Odd Lots - These Are the Sharps Actually Making Money on Prediction Markets

Episode Date: July 6, 2026

Here's a couple things about prediction markets. A lot of it is pure gambling and speculation, much of it on things with very little economic relevance. Another fact is that in all likelihood, if you yourself started trading right now, you'd probably lose your shirt. But there is money being made by some dedicated traders, really focused on areas like politics and economics. On this episode, we speak with Brian Golden and Daniel Reichman, who are part of a private Discord called Maga Kiwi Club, where serious prediction markets traders swap ideas and make real money. We discuss the remarkable efforts they go to in order to spot opportunities, the systematic biases among traders, how they feel about insider trading, and other major issues that surround the space. Alongside Brian and Daniel, we also speak with NYC-based journalist and producer Adam Iscoe, who recently profiled these traders for The New York Times Magazine. Only Bloomberg.com subscribers can get the Odd Lots newsletter in their inbox, plus unlimited access to the site and app. Sign up at bloomberg.com/subscriptions/oddlotsSee omnystudio.com/listener for privacy information.

The Big Take podcast from Bloomberg News keeps you on top of the biggest stories of the day. My fellow Americans, this is Liberation Day. Stories that move markets. Chair Powell opened the door to this first interest rate cut. Impact politics, change businesses. This is a really stunning development for the AI world and how you think about your bottom line. Listen to the big take from Bloomberg News every weekday afternoon on the IHeart Radio app, Apple Podcasts, wherever you get your podcasts.

Inberg Audio Studios. Podcast. Hello and welcome to another episode of the Odd Lots podcast. I'm Joe Wisenthall. And I'm Tracy Allaway. Tracy, can I reveal a very, um, rumor take of mine, so to speak? Go on. I actually really load anything that's sort of like identified as like,

get rich quick or the gamification of stock trading or like gamification of stock trading. Gamification would be something different. That would probably be something different. I don't know why I pronounce it that way. Gamification of stock trading, gambling ads. I really don't like gambling ads that imply they are going to be a winner. And I really don't like, even though I'm very interested in prediction market, I generally

don't like, you know, a lot of the marketing, there was a really good Wall Street Journal article about Polly Market and these ads that they had created, this idea that everyone's a winner and there's all this free money out there. You just have to trade your knowledge of whatever rainfall or whatever. Like, I really, like, it really viscerally bothers me. Yeah, I think this is the key difference with prediction markets is it's zero sum, right? If you make a bet, someone is on the other side taking the opposite of that bet. And that feels a little different to me than like traditional stock markets where, you know, you would get some cash flow, some dividend, you sell, monetize whatever you got and someone else buys. Like,

No, I totally agree. I mean, look, there are certainly zero-sum, there are all kinds of zero-sum markets in what we call Trad V. Sure. Future's there are zero-sum options or zero-sum, et cetera. But on the other hand, like, but yes, zero-sum games, even if we're talking about like options or futures or swaps or whatever, that's not investing. That's trading. That's trading. And that can often be speculation and a lot of people lose a lot of money. And when we know in a lot of these environments, a lot of, like most people lose. Some people are very sophisticated. but a lot of people think they're going to go into some of these markets or whatever, whether we're talking about prediction markets, whether we're talking about options trading on Robin Hood and they have dreams to make a lot of money, or just talk about crypto, which is also zero-sum, I think, and they don't. Yeah, absolutely. The other interesting thing about prediction markets, just from a sort of market structure question.

And we've done episodes on this with Susquehanna is the liquidity aspect. And as more professional investors get in, Does that start to maybe arbitrage some of the edge that certain traders have seen so far? Because, you know, you read these stories, specific story, the average guys outsmarting Wall Street on prediction markets. Like, average guys, I have a question over whether or not they're actually average. But you can imagine a scenario where more professionals get into prediction markets. And maybe it becomes harder to actually beat them. Absolutely. I think everyone should actually go back and listen to our episode that we did with Jeremy Mallich,

who runs the prediction markets desk over at Susquehanna before listening to this. Because the other thing he talked about is like how even some of these low liquidity markets, they put a lot of stock in the price, and therefore they can feel comfortable doing OTC transactions based on what the price. So there's interesting stuff going on. Anyway, you mentioned this article, came out in the New York Times, May 26th, the average guys outsmarting Wall Street on prediction markets. And it is important, there are some people who are doing very well.

And of like a handful of, they would say sharps in various like other contexts who are like, sharks, very good. Most of us are minnows and some people do really well. And the vast majority are total idiots, right? Yeah. If I went on there, I would quickly lose $1,000 and some fraction of it would go to the house and a bunch of it would go to some of the best traders, most likely, especially because it's peer-to-peer. Anyway, we have a very complicated special episode. I don't even know how this is going to work, but I thought it would be fun.

So this was a great piece. We have the reporter on the piece with us as well as a couple of the sharps. They are in a discord together, a bunch of them. We're just going to be talking with two of them. The discord is called the Maga Kiwi Club. That sounds fun. So we're going to be talking with Adam, the journalist, as well as some of the members of the Maga Kiwi Club. We have Brian Golden, who is in the article.

he was identified as someone who's really top-notch in trading inflation contracts. We've Daniel Reitman, who also goes by Carnitas Taco, who does a lot of election in politics. And, of course, we have Adam here, who is a journalist, reporter, and producer here in NYC. Recently joined the tech company Notion, which all journalists might end up working at tech company. Well, we do. We don't get to talk to a Carnitas Taco that often on the podcast. I'm very excited about this episode. Thank all three of you, Brian, Daniel, and Adam.

for joining us on Oddlob. It's great to be here. It's a pleasure, thanks. Let's just start, Adam, you know, I guess actually we're sort of trusting you. We've sort of delegated some of our judgment. But you know, you reported out this story like, how did you like identify that there exist people in the world who consistently went on prediction market? Yeah, I mean, I think it started for me.

I got very interested in these markets because I was playing around in them, right? Yeah. And I was losing a lot of money. You know, not a lot, a lot of money. But for me, it was a lot of money. And I was wondering, who the heck am I losing this money to? Am I losing to market makers? Am I losing to, you know, the sigs of the world?

And it occurred to me maybe that maybe there are some people who are just a little bit sharper than me who are out there. And then I started asking around and I sort of started, you know, looking around on, you know, just started, you know, just asking around, basically. And one person sort of leaves the next. And suddenly you find yourself in a disqualification. with a lot of guys who are just really crushing it sharper than anybody else. And, you know, two of those folks are Brian and Daniel. Well, Brian and Daniel, tell us about the Discord group because from what I can tell from the article, you know, a bunch of prediction market traders get together, share information,

maybe you share some actual P&L. It kind of sounds like a multistrat hedge fund where everyone's like in charge of their own portfolio. But tell us about the Discord group. Yeah, well, the first thing is the mega Kiwi club name is ironic. It's not a MAGA club, but most of the names of the group end up being some form of inside joke that emerges during the conversation because we spend almost all day, every day talking to each other about markets ranging from economics to culture to sports. And it is sort of like that I would describe it almost as an Avengers model where there are different people in the group that have different specialties. And everyone has their own portfolio, but there is kind of a spirit of community in the way that information is exchanged in that I know that if I am giving helpful tips to Daniel and others on inflation, that they're going to give me helpful tips back on things that I may be adequate at, but not expert at. And we sort of work together in that way.

Yeah. So a lot of us actually know each other dating back all the way. related to 2016, 2017, when predicted was the dominant prediction market. And we mostly know each other through politics originally because that was the prediction market game. And, you know, pretty much all of us had some interest in politics or very large interest in politics to start with. And the prediction market space has grown very large and, you know, the money has gotten larger. But a lot of us would be doing a lot of this stuff any way would be unpacking elections, trying to find the truth of things, trying to, you know, solve puzzles together. And it just so happens that the space has grown large around us, but we're

kind of doing the same thing we've always been doing. And the way I found myself, you know, talking to Brian and Daniel was, you know, I met another trader who, who loved elections. You know, this is sort of where, where the journey began for me. And, you know, we were just talking about elections. And, It was after maybe six weeks of talking in source building that finally he says, oh, yeah, I'm actually talking to all of these other people. I'm not just doing this alone. I'm not just building models alone in my basement. You know, I'm like, I'm talking to all of my colleagues, really.

And I said, colleagues. You're working at a fund? No, no, no, no, not quite. We're actually all in a Discord together. Yeah. I have to say it does something pretty fun. Wait, just between us, is it 100% male? This one is.

Yes. Okay. Thank you. I sort of assumed such. Let me ask you guys a question. I'm like an EMH bro. I think that generally across all markets, most people like markets are generally well priced. And I think I think that with prediction markets too, in the specific sense that like I think it is not it is difficult to make money, but evidently in stocks, even though I think stocks are efficiently priced, some people seem to consistently make money in stocks, whether they're a or whether they work it a long short. And evidently, some people consistently make money in prediction markets. How do you guys think about market efficiency generally and how high quality that signal is on a price? And like, would you say like those of us in the media who sometimes increasingly quote prediction market quotes, like these are, are they decent? Or when you look at them, are they like, oh, there's just easy picking these everywhere? Well, I think if they were all efficiently

priced, you wouldn't be able to get some of the returns that some people in this group have gotten. I think it would be much harder to enter and sort of crush markets repeatedly if the price signal were better. I guess where I see it is that there is a lot. So who I would call kind of prediction market evangelists would like to go out and say, oh, prediction markets are the future. They're this incredible price signal. And they're more accurate than all these other places. I don't really believe that. I've just seen too many markets that are way, way off. The reason that I think prediction markets have value is because there are consequences when you're wrong and there are consequences when you're right. And we have so much kind of expertise in the

world that says a lot of things under the expert banner, but then doesn't really have any bills to pay when they mislead people or when they're wrong. And so really the most appealing part of this ecosystem for me is that when you're wrong, you pay a price. And I think that we might have a better expert culture in this country, if that were true in media that covers economics and politics. It depends on the market, certainly, in terms of, you know, how correct these prices are going to be. But, you know, going back to what Joe was talking about in the intro about the zero-sum nature

of these prediction markets, a lot of the events, most of the events that we're betting on are zero-sum. You know, we have an election and two campaigns spend a ton of money, and then one wins and one goes home. And the nature of politics in this country, especially, but all over the world, is that people live in totally siloed environments and believe different things and often engage with reality in totally opposite ways. And having a mechanism to, you know, essentially bet your beliefs and try to find real truth is, you know, it's not going to be a perfectly efficient way, but at the moment, it seems to be better than at least anything else we've got.

Well, I think to Daniel's point, you know, unlike inflation, politics brings out matters of the heart and is, I think, much more subjected to that siloed effect. I mean, you can look back at the Los Angeles mayor's primary that just happened. And Spencer Pratt's price to not just make the top two, but to actually win. the mayorship of Los Angeles got so unbelievably high. And there was this right-wing media ecosystem and sometimes even a mainstream media place that was like sort of flirting with this idea.

Like, can this happen? Everyone I know is saying that this is live. And there wasn't a sharp that I knew that didn't have one of the biggest positions of their lives on Spencer Pratt not winning the mayorship of Los Angeles, because the math was just not there to be mapping. Los Angeles is a Democrat plus 42 city. A Republican is not going to win that race.

But this sort of siloed media of people sort of only following certain accounts on Twitter and watching certain media can lead to what feels like to them an abundance of evidence in a certain thing happening. And in that sense, I think that elections will always be. be some of the most mispriced markets because, you know, people don't really have a heart connection to, gosh, I really believe I want inflation to be 3.6 instead of 3.8. I do think that the future of economics markets is probably a tightening. But people like Daniel are fortunate because I think elections will always be a little softer. This was my problem in the last election.

I spent way too much time on Reddit. And so I thought Harris was going to win. And then I was very surprised. Just to press on this further, when we talk about you guys having an edge in this market, you know, a lot of people will say, a lot of investors will say that they have an edge. And usually it's like they got lucky a few times and then they built a whole narrative around it. But how would you describe what you are doing differently to others? So you mentioned, you know, looking rationally at the numbers, keeping feelings out of it, social media echo chambers, that sort of thing. But you're also doing some original on the ground reporting. You have your own models. What is the edge exactly? A lot of it is really just work that we put in. So it's being

open to changing your mind, trying to quantify and test your assumptions. With politics, it's a lot of history. I mean, it's just knowing this has happened before. This is the trend. We think the trend might be, you know, this big, this time when it was only, you know, half has big last time and then seeing numbers come in and trying to stay calibrated with your assumptions when you win an election or win a bet, you don't just say, yay, I won, you say how much did I win, you know, what was my belief in the probability, just like really digging in and unpacking it. And then as the money has gotten bigger recently, we've started trying to learn more. We tried to do some polling in the Texas primary commissioned our own phone polls. Some of the guys in the group

have done this live door-to-door polling, which we did a bigger trip with Adam that's written about in the article. But, yeah, it's mostly just work and openness to data and changing your mind. I think Daniel's even underselling how good the elections team is in our group at elections and what they do.

I mean, I can tell you for the Los Angeles mayor's race, these guys had a model built of on election night what certain areas should look like in terms of the early votes, the in-person vote, what it would take for Pratt to have what he needed. You know, what we know from California is that so much vote comes in late, that really predicting what that vote is going to look like. So these guys did historical work by precinct and region. And on election night, when Nithya Rahman was in tears speaking to her supporters because she thought she lost,

Daniel and the crew were betting on her to make it to the top two because they had a better vibe on her chances than I think her actual campaign did. Wow. So I really, I think he's, it would be hard actually to oversell how good this elections crew is with data and not just needing days to solve it, but being able to really solve on the fly based on on incoming numbers. Canadian women are looking for more. more. More to themselves, their businesses, their elected leaders, and the world around them.

And that's why we're thrilled to introduce the Honest Talk podcast. I'm Jennifer Stewart. And I'm Catherine Clark. And in this podcast, we interview Canada's most inspiring women. Entrepreneurs, artists, athletes, politicians, and newsmakers, all at different stages of their journey. So if you're looking to connect, then we hope you'll join us. Listen to the Honest Talk podcast on IHartRadio or wherever you listen to your podcasts. The Big Take podcast from Bloomberg News keeps you on top of the biggest stories of the day. My fellow Americans, this is Liberation Day. Stories that move markets. Chair Powell opened the door to this first interest rate cut.

Impact politics, change businesses. This is a really stunning development for the AI world and how you think about your bottom line. Listen to the big take from Bloomberg News every weekday afternoon on the IHeart radio app, Apple Podcasts, or wherever you get your podcasts. Even though, like, my assumption was that prices are somewhat efficient, I do notice that on election nights, there's a lot of noise based on timing of vote batches with multiple elections. We even saw it in the recent Canadian Prime Minister election, for example, where there

was a spike for Paulyev on election night because of some early votes that were clearly not representative. So that always does make me sort of question whether I should ever be quoting these things. But Brian, in Adams article, and maybe. Adam, you could talk about this. Your inflation models are described by some economist as quote being like nostridamus of inflation. Give us a general overview of what you're doing and explain to us why you are not working at a, I think Matt Levine talked about this in his newsletter. It doesn't make sense. If you're like an inflation nostridamus, why aren't you

managing a, you know, multi-billion dollar rates hedge fund or something? Well, to be clear, nobody's called. But the first thing that I did was the BLS has a formula to the way that they take all of their price inputs to calculate the inflation number. As I know your audience knows, but just to set the table, it's not one big number. It's 200 plus subcategories of how prices have moved, which we call the basket of goods. And the basket of goods changes what percent each subcategory is worth every month based on how much Americans are spending on it. So this formula to me, I mean, look, my degree, I have an undergraduate degree in drama. I'm just a theater kid from the Midwest.

Like, this is very complicated. I'm sure that I know less about the macro economy than any guest you've ever had. But I rebuilt their formula on Excel. It took me like three months to figure out exactly how they math the formula and a lot of really helpful public servants at the BLS answered my questions about just how the math works. And then you go from there to predicting the prices. There are some price categories that have public data like gas and natural gas and sometimes cars, but most of it is just trend work and guessing and looking at the last six months and sort of where prices seem to be heading.

But the real thing for me is I just think that this says a lot more about. the sort of softness of the people, the investment banks and people who predict this in the institutional end than it does about me. Because when you predict inflation, it's not even a prediction. It's in the past. It's data that has already happened. And it has been very surprising to me since I entered this space that the places who advise billions of dollars of capital with their inflation forecasts aren't better at this. Well, this is what I wanted to ask because, by the way, BLS employees, very helpful. Very helpful.

You can actually call them on the phone and they will like walk you through stuff. But on that note, when you describe just like, you know, working out the BLS formula, calling some people up and asking them how it all works, why aren't more people doing this either in the prediction market or in traditional finance? I mean, you'd have to ask them. You know, it's shocking to me when, you know, it just really shouldn't be the case that my average absolute error on predicting inflation is better over the last two years than the Bloomberg consensus. I'm just one guy with Excel and they are, have pretty much unlimited resources to find this data. It's, you know, not just shocking from a kind of what are they doing and why aren't they trying harder, but. I think we find in both economics and elections that expert forecasts really shape expectations, and that can play a big role in narrative creation and how the public response to that. I mean, I've seen many times the headline on Bloomberg, 20 minutes before the inflation number,

will say inflation to show blank, as if it's a foregone conclusion because Goldman and J.P. Morgan and Bank America have said so. And then when the inflation number is wrong, they just change the headline like that never happened. And the market reacts to it either being above or below that expectation, which maybe wasn't that good of an expectation in the first place. So I don't know why they're not trying harder. I mean, they certainly have more resources to chase down these numbers than I do. For what it's worth, like the best inflation people we know all did it the same way you did, Brian, in terms of actually the bottoms up approach to learning the formula, like all the best inflation.

And of course, like someone like Omar Sharif comes to mind. He's great. There's a handful of people who like really, yeah. And this is what, I mean, this is what not just Brian, but all of the sharps that I talked to, whether they're doing inflation or they're doing elections or they're doing meteorology, how much is it going to rain next weekend in New York City, whatever. They're all just making calls and going on the ground and talking to people

and gathering so much data. They're calling meteorologists, they're calling geophysicists, they're calling, you know, Bloomberg reporters in many instances. You know, I talked to a few sharps who are like, yeah, I'm on the phone with Bloomberg reporters all the time. But, you know, I think these, a lot of these sharps are just, you know, they're constantly on the phone gathering information, which makes sense, right? This is also what you do if you're at a fund.

Yeah. Can I ask, obviously, this is more of like a sort of, I don't know, of a tactical question or market structure question. Maybe it's too interrelated things. So sometimes an event happens. and then there is a period of time before it results. And Kelshi and Pollymarket have different approaches to resolution. Polymarket is based on a sort of third-party, quote, Oracle, unquote, that is also sort of like, whatever.

And then Kelshi is more centralized. And I'm curious, like, what your trading philosophy is, it's like, okay, you get the L.A. mayorship right. Do you wait until resolution, or do you sell it when it hits 99% and then move on to the next big thing. And is there alpha or profits to be gained in holding from the 99 to 100 during that period of resolution? And is it different on either of the two sides? I think it depends how much time it is and what other plays are available. I mean, usually, you know, if a market is going to resolve in the next 48 hours, I mean, you're pretty much always going to hold that from 99 to 100. But

there are certainly elections that the answer is clear. And then, you know, you're you're not getting that payout for a month. And I mean, usually I can turn 99 cents into a dollar over a month faster doing something else than waiting. But I suppose it depends on the context. I mean, I don't know, Daniel might have a different approach. It's really important to know the difference between is your market 98 or 99 just because of the time it's going to take to resolve? Or is there a one or two percent chance of it actually going the other way? I try really hard to avoid these rules, disputes, and these, you know, thorny markets where it ends up kind of a debate.

I think polymarket system is very problematic. They have basically undermined their Oracle, and now every market just settles on how polymarket clarifies. I have generally, for the most part, been happy with Calci's resolutions, but when you trade and stuff like, will a cabinet member get confirmed or who wins an election, it is almost never. up for debate, you know, 2020, notwithstanding, you have clear answers. And so it just depends. I'm holding the Peruvian election right now from 99 to 100 because I don't have anywhere else to put the money. But if I had another play that I liked and I wanted the money freight up, I would sell it in a second and, you know, put it in whatever else there was. Let's talk when we get off the call. I got some places for you. Okay. Since we're talking about probabilities changing, I wanted to bring up this, there's a long

running debate, I guess, about whether prediction markets are actually better than traditional polls when it comes to forecasting election results or whether they just look better because they're able to update faster as the results come in. And Daniel, I'd be very interested in getting your take on this. Like, are these genuinely producing better probabilities or is it just a matter of speed? Yes, but it depends on how much money is coming into each. each side. A really noteworthy election, I think, recently last November was the New Jersey governor's race, where the polls really all said this was a pretty close race. You know, two, three, four, five. One of the guys on her channel had made a very simple model, not even really

a model, had basically just said, you know, Kamala won the state by, I forgot, five or six. Trump's approval had fallen maybe eight or nine points since then. You know, Trump was president Instead of Biden, Cheryl's probably going to win by about 14. And this was just sketched out on priors on an upkin very quickly, three months before any polls. And then all these polls came in showing this close race. Very, very few polls showed a big margin. And we actually, we didn't ignore the polls. We kind of tried to standardize them all.

But we did genuinely believe in our channel that this was a 12, 13, 14, 14 point race that the polls didn't show at all. we couldn't make the prediction market prices reflect that because there was so much money on the other side. So, you know, ultimately the prediction markets, I think were higher than the polls, you know, pointing to a higher margin, but still well below what it would eventually come out to. So, you know, on an election where the liquidity on the, you know, the square side is large enough, the prediction market prices are still going to be wrong. I mean, you can look at Pratt again, you know, Pratt's price was never 27 to be the mayor. It was, you know, less than five always in truth. But it was also still that 27 was still much more accurate than anybody's bubble who would have said. Actually, this brings me to a question I wanted to go to the bubble question again.

Adam, obviously, your piece was great. There was another great piece of prediction markets journalism in the last year about Alan Cole, who had bet his life savings that Elon Musk wouldn't actually reduce the deficit very much. And he, like, knows the deficit very well. And he's like, this is never going to happen. And the money quote in that article is from Ellen's wife who said, I read through the comment section in the prediction markets. And they all seem like idiots, at least relative to her husband. And therefore, I was very comfortable with him risking all of our family's life savings on this one particular bet.

I'm curious, like, if you, like, okay, when maybe there's sort of bubble mentality emerging or it's like, this is a price that reflects people not getting good information. How often in your group can you use the comment? sections to gauge like, wow, there's a lot of dumb money on this contract. Always bet against the comment section. Okay. For real? I mean, not always, but it tends to be a guiding principle because sharps tend to keep their mouth shut except when talking to each other.

And generally, the more ideas or comments there are sort of advocating for one side, I do think that tends to be the wrong side. Yeah. I was going to say it was surprising how, or is surprising, how reliable the comments indicator is. Back on predicted, there was actually a lot of good information. People hadn't built these discord networks. They hadn't, you know, ended up in their silos where we talk about all the useful information ourselves. And so there was a lot more sharing and helping. And, you know, part of that is also because the money's gotten larger, the importance of protecting your reliable information is so useful that you just don't see, you know, someone like me or Brian going on to Kalshi's, you know, message board and explaining,

no, you guys have it wrong because you're not, you know, accounting for this, that, and the other. I mean, predicted having an $850 limit, you know, made it very possible for people, you know, the limit meant you could share. Like, I'm done. I can't fill up anymore. But Kalshi not having kind of a meaningful. position limit, you know, changes that equation dramatically. Since we're talking about betting against the comment section, you know, there was the article

in the journal recently talking about how on polymarket, 67% of profits go to 0.1% of accounts. And we also have more professional investors who seem to be expressing some interest in getting into this market. If a bunch of people are just losing money on this, which it seems like they are. Does the dumb money eventually go away and it becomes harder for you to, you know, make these bets? It should.

That's been the history of, you know, the poker boom got harder. Daily Fantasy Sports was big money for a lot of people. That got harder over time. You know, certainly it should happen that way. So far, certain markets have gotten harder. Elections appear to still be dominated by vibes and emotions, you know, we'll see.

Hopefully these prediction market spaces are still new enough that there's a lot more people still to be onboarded and anything can happen. But so far, they still seem to be pretty beatable. Yeah, I remember during the online poker boom, people would like talk about like soft tables and all these, and then like eventually, like, they all lost their money and they were like no soft tables. And then the, the, I don't know. I didn't know that about the poker.

Yeah. Then it was just all like sharks versus sharks. And the only when it's like you go to like the high limit room. at a casino and there has to be like you know there has to be some celebrity there or like a shake or someone who has like a bunch of money who just wants to lose to pros there that night but if it's all like you know adam ivy and all these guys playing high limit poker against each other the only one is they're just going to grind each other down and the money it's going to go to the house how did um how did you guys do on the uh 2025 romanian election

was a dark day for our channel Yeah, tell us about that day. Tell us about the Romanian election and the dark day for your channel. Yeah, Daniel. What happened? So in the first round, well, the first round of the Romanian election was actually annulled due to Russian involvement. It was a very strange event. But the next first round, this guy, Simian won it by, I believe about 20, and it was headed to a runoff.

And basically in the entire history of European runoff elections and even, you know, expanding beyond European, nobody had ever really come back from a deficit that big. And there was also a correlation where the places that the other candidates had done well, this guy, Simi and the leader had also done well. So it really just seemed at the beginning like he would win easily. And a lot of us put a lot of money on it at various times. He then proceeded to leave the country, skip all his debates, became a laughing stock on Romanian media, which we, to be clear, did not pick up on just how much he had become a joke in Romania. And so it ended up being a case where a lot of Romanians were betting a lot of money against a lot of internet politics sharps. Yep, I mean, they were right. We were wrong. Canadian women are looking for more.

More to themselves, their businesses, their elected leaders, and the world are out of them. And that's why we're thrilled to introduce the Honest Talk podcast. I'm Jennifer Stewart. And I'm Catherine Clark. And in this podcast, we interview Canada's most inspiring women. Entrepreneurs, artists, athletes, politicians, and newsmakers, all at different stages of their journey. So if you're looking to connect, then we hope you'll join us. Listen to the Honest Talk podcast on IHartRadio or wherever you listen to your podcasts.

The Big Take podcast from Bloomberg News keeps you on top of the biggest stories of the day. My fellow Americans, this is Liberation Day. Stories that move markets. Chair Powell opened the door to this first interest rate cut. Impact politics, change businesses. This is a really stunning development for the AI world. how you think about your bottom line. Listen to the big take from Bloomberg News every weekday afternoon on the IHeart radio app, Apple Podcasts, or wherever you get your podcasts.

How do you feel about insider trading in prediction markets? Because this is also one of the big debates now, the idea that people, I don't need, it's not illegal, right? Well, I think it is. I can't get clarity on this, but I know there are some charges against people for using, like, legally protected information to make these bets. But how do you feel about the idea that you might be betting against someone who is actually like fully informed? In the room and fully informed. I feel like there's sort of a mixed feeling here where one of them, on one side,

you're like, well, yeah, that's really terrible for retail traders to know that they are, you know, going to be going against someone who literally has the answer. On the other hand, you know, I think one of the early arguments for why prediction markets should be allowable is that they can provide price signal by allowing all information that exists to come into the public sphere and not stay private. I mean, you can imagine a scenario where, I mean, you could cook up a very, Hollywood scenario, which I won't. But you can imagine where someone who was aware of illegal activity and had no way to, you know, make that public, we're trading on that information and sort of

creating a little bit of price signal there. I don't know. I mean, you never want to be trading against an insider. And of course, Cal She and Polymarket would very much like people to think that there are no insiders and all. They have policed this aggressively. I don't really find that to be the case. I could tell you specific markets that I am 100% sure that I lost to someone with inside information. I think you can pick out a market and see, is this possible for this market to be insidered? You get a little bit of a sense of what price movement looks like when someone actually knows the answer, huge volume coming out of nowhere at a price that hadn't been traded on before. I can tell you, I would bet my life savings that someone who knew the Critics Choice Awards winners,

last spring knew that Jacob Allorty was going to win Best Supporting Actor the night before because he went from one cent to 40 cents on massive volume, which was a trade that I lost because I really didn't think he was going to win. So, you know, we've taken some of those Ls. I think ultimately you want to not allow it, but it's hard because it also can be part of giving a price signal on important events. So what I'd like to see and what I think we're moving toward is the sites, and the companies making the serious insider trading not make financial sense for the people that do it. So we just saw the guy who insidered the Google urine search, lost his Google job,

and I believe charges were referred. The military guy who bet on the invasion was arrested. You know, he made something like 400K and now he's facing charges. I mean, there's no way that math works out for those people, right? So it's really the small insider ones. But then you also have these situations where it's debatable what's an insider. Like there were insiders on the Super Bowl performance market where, you know, somebody who has no actual attachment to the gig or the performance, you know, happens to hear something that, you know, makes them know more than the market. But they really have no technical, like, relationship of being an insider.

I don't think you can police that. So I like to stick to stuff. You know, again, like in elections, you can't have insiders. We bet a lot on the cabinet confirmations, and that was interesting because you could have insiders on those. You know, some staffer or two, a senator knows how their person's going to vote. You know, you just kind of have to ask in every event, you know, who's my counterparty, could they know more than me?

And in situations where someone could know more than you, you really got a size appropriately and make sure that you're not just blowing a ton of money to somebody who only is in it because they know. more than you. Just for what it's worth, not that my opinion matters at all, but I don't think the government should be expending resources to police insider trading on the length of the Super Bowl halftime show, because it's like, it doesn't matter if you guys lose a bunch of money to an insider on that, I don't care because like I think like regulated while markets are a good thing. I do not want like, you know, public resources protecting people who are like gambling on it.

But just, you know, I'm curious and maybe all three of you like this story is. and people discovering that you guys have this discord, et cetera. Like, from the perspective of the companies, like, I could see the Calhoshies and Polymarkets for the world loving this because they're like, look, a bunch of people get in their minds that they could be Brian and Daniel and they could have a crew and do a bunch of information and win. Or I could see them disliking it because they're like, wow, you know what?

I'm not going to start. I'm not going to trade because I do not have anywhere of the means to come close to this group in terms of like the resources required to invest to trade consistently well. I'm curious, like, what you've seen is like, are stories like this good for the markets? Or do they, would they rather sort of perpetuate the illusion that it really is like totally random?

I just made my rent money because I knew it wasn't raining today and that simple, which is how some of their ads are. And this is like really like the sort of the advertising, the misadvertising, et cetera. I've seen, you know, you've seen it from both of the two major platforms. At a high level, I'm very, you know, concerned with like, how are people going to read this thing? And I think my hope and,

you know, what folks have told me is, wow, I didn't really realize that I was the dumb money. Yeah. And I don't even think I realized, you know, at the beginning of this journey that, like, I was the dumb money. And so the hope, I think, is that, you know, people read something like this, people listen to a conversation like this and they think, oh my gosh, okay, I maybe don't stand a chance against Brian or Daniel or the rest of these guys in these Discord groups. But, you know, Kashi and Polly Market can kind of flip the script and tell you the other story. Yeah, I mean, I think what is in the long-term good of prediction markets continuing to be legal and regulated is stories that are like Adams because a lot of journalism reporting on prediction markets has sort of focused on, wow, isn't it crazy that people are making money on how long a handshake will last and what word someone will mumble at a speech. And, you know, I mean, my personal opinion is that people should be able to bet on

things because it's their money. But these are not important questions that prediction markets are built to answer. And I think that in some ways, Kalshi and Polly Market have been so aggressive in trying to make as much profit as possible as quickly as possible that they have gotten deep in markets that are not only pushing against state regulation, but are clearly, not the kind of important social questions and economic questions that prediction markets are really should be answering. I mean, what I appreciated about Adam's story was that it was essentially about people who are going the extra mile and working really hard to try to answer questions that actually matter. Who will win elections? What prices will look like? And in some cases,

people who are working harder than, you know, publicly accepted experts on those. So I think for the long-term existence and regulation and legality of prediction markets, you know, stories that focus on I don't want to say people like Daniel and I, because it's not about him and I, but it's about what questions are we all trying to answer and what puzzles are we trying to solve? And if those puzzles matter to the general discourse in the economy, then absolutely and should be legal. But some of the extraneous stuff that is just, you know, a silly excuse to gamble, you know, I don't think that that is really the future of where this should be headed. Yeah, I think that's an important point because we talk about the price signal of all of this.

And the price signal really doesn't matter if it's like a dumb question being asked. One more question for me on your research process. How much of this has been enabled by AI and the tools that are now at your disposal? AI is very helpful for getting started on something like an international market or especially for searching in foreign languages, where it can intermediate the language barrier for you. There's basically been, I think very few of us use much AI for modeling. Some of the guys who code more have been using Claude Code a bunch just to do some statistical stuff, you know, quicker and easier. But the people who just ask LLM's question and think that that gets them an edge on a market are some of the squarest money out there. You know, these LLMs will tailor their answer to what you ask.

And, you know, if you ask the question a certain way, it will tell you this is the probability and it will ignore. What an insightful question. You are on the right track. Wait a second. Is square money, is that what you guys call soft money these days? Or like, is that square money? Is that like the term for like a small? soft table or whatever.

Right. There's plenty of it. Got it. Oh, of course. The squares of the sharps. You saw tons of this again going back to Pratt. You know, all the people on Twitter, my, you know, LLM told me the chances of this were one in a trillion, et cetera. I've asked chat GPT things like, what will inflation be next month?

And it will give me a number. And it'll be like, wow, great question. I think it's going to be this because of these reasons. And then I'll just say, without, without anything else, I'll just say, that's too high. And it'll say, you're right. I'm glad you brought that up. It actually will be lower for these reasons. And then I'll say, that's too low. And it'll be like, you know what, thanks for bringing that to my attention. So not only is it telling you what you want to hear, but it only has grounding in other expertise that it that it gathers. And if that expertise that I'm already trading against

is beatable, then I don't really see why the AI is any less beatable than that, at least in its current I lied. I have one more question. Very important question. Daniel, why are you called Carnitas Taco? So when I used to play a lot of poker, I would often be in tournaments all night and then stay up for breakfast tacos in the morning. And that has stuck with me as a DJ name, a Twitter name, a prediction market name. That's my online name. Brian, Daniel, and Adam, thank you all so much for coming on Avla. I think that actually worked. That was a little bit complicated to organize, but that was a great conversation and really appreciate all of you taking your time. Thanks for having us. Thanks. It was great to be here. Tracy, that was really fun. That was a,

it was sort of a complicated episode to do. But I thought that was like, I actually felt like I learned a lot in that conversation. Yeah, absolutely. I didn't realize that the poker boom had sort of gone through a similar thing where you had a bunch of people playing online and then they just kept losing and they left. Yeah, because the story was like, do you remember like how the, why, the online poker boom, like, really happened. Fagely, but remind me. Because this guy named Chris Moneymaker won the World Series of, he was a total,

his name was Chris Moneymaker, and he was a total nobody, and he won the World Series of poker in Las Vegas. So everyone got in their head that, like, actually anyone can win a lot of money in playing poker. And that was the sort of catalyst for, like, poker becoming this thing that, like,

ESPN would cover and et cetera. It's huge, like, wave after wave. And then eventually, like there was, I think sometime in 2009 or 2000, I think it was 2009. It was a big government crackdown on some of these like quasi illegal offshore sites. But that was already at that point, I think, like the minnows were coming out of, because a bunch of people were losing that Chris Moneymaker was really a fluke. There were a lot of interesting things on that, including, to your point, to like,

will eventually the square money or the dumb money or the minnow is just like flush out of the system. And then it's sharp versus sharp and only the platform. are making money, all the stuff about like, okay, what is a healthy future for these predictions markets look like? But also it is, you know, the real work involved to actually have an edge.

It's like if you are listening to this and you think you're going to make money, you probably aren't unless you actually have some reason to think that you're like putting in work. It kind of emphasizes that in the age of AI, like the edge is still going out and finding new data, like picking up on turning points because most of the LLMs are still very backward looking. And I guess having that sort of like human connection.

No, if you think about it like... You have to know the vibes, right? But if you think about it too, it makes sense because one of the things that like a lot of our AI guess we'll talk about is the value of proprietary data, right? And so, so that is it actually makes sense. Like what is, quote, scarce in the age of AI? Well, someone knocking on doors. Yeah.

And asking questions of people rather than someone just asking the model what they think is going to happen. I also think that story. I didn't mean to turn this into another AI conversation, by the way. I was just curious. Yeah, no, it's good. It was important question. I want to, I'm curious how much money was lost on that 2025 Romanian election because I know that that was like a big upset. And so, and he walked through, you know, respect the candor of admitting they really whipped on that one.

And then that all the randos in Romania who were paying attention to it knew more than the sharps on that one. Shall we leave it there? Let's leave it there. All right. This has been another episode of the Odd Lots Thoughts podcast. I'm Tracy Alloway. You can follow me at Tracy Allaway.

And I'm Joe Wisenthall. You could follow me at the stalwart. Follow our producers, Carmen Rodriguez at Carmen Armin. Dashel Bennett at Dashbot. Kail Brooks at Keel Brooks and Kevin Lozano at Kevin Lloyd Lazzano. And for more Oddlots content, you should check out our daily newsletter.

You can find that at Bloomberg.com forward slash oddlots. And you can chat about all of these topics 24-7 in our Discord. Discord.g.g. And if you enjoy Oddlots, if you like it when we talk to sharps about beating the squares or the circles, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes, absolutely add free. All you need to do is find the Bloomberg channel on Apple Podcasts and follow the instructions there.

Thanks for listening. The Big Take podcast from Bloomberg News keeps you on top of the biggest stories of the day. My fellow Americans, this is Liberation Day. Stories that move markets. Chair Powell opened the door to this first interest rate cut. Impact politics, change businesses. This is a really stunning development for the AI world and how you think about your bottom line. Listen to the big take from Bloomberg News every weekday afternoon.

on the IHeart Radio app, Apple Podcasts, or wherever you get your podcasts.