
than prediction markets, which is unusual. Usually publicly available information
is not better than the market. However, they've been pretty
well calibrated according to most estimates.
Speaker 2 (14:45):
And also I think the markets.
Speaker 3 (14:47):
Are maturing a lot where Look, I've talked to a
lot of different types of businesses, investment banks and hedge
funds and things like that, and they understand that like
political risk is market risk when you have this bigure
difference between the two parties, that like whether Donald Trump
or Kamala Harris is the next president, has a lot
of implication for every sector of the economy or any
trades you want to make. And so you have seen
(15:09):
more institutional attempts to either bet directly through prediction markets
or bet on proxies. And again I'm an advisor to
poly market, but their volumes are meaningfully much higher than
in the past, their structures are good, so you don't
pay as much of a tax in essence, so I
kind of think they've turned a corner from being pretty
good to maybe verging on very good.
Speaker 1 (15:31):
Yeah, I think, Nate, you just head on a really
important point, which is volume. Right, prediction markets are only
as good as the traffic that they get, and so
for a long time, you know, there was no legal
prediction market in the United States, and so it's very
difficult when you're talking about betting on political events within
the United States to have a well calibrated market if
people within the United States can't actually bet on it. Right,
(15:53):
So I think that a lot of things are changing,
and hopefully we'll change for the better because volume is
essential in calibrating correctly, and you need people with expertise
doing it as well. But you also you just need
bodies to you need both of these things.
Speaker 3 (16:06):
The ratio of smart money to dumb money is really important. Yes,
in the Super Bowl, the literal actual chiefs versus forty
nine ers whatever, super Bowl, there is so much dumb
money being bet on the Super Bowl that the sharp
money can't consume all of it, and so therefore you
often have positive expective value bets by fading the public
in the Super Bowl. That's not true for a regular
season Hornet's Wizard's Game in the NBA or something, but
(16:29):
for very very big events like a big UFC fight
or the super Bowl, talk about some in the book
a little bit. Then those things potentially you have more
dumb money than sharp money. And so what you now
have happening, I think is like more of a professional
class of betters on politics, whether it is hedge funds
or whether it is just smart individuals who are betting
on the US election and elections around the world. You
(16:50):
see some sharp money coming into these markets.
Speaker 6 (17:10):
So just on this idea of like where the information
and the bets are actually coming from. Talk to us
a little bit about the difference between a book maker
versus a prediction market, because my impression of a bookie
is like they kind of set the odds and then
people decide whether or not they want to place money
on them, and then you know, they might calibrate those
(17:31):
odds depending on the response they are getting from people
placing the bets. But there's like a starting point that
the bookies have, and I guess it must be different
for prediction markets. Talk to us about like the difference
in establishing those probabilities.
Speaker 3 (17:46):
I mean, yeah, the classic act of bookmaking is where
you have some in essence prior. I guess it's an
advanced show, right, So like you have. You start out
with some number that you kind of probably comes out
of a model or some conversation. You have the initial
line that a sportsbook post on an NFL game is
actually probably often quite beatable. Right, it's just some like
nerd in a back room somewhere who's doing his best.
(18:08):
But then you look for action from sharp betters. Maybe
the book maker thinks that Maria is really good at
sports bidding and I'm a total hack whale.
Speaker 1 (18:16):
Definitely, definitely anyone listening that this is accurate.
Speaker 3 (18:20):
So Maria bets on the Chiefs, she bets five K
on the Chiefs, and they'll move the line toward the
Chiefs in Maria's direction. Right, So now it's more extensive
for me to about on the Chiefs. If I bet
I think I'm a whale, they to do about it, right,
because they think that's just dumb money they're trying to
make a profit from. So that's traditional book making, whereas
the prediction markets, it's all happening more organically, right, there's
(18:41):
no human at the switch who was deciding and evaluating
where to move their numbers.
Speaker 1 (18:46):
I think that the other important thing is that you,
I think suggested Nate but didn't say explicitly when you're
talking about sports books, when you're talking about bookmaking, this
all happens pretty much manually, where people actually look to
see who's placing the bets, and then they actually adjust
the lines, right like there is a human adjusting the
(19:06):
line and deciding, okay, this is what we need to do,
and that might happen hundreds of times a day, maybe
even more, and the line gets better and better. But
in prediction markets, those adjustments are just happening all the time.
Speaker 3 (19:18):
It's the invisible hand, the same as like the stock market,
for example.
Speaker 1 (19:21):
YEP.
Speaker 5 (19:22):
I could imagine that there are various types of betters
on prediction markets, and you broke it down into sharps
versus whales or whatever it is, or done money versus
smart money, but they're also different. Even within the category
of smart money, there are probably many different approaches. So
I could imagine that there are some people who are
very sophisticated in their political analysis, and they could say,
(19:43):
you know, this person is a better chance of winning,
you know, getting the vice presidential tap than someone else.
Someone else might just say, you know what, anytime the
model or the price diverges from the silver bulletin model.
I'm going to go either short or long that I imagine
that there are arbitrage traders who are just sort of
maybe looking at the price on one exchange versus the
(20:05):
price of another exchange and attempting to take advantage of discrepancy,
just like it exists in stock market. I assume maybe
there are momentum people. It's like this is hot right now,
even if I don't believe it. But talk to us
about some of the different strategies that the good betters
on prediction markets take.
Speaker 3 (20:22):
I mean, I think you identified most of them, Joe.
And you know, one thing you learned being in the
gambling world, playing poker and so forth, is that if
there is an arbitrage to have or an edge to
be had, someone's going to.
Speaker 2 (20:32):
Hoover it up. Right.
Speaker 3 (20:33):
There are actually people who go around and are professional
slot machine players, for example, because there are odd circumstances
where you might have a jackpod or a conditional probability
where playing a slot machine can don't do this at home,
do not do this at home, but there are cases
where race.
Speaker 2 (20:47):
Is going to do it.
Speaker 3 (20:49):
Yeah, Plus you need to play a slot machine. So
at the end of the day, something like the vice
presidential race. It's inherently somewhat subjective, but if you have practice,
I mean as a poker player. Poker players develop uncanny
intuitions for probabilities. They'll say, I need thirty one percent
to make this call profitable on the river, and it
(21:10):
was only getting thirty percent and so I folded, right.
I mean, they'll literally get to like one percent delta
versus the actual odds.
Speaker 1 (21:17):
Are good poker players. You need an adjective in there.
Speaker 3 (21:20):
Yeah, yeah, but you learn it kind of. I mean,
it's just it's muscle memory at some point.
Speaker 2 (21:24):
Yeah.
Speaker 1 (21:25):
Absolutely, And sometimes you don't even quite know what the
probabilities are. You just know that you have those odds
or you don't have those odds. You really do start
feeling them. So that is something that develops over time.
And I'm actually not sure though that it would develop
over time when you're doing something like prediction markets, right,
because slot machines are also something that is very experiential,
(21:47):
right where you actually kind of are doing this and
you're trying it over and over and over. And for
prediction markets, I think you often just place lots of
bets and it's not like you're sitting there actually watching
this and experiencing it and learning from it. So I
think you already. If you want to be a good better,
you need to learn those intuitions from something like poker
(22:08):
and then apply them to the prediction markets. I don't
think it works the other way around, because the way
that the brain works, you need that experience. You need
to sample those probabilities over and over and over. That's
why poker players know what one percent feels like, because
they've played tens of thousands, hundreds of thousands of hands
and they have seen the outcomes they've sampled correctly, right,
(22:29):
so they know exactly what that feels like. That doesn't
happen in prediction markets. So Nate can go into a
prediction market and he's going to crush, right, because he
has a good instinct for those probabilities. But someone who
doesn't already, I don't think that they're going to suddenly
develop it because they were betting in prediction markets.
Speaker 6 (22:47):
Joe, I can say with one hundred percent confidence that
I have failed to apply my poker intuitions to my
slot machines playing strategy. That is definitely true. Okay, Wait,
so I'm looking at polymarket right now, and I should
look at this more because this is actually kind of fun.
How are the particular events that people are betting on?
(23:09):
Are those chosen or selected? Because right now I am
looking at will the US confirm that aliens exist in
twenty twenty four? What will Trump say in August? I
mean really, I feel like that could be anything? And
then will Taylor Swift get engaged in twenty twenty four?
So the big questions of our time? But how are
those sort of like why those particular questions? Is it
(23:31):
just if anyone wants to start a market in a
particular event.
Speaker 3 (23:35):
Yeah, I'd say the polymarket guys who I know a
little bit, are very attuned to finance, Twitter and politics,
Twitter and crypto Twitter. Sometimes they're kind of jokes and
kind of troll is. I mean, they're trying to have
some fun, right, and so you'll see some questions that
are a little bit memified.
Speaker 2 (23:50):
For sure.
Speaker 1 (23:50):
I actually saw Nate and I'm not sure if this
was I don't remember if it was on polymarket or
one of the other prediction markets, but there was a
prediction market on our podcast, including you know, number of
f bombs that Nate will drop within the first ten minutes.
You know, things like.
Speaker 6 (24:05):
Wait, do you guys bet on that? Presumably you can
make a lot of money.
Speaker 3 (24:09):
I mean some sites say that that's okay, right if
you talked so. The other the big free money prediction
market site is Manifold, which has a s very dedicated
community traders. So even though as a polymarket advisor, now
I'd say I think real money is a way to go,
it's pretty good. I certainly have a lot of respect
for Manifold, But yeah, a Menifold is kind of radical
transparency where anyone can put up a market about anything
(24:31):
and they will even say yeah, as long as there's
no complict of interest, then inside information only makes the
market smarter.
Speaker 2 (24:38):
I'm a little bit worried about that.
Speaker 3 (24:39):
I mean, this is an issue in sports markets too,
where now you have ESPN bets might offer a market
on like the NFL draft or something. Right, well, if
you're an ESPN NFL beat reporter, you might have a
lot of knowledge about what the Atlanta Falcons are going
to do. And for politics markets, I mean something moved
the markets toward Tim Walls, Kamala Harris's VP pick aggressively
(25:00):
about fifteen minutes before that pick was confirmed.
Speaker 2 (25:04):
What is that? I don't know.
Speaker 3 (25:05):
Maybe it's that there were SUVs as there seemed to
be outside of Tim Wallas's resident Minnesota where we lives
in Minnesota. But inside information is I mean from a
user standpoint, it's all incorporated, so it's useful. But like
you do wonder a little bit about like are there
ulterior motives for people who have, you know, inside knowledge
about sports, politicst cetera, financial events to bet?
Speaker 1 (25:26):
Yeah, and then you know there's a thin line. I'm
working right now on my next book, which is about cheating,
and there's a thin line when you can use inside
information where you know everything is fair game between that
and cheating right and starting to throw games and starting
to actually do things where how you bet affects how
you act, and that's incredibly difficult to police. It's always
(25:46):
been difficult to police, and I think it's going to
become even more so. So I personally, and I'm not
involved with any prediction markets, I personally would like to
see there be some sort of penalties in it. Not
being quite as open to that sort of thing, just
because I think that there is a huge possibility for
abuse and for things that actually end up sabotaging the
(26:08):
integrity of especially things like sports games, but politics, you know,
all sorts of contests.
Speaker 5 (26:13):
Right, Tracy, and I I think it was last year
maybe twenty twenty two, we interviewed Roustin benham Oh, the
head of the CFTC, and they have not been friendly
towards prediction markets for some of these specific reasons which
you there are probably good reasons why you don't want
manipulation of actual political events to have money on the line.
And actually, while we're on this topic specifically, since you're here, Nate,
(26:37):
my understanding is that polymarket is not legally available to
people in the US, but as many people know, VPNs exist,
and because it uses stable coins to fund it, there
are ways around it. Is that an accurate characterization of
its state we look?
Speaker 3 (26:53):
Since I am in an especial capacity for them, I
las say is that you are not allowed to bet
on polymoticket if you're in.
Speaker 2 (26:57):
The United States. Got it?
Speaker 5 (26:58):
Okay, we know what it's going on here. You know,
you mentioned prediction markets on podcasts actually there and you
mentioned manifold at one point, Tracy, I don't know if
you saw it. This fellow who's like it used to
be a pro magic the gathering player and gambling's Vmashevitz.
He put up a contract and it said, well's Vmashevitz
get invited onto the Odd Lots podcast this year. And
(27:20):
I thought about going, Oh, I was.
Speaker 6 (27:21):
Like, I just got money on there.
Speaker 5 (27:22):
I'm gonna take all my I'm gonna take all my
fake manifold currency go along and then invite them on
the I didn't do that, but it is very amusing
to think of the various ways you could very easily
get Thank you.
Speaker 6 (27:34):
For protecting the integrity of the podcast and.
Speaker 2 (27:36):
The market, yes, and the market the most.
Speaker 6 (27:38):
The price discovery mechanism of prediction markets. Thank you.
Speaker 5 (27:41):
But I want to get back to actually get deeper
into this question of like you know, on polymarket, there's
a leader board or there's a top volume this week,
and I think you can see leaderboards just kind of
open so you can see talk to us more about
like what good traders are doing and why some people
seem to be better at this than others.
Speaker 3 (28:00):
I think good traders are good at kind of quick
slice intuition and working with limited information, and you know,
where's that skill come from. I mean, it's partly the
common nation of being both analytical and really competitive.
Speaker 2 (28:13):
Right.
Speaker 3 (28:13):
These are not people who are just in the abstract
building academic models, but they're people who have to use
the cliche and other author They have skin in the game,
They have a lot of practice, and they really want
to win, which is why gamifying these things and having
leaderboards and having discussion forums for people to explain the
rationales behind their bets.
Speaker 2 (28:33):
I mean, these are really.
Speaker 3 (28:34):
Really competitive people, which is true for the other fields
that Marie and I indulge in, and the cream rises
to the top over the long run, I suppose.
Speaker 6 (28:59):
So one thing I wanted to ask is we've obviously
been focused on prediction markets, but if I want to
express an opinion or bet money on something like who's
going to win the US election, putting a bet on
poly market or something like that is not my only avenue.
So we know that Trump has that spack DJT. I'm
(29:22):
looking at the share price right now. It's spiked, you know,
in sort of early July, I guess, post the assassination attempt,
but it's come back down dramatically. And there are also
things like I mean, I think at this point there
are a number of them, but Trump related cs and
tokens and things like that. So I could just buy
one of those if I think that Trump is going
(29:44):
to win in November. How are you seeing people sort
of evaluate the opportunity from prediction markets versus things like,
you know, a Trump spack or Trump token.
Speaker 3 (29:56):
I mean, look, if I were talking to the CFTC,
then one thing I'd say is that because there are
proxies for all these things anyway, that certain sectors of
the economy might be better off with the Harris versus
Trump administration, or interest trades treatments might be different.
Speaker 2 (30:11):
Or Bitcoin itself, yeah, which has sort of.
Speaker 6 (30:13):
Become yeah, which has become like a true administration.
Speaker 5 (30:16):
Become kind of a Trump proxy, given how suddenly Bitcoin
friendly has become yeah.
Speaker 2 (30:20):
Yeah.
Speaker 3 (30:21):
So you know, why have people bet on these noisy
proxies when they're trying to hedge political risk, which is
also economic risk. So that's me as I guess now,
as a paid spokes and for prediction market company talking
to the CFTC and saying you and we're all making
you all have to figure out this risk anyways, So
why not have prediction markets instead of having to bet
on DJT coins or whatever.
Speaker 1 (30:41):
Yeah. I think a really important point is that this
is what traders do all the time, right, This is
the job of a professional trader is to buy and
sell things and trade things based on what they think
is going to happen, especially if you're a macro trader. Right,
there are people so Nate and I this week on
the podcast had Bill Perkins, who is a very famous
(31:01):
energy trader who made millions of dollars trading on predicting
correctly what's going to happen to oil future prices too,
energy prices depending on certain global events. What was he doing.
He was betting on the likelihood that those events were
going to happen, right, and he thought that the market
was off, and then he was able to make those
trades accordingly. And so if you think about it in
(31:24):
those terms, I mean, we have prediction markets. That's what
the stock market is, that's what all of these different
commodities markets are. You're constantly, constantly betting on the future
and betting on these things that will happen. And the
best macro traders out there, the people who trade events,
are the ones who have those intuitions and who are
able to figure out, Okay, what do I do and
(31:46):
how do I pull the trigger? Right? These are also
people who have to have a high risk tolerance and
who need to understand risk taking. For someone like Bill Perkins,
he's also a poker player, right, So a lot of times,
once again, these things go hand in hand.
Speaker 5 (31:58):
I remember Tracy when I really was like into poker,
and I used to read these like biographies of poker
players and reading about like how much some of them
just like love to bet on literally everything was really fascinating,
Like they would like two guys would see like a
fly on the table and they're like, oh, I'll bet that.
I'll go that's right, one thousand dollars that that fly
is going to take off in the next ten seconds
(32:18):
from the felt or something like that. And I get
the impression, and it sort of speaks to what Maria
was saying about building up then intuition, like over thousands
and thousands of events. It almost read to me like
the great poker players see probability on something like the
way we see a color of something. It's like that
I see your sunglasses on the table, they're green. Someone
(32:40):
else looks at that sunglass and say, I see there's
some chance that Tracy's gonna pick up the sunglasses.
Speaker 6 (32:46):
But probability that they're gonna break or the.
Speaker 5 (32:48):
Products here they're gonna self combust. And it's just like
becomes the way they see the world. We have a
few minutes left, Nate, what's going to happen in the election?
Speaker 3 (32:57):
So we are actually pretty close to prediction markets. The
Silver Bullets and forecast as of this morning has Harris
with a fifty three percent chance and Trump at forty
seven percent. If you want to round that down to
fifty to fifty, a poker player would say it's not
quite the same, but fifty fifty more or less. I
think the question is like whether she so she clearly
has momentum now in the polls. We can debate what
momentum means exactly, whether that implies momentum will continue. But
(33:19):
there are a couple of downsides for Harris. One is
that the electoral college likely still favors Trump. It's a
very very close popular vote, and to us that she
could be at something of.
Speaker 2 (33:27):
A high water mark.
Speaker 3 (33:29):
There is enthusiasm among Democrats right now that verge is
almost up to being like rapidly excited for Kamala Harris,
but we still have three months to go.
Speaker 2 (33:38):
Cannot be sustained.
Speaker 5 (33:39):
We shall see and then, you know, looking across the
different markets, you know, as you mentioned, I'm looking at
poly Market right now. It's forty nine forty nine percent kamalas,
so they're a little bit tighter than what you haven't
like so far. I don't know, are there things that
you're watching for in the markets themselves. You know, we
did an episode on sports gambling with The Sports Better
(34:01):
and he was talking about, you know, sometimes there's edge
in very niche markets. So he was a tennis he
liked to bet on tennis, but he was saying, you know,
there's there's often opportunities where you can like bet like,
well so and so will win in two sets or
three sets instead of four or whatever it is. Are
there interesting things that you're seeing on the markets, whether
it's Polymarket or others that seem off or on or
(34:23):
interesting or things that we should watch perhaps besides that
headline Harris versus Trump contract.
Speaker 3 (34:30):
I mean you can bet on individual states. You can
bet on things like margins of victory and individual states.
And you know, if you have a model like mine,
then you have lots of opinions about that that you
can bet on potentially, However, the volumes tend to be
a lot smaller. There's also kind of a more macro question,
which is in recent elections, the markets have been a
little bit Republican leaning relative to what the models say.
(34:51):
Hum Partly that's because I think the demographics of who
trade on these markets, right, they are a little bit
crypto pilled, very literally, so in cas it's looking like polymarket,
So that affects things a little bit.
Speaker 2 (35:02):
But also, you know, poles have been off.
Speaker 3 (35:05):
By a little bit in favor, you know, the low
bulld Trump in twenty sixteen, twenty twenty, not in twenty
twenty two.
Speaker 2 (35:12):
But Trump wasn't on the ballot.
Speaker 3 (35:13):
So one way to read the delta between my forecast
in the markets is that the market is pricing in
just a little tiny bit of Trump beating his poles,
which you know, might not be entirely irrational.
Speaker 6 (35:26):
I'm glad you brought this up because the wisdom that
is being derived from this particular crowd, Like the crowd
is technically non American, but definitely you know, mostly male
from what we know, and maybe a little Republican leaning,
as you just mentioned. Are there like efforts underway or
(35:48):
is there a desirability to broaden out the number of
people who are using this in order to maybe like
up the size of the crowd and make sure that
you're getting the best sample that you could possibly get.
And again, if you look at the official polls, the
poles always attempt to get a slice of the American
(36:10):
population that is reflective of its actual makeup. That's not
really happening on these prediction markets. So is there anything
that you could do about that or is it a concern?
Speaker 1 (36:20):
I think that in an ideal world, of course we
would take all of these things into consideration and you
would have a more representative sample of betters. But we're
not living in an ideal world, and like we're not,
I can't affect the regulation, but I do think that
it's important to get a sort of sample that is
(36:42):
representative of the people who are going to be voting, right,
So it's not just representative of the population, but who's
actually going to be going to the polls, who's going
to be casting the ballots. Those are important questions to ask,
and sometimes the fact that things are skewed also reflects
like who's actually going to be walking? Who are we
actually going to be asking? So I think there's so
(37:04):
many different parts of this question. And yes, Nate, as
you correctly point out, I am worried about, yes said,
I am worried about all of these different things. But
some of them are just like a fact of existence,
and we need to account for them. But we need
to realize that, Okay, like if we try to make
it representative, we might actually be skewing things if the
vote isn't going to be representative. If that makes sense.
Speaker 5 (37:26):
Yeah, Actually that leads me to one more question, which
is that just thinking about the election itself, setting aside
betting markets. So there is reason to think that maybe
in twenty sixteen, perhaps the polls weren't capturing all of
Trump's support, and I guess it's sort of played out
like that, but right now it actually seems to cut
in both directions. So there is a view that, okay,
(37:47):
polls aren't good anymore, and that people don't pick up
the phone and they become much more expensive and less efficient,
and that there could be a skew in the type
of person who answers the phone On the other hand,
one thing that we've seen particularly emerging in midyear elections
is that Democrats just like they love to turn out
to vote, They loved the vote in any random election,
(38:08):
And there is the PERCEP shouldn' probably accurate that many
Trump voters are you know, less engaged and they might
support Trump, but whether that support actually translates into showing up,
registering to vote, finding the polling location, going there, and
voting is another question. How are you thinking about like
some of these sort of risks right now in twenty
(38:29):
twenty four, with some of the quality of data, and
you know, ways it could be biased right now.
Speaker 2 (38:35):
Yeah.
Speaker 3 (38:35):
Look, the model more or less assumes that although polls
can and probably will be biased some degree, that the
direction of the bias is unpredictable, which I Joe kind
of see as a spinoff from like efficient market hypothesis.
Speaker 2 (38:48):
The markets aren't always right. They do silly things.
Speaker 3 (38:50):
But if you think you know better than the market
what Nvidia should be priced at or something, then then
you can make a killing trading options or whatever else. Look,
pollsters have an incentive to get the right answer, And
we've also moved away from kind of like a purist
world where you call everybody in the phone book at
random and say can I speak to the person with
the next birthday? And they always answer. We moved away
(39:11):
from that to where like poles are basically models, so
my model is kind of like aggregating models into one
big meta model. And so therefore I think the market
incentives are pretty good, right, And when poles are biased
toward Democrats, the Republican leading polsters tend to get more
work the next cycle, so it's a little bit it's
fairly self correcting.
Speaker 2 (39:32):
I think, actually that's a.
Speaker 1 (39:33):
Very good way of looking at it. So I hope
you're right. Night.
Speaker 5 (39:37):
Nate and Maria, thank you so much both of you
for coming on the podcast. Good luck and congratulations on
the launch of the new podcast. Maybe a little competition,
who knows, but no really appreciate having you both on.
ODD loves to talk about something that's very timely and exciting.
Speaker 1 (39:51):
Thank you so much. It's been a pleasure.
Speaker 5 (40:06):
Tracy, that was a lot of fun. I'm a terrible gambler,
really bad, but I still like it. I don't like
losing money, but I still like in my mind, I
wish I were good, and I like talking about it, well, I.
Speaker 6 (40:18):
Thought Maria's point about when you actually have to put
money behind like your thought process about who is going
to win the election, it sort of sharpens your reasoning
and your thinking. I thought that was interesting. By the way, Joe,
I have good news for you and I have bad news.
Oh okay, So the bad news is there's a question
(40:40):
on poly market that is, will America bans in in
twenty twenty four. The good news is that the current
probability is seven percent. So I think you're okay, that's
all right.
Speaker 5 (40:51):
I have Zalt instead. There's one hundred other ones that,
as we learned in a recent episode, will probably get
through border security regardless of the regulatory environment. But no,
I thought it was fun. And look, it gets back
to two things that I still basically think, which is
that A, in the form of regular markets prediction market
have worked for a long time, and B they're just
(41:13):
from my perspective, I don't participate in betting markets, but
I find it interesting, is like, what is the conventional
wisdom right now on what's going to happen where people's
heads at And as a news consumer, I find them
additive in a way that just say tweets like I
think Kamala is going to win or has the momentum.
It's it's something helpful. On top of that, it's.
Speaker 6 (41:34):
Definitely something to talk about in the media and aout
that is true. I do think not to go all
existential again, but I do think it opens up really
interesting questions about the nature and the purpose of market.
So Nate talked in the beginning about, well, this is
a price discovery vehicle, and you know, I can see that.
(41:55):
But I guess if you were a market traditionalist, you know,
there might be people out there who think that markets
are about efficiently allocating capital, and so the question is like,
what are you really allocating capital too in this particular instance.
But then I guess the reverse argument would be like, well,
there is value in making a correct prediction, and so
(42:17):
you are rewarding that behavior.
Speaker 5 (42:19):
So I think that's a great point, And I think
I would say two things from my perspective, which is
Ny pointed out. For some of these bets, there is real.
Speaker 2 (42:27):
Economic issue at stake.
Speaker 5 (42:29):
So if you are interested in the future of electric
vehicles or oil or whatever it is, then it might
make a very big difference who wins the election. In
other words, like you like you already have skin in
the game and this becomes an instrument to hedging, or
I'm like a little bit more skeptical as like, okay,
so here is one of the things I see. What
will Trump say during his interview with Elon Musk. There's
(42:50):
a seventy two percent he says make America great again.
There's a forty nine percent chance he mentions crypto. There's
a fifty seven percent chance you mentioned censorship, et cetera.
Like for a market like that, that seems like pure
speculation because there are very few actual outside exogenists.
Speaker 6 (43:08):
Well crypto, but yeah, no, that's I take the point.
Speaker 5 (43:11):
Well, like so okay, like okay, so for maybe a
better one, will Taylor Swift get engaged?
Speaker 2 (43:15):
Right?
Speaker 5 (43:16):
Or you know the number here.
Speaker 6 (43:18):
That might that might actually mean something for inflation.
Speaker 5 (43:21):
Or the marriage market, right, because a lot of people
think that if Taylor Swift gets engaged, then a bunch
of people are like, it's time for us to tie
the knot and sort of do the same thing.
Speaker 6 (43:30):
Maybe we should just do this for a while and
just play a game where we go through all of
these particular events and questions come up with the real
world economic it come.
Speaker 5 (43:38):
Up with a j there's one. The number of Elon
Musk tweets between August second August nine, currently between eighty
and eighty nine is at one hundred percent, So people,
well to keep tweeting.
Speaker 6 (43:50):
Maybe Elon must tweets have an impact on the presidential election.
There has an impact on a bunch of real world stuff.
Speaker 5 (43:56):
Five percent that there's a doge coin etf in twenty
twenty four. That seems a little high to me, because
but you know, we don't even have anyway. We could
go on and on. It's very fun. It's just another
way for me to consume the news.
Speaker 6 (44:08):
All right, Well, I'm sure we'll probably end up doing
more prediction market episodes in the future, but for now,
shall we leave it there?
Speaker 2 (44:16):
Let's leave it there.
Speaker 6 (44:17):
This has been another episode of the Athlots podcast. I'm
Tracy Alloway. You can follow me at Tracy Alloway.
Speaker 5 (44:23):
And I'm joll Wisenthal. You can follow me at the Stalwart.
Follow our guest Nate Silver, He's at Nate Silver five
thirty eight. Maria Kanakova, She's at Mconnakova. Follow our producers
Carmen Rodriguez at Kerman armand Dashill Bennett at deshbot and
Kilbrooks at Kilbrooks. And thank you to our producer Moses Onam.
And for more Oddlots content, go to Bloomberg dot com
(44:43):
slash odd lots, where of transcripts, a blog and a
newsletter and you can chat about all of these topics
in our discord. In fact, there's a very active channel
where people are talking about this stuff all the time
in the elections channel and the pundit dunk take channel
where they people drop bad predictions or make fun of people.
Very entertaining subchannel, and there might be my favorite. Check
(45:03):
out our discord, Discord dot gg slash odlot.
Speaker 6 (45:07):
And if you enjoy all thoughts, if you like when
we talk about prediction markets and the nature of markets themselves,
then please leave us a positive review on your favorite
podcast platform. And remember, if you are a Bloomberg subscriber,
you can listen to all of our episodes absolutely ad free.
All you need to do is connect your Bloomberg subscription
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(45:28):
the Bloomberg channel on Apple Podcasts and follow the instructions there.
Thanks for listening.
Hosts And Creators
Maria Konnikova
Nate Silver
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