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