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Hello and welcome to another episode of the Odd Lots podcast. I'm Joe Weisenthal.
Tracy, can I reveal a very un-rumor take of mine, so to speak?
I actually really loathe anything that's sort of identified as get-rich-quick, or the gamification of stock trading, or gamification of stock trading.
Gamification would be something different.
That would probably be something different. I don't know why I pronounced it that way. Gamification of stock trading. Gambling ads. I really don't like gambling ads that imply that you're going to be a winner. And I really don't like the, even though I'm very interested in prediction markets, I generally don't like, you know, a lot of the marketing. There was a really good Wall Street Journal article about Polymarket 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, 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, sell, monetize, whatever you got, and someone else buys.
No, I totally agree. I mean, look, there are certainly zero-sum, there are all kinds of zero-sum markets in what we'd call trades are zero-sum, options are zero-sum, etc. 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 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 new markets or whatever, whether we're talking about prediction markets, whether we're talking about options trading on Robinhood and they have dreams of making 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, this specific story, the average guy's 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 Mallen, 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 like feel comfortable doing OTC transactions based on what the price is. 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 like a handful of, they would say sharks in various 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'd 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 at trading inflation contracts. We have Daniel Reichman, who also goes by Carnitas Taco, who does a lot of election and politics. And of course, we have Adam here, who's a journalist, reporter, and producer here in NYC. Recently joined the tech company Notion, which all journalists might end up working at tech companies. Well, we do. So, 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 Odd Lots.
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, you know, you reported out this story. Like, how did you identify that there exist people in the world who consistently win on prediction markets?
Yeah. I mean, I think it started for me, I got very interested in these markets because I was playing around in them, right? And I was losing a lot of money. 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 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 asking around basically. And one person sort of leads the next and suddenly you find yourself in a Discord 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 multi-strat 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 MAGA 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. And 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 really to 2016, 2017 when PredictIt 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 anyway, 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 loved elections. You know, this is sort of where the journey began for me. And, you know, we were just talking about elections. And, you know, it was after maybe six weeks of talking and 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 talking to all of my colleagues.' 'Really?' And I said, 'Colleagues? What? You're working at a fund?' 'No, no, no, no, no, not quite. We're actually all in a Discord together.'
Oh, yeah. I have to say it does sound pretty fun. Wait, just between us. Is it 100% male?
Okay, thanks. I just sort of assumed as such. Let me ask you guys a question. Like, I am like an EMH bro. I think that generally across all markets, most people, like markets are generally well priced. And I think that with prediction markets too, in the specific sense that like I think 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 Warren Buffett strategy or whether they work at 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, do you find are they decent or when you look at them are they like, oh, there's just easy pickings 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, you know, 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 mathing. 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 overabundance of evidence in a certain thing happening. And in that sense, I think that elections will always 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 as 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 the edge is 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 vote, 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 Raman was in tears speaking to her supporters because she thought she'd 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. So I really, I think 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 incoming numbers.
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 Poilievre 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 Adam's article, and maybe Adam, you could talk about this, your inflation models are described by some economist as, quote, being like Nostradamus of inflation. Why? 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 Nostradamus, why aren't you managing a, you know, multi-billion-dollar rates hedge fund or something?
Well, to be clear, nobody's called, but... Okay. Well, 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 macroeconomy 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, you know, 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. 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 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 responds 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 JPMorgan and Bank of 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 it, Brian, in terms of like 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. 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, 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 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, this is more of like a sort of, I don't know, a tactical question or market structure question. Maybe it's two interrelated things. So sometimes an event happens and then there is a period of time before it resolves. And Kalshi and Polymarket 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 Kalshi is more centralized. And I'm curious like what your trading philosophy is. It's like, okay, you get the LA 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 sites?
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 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's system is very problematic. They've basically undermined their oracle and now every market just settles on how Polymarket clarifies. I have...
Generally, for the most part, been happy with Kalshi's resolutions. But when you trade in 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 freed 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.
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. 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 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 in our channel had made a very simple model, not even really a model, had basically just said, you know, Kamala won the state by, I forget, five or six. Trump's approval had fallen maybe eight or nine points since then. You know, Trump was president instead of Biden. Kamala or Sherrill is probably going to win by about 14. And this was just, you know, sketched out on a napkin 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, you know, 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 point race that the polls didn't show at all. Now 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, 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 Mamdani again. You know, Mamdani'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 model who would have said, actually...
This brings me to a question I want to go to, the model 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, that's never going to happen. And the money quote in that article is from Alan'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?
