Episode Transcript
[00:00:00] Speaker A: Predictable, Predictable Predictions Predict Predictable predictions Predictable.
[00:00:03] Speaker B: Predicted Predictable predictable.
[00:00:08] Speaker A: Predictive programming. Episode 12 Huge Guest Domer is in the building.
[00:00:14] Speaker B: Thank you so much, Domer, for coming. I'm very excited to have you on.
[00:00:17] Speaker C: Yeah, I'm excited to be here. Thanks for having me.
[00:00:19] Speaker A: For those who don't know, I'll do the shortest bit of bio. Domer is up piles on everything.
Basically everything was sports. I looked at your portfolio today and it was like whether or not E girls are actually men. Like just the craziest things I've ever seen. Anything but like an NFL football game.
[00:00:39] Speaker B: You're in there.
[00:00:41] Speaker A: Really impressive. But why don't we start from the top just a little bit so we have some solid ground underneath us. Can you tell us a little bit about how you got started in trading gambling, whatever the journey was, and how you've arrived at the point you currently.
[00:01:00] Speaker C: Yeah, so, I mean, I graduated from college, I had a normal job and that was around like Chris Moneymaker, ESPN poker thing. That's when that was going kind of crazy. And so everyone my age that was like a young guy was like starting to get into poker and like. Cause it was so easy to do it online too.
[00:01:16] Speaker A: Full tilt was active.
[00:01:18] Speaker C: Exactly. Yeah. Still. Still a thing. Yeah. But before it all came crashing down. Yeah. So I was doing that on the side and I was doing that like in addition to my normal job. I would do it at night and it got to the point where I was making more doing that than I was at my job. So I was like, let's give it a go. Worst that can happen is I just quit and go back to my job.
[00:01:36] Speaker B: How did you study poker back in the day?
[00:01:37] Speaker A: Yeah, I've always been intrigued by this. Cause the tools were not good in like mid aughts, which is when this was.
[00:01:43] Speaker C: I mean, I wouldn't even say that I studied poker. It's just like if you know math and you're take a little bit of risk, like you're gonna beat the game. Yeah.
[00:01:50] Speaker A: In that era, I would go party all night, get home at 3am and dump on those sites. So I do know that it was very soft.
I was unloading.
[00:02:02] Speaker C: Yeah. And then people had multiple tables open. So you had a bunch of games going at once. Yeah. Yeah.
[00:02:07] Speaker A: It was an interesting era. Okay, so that. That got you into it.
[00:02:10] Speaker C: Yes.
[00:02:11] Speaker A: When do prediction markets get on your radar?
[00:02:14] Speaker C: Yeah. So I mean, I. You know, the thing with poker is there's a lot of downtime between hands. Like you're waiting for the other people to finish and it's like, okay, this is boring. I've seen this 10 million times before. And so I was clicking around on the site. I think it was Bodog at the time, which I don't think exists anymore.
[00:02:27] Speaker A: No, it does.
[00:02:29] Speaker C: Okay, cool. Well, credit to them.
Calvin Harris, I think was the guy or something like that. Calvin. Anyway, so I was clicking around on the site and I ended up like I first started, like sports, like three bucks, I'm gonna bet on the Knicks or whatever. And then I scrolled down and I was like, okay, you can bet on the Oscars. Like that's a thing. Like I watched the oscars like, like.
[00:02:50] Speaker A: 50 bucks at a time.
[00:02:52] Speaker C: Yeah. My first bet was 10 bucks on I think Crash to win Best Picture, which is very controversial.
[00:02:57] Speaker B: Right.
[00:02:58] Speaker C: But it was like 8 to 1 odds and I won like 80 bucks. And I was like, I'm a genius, right? I'm gonna do this. And so. And then I started to look into it and I figured out that there was like a site like, like purely devoted to it. It's called Intrade. It doesn't exist anymore, but yeah. And I deposited money and started from there. I think my first spot was 200 bucks.
[00:03:19] Speaker A: So what's the first year that prediction market trading is your primary source of revenue or six figure source of revenue? When does it become like, oh, maybe I'm going to go all in here?
[00:03:31] Speaker C: 2008. Yeah. Because back then. Yeah, okay. Yeah. There were really only two big events. It was the presidential election and then the Oscars. Like everything kind of revolved around that within prediction markets. There was not like if you go to Polymark and now you, you can scroll for an hour, the number of markets that they have.
[00:03:47] Speaker B: When would were you on predict? When did predicted even start?
[00:03:51] Speaker C: So there's in trade before predicted. Yeah, predict. It was like 2015.
Yeah. And when the guy was starting it, he was like, I was emailing him, I was like, oh, here's some tips on what in trade would do. And yeah, it was kind of wait.
[00:04:03] Speaker A: So if it's just Oscars and elections and that, how are you, how are, how are you doing career defining volume, you know, like, how is that setting off like, oh, I'm going to make this move.
[00:04:15] Speaker C: Well, that's a great question. Because both of those are very slow moving events. Right, right. Because like movies come out and then.
[00:04:21] Speaker A: Awards and elections a lot bigger than.
[00:04:23] Speaker C: Exactly. And then there's primaries and there's debates. And so these are both like very slow moving things. And like what I was making A lot of money doing. I mean, not relative to then I was making a lot of money is like, okay, Romney goes up from 20 to 25, take some profit. I'm gonna bet on Rick Perry now or whatever the case may be. So you, you were doing a lot of like active trading based upon the latest news or the latest debate, and then picking the BP was also a big one.
[00:04:48] Speaker B: So in trade was actually a prediction market, like P2P. Okay, exactly.
[00:04:53] Speaker C: Yeah.
[00:04:53] Speaker A: Okay.
[00:04:54] Speaker C: And they were shut down in 2012.
[00:04:55] Speaker B: Got it.
[00:04:56] Speaker C: Yeah.
[00:04:57] Speaker A: Polymarket and Kalshi. When do you start in earnest using those?
[00:05:01] Speaker C: Immediately? Yes. I was an alpha user on Kalshi. Like even before the site really existed. I was on it, like testing it out.
Polymarket, I think I joined a few months. I was very skeptical of Polymarket because it's like crypto site and it's like.
[00:05:14] Speaker A: I don't know what the hell you're skeptical from. Like a counterparty risk.
[00:05:17] Speaker C: Everything.
[00:05:18] Speaker A: Everything.
[00:05:18] Speaker C: Right. Okay. Depositing with too many. Who am I betting against? Yeah, I didn't know anything about it, so I was very, I wouldn't say nervous, but I was skeptical of it. And so I probably waited a couple months past when I heard about it to finally join up.
[00:05:31] Speaker A: But yeah, and so when those launch, you have like infrastructure, be it models or just approaches to both elections and awards. No, no, no. But you had some ball knowledge, right?
[00:05:42] Speaker C: Yeah. Okay. Yes. Yeah.
[00:05:44] Speaker A: And so experience.
[00:05:46] Speaker C: Yeah, yeah.
[00:05:47] Speaker A: By the way, do you do any quantitative modeling now or is it. You're just.
[00:05:50] Speaker C: I've hired people to do it, but yeah, okay. Okay. Nothing that I'm doing.
[00:05:54] Speaker B: Can you give like an example of an Oscar prediction or bet you made any time that was like. And walk me through your process. I'm just kind of curious because I've never.
[00:06:04] Speaker A: Without leaking too much.
[00:06:05] Speaker C: Yeah, no, no, no, no.
[00:06:06] Speaker B: Right.
[00:06:06] Speaker A: We're not being jerks.
[00:06:07] Speaker C: I mean, well, the way that they, that they divvy out the Oscars has changed over the years in response to like controversies where I won money.
But so obviously my first big win, big win was 80 bucks. And I was like, okay, I'm launching that. But then my second really big win is when I was like, okay, I'm actually like doing this now. I'm like successful is when I bet on. I was betting against Avatar the first Avatar, which was like a super popular movie. Everyone was loving it. And I think it was like 50, 50 to win the Oscars. And I was like, okay, there's 6,000 Oscar voters, like 3,000 of these people are, like, older than 70. Like, they're not going to vote for this cartoon blue alien as the best picture of the year. And so the odds were 50, 50, and I bet pretty much everything I had that it was not gonna win Best Picture.
[00:06:53] Speaker A: What?
[00:06:53] Speaker B: Okay, when you do that, do you have, like, an idea of, like, a fair price or you're just like.
[00:06:58] Speaker C: Yeah.
[00:06:58] Speaker B: What was your fair at that time?
[00:07:00] Speaker C: Below 10? Way below 10. Maybe 5.
[00:07:02] Speaker A: Okay. So truly a Kelly size. Approaching full bankroll.
[00:07:06] Speaker C: Yeah. Double Kelly, lose the house, whatever it was, I was all in.
[00:07:10] Speaker B: Yeah.
[00:07:11] Speaker A: And you're on platforms where you can actually sell. Yes. Buy no, or are you just buying other.
[00:07:18] Speaker C: Yeah. So it was on exchanges. So it's me against someone else.
[00:07:20] Speaker A: So you were able to. Can you say how much your entire bankroll was at the time?
[00:07:24] Speaker C: I mean, it's not going to be very impressive, but it was. It was 50,000.
[00:07:27] Speaker A: Okay, so you have 50,000 down on.
[00:07:29] Speaker C: No. Yes.
[00:07:31] Speaker A: I feel like he's living in some alternate world where this has been, like, a liquid ecosystem for 20 years.
[00:07:37] Speaker B: The fact that you can, like. I look at some of these markets now after all the hype and you can only get a few thousand, the fact you got 50,000 down, like, almost two decades ago, is it very impressive? Yeah, I'm very impressed. How long did it take you to accumulate that position?
[00:07:49] Speaker C: Yeah. Probably over the course of, like, three or four weeks.
[00:07:51] Speaker B: Okay. Yeah.
[00:07:52] Speaker A: So when we've talked about, like, learning how to win is the first thing, but then winning at scale is so much different. And even learning how to, like. Okay, like, knowing, for instance, it's only worth it if I get 50 down. It takes four weeks to get 50 down. The price slippage is brutal. So, like, how big an angle do I need to even have it be worth my time? It's like a very small subset of what you can actually win on.
[00:08:15] Speaker B: Now, that is. That brings you another question. So you obviously want to take a monster position here. It takes you four weeks to get, you know, 50,000 on. It's not that liquid. How do you not, like, spook the market and, like, bring it from 50 to, like, 30? By. By, like, what is your process there to execute?
[00:08:33] Speaker C: Well, thankfully, there was a ton of hype around Avatar, so it was not like anything. And they didn't even know that I was on. Like.
[00:08:40] Speaker B: Yeah, no, no, it's not that. But it's like, if you are, like, putting in, like, the order book.
[00:08:45] Speaker A: Yeah. Who's going to reload? Somebody's got to come around and Reload.
[00:08:48] Speaker C: Yeah. Yeah. So mostly what I was doing is matching other people.
[00:08:51] Speaker B: And so you weren't making. You were taking there.
[00:08:53] Speaker C: Yes.
[00:08:53] Speaker B: Got it.
[00:08:53] Speaker C: Yeah. I wasn't trying to be, like, super aggressive because I. That is a fair point. Like, if you're putting in a big order, like, sometimes the order book crashes.
[00:09:01] Speaker B: Yeah.
[00:09:01] Speaker C: Just seeing the big order, it, like, spooks people. Yeah. So I was going pretty slowly.
[00:09:05] Speaker B: Got it. Got it.
[00:09:07] Speaker A: How.
How has that evolved now? Do you find what percentage of your efforts and timing and your skill as a trader do you feel like is dedicated to. Okay, given some angle, some fair price with alpha, et cetera?
I know how I want to attack the exchange. Attack the order book, wait for the timing of the size to be appropriate, make just outside the spread versus crossing spread, et cetera, et cetera. Like, is that right now really important to your returns, or do you have an approach where you can kind of ignore all that and just attack?
[00:09:44] Speaker C: Yeah, I mean, that's a really good question. So I think it really depends on how liquid the market is versus how much you want to bet. Like, there are markets where I'll just show up and I'll be like, okay, this price is so far off, I'm just gonna move the price $0.10 immediately and crash it down. But then there are times where it's like, okay, I'm gonna try and get someone to bet into me, but I don't want to put too big of an offer up because then the price will go down by 3 cents or whatever. So, yeah, it's dependent. It depends on what I think the price is worth. It depends on what I think. Like, you know, the impotent. Like, what events are going to happen between now and, like, let's say two days from now. Like, is there going to be price movement for XYZ reason? So there's a lot of factors that go into that decision of what I'm going to do as far as, like, crossing the book or putting. Putting up an offer or whatever.
[00:10:29] Speaker A: Right now, I would say things have gotten better and better for a guy like you because of increasing liquidity, increasing platforms, et cetera, et cetera, et cetera.
Do you feel still that each passing day your situation is better than the day before it? Or are the other participants getting stronger, the pricing getting stronger? Are you starting to feel some other winners nipping at your heels?
[00:10:58] Speaker B: Like, where.
[00:10:58] Speaker A: Where are we on that trajectory?
[00:10:59] Speaker C: Yeah, I mean, it's a lot harder. And I would say, you know, it used to be the case where I was like, okay, I'm easily like the best or one of the best, but now it's the case where I'm not necessarily feeling that in every single market. So I mean, the, what happened, what has happened with prediction markets is previously it was like very small number of markets, but they would be very big. Now it's like a very wide ranging number of markets and some of them can get really, really big. So it's, yes, it's gotten a lot harder, it's gotten a lot more challenging and that's fun in some respects. But then by the same token, like it's the latitude of the markets has just gotten so like you can bet on pretty much any topic that you want.
[00:11:38] Speaker B: So something that's interesting to me is I've heard you speak that like you'll look at a market and then try to do some research. If you think based on the volume of thinking, get it done. But as you're saying, it's getting harder. Don't you run into adversarial selection at this point? Because like, if there's so many markets and you become like a jack of all trades, aren't you just asking to get crushed in the end game? Isn't it better to stick with like a couple and be the end boss of those markets? And when we look at your portfolio, you have every market.
[00:12:09] Speaker C: Yeah, I mean, yes, maybe that would be better, but it's not as fun. I mean, like, yeah, I'm trying, I'm trying. You know, part of it is like with prediction markets, especially on like news events, like you're trying to like solve a puzzle. Like if you're trying to figure out what the VP is, like they're gonna, they have some rubric that they're working with. You have to figure out what their rubric is. You have to get inside their head. So it's like, it's like a problem solving. So that to me is like super appealing. So even if I was only able to bet like 500 bucks on this stupid thing, like, I would still probably do it as a hobby in addition to my regular job because I just, it appeals to me, like being able to solve these things.
[00:12:45] Speaker A: Can you talk about the process of identifying a new market type? Like, oh, this is the first time I've thought about time person of the year, or the first time I've thought about, you know.
[00:12:59] Speaker A: ChatGPT benchmarks or something. And, and when you decide, okay, I'm going to approach this, do you start by thinking about things that maybe you can reuse? Like, oh, Do I have some tool that's already available? Do you always want to do it from scratch? Is the novelty part of the appeal? Like. Like what. What is day zero of attacking a brand new market type look like for you?
[00:13:21] Speaker C: Yeah. So, I mean, I would say, first of all, I scale up my bets with how much research on how confident I am, so I would not be opposed to just putting in, you know, some brand new markets. Looks fun. I'll put in 200 bucks or a thousand bucks and not think too hard about it. And if I lose, whatever. But, like, as the market gets more popular, you know, as volume is going up or as people are building big positions, then it's like, okay, I need to get more serious about this. So it could be the case that I don't research it. I'm working on 10, 10 different other things, and I never increase my bet. But sometimes it's like, okay, I'll. I'm gonna try and get serious about this. I'm gonna research it, and then I'm gonna increase my bet. So it's a little bit of both in terms of, like, willing to bet on anything, regardless of whether I'm an expert on it. But then if I'm gonna bet a lot of money, I'm not gonna just gamble on it.
[00:14:06] Speaker A: Do you think you learn more from.
[00:14:10] Speaker A: Studying and thinking about a market and putting no money into it, or just, like going for it, vibe trading and then feeling the actual pain of loss?
[00:14:22] Speaker C: I mean, that's a good question.
[00:14:26] Speaker C: I feel like researching it. Yeah. Is super important. But also, nothing crystallizes thoughts more than winning or losing blood.
[00:14:33] Speaker A: Yeah.
[00:14:34] Speaker C: Yeah. Cause it's like you still remember all these things. Yeah.
[00:14:37] Speaker B: I feel like you're the embodiment of the meme of, like, the bell curve. Like, just no ball, and you have the one end, but you're on the right tail. Or just like, just no ball and bet and that's you. But I did want to ask, how does it, like, in sports? I know you don't do a lot of sports.
[00:14:52] Speaker C: Yeah.
[00:14:53] Speaker B: If you click or bet into a sharp bookmaker and that price moves back, you are in some serious trouble. You've probably got some adverse selection.
[00:15:02] Speaker C: Yeah.
[00:15:03] Speaker B: If you make a bet or a prediction or whatever you want to call it, and the price comes like, you bet at $0.55, and then you can get it at $0.53 the next day or a week later. Are you like, yes, I can get more? Or are you like, damn it, I might be wrong here. What is your reaction?
[00:15:19] Speaker C: It really Depends. Like, yeah, it depends on how confident I am, how much research I've done. Sometimes I'll just instantly bet. Other times I'll be like, okay, who made this? Who moved it back? Why'd they move it back? Maybe I'll talk to the person who moved it back and, like, you know, try and get a level.
[00:15:35] Speaker A: Yeah, I know who it is. It's my boy, he's dumb.
We know a few guys in sports who, if it comes back, they're in full on. Oh, great. I get more mode. But it's rare. It's rare to feel that way, actually.
[00:15:47] Speaker C: Be right and not.
[00:15:48] Speaker B: You know, it's funny, I had an interaction with this because I was on the do the opposite side of Domer in the gambling tax getting. And I was like, I thought I had.
[00:15:58] Speaker A: And whether or not the gambling tax.
[00:15:59] Speaker B: Is going to go. I thought I had some good inside information. I knew some people in connected places. And then Domer's like, yeah, you're fucked.
[00:16:08] Speaker C: I mean, I think it's still live. I think it's still live.
[00:16:10] Speaker B: I'm 4% now, and I bought it at, like, 65%. I'm pretty fucked. Yeah.
[00:16:15] Speaker C: Yeah. But, yeah, I think. I think it was someone who was very overconfident on something where they didn't have a lot of knowledge on how bills get passed.
[00:16:24] Speaker B: Yeah. Yeah, that was me. Like, I will own it. And it was fun to see that you were, like. You were reaching out and you were, like, trying to figure out if I had some other angle, which I respect. Like, I like that a lot.
[00:16:33] Speaker C: Yeah.
[00:16:34] Speaker A: In general. And I don't mean this to be a criticism of you, but you have done this before.
I think sports people.
[00:16:41] Speaker A: Are often overconfident. Getting into politics.
[00:16:43] Speaker B: Oh, yeah.
[00:16:43] Speaker A: Where they have one or two pieces of information and they can't contextualize it. Like, oh, I know this person is exploring Iran. It's like, you don't understand. All of these people put together these committees because they're so vain and in love with themselves.
[00:16:59] Speaker B: That was the problem.
I had this piece of information that even Domore didn't have. And I was like, this is it. I've got it. I'm gonna get the market. And then I didn't realize that that doesn't really mean shit. The piece of information doesn't mean shit. I learned that the hard way.
[00:17:15] Speaker C: But I remember your offer because it was huge and it was on the book.
[00:17:18] Speaker B: Yeah.
[00:17:18] Speaker C: And I was, like, talking with people. I was like, should I match all of this? Should I Match all of this. It took me like a couple hours and then I finally just.
[00:17:24] Speaker B: I wish you didn't match it all.
[00:17:26] Speaker C: Yeah, I apologize.
[00:17:27] Speaker A: Now I think the big takeaway is if you find out a large offer is Chris's, you just fill and move on and you don't think about it.
[00:17:33] Speaker C: Exactly. Yeah.
[00:17:35] Speaker B: But it is interesting. Like, I am curious because I did see it firsthand. You did reach out to Karen Party is there. If I had said something that made you think that you were wrong, what would you have done?
Try to sell off or like just accept the L or what would you. What would you do?
[00:17:53] Speaker C: Yeah, I mean, it just really depends on what the price. Because you know the other thing about the market that you traded and this is really big on prediction markets, like on news events is it had to be done by the end of the year. So there's. There's a time decay there. So part of it was like, I think you were betting in like, let's say August and they were about to take a few week break. So I was like, okay, I think there's gonna be. Even if this is gonna happen, I think it's gonna time decay.
[00:18:16] Speaker B: Fair. Fair.
[00:18:17] Speaker C: Yeah.
[00:18:18] Speaker A: So now. But now a perfect pricing system would understand that that break time is not real time. And it would be like be like halftime in a football game or something.
[00:18:26] Speaker C: Right.
[00:18:27] Speaker A: Where like you shouldn't say, oh, the dog is running out of time. Right. But what you're kind of implying is that these are not mature pricing mechanisms yet and they might be making naive updates.
[00:18:36] Speaker B: That's a very good point.
[00:18:37] Speaker C: And the riskless price on prediction markets is pretty high. Right. So if you think you deposit money in a bank account, you earn 3.5%. Well, on a prediction market, it's probably like closer to 10% that you can make just betting on riskless stuff.
[00:18:49] Speaker B: I do have to ask because I bought it 65 cents. How bad was my. What was your fair price when you bought it? How bad was my fucking there?
[00:18:58] Speaker C: 40. 30 or 40.
[00:18:59] Speaker B: All right, that's all right. If you said like horrendous, it's really bad. No, no, no.
He said he had like a roar of like 50 to 10 for the avatar. I was like, if he thought it was five, I was gonna be like, okay, that was really.
[00:19:10] Speaker C: No, no, no, 40.
[00:19:11] Speaker B: I mean, it's horrendous. It's horrendous. It's a horrendous price. So.
[00:19:14] Speaker A: So I gotta. And maybe you've said this before. Why aren't you touching sports yeah, that.
[00:19:19] Speaker B: Is a good question.
[00:19:20] Speaker C: Well, I'm. Okay. So for instance, like pricing a bill, like, how many people know how to do that? Or how many people would be able to react fast enough?
[00:19:28] Speaker A: Like, I can't even handicap that question.
[00:19:30] Speaker C: Exactly. Yeah. So it's very, very qualitative and it requires a lot of knowledge and, you know, you can research it and there's a lot of fun. Whereas sports, I feel like, is pretty darn quantitative. And so, yeah, I mean, I will get involved with like, if I see a quarterback injury really quick, sometimes I'll pop in and like just fast feeding stuff. Yeah, yeah, yeah. But like, I'm not trying to beat 54% with 52% or anything like that.
[00:19:56] Speaker B: What about in spots? We had a Foster on the other day and you know, Foster.
[00:20:01] Speaker C: Yeah. Mentioned Marguerite. Yeah, yeah, yeah.
[00:20:03] Speaker B: He's talked about this where it's just like an example he had was like the spread was 17 and a half and the team is kneeling, showing that they're not going to score and it's a very slow feat. Or you know, the example I gave was like hockeys and goalie pools. Like, that's a very qualitative thing. Like no one knows the true price of a goalie poll. But like, I do know if they pull at five minutes compared to two minutes, you're much likely to bet. Do you do anything in that at all or. No.
[00:20:30] Speaker C: In terms of like, like getting in.
[00:20:33] Speaker B: The streets, battle and prediction markets there.
[00:20:36] Speaker C: In sports or in sports? Yeah, no, not really. Although early on I was making a lot of money live trading sports. Like 2000, like the late 2000s.
[00:20:44] Speaker B: Okay.
[00:20:45] Speaker C: 2008, 2009, 2010. There was a World cup at some.
[00:20:48] Speaker A: Point, maybe 2006, taking advantage of like inefficiencies and stuff like that.
[00:20:53] Speaker B: Yeah.
[00:20:54] Speaker C: I don't know what was going on with the feed that I was betting against, but I was in the, in the US at the time and I took off from work and I watched the World cup and I was like 30 seconds ahead of the market maker. Yeah. Like for every goal. And so it was like Columbia could score. And then I was like, okay, not being called back. Okay, let me bet 2,000 bucks. And that just happened for like days. So I was like, okay, I need to.
[00:21:16] Speaker A: Like, this was the early, early days of online sports betting.
[00:21:19] Speaker C: And then you could also, like, this.
[00:21:21] Speaker A: Was literally places that were switching from phone banks, so you're just court sighting.
[00:21:25] Speaker B: But just like their feed is just like unbelievably horrible.
[00:21:28] Speaker C: Yeah, I mean, that, that that was a bad example. But like getting. Using the radio to get ahead, that was. I think I got banned actually.
[00:21:36] Speaker A: Just.
Well, I say I haven't done this, but like, AM radio broadcasts in cities are basically zero decay. Like it. It's true. Like physical matter stuff. So if. If court sighting in a stadium works, AM radio for baseball, etc, also basically works. So you can only get basically one station in any given location.
[00:21:57] Speaker C: But yeah, the only time I've been banned by a sportsbook, I was using the radio to bet Yankee games live. And they were like, no, we don't need you.
[00:22:04] Speaker B: Yeah, don't blame.
[00:22:05] Speaker A: That's the only time.
[00:22:06] Speaker C: Yeah, that was.
[00:22:06] Speaker A: Bo Dog never cut you off.
[00:22:07] Speaker C: That was.
[00:22:08] Speaker A: That's how you got caught up in Bodog.
[00:22:09] Speaker C: Yeah.
[00:22:10] Speaker A: Well, you got a second bite at the apple with Bovada.
[00:22:13] Speaker C: Yes. Yeah. Yeah.
[00:22:16] Speaker A: I want to ask you about. You said. I'm gonna ask you about scaling.
[00:22:19] Speaker C: Okay.
[00:22:20] Speaker A: You said you've hired people to build some models for you. Do you have any full time employees.
[00:22:25] Speaker C: Or is it all. Not yet. Okay. Yeah.
[00:22:27] Speaker A: Is that the plan?
[00:22:29] Speaker C: We'll see.
[00:22:30] Speaker B: Okay.
[00:22:31] Speaker A: Like in sports, you know, there's.
There's true, like qualitative ball knowledge, guys.
[00:22:42] Speaker A: Who.
That, you know, just things like I grind every press conference, every beat reporter, etc. Etc.
Who may just apply that knowledge to a market that they assume is otherwise efficient. Or they often get to the stage where they say, you know, I. I want somebody in my team who can model these games. And they don't necessarily have to be the greatest modeler in the world, but just so I know if my piece of information appears to be priced in or not. And then the modeling people often, you know, they're able to, you know, trade on exchanges or bet. But the better you are, like we talked about at getting the money down quietly and efficiently and etc. The. The better your turns are. So they often partner with somebody who's called a mover or you know, some kind of group that is in charge of handling all that. And so there's a natural way.
[00:23:33] Speaker A: That you can only get so big in sports before you really need to start building a team. There's a lot of things that don't happen. Like those groups basically never raise outside capital. Have you ever heard of them just raising funds?
[00:23:49] Speaker B: Never.
[00:23:50] Speaker A: Because you're. So the margins plummet with every marginal dollar wagered. Right. So it's so important to source your own.
[00:23:57] Speaker B: It's so funny, when I was more actively trading, like I had people like, oh, you do success? Do you Want to invest it? I'd be like, no, it's actually negative to take your money.
[00:24:06] Speaker A: So yeah, and I'll probably repeat parts of this question, but I'm wondering because I think you're kind of at the, the limit, like the literal mathematical limit of what one person can achieve in prediction markets right now, more or less.
[00:24:22] Speaker C: What do you think.
[00:24:25] Speaker A: The next hires for you would be or what the team would build out would look like? What do you think in general will become the consensus way people form prediction market syndicates or whatever?
And do you think we will see VC funding for these groups or will they raise funds like a hedge fund with 2 and 20 fees? Or will it be like sports where it's always they're sourcing their own capital?
[00:24:50] Speaker B: They like.
[00:24:50] Speaker A: Do you have any kind of view of where all that stuff is going?
[00:24:54] Speaker C: I mean it really depends how much because you know, prediction markets are starting to blend into finance, like what, what's the Fed going to do? And so the degree to which that happens will probably dictate like how much money is involved and like, because obviously they need to be big enough for something like a hedge fund to spin up or something like that.
Whereas now it's like as it exists currently, not, not imagining any, any future time, you probably would want to form people like using your own money. Right. And just kind of keep it in house. And, and the way that I would build a team is probably find people with different specialties. Right. Because like my specialties would not be analyzing election day results. Right. I'm not, I'm not building models, I'm not very good at that. So I would want someone doing that for instance. You know, I would want someone doing XYZ and abc. And so it would be more around like forming like, like a team of people who have different specialties.
Yeah.
[00:25:52] Speaker A: Well, what would be the canary in the coal mine for you on the financialization of prediction markets where you would say, oh, jump trading or whoever is like, is now going to be a real player like that We've crossed the Rubicon on this. Is there anything that you're kind of looking out for that you say as long as, as long as we're in this regime, guys like me are still going to be the big dogs. And, and this is where I might start second guessing how long the edges are going to last?
[00:26:19] Speaker C: Well, I mean it's a good question because I feel like just because money is coming in and maybe it's very smart money, doesn't mean that I would be any worse. It's not like they have some super secrets that they're about to deploy. Obviously they may have different sources or whatever, but like, I wouldn't be like skeptical about that, number one. Number two, like, you mean like canary in the coal mine in terms of like just signals.
[00:26:45] Speaker A: Signals that maybe the, the.
In 12 months the big winner in this field is going to be operating at a level that I just can't compete with.
[00:26:53] Speaker C: Gotcha. Yeah, I mean we're, I think, I think we're really approaching that point because like, yeah, like, especially have you seen like the liquidity on the Fed markets?
Like, it's like hundreds of millions.
[00:27:05] Speaker B: Part of that. Okay. Part of the problem with the Fed markets is like you can just use like the yield curve and like they're easy to price and they're easy to price. Like, and that.
What?
[00:27:16] Speaker C: No, I mean, so, I mean, so there is a market already. So it's a cme and they have Fed fund futures. Now if you go back over the past few years and you look at how accurate the CME market is versus how accurate prediction markets are. Are prediction markets are more accurate. Period.
Yeah, yeah, yeah. And like CME is slow moving and it doesn't react as fast and, and sometimes the reactions are wrong. So I feel like prediction markets have a huge interesting. Like obviously those will probably change. But I do feel like prediction markets are ahead right now and I feel like the money is more likely to come to prediction markets rather than using some antiquated CME fund which is very hard to trade.
[00:27:55] Speaker A: Do you think there are different parties who are trading on both?
[00:27:58] Speaker C: Yes. Yeah, for sure. That's strange. Yeah.
[00:28:00] Speaker B: Wow.
[00:28:02] Speaker A: Who do you think is the institutional or who's. Who is the player that is making the prediction market so efficient on those markets?
[00:28:10] Speaker C: Well, I think it's mostly people like me now. I really. Yeah. Now on Kalshi, they have like sig, who they're actually not that good at pricing Fed stuff, but like, they're probably going to get a lot better. So someone like SIG would be coming in. They would be hiring people to react very, very quickly to things. But like, I feel like prediction market players are much better at digesting minute pieces of information and converting it into price changes and they can do it very quickly.
[00:28:37] Speaker B: Yeah, this, this doesn't make any sense.
[00:28:39] Speaker A: To me because like, makes perfect sense to me.
[00:28:41] Speaker B: No, no, no.
[00:28:42] Speaker C: Are you.
[00:28:42] Speaker A: I'll let you figure it out.
[00:28:43] Speaker B: Okay.
[00:28:47] Speaker B: Because like when they, when you trade like swaps or stuff over the counter that's getting priced in to like, what if what the percent chance that there's a cut is. And you're talking about like funds that are dealing in like hundreds of millions and billions of dollars and you're saying that's less efficient than people betting thousands of dollars. I just.
[00:29:08] Speaker C: Well, I mean, people are betting tens, hundreds of thousands and millions of dollars on prediction markets now. But I mean, yeah, to your point, the scale is different. Yeah, but you know, the thing about prediction markets also is you're betting on the exact thing, whereas a lot of markets on like, you know, Fed adjacent in financial world, those are kind of proxies. Right. Or they're doing different things or there's.
[00:29:32] Speaker A: So marginal inaccuracies just kind of get eaten up by transaction cost and then.
[00:29:37] Speaker C: You don't have to be that good to some extent. Yeah.
Whereas, you know, a pretty market is trying to trade the exact, trying to forecast the exact percentage chance that there's going to be a cut in this meeting.
[00:29:48] Speaker A: You know what it kind of reminds me of is how like in the NFL, for instance, the, the end bosses of the NFL.
[00:29:57] Speaker A: Who have been around a long time were raised on spreads and totals because that's all you could bet for a while and then it was all you could get down money on.
And many of them are very good at predicting rosters and snap counts and things insofar as it affects all that stuff. And when player props came out, they take no interest because it's too small ball for them. And then you have a new generation of people who solve for player props because $500 is a lot to them. And over time, they kind of do start getting better at it than the guys who are betting 50 a game because.
[00:30:36] Speaker A: There'S just a new wave now. Look, I'm making the case, I'm not saying that this is actually true, but I'm just.
[00:30:43] Speaker B: It's hard for me to believe the size is so much more. Like I remember, like I used to work at a family office that had billions under assets. And when Trump was going with Kamala, we were trying to figure out the odds that Trump was back testing, not back testing, by pulling out like, okay, well, we know if Trump's elected, the bank sectors are going to boom and some other sectors are going to bust if Kamala is up and how much of the price change and how much of that is baked into other things. We're trying to pull that data in. And yes, there was also a market that we did look at the polymarket odds because it had significant volume, but I don't think we really cared that much about it.
I would have guessed that if we actually came to a real number that ours would have been more accurate. But, like, maybe I'm just arrogantly thinking that, like, I don't know if you understand what I'm saying.
And we had, like, we had like, so much capital to deploy. I was just. I just don't know how you could think that we were doing a shittier job, you know? You know what I mean?
[00:31:51] Speaker C: Like, well, you're just going to have to start betting and see how it goes.
[00:31:53] Speaker B: That's fair.
[00:31:53] Speaker C: Yeah, that's fair.
[00:31:54] Speaker A: That is the main takeaway.
[00:31:55] Speaker C: Yeah, right.
[00:31:56] Speaker B: That's true.
[00:31:56] Speaker A: If you really think it's that bad, go act on it.
[00:31:59] Speaker B: But we were.
[00:32:00] Speaker A: Yeah, you were.
[00:32:01] Speaker B: In terms of like, we deploy it in the financial markets.
[00:32:04] Speaker C: Right. No, I know, I understand that. And I think, you know, what may start happening and something that I'm looking into is like, prediction market traders starting to trade financial markets because we've noticed that there's. Sometimes there's a delay, sometimes they're pretty slow, sometimes they're really bad at pricing stuff. Like, someone I know who's really, really smart but, like, was looking at all the signs and was like, okay, I think Israel and Iran is about to flare up. And he bet a ton of money on oil. And he was like, way ahead of the oil traders. Like, we do this 247 and he.
[00:32:32] Speaker A: There's got to be some stat arb spots too.
[00:32:34] Speaker C: Yeah. So it's like, you know, you can pick your spots, you can find. Okay. I think we have an advantage here versus the oil traders who are looking at totally different things. So I think, you know, there's a possibility there where prediction market traders are finding more efficiencies, finding them faster and reacting faster. And that can get ahead of the people who. I get the interesting thing to it.
[00:32:54] Speaker A: The thing about statistical arbitrage, too, is that it's, it's like free money. It's arbitrage, it's free money. But it's very hard to identify and execute oftentimes. So you, you do have these lags where it's like, okay, we can see that these things that are extremely tightly correlated are drifting out of phase with one another and, and the player has not spun up. Who is every single time calculating which side is more likely to be right, clicking both sides proportionally correctly and then realigning, which is something that happens, like options, equities, markets.
[00:33:29] Speaker B: Right.
[00:33:29] Speaker A: Which is like, anytime anything is trading out of Sorts with how, you know, Black Scholes or whatever, more or less as it should be. Somebody is just running a constant bot to kind of hammer it into place. And that process is often where you do the discovery, you know, because sometimes it's the tradfi market is right, sometimes it's the PM is right. Certain regimes, it's going to be one or the other like you know, volatility or news timing, whatever might affect all this. And somebody just has to solve for that piece of it and has to have a lot of faith that this size is going to be there long term for it to be worth their time. I don't know anybody working on this.
[00:34:03] Speaker C: Problem by the way, but so there's a couple of examples that come to mind of like prediction market traders being ahead of the market. And that was Covid when that was breaking out in, in China. It was like me and a bunch of other people were like, okay, this is about to hit the US like, like probably a week before the stock market figured it out. And you know, because we were betting on it because there's markets like, oh, is there going to be a case in the US and it's like, okay, it's going up like, like we're figuring it out, we're mapping it out and it's like a bunch of us shorted the S and P. We made some money doing that. Yeah. So I mean not like a fortune or anything, but like, you know, that's one example. The second example, look, by the way.
[00:34:37] Speaker A: All these things, you could just get lucky already sized sample, just putting it out there before.
[00:34:43] Speaker C: Yeah, okay.
[00:34:44] Speaker B: To be fair, I was just thinking about this like free, I want more.
[00:34:47] Speaker A: Examples because people love the examples. We clip the examples and nobody listens to the rest of it.
[00:34:53] Speaker C: You know, responding to your comment, I've not had a losing month yet, so I mean, hey look.
[00:35:00] Speaker C: We, we love having you here. I know.
[00:35:01] Speaker A: You know what I'm saying?
I'm just continue with other times, you guys.
[00:35:06] Speaker C: The second time is when inflation was starting to creep up and it kind of surprised the Fed and I think a lot of us were starting to figure out that inflation's about to hit and we were betting on like inflation indices and stuff like that. And that was another point where he made a bunch of money. Ooh, I just thought of a third example, the dollar. We bet against the dollar thinking that Trump was about to unveil some tariffs and that was like probably a week or two before it happened and the dollar kind of crashed a little bit. We made some money on that. So you know, to me, when, when I think about the financial markets, it's like that's an opportunity for prediction market traders to find their spots.
[00:35:44] Speaker B: Right.
[00:35:44] Speaker C: We're not going to be amazing at everything, but just pick your spots and find some opportunities.
[00:35:48] Speaker B: And to be fair, I was just thinking about this to further your point. It's possible if I told you that Company X smashed their earnings, that doesn't necessarily mean the stock price goes up because they guide differently. And a lot of the times I guess with like pulling back my presidential example, we bought stocks and shorted stocks based on what we thought was happening with the presidential election. But we might have been letting our financial hats bias us where it's like we might be directionally correct on something, but we're actually just waiting way too much on a financial thing.
So you're probably gonna get pinpoint the true presidential odds better, but not price the stock price better. If that makes sense.
[00:36:36] Speaker C: Yeah, it makes a little bit of sense. The other thing that I was thinking about there is like to me, you can get into a really crowded trade where even if you win, you don't necessarily win any money, which is kind of like the appeal to me partially of prediction markets. It's okay, there's a set payoff. Like you can't really get into a crowded trade where it doesn't pay off if you're right.
[00:36:55] Speaker A: You know what else I was thinking of that's kind of funny is so like our friend Adi does consulting for part time living, right? I don't know who he's consulting for. He hasn't told me, so I'm not doxing him. But the kind of company you might consult for in his position would be like a hedge fund or a family office or somebody who is a VC fund that is investing in prediction markets or in competitors or whatever. And so there's a world where you might say, you know, well, you can't beat my old family office. They have billions of dollars of capital. What do they do with that money? Well, they hire the best consultants. Well, who are the best consultants? Well, there are people on prediction markets, so that's why you can't beat them. Like at some point it does just boil down to people, right? Like how there's some man or woman who knows a lot and has worked really hard on this and has a good opinion and puts their money.
[00:37:48] Speaker B: But it is true that that person.
[00:37:50] Speaker A: Tends to win, be allocated more capital. And so capital and talent are very closely linked over the long Term always.
[00:37:57] Speaker B: What has biased me so much in this exam and why? I think, like, the offices, not only from working there, but I remember, like, first couple weeks I worked there, I talked to the analyst that covered Flutter, and I'm like, I know more than, like, probably anyone on the street about their.
How they. How they hold, what their whole percentage is going to be, how they make money, et cetera, et cetera, et cetera. Let me, like, look at your model, what you're going through. And he just explained it all, and he encompassed everything that I would have given him.
[00:38:26] Speaker A: It's cool when it happens.
[00:38:27] Speaker B: And I'm like, I can't even add any value. Like, you don't even.
This guy has never placed a sports bet in his life, doesn't know how the trading team works. And he encompassed everything that I would have done. And I'm like. And then I hear, like, some prediction market. Oh, yeah, I know more than you guys. And that's why I'm like, come on, you have to be joking me. So that's where my bias kind of comes from.
Situations like that.
[00:38:49] Speaker C: I would say in response to that, sometimes you can be too close to it and you're too familiar with it, and very surprising things can kind of catch you by surprise. So that's why, like, for instance, stuff like Covid, where it's like, people are very dismissive of it. They're like, okay, yeah, maybe it'll come to the US but it's not gonna do anything. Or like, inflation, like, okay, maybe a bit, like, you can figure out that, okay, if this hits and it's really big, you can make a lot of money, like, and people kind of take for granted. One thing that people take for granted is that things are gonna stay the same, and especially if nothing ever happens. Yeah, exactly. Yeah.
[00:39:23] Speaker A: Yeah, exactly.
[00:39:24] Speaker C: Now, you could take advantage of that the other way by betting against things happening. But, yeah, if you can find some low probability, like, Black Swan event, like, you can literally retire off of it.
[00:39:33] Speaker A: I had a coworker at Bloomberg who was in Wuhan, like, in January, like, went in January and then couldn't get out cause of lockdowns. And he was, like, in chat with us.
And so we were stocking up on supplies and stuff in my house, and I was talking. Friends thought I had lost my mind. Like, I was speaking like a qanon insane person when nothing had happened. So. But there was this, like. And also I remember that the US Stock market actually got hit. Probably, like, the crash, so to speak, happened maybe three weeks before anybody stopped going to work or anything. Is that your record? It was like, February, you saw stock market impact.
March was when social impact was. And the stock market kind of didn't get hurt anymore in March, was my recollection, and then kind of slowly crawled back over the course of the year because everybody just piled into, like, remote type stocks anyway, like, peloton ripped and stuff like that. Yeah.
[00:40:30] Speaker B: So it sounds like you really prefer betting on, like, clear. Yes. No. And not a lot of derivatives for the most part. And when I ask if you don't, we can cut this if you don't want. But you're clearly taking a position right now looking at portfolio on, like, the Person of the year being something AI related. But, like, you're taking. You're. You're making a lot of trades based on the derivatives of that. Like, are you thinking that you might be like, are you pricing every unique AI Jensen type of thing itself? Or you're just like, I'm directionally right here and I'm going to be betting a bunch of derivatives? Or how do you approach something like that?
[00:41:10] Speaker C: Gotcha. So it probably shows up as me having a lot of AI shares just because I'm betting so much against the Pope.
[00:41:16] Speaker A: Yeah, he's no Pope.
[00:41:17] Speaker B: Got it, got it.
[00:41:18] Speaker C: Yeah. I have half a million on the Pope being here, which is probably too much, but maybe cut that for my family members. But they're all right.
[00:41:27] Speaker A: They're used to it.
[00:41:29] Speaker C: But. Yeah. So I do think it's going to be something AI or AI adjacent.
[00:41:34] Speaker B: Got it, got it.
[00:41:35] Speaker C: How I would handicap that from there, that's really tough because it's like, I think literally one person at a time. That's his job. So how do you figure out. And I've tried to talk people to people near him, and I'm like, asking them, like, kind of questions around the topic and nobody will really answer me. So it's just kind of like a thing that's pretty zipped up. It's hard to handicap.
[00:41:55] Speaker A: Why. Why are you so short on the Pope?
I know you have a lot down.
[00:42:00] Speaker C: No, no, no, no. It's all good.
[00:42:01] Speaker A: By the way, in sports, it's, like, very dangerous.
[00:42:02] Speaker B: Yeah, yeah, I know about this, but.
[00:42:04] Speaker A: I feel like it's different standards.
[00:42:05] Speaker C: No, no, it's all good.
I don't feel like he's done much. And like, the. The previous Popes who have won, like, they've actually, like, accomplished something. And when Francis was named, he was named Person of the Year, the year he was elected. But it was kind of like Obama, where Obama was, like, immediately like, okay, things are different now just by virtue of being named or elected. Whereas I don't think this pope is really, like, a transition.
[00:42:29] Speaker A: He's, like, gonna miss the playoffs. He's just like, yeah.
[00:42:32] Speaker C: And plus, like, you know, he could be named person of the year for the next 20 years or however long he's gonna live. So I. I don't think there's any time pressure to name this guy.
[00:42:40] Speaker B: So I want to ask you, going back to your avatar trade, I heard from another podcast, you talk about your Sarah Palin VP trait, which was legendary. Great, great work there.
[00:42:51] Speaker B: When you said you handicapped it at, like, 5 to 10% for the avatar, how were you coming to that now, if you could, like, were you going through and being like, did you know?
[00:42:59] Speaker A: Wait, back up, back up.
What was the Sarah Palin trade that was handicapped at 5 to 10%? No, no.
[00:43:05] Speaker B: Oh, sorry, sorry. I'm saying Sarah Palin, like, his story about Sarah Palin, which we don't have to talk about now because it's already public and everything like that. He just did a ton of work for that.
[00:43:15] Speaker C: Okay.
[00:43:16] Speaker B: When your avatar trade.
[00:43:17] Speaker A: Sorry, the Avatar trade was 5%, you.
[00:43:19] Speaker B: Said it was 5 to 10%, and you said 3,000 of the 6,000 for seven. Did you actually go in and count every single voter and you look up and be like, I know this person is.
[00:43:31] Speaker B: I'm curious how you arrived at that thing. Or was it just like, the public's a moron? Here, let me fade him.
I'm curious.
[00:43:40] Speaker C: I mean, so I think there's a degree to which people kind of take things for granted, and I feel like now it's so much more known that the Oscars tended to be older and white. There was, like, an Oscars so white thing. There was like, oh, we have all these old people. We need to get some young blood in. But before that was kind of known, like, if you were really, like, studying up on this and reading up on it, like, you can figure it out very easily. So the exact number of members was known, and I think, like, the average age was known. And then there's a lot of reporters for the Oscars, and they talk to voters all the time because they're going to events where voters are and they're chatting with them, and you can see like, okay, these people are all. You know, their movie credits are from the 60s and 70s or whatever. So you can kind of. And the other thing about the Oscars that made me extremely confident Is that there are precursor awards. So Hollywood loves giving themselves award for everything. So, like, directing, editing, like, every stupid thing that happens in a movie, there's an award for that.
[00:44:34] Speaker A: Editing movies is so stupid.
[00:44:37] Speaker C: Well, whatever. Yeah. So there's a lot of awards. And so you can kind of look at the precursors and be like, okay, well, like, got it. These people that are voting don't really like Avatar. Like, maybe they went and paid money and, you know, brought their grandkids, but they're not gonna.
[00:44:50] Speaker A: A lot of that is priced in now, too, right? Like Screen Actors Guilds. Yes.
[00:44:53] Speaker C: Yeah. I mean, the pricing is just so.
[00:44:55] Speaker A: Much more that actually kind of.
There was a. Last year in the NFL, Lamar Jackson was the first team All American, or, sorry, All Pro All American quarterback for the afc, which is extremely correlated with mvp, particularly if, you know, it's not an NFC quarterback.
And then Josh Allen won mvp. And there was a period where Allen was getting reloaded over and over and over again on the prediction markets and slammed again and again and again. And it seems like a year ago, awards markets were deep markets on prediction markets, and now they are shallow. Like, somebody has figured out, you don't want to mess around quoting these things for too much size.
[00:45:39] Speaker C: I think you should be. You should be a little cautious after the voting is over or after somebody can know the winner, especially if you're seeing large bets.
[00:45:47] Speaker B: Well, I'm just the reason I was asking, because I've heard some people for awards markets, like, they. They know all. Like, there's only 50 voters or something like that for, like, MVP, and, like, they'll go.
[00:45:59] Speaker A: And a lot of times there's only a few that anybody listens to, like Zach Lowe in the NBA, People kind of wait to know what he's going to do.
[00:46:06] Speaker B: Right? And it's like, well, some of them, it's like, okay, this guy lives in Maryland.
I'm gonna say that he's more likely to vote for Lamar over Josh. And it's like this person reported on the Ravens, like, eight years ago. Okay. And they have different percentages for everything. And, like, that's how they're coming to a number. And, like, I was just trying to.
[00:46:26] Speaker A: And there was a media, too. They all put stuff out there.
[00:46:28] Speaker B: Right? Right.
[00:46:28] Speaker A: Every once in a while, they just announce their vote in advance.
[00:46:30] Speaker B: That's why I was asking about that. I was curious. Like, 6,000 is a lot, but maybe you did all that work for, like, every single voter.
[00:46:37] Speaker A: The other thing that's definitely happened in sports. Sports and a few of the voters have admitted to this is they're all now way more aware of the odds and they're not confident. People who feel comfortable going against the grain, like it's a total hive mind and they really don't want to vote against heavy favorites.
It's like a major impact. And I wonder if we're gonna get to a point where people start manipulating.
Maybe not manipulate, but hammering markets. Feeling like if I can push this thing past a point of no return, voters will feel like they simply have to vote this way or else they're going to look foolish. I don't think that's that far off. Right.
[00:47:22] Speaker C: It's like where the tail wags the dog a little bit. Yeah, yeah, yeah.
[00:47:25] Speaker A: Do you do that gets us kind of like integrity concerns? Like, do you have any integrity concerns with prediction markets that you feel like the markets themselves should be taking concrete steps? Like, I remember you had a great, long, detailed post about the Alaska. Tom is the other guy's name.
[00:47:47] Speaker A: The guy who's doing a fast. A water fast.
[00:47:52] Speaker C: Oh, yeah. Oh, yeah, I forgot that. And just.
[00:47:54] Speaker A: And how, like, disreputable the thing was from top to bottom. Do you feel like Polly and Kelsey should be stepping back from stuff like that?
[00:48:03] Speaker C: Yeah. You can't let the market become more important than the event. Right? So like, let's say, for instance, let's say there's a market on whether you're going to cough this afternoon, right? And there's like tens of thousands of dollars bet on it. It's. It's so out of proportion. Like, someone can just be like, okay, I'll give you a thousand bucks. Can you cough? And it's like, yeah, I'll call for a thousand bucks. Like, the proportionality gets totally skewed, so you have to be really, really careful. So I think, you know, maybe the future of prediction markets, especially on like unimportant, quote, unquote, unimportant things, is lower limits and like, more.
[00:48:36] Speaker A: But you can't set limits, Right. Like they're.
[00:48:38] Speaker C: Yeah, no, as of now.
[00:48:39] Speaker B: But like liquidity providers, like.
[00:48:41] Speaker C: Well, I mean, this is theoretical. A theoretical solution is that you institute limits on events which aren't super important so that you don't end up.
[00:48:50] Speaker B: Okay.
[00:48:51] Speaker A: Does the CFTC appreciate that? Because I'd love to set limits on markets I quote from.
[00:48:57] Speaker B: I think the problem with that is there's always ways to circumvent.
[00:49:00] Speaker C: That's true.
[00:49:01] Speaker B: You put $100 a limit and then I go to just every friend I know.
[00:49:06] Speaker C: Yes.
[00:49:06] Speaker B: Do you Want to make 50 bucks? Bet 100 bucks here and bam, we've just circumvented it.
I think what naturally happened. Tell me if you disagree. Is just for unimportant events. The liquidity is just way lower because everyone's scared to do anything because the rigging is so real.
[00:49:24] Speaker C: Right. But prediction markets are peer to peer, so you can't control the liquidity. So like you can put up a thousand bucks or someone else can, but.
[00:49:30] Speaker B: Right. But I guess my point would be like, if, okay, something like the Fed market.
[00:49:35] Speaker C: Yeah.
[00:49:35] Speaker B: I would be comfortable coming in and making like a 3 or 4 cent wide thing if I had like a good model and for hundreds of thousands of dollars. Because I'm like, it's deep enough and there's going to get enough liquidity. If you said, I think the fair price for whether Henry will cough in the next predictive programming, like, I'm not going to market, make that for deep. Because like, it's so manipulative.
[00:49:55] Speaker A: Like, by the way, I would, I would never cough just to make it easy.
[00:50:01] Speaker A: Rock solid.
[00:50:02] Speaker B: You understand what I mean? Because you could have the best model. But like, if it can be like.
[00:50:07] Speaker A: Well, this gets us to a question.
Why was there depth on these markets in the first place? Why is somebody showing up and quoting something so toxic today?
[00:50:15] Speaker C: Okay, because it's fun. It's degenerate. You know, people are paying attention to it.
[00:50:19] Speaker A: Market making people are doing that for.
[00:50:21] Speaker C: No, but I mean like for instance, the guy who was in the desert or whatever.
[00:50:25] Speaker A: Yeah, I can understand taking it for fun. I can't understand quoting both sides for fun.
[00:50:30] Speaker C: Well, but that's what people were doing. They were really putting up offers.
[00:50:33] Speaker A: I was, I was assuming that the reason you see offers there is because there are rebates that make it worthwhile.
[00:50:39] Speaker C: Maybe. Yeah, maybe that helped like facilitate it. But no, people were getting very, very into it. And then the controversy itself sometimes on prediction markets draws in people. Right. So if people think there's going to be a big rule fight that's like, you know, moths to a flame.
[00:50:53] Speaker A: I know people certainly think they have angles on rules. Right. Like there might have been somebody who'd said, oh, I, I think this is the settlement here is going to bias towards yes or no and people aren't reading the fine print. And so that's a reason to get involved.
[00:51:05] Speaker C: Yeah.
[00:51:06] Speaker A: But that also feels like something you don't want to be the long term impetus.
[00:51:09] Speaker C: Yeah, yeah, yeah. So there's skeevy things that can happen that you Just got to be. You just got to navigate them.
[00:51:15] Speaker A: What do you see as the future of, like, canonical settlement stuff? Because I know you've written about criticism of the uma. I wouldn't say you're like, I think you're very. I think all these things are very fair. And you, whenever it's, like, thorny, you write very detailed threads.
[00:51:30] Speaker C: But.
[00:51:30] Speaker A: But, yeah, go ahead.
[00:51:31] Speaker C: Yeah. I mean, and then even as fair as I can be, usually the other side of the equation has at least some point. So it's hard to be like, you know, things are black and white. But one thing that they don't do that they really should do is, like, keep track of all these decisions that they make. Because one of the problems with these people, with the people that are deciding these markets, is that there's no, like, continuity. There's no, like, you know, okay, there's. They don't stick to precedents. Like, so there's no one keeping track. Like, okay, two years ago we were faced with this exact same problem, and we did xyz. And now it's like, okay, that person no longer works at the company. They have someone different who's 10 years younger. He has totally different view, and he does abc. And then somebody who has bet on the same market twice is like, well, hold on a second. Like, this doesn't make any sense. Like, you expired it this way and then you expired it this way.
[00:52:16] Speaker A: So there's Lenski suit was kind of like this, right?
[00:52:19] Speaker C: Where it's a little bit.
[00:52:20] Speaker A: That's probably a suit. But he's worn that jacket before and it settled. No.
[00:52:24] Speaker C: Right.
[00:52:25] Speaker A: So how can you settle it? Yes. Even though the pants kind of match better today.
[00:52:28] Speaker C: Right, Right. But then that's a tough one, though. Yes, exactly. Yes. And it's like kind of in the eye of the beholder. And some of these things are, like I said, like, qualitative and, like, there's no, like, determinative answer. And so it can be very, very hard to navigate. But one thing, that one thing that they can definitely do is keep track of things and write stuff down and make like a quasi, like, rule book. Like, these are the things we're going to try and figure out. Because, you know, if you imagine a new user to a prediction market, right. And you imagine he's bet on the supermarket, he has no idea that they've expired some previous one.
[00:53:01] Speaker A: Right, Right.
[00:53:02] Speaker C: He doesn't know precedence. He doesn't know who he. He doesn't even know who decides whether it counts as a suit or not this person has just signed up and they just want to bet on whether this guy's wearing a suit or not. So there's not much visibility, it's very opaque. So it just needs to be a lot more transparency.
Especially with like New Year's and stuff.
[00:53:21] Speaker A: Platforms can become beholden to these traditions in a way too. Like for instance, we, we have tennis markets that we avoid everything on, on mid match retirements, which for a long, long time was the standard everywhere and is starting to shift and saying to somebody who's relatively new to sports like oh, this is how it's always been done means nothing. It's like, oh, we should probably change all this because as much as it is the way of the world, it's probably doesn't have to be that way. And you can lose a lot of market share by just kind of being lazy about it. I say that we haven't changed any of it. Yeah, probably by the next major we'll have it goals modified.
[00:54:02] Speaker B: I want to ask two last questions for you.
What is the future of Domer and what do you think the future of prediction markets are?
[00:54:10] Speaker C: Yeah, so I mean I think the future of prediction markets is probably they're going to continue to get more widespread, so more topics, probably a focus on like important things. And then one question is whether it starts to filter.
[00:54:25] Speaker B: Is like what Joe Buck will say in the next announcement not important?
[00:54:29] Speaker C: Yeah, right.
[00:54:30] Speaker A: Are you bullish on the actual businesses themselves or is that something you don't think about?
[00:54:34] Speaker C: I mean, so I've been bullish on prediction. I've been bullets on like peer to peer markets for a long time. Like Betfair I think is great. I think one of their failures is like marketing and like they kind of focus on like non recreational people and so, you know, it's very hard to. So and that's one thing that prediction markets are trying to solve is like making the interface because obviously the core of the product is an order book and that's not very friendly to someone that has just showed up off the street. So you have to kind of make the UI something that's very conducive and very easy to understand. So it's kind of like hiding the complexity of the market a little bit. So yeah, I'm very bullish on prediction markets as like an operating system for how we're going to be betting on this stuff. I do think it's better than, you know, experts. Right. Because if you think about, let's say we're trying to figure out whether there's going to be a recession, right? And 20 years ago, you'd get a bunch of economists on TV, or maybe you get a business leader and you're like, okay, what are the odds? And maybe one guy says 20, another guy says 70. You have no idea what to believe. So if you put up a market on it, then people are studying statistics, like, we've grounded this in some variable, and then there's accountability.
So I do think prediction markets are a huge upgrade over the alternative, which is experts.
And it's something that people can kind of like consult on and be like, okay, like, maybe there might be a recession this year, so maybe I'm gonna hold off on buying a house or whatever. So I think the markets are very important, and they're gonna get bigger and more widespread, and the more important markets are gonna get even bigger in terms of liquidity and trading.
And then as far as me, so I think I would love to. First of all, I'm very content doing what I'm doing now. I'm have a ton of fun. It's like a blast. Like, every day is different. Which is really, really cool as like, a prediction market trader because, like, you never know what marketing be trading today. But if I were to do it, like, far more seriously, I'd want to. Going back to what I said, like, build a team of, like, people who are, like, experts in, like, certain areas and kind of deploy a lot of money and being able to work together. Because one thing about prediction markets is it's, you know, person versus person. PvP. Right. And so it's like a bunch of people trying to shoot each other all the time. Whereas if you can get a team and you can build a bunch of guns yourself, you're gonna be better off than trying to go through the wilderness on your own. So. Yeah, Makes sense. Yeah.
[00:56:51] Speaker A: All right. No, you.
[00:56:53] Speaker B: What?
[00:56:53] Speaker A: You asked the big closing questions.
[00:56:56] Speaker C: No, you feel free to ask.
[00:56:57] Speaker A: We're good.
Thank you for coming by.
[00:57:00] Speaker B: Great.
[00:57:00] Speaker A: Really appreciate it.
[00:57:01] Speaker C: No, I appreciate it.
[00:57:02] Speaker B: What a.
[00:57:02] Speaker A: What a treat to have you. All right, that's it.
