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