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They Made $0 for 4 Years. Then Built a $22B Startup | The Kalshi Story

EO31:10Added Aug 31, 2026

Most startups spend their early years shipping products and growing users. Kalshi spent them fighting to exist.Founded by Tarek Mansour and Luana Lopes Lara,...

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Contributed by 刘嘉琪

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  1. Intro

  2. 00:00I disagree that without money you can get the same level of accuracy. A lot of the research of course is always in very
  3. 00:06controlled environments, right? You're getting a very small [music] set of people and you're testing specific things. But when you actually take this
  4. 00:11into the real world, you're talking [music] about millions of people. Incentives really matter. And that's why when people are putting money where
  5. 00:17their mouth is, when they're actually putting money behind their convictions, that's why you get the best forecast because people at the end of the day are incentivized to make money. If you ask
  6. 00:23someone who they think they're going to win an election, there's a [music] lot of research that says that people go, "Oh, of course this person like the the
  7. 00:29other person is stupid. This person not going to win." But when you ask them, okay, would you put money behind [music] it? Then they take a step back and
  8. 00:34they're like, "Well, I'm not really sure because maybe inflation is going to make a lot of people vote this other side or
  9. 00:40maybe co is going to make people [music] change. Talk is cheap. On prediction markets, you're able to put your money where your
  10. 00:46mouth is." We really wanted prediction markets to [music] exist. We love markets. We love this idea that markets
  11. 00:51can bring more truth and more objective conversation to a lot of our most important questions. We really want
  12. 00:56wanted [music] this to to exist to go mainstream for people to see its power and start utilizing it. And this was essentially the [music] guiding light
  13. 01:03that in the hardest times kept us going and kept us trying in the start a single day that we called
  14. 01:08I think 60 or 65 [music] lawyers and then when we finished the list we were like wow none of them said this was
  15. 01:13possible. We had talked to pretty much any lawyer [music] that would talk to us about this and you know everybody rejected us. this
  16. 01:18regulatory first approach you cannot show progress. Other companies in our batch were shipping products, acquiring
  17. 01:23new users and growing [music] every week whereas we had we were stagnating. So as a company the only choice we had if we
  18. 01:29believe that we were right on the law, if we believe that this [music] should exist in society is to sue our own regulator which is what we did.
  19. 01:35Forget product market fit. He [music] doesn't have regulatory market fit. There's probably nothing more bold, more
  20. 01:41ambitious than suing your [music] regulator. We won and then I don't remember what happened after that but I think everybody was screaming in the
  21. 01:47office and like there were chairs flying around and we celebrated that day. It was it was really great. It was insane. It we got over 2 million
  22. 01:53customers [music] in I think 2 weeks. Did over 2 billion in volume. We were still a very small team. We were 20 [music] 25 people.
  23. 01:59We scaled 100x overnight. So
  24. 02:10prediction market startup Kelchi announced on Thursday a $1 billion [music] series F round valuing the
  25. 02:15company at $22 billion. That's double the 11 billion valuation Kelchi nabbed just [music] 5 months ago after raising
  26. 02:22a $1 billion series E.

  27. From Ballet to Building a $22B Startup

  28. 02:31When I was very young, around two I think I started doing ballet classes and that's was like my first big [music]
  29. 02:36passion was ballet and I I started doing it more and more and more and more up until I was doing it professionally.
  30. 02:42My days were very full. So, I would used to wake up at like maybe like 6:00 in the morning, eat a little bit, and then go to to normal like technical school,
  31. 02:49study, [music] math and science and all those things from 7:00 to 12:30. And then I would drive to the ballet school,
  32. 02:55which started around 1:00 and ended at [music] 9:00 p.m. Then I would go back home 9:30. And then I would actually start studying for whatever exams I had
  33. 03:01in school or SATs and all those things I had to do. [music] So, it was like 3 years that I was sleeping, I think, for
  34. 03:074 hours a night. My parents do today make the joke that they don't know how I grew to be a normal height because you know in Brazil we say you have to sleep
  35. 03:13a lot to be able to grow and they're like you're not sleeping for three years. How did that how did that work out?
  36. 03:19Since I was very little I was always very disciplined and worked very very hard. I feel like I get a lot of like pleasure on working hard and it makes me
  37. 03:26feel like [music] it's like I'm doing something with my life and that's always since I was very little I remember that
  38. 03:32on the discipline side and the other side is like kind of like this delayed gratification side that to me I liked
  39. 03:37doing things that were hard and and painful in a lot of ways because I thought there was going to be a big reward or something that I really was
  40. 03:43looking forward in the end and [music] and that's why ballet is very very good cuz you rehearse for like a year to have one hour on stage right so those things
  41. 03:50in a lot of ways I think my personality matched the kind of challenge challenge I was I was setting myself up for it was
  42. 03:55it's a lot easier for me if I have a very clear goal. It was like I wanted to figure out how to both excel in normal
  43. 04:02school and in ballet and I wanted to do that and I know it was around 3 years I had so it was kind of like a eye on the target type of thing but definitely not
  44. 04:08typical teenager. I remember like multiple weekends that I'm like wow I don't have exams next week I can just sleep like 8 hours and my friends be
  45. 04:15going to parties and all that stuff and it was just definitely not me.
  46. 04:20I only decided I wanted to [music] come study in the US. I ended up picking MIT because I thought it was the school that
  47. 04:26was going to take me most out of my comfort zone. But it was very hard transition first of all because I used to train a lot every day and it was a
  48. 04:33very important thing in my head. When [music] I went to school the first Saturday I was there to when I went to MIT I remember going to the Boston
  49. 04:39Ballet and try to take one class and I looked at myself [music] in the mirror and I was like oh my god I'm losing my form my arm looks bad and all those
  50. 04:44things and I thought it was better to just completely [music] stop it so I could remember myself being very good. So that was very hard to like go from
  51. 04:51eight hours a day doing something to [music] not even though I think it was the right decision.

  52. Conviction: 65 Lawyers Said No

  53. 04:58So I'm I'm a big math nerd. I grew up loving math. That was my biggest passion. And I think one of the things
  54. 05:03that happens when you grow up in a in a country like Lebanon, there's a lot of similar countries that have similar issues is that everything is very
  55. 05:09dynamic. Anything could change at any given [music] day. You have to adapt. You become very adaptable basically because one day there's war, one day
  56. 05:15there's civil war, one day there's bombs, one day the country is doing okay. Lebanese people in general, they're very adaptable. They can change
  57. 05:21their entire life pretty quickly [music] to adapt to something new that gets thrown at them. And then two, they they always smile at life. Like they got so
  58. 05:27used to h bad things happening that like they don't take them too seriously. [music] So you could have a bomb happened during the day and then
  59. 05:33Lebanese part people would party at night. They would not cancel their social plans or anything like that, which is which [music] is I think very
  60. 05:38cool. But I think that that definitely has come with me in founder journey, which is you're going to get hit hard and there's [music] going to be new
  61. 05:44things as an entrepreneur. There's always new things that get thrown at you every week, every month. and you're going to have to adapt and then not complain too much about it. Don't
  62. 05:50[music] take it too too seriously. You're just going to have to change the way you're approaching things and then hope that over a long period of [music]
  63. 05:55time if you're doing the right thing it's going to work out. I was an intern at Goldman Sachs in 2016 and I was very
  64. 06:00young at the time. I was discovering financial markets and learning about how they work. Two things really surprised me that summer. The first thing was
  65. 06:07institutions and investors. What they really cared about was not what is the price of a stock or the price of
  66. 06:12treasury bonds or other complicated assets. they really cared about whether Brexit was going to happen or not, whether Trump was going to win the 2016
  67. 06:19election or not. And so, at the time, there wasn't a very good way for them to get that exposure. And so, for example,
  68. 06:24when people wanted to hedge against Trump winning the 2016 election, there was this thing called the Trump trade that Wall Street bought a lot of. And it
  69. 06:31was basically shorting the S&P [music] on the week of the election. And that was a really bad trade because people were right about their predictions. So,
  70. 06:37Trump won, but then they lost money. This was really one of those moments where that made us think [music] maybe there is a better way. Maybe you could
  71. 06:43build a financial market that essentially answers these yes or no questions about whether important events are going to happen or not. Because if
  72. 06:49you could build that market, it would be a much more precise and direct way for people to get the exposure that they really wanted, which is whether an event
  73. 06:55was going to happen. And you know, I would say that was the initial idea for the company. The first time we actually fully talked
  74. 07:01about it was when we were both working at this prop shop called Five Rings and we were interning there together and
  75. 07:06there was this market making game that you basically made markets on it all day. You'd be [music] like, "What's the market on?" we started connecting a lot
  76. 07:13of different ideas and different things we've seen at this internship but also previous ones and I was like well when I
  77. 07:18was at Bridgewwater this was happening with with this other event and the five rings this was happening there and that's kind of where we started
  78. 07:23connecting the dots of all these different kind of like cow shei koshi behavior we were seeing [music] and thinking about it's insane that there
  79. 07:30isn't a legalized great big prediction market in the US that's liquid and [music] you can trade on everything and that's really the first time that we
  80. 07:36thought about it was a winter of um maybe [music] 2017 or 2018 that we're put everything
  81. 07:42together um into kind of really the the couch idea. In the start there was um a
  82. 07:47single day that we called I think 60 or 65 lawyers and we just had a spreadsheet and we're like well let's see let's see
  83. 07:53maybe the lawyers will will add some clarity here. We had a list of 60 lawyers and we were like tar Lana ta Lana who's going to call who and we
  84. 07:59called everyone and then when we finished the list we were like wow none of them said this was possible. Then Lana through multiple contacts got
  85. 08:07to Jeff. The first call we had with Jeff, he didn't say no, but he said all the reasons why this wouldn't work and how hard it is to get a regulated
  86. 08:14exchange and then a regulated clearing house and all the difficulties that will be ahead of us. And then he also explained that there is rules. There are
  87. 08:2123 core principles that you have [music] to uh prove that you are satisfying to become a regulated exchange and they're
  88. 08:27very hard to do and it takes a long time. We took those rules and we didn't have much context but it was a Thursday night and then by Monday we had a full
  89. 08:33analysis. Luan and I did it, the two of us by ourselves on how we would create this entire system that would abide by
  90. 08:38those 23 rules. And I think when Jeff got that, he realized we were very serious about this. He was like, "These people, yes, they want to build product
  91. 08:44and commit committed to it, but they understand that there's a long regulatory journey they're going to have to take and they're probably going to be
  92. 08:49able to balance those two things together." And so he got excited about, you know, joining and helping us make [music] make this happen. And I think
  93. 08:55that was a very big early win for us.

  94. Legitmacy: Four Years to Earn the Right to Launch

  95. 09:01we were started talking more about should we actually try to do this? Should we actually build this company? It was in the summer when we were both
  96. 09:06working at Citadel and one of our first things was well why don't we just try to go to this Y cominator hackathon you know it's like where these massive
  97. 09:13companies like Airbnb and whatever they all go there so let's try we presented and we had kind of like this very janky
  98. 09:18demo that kind of it was stable Coinbase at the time and you had to like it did move place A to place B but it was kind
  99. 09:24of only this and a very simple user interface and the first thing he said was that's illegal and then we're like
  100. 09:31well but maybe we can figure this out and and he's like well then why haven't other people done And we didn't really have a good answer for any of that.
  101. 09:37Yeah, I definitely remember the moment and when we were first really deciding whether to start a company and and and
  102. 09:42how to start it. This moment was very foundational because this was the time when as a company we decided to define
  103. 09:48[music] one of the most important principles of the company which is we're going to do everything regulatory first. We're not going to launch. We're not
  104. 09:54going to market. We're not going to build product. We're not going to do anything up until we figure out the most important thing for [music]
  105. 09:59the company to exist, which is how do we legalize and regulate this and [music] how do we create an ecosystem that is
  106. 10:05safe and transparent for customers. And that has informed everything we have done at [music] Koshi till today.
  107. 10:11And I think that YC kind of Michael Sabo actually says this to today that he's like this sounds insane, but these two
  108. 10:17kids from MIT sound really motivated and we should give them a try. When we were in YC, every other group in our batch
  109. 10:23had [music] week overweek like metric growth where they were like, "Well, we grew 20%. We're making this amount in revenue. We're we're new users and
  110. 10:30building this [music] product." And our entire journey was we talked to these lawyers and the next week like we talked
  111. 10:35to these other lawyers and the other week is like we filed this document [music] and all of that. So, it was a very different YC experience for sure.
  112. 10:42We were stagnating. there was no real progress because we were just [music] talking to regulators and writing legal documents and figuring out policies and
  113. 10:48procedures, all the stuff that entrepreneurs usually don't want to deal [music] with. It's kind of the unsexy parts of of building a company. And it
  114. 10:53was even more hard because our some of our competitors launched [music] and did it offshore without the license without
  115. 10:59really this regulatory structure that we were seeking. And I would say that was the hardest part of the path. It's not necessarily the period of time or the
  116. 11:05work itself. It's just the fact that you [music] cannot make real tangible progress. But we were very committed to
  117. 11:10it. We did not want to launch unless this was 100% regulated. It goes back to how we started the company. We we were not necessarily looking for ideas to
  118. 11:18start a company. [music] We we started the company because of this idea. We were a bit different. So there are sometimes teams that start [music] and
  119. 11:24they they pivot and they look for a bunch of different ideas to decide which one is the best one to to work on. [music] We were committed to this idea
  120. 11:30from the start. And so my answer here is that we really wanted prediction markets to exist. We love markets. We love this
  121. 11:35idea that markets can bring more truth and more objective conversation to a lot of our most important questions [music]
  122. 11:41and we really want wanted this to to exist to go mainstream for people to see its power and start utilizing it and
  123. 11:47this was essentially the guiding light that in the hardest times kept us going and kept us trying.
  124. 11:52Nowadays it's very hard to find very good and reliable [music] data sources for what's actually true and happening
  125. 11:58in the world. It's very hard to know if what I'm seeing on Twitter is it writer is it bots or who is writing this? What
  126. 12:04prediction markets do is that they kind of like take away the noise and you can really look at a like forecast that's
  127. 12:09come from millions of people putting money on the line and putting money where their mouth is to really see I believe this is going to happen. I'm
  128. 12:15have a lot of conviction and and [music] kind of aggregating all of that to see to see the future. So even if people are
  129. 12:20not trading in the markets actually the most important part of these markets is the single point of data the price that
  130. 12:26comes from these markets which can benefit anyone and I think that's the most important. If there's one thing people know about prediction markets, I
  131. 12:31really hope they they know that [music] if they want to know anything about the future, it is the best way to get a
  132. 12:37correct unbiased forecast.

  133. Payoff: Four Years of Fighting. Four Weeks to Scale 100x.

  134. 12:43I [music] take hundreds of meetings a year. My first meeting with Tar really
  135. 12:48stands out. We were in Cafe Liria, which is this hipster coffee shop in New York
  136. 12:55City. It was really crowded. We could barely get a seat. We were surrounded by people. I'm thinking to myself, no one
  137. 13:02around us has any interest in this [music] conversation. I meet Taric for the first time. Forget product market
  138. 13:07fit. He doesn't have regulatory market fit. Part of the reason that meeting
  139. 13:12stood out so much was he's telling me the story of how he's suing his regulator. We love to back ambitious
  140. 13:21founders, bold founders. There's probably nothing more bold, more ambitious suing your regulator.
  141. 13:28They blocked it a lot of a lot of times. So we try to engage with them for over two years on like the usual process that
  142. 13:34we have for new markets and we talked to them about the use case of this market. We actually had a public comment period
  143. 13:39that over 200 people including [music] very very big academics like head of the council of economic advisors all of
  144. 13:45these folks wrote in saying these markets are very important. You should allow these markets to operate here and just regulate them so that they're safe.
  145. 13:51And then we realized that I think working with the regulators or trying to convince them wasn't going to work. But we didn't decide to list it like
  146. 13:57competitors. We stayed committed to the regulatory first principle. So as a company, the only choice we had if we
  147. 14:02believe that we were right on the law, if we believe that this should exist in society is to sue our own regulator, which is what we did. It was a very
  148. 14:08difficult decision. It's very hard for a company, especially a startup, a small company, to sue the part of the government that oversees you because
  149. 14:14they have all the power over you. But we decided to make this decision regardless [music] because we really believe that these market should exist.
  150. 14:20And it was a very hard decision because four years for [music] us to get regulated and we were kind of putting that in jeopardy in a way by suing them
  151. 14:27because we're basically saying like we're we're trying to really like okay we're we're fighting I very officially
  152. 14:32fighting uh in court um at that time and [music] but it was two things that really
  153. 14:37mattered to us. One these markets are the holy grail of prediction markets. They should be legal. They should be regulated. They should be in the US.
  154. 14:43They're very important. and the other sides. We knew we were right on the law. We ended up winning. Actually, every judge that looked into our case ruled in
  155. 14:50our favor on the district court and then the appeals court for two weeks and then when we won it
  156. 14:55was amazing. The next day the government is like we're going to appeal this. We extremely against I think this decision is wrong and then the stress all came
  157. 15:02back up. Okay, so now we have to go through the entire appeals court and process. Is it going to be done in time? Cuz at that time we were like 2 months
  158. 15:08before the election. maybe there was a chance we're going to run out the clock and we would lose the 2024 elections even if we won the lawsuit. So then it
  159. 15:14was one month of like we had this one big hearing on the appeals court in the state um pending appeal. And I remember
  160. 15:20it was like both Tark and I we we listen to to the court hearing at at the time and we were just pretty much only
  161. 15:26listening to this one recording of of the court and and trying to like get the company to keep moving and building
  162. 15:31things and all of that in case we want. But in our heads we were like this is the most important thing ever. we weren't being able to focus on anything
  163. 15:37else or sleep or eat or or anything like that. But after we we won, I think it it
  164. 15:42was like at 1:00 p.m. and we were extremely happy. It was like, "Okay, but then next day we have to launch this market and then we're going through like
  165. 15:48the we're going to go through actually the most intense period ever because [music] it's 4 weeks for us to go from a
  166. 15:53small niche website that not a lot of people know about, what are prediction markets to hopefully one of the most important things in the 2024 election
  167. 16:00and one of the most important data sources. We won. We won. We won. We won." And these moments are great because it's part of what a lot of entrepreneurship
  168. 16:06is about. You get frustration after frustration and no and disappointment after disappointment. But then all of these are counterbalanced by these very
  169. 16:13short moments where [music] you get big wins and those big wins make the whole experience totally worth it because you know you put so much effort and you see
  170. 16:20results. Yeah, those moments I think it's uh it's important to try to celebrate them but but it's also important for us at least we don't try
  171. 16:25to celebrate them for too long. We celebrate them for a bit and then we go back to work because then you have the next milestone. We're lucky enough that
  172. 16:30we got this win. we have to now make it count and we have to figure out [music] how to scale the product, bring in the customers, make the election market
  173. 16:36count and we only had a month to do that. So we celebrated for a few hours and then we got back to work. One of the very tricky things about
  174. 16:42Kawoshi is that a lot of our story is tied to very external factors that we don't have control over, right? So it's
  175. 16:47the government, it's a lawsuit, it's this, this and that. But it was one of the first times that actually it was fully in our hands how big it was going
  176. 16:54to be and if we were going to win or not. We felt like we had fought so hard, you know, for years [music] to get to
  177. 16:59that to get the chance to be able to do these markets. We felt like it was our shot. We we cannot mess up that shot. We
  178. 17:05have to deliver. So, we decided like, you know, for this whole month, our entire team and it's not just one and I think we [music] often times get
  179. 17:11disproportionate credit because a lot of the real work was basically the team. It was the engineers, products, markets,
  180. 17:17the [music] marketing. Everyone was just like for 4 weeks put their life on pause. it will be close to 247 in the
  181. 17:23office in the weekends just completely committed to making this [music] thing work. It was really hard because we scaled 100x overnight and that's not
  182. 17:30easy for systems to sustain [music] and a team to sustain but we you know we had a very small team that made that happen. It was insane. It we got over 2 million
  183. 17:37customers in I think 2 [music] weeks did over 2 billion in volume. It was crazy. We were having everything engineering
  184. 17:43wise was kind of breaking right. We've never gotten that many deposits like ever in the years of the company and everything was kind of breaking. But
  185. 17:49yeah, it was like the the the numbers the result that we got in the end, it was actually weaving would have grown a lot more. But the problem was that our
  186. 17:55deposit flows and signup flows were breaking because of the amount of people coming in that we had to kind of like almost like slow down.
  187. 18:01So the hardest thing that happened is at the time there are two key pieces to running a financial market. There's the
  188. 18:08exchange and then the clearing house. [music] The exchange is the marketplace that matches buyers and sellers. The clearing house is the place that handles
  189. 18:15all the money movement like how much money you have to put up to back this trade. Where does the money go? How do
  190. 18:20you keep it safe? We at the time had the cashi exchange and we were using a third party clearing house. [music] We had
  191. 18:26just gotten approval for our own clearing house. So to stop using the third party, but we were not ready to use our own clearing house at the time.
  192. 18:32The [music] issue is when we won the lawsuit and this was really unfortunate. The third party clearing house decided
  193. 18:37to block the election market. They did not want to let us list it. And so the hardest thing we had to do in [music] that weekend, and we knew we had only
  194. 18:43four weeks left, so we had to do it really fast, is basically move all of our business from the old clearing house
  195. 18:49to the new clearing house, and usually you do this over the span of a of a six-month window. You [music] plan it.
  196. 18:54There's a lot of different things that go into that movement. It's very complicated. It's a very big migration. And we had to do it [music] over a
  197. 19:00weekend because otherwise we wouldn't be able to do the election market. So it was a very disappointing situation, but we made the most out of it. And
  198. 19:05honestly, the engineers had done an incredible job navigating that. But that was definitely the hardest part uh of
  199. 19:10the month. That was very very difficult. If you look at the 2024 election, Khi was able to call the results before the
  200. 19:18media, you were able to see live probabilities throughout the night. And so long before it was declared that

  201. Signal: Not a Casino. A Market for Truth

  202. 19:24Donald Trump was the 2024 winner on mainstream media,
  203. 19:31the question of whether prediction markets are betting or gambling [music] is very similar to the question of whether financial derivatives are
  204. 19:37gambling or betting. And that has always been a question uh historically that has happened in financial markets. And the reason this question exists is because
  205. 19:43[music] there is speculation in financial market. And speculation can look in some cases like a bet. It's like
  206. 19:48you're putting money to make more money on something you [music] don't control. But there are key differences. One is are you participating in something that
  207. 19:55is a natural risk? [music] It exists in the real world. It is tangible. You know, people care about it versus like
  208. 20:01rolling a dice that has no, you know, it's an artificial thing that you're creating for the purpose of uh betting.
  209. 20:07[music] The second core uh pillar of this, the market structure. In gambling, the market structure is you walk into a
  210. 20:13casino or a house, the house's [clears throat] revenue is [music] equal to the customer losses. There's inherent conflict of interest in the business
  211. 20:19model because the company benefits when their customers [music] lose. Prediction markets, just like traditional financial
  212. 20:25markets like the New York Stock Exchange or other places, yes, the underlying is different. Like what you're trading on is different, but how you're trading or
  213. 20:31how [music] you're participating is the same. It's an open marketplace. It's fair and people are trading against each other. So, the market is neutral. The
  214. 20:38market doesn't make more or less money if their customers lose. It's more of a fair and transparent place for people to [music] participate. And that's why it
  215. 20:43makes it, you know, a financial market and makes it kind of structured or or or placed in a [music] in a very different way than traditional, you know, betting
  216. 20:50or gambling places. I disagree that without money, you can get the same level of accuracy. A lot of
  217. 20:56the research, of course, I come my background is an academia. So, a lot of the research is always in very controlled environments, right? You're
  218. 21:02getting a very [music] small set of people and you're testing specific things, but when you actually take this into the real world, you're talking
  219. 21:07about millions of people. Incentives really matter. And that's why when people are putting money where their mouth is, when they're actually putting
  220. 21:13money behind their convictions, that's why you get the best forecast because people at the end of the day are incentivized to make money. And you see
  221. 21:18a lot of it is like the decrease [music] of polarization, right? If if you ask someone who they think they're going to win an election, there's a lot of
  222. 21:23research that says that [music] people go, oh, of course, this person like the the other person is stupid. This person not going to win. But when you ask them,
  223. 21:29okay, would you put money behind it? Then they take a step back and they're like, well, I'm not really sure because maybe inflation is going to make a lot
  224. 21:36of people vote this other side or maybe co is going to make people change. So, it kind of decreases polarization, but
  225. 21:41it's a whole point about money being the incentive to bring truth and information to markets, which you can't have if if
  226. 21:47you [music] don't have it. Prediction markets cut through the noise. They're the true signal of what's
  227. 21:52happening. If you think about social media, it's qualitative opinion. [music] If you think about prediction markets,
  228. 21:58it's quantitative conviction. Talk is cheap. On prediction markets, you're able to put your money where your mouth
  229. 22:05is. Regulation means a lot of different things, but I usually bucket them into two main pieces. One is market
  230. 22:10integrity, [music] which means fairness. Is the market fair? And then number two, customer protection, which means like clarity and
  231. 22:16transparency. And if we find that people did something wrong, it's the same as the stock market. We can do a [music]
  232. 22:21fine or we can refer to the government for uh criminal prosecution. If someone commits insider trading on cash, it's
  233. 22:27the same as insider trading in in the stock market or other places. And this is all structured, all these different
  234. 22:32rules are structured so that you get like you get a marketplace that is fair. And then the customer protection piece, it's [music] really all about making
  235. 22:38sure you're treating all your customers the same way that everything is transparent. So all of the trades, we [music] have a duty to make all of our
  236. 22:44trades and activity publicly available so that everybody can see it and we report to the government. We cannot [music] have discriminatory access. We
  237. 22:50have to give the same rights and same obligations to everybody else which is one other [music] thing that's very unique about financial markets or Koshi
  238. 22:56where like you cannot for example block the winners and then promote the [music] losers so that you know if somebody wins
  239. 23:02on your platform you you block them like some of the gambling sites do and if somebody loses money you basically figure out how to [music] get them
  240. 23:07hooked. You cannot do these types of things on a regulated exchange because it has to be neutral. The biggest misconception about
  241. 23:13prediction markets is they're just around sports. It's all about sports [music] and sports is a meaningful
  242. 23:19portion of prediction markets, 10x, but non-sports today has 300 to 400 million
  243. 23:26of weekly volume that translates [music] to 15 to 20 billion annualized. And
  244. 23:31while everyone talks about sports and it's growing so fast and so much of the volume, if you were to just look at
  245. 23:36non-sports, it's growing really fast, too. It's [music] growing 5x year-over-year. These markets cover
  246. 23:43economics. Where are interest rates going? Politics, who's going to be the next president, who's going to be the
  247. 23:48Fed chair, culture, who's going to win the Oscar, even the weather, how many interest is it going to snow in New York
  248. 23:53next week. But these other categories are growing really quickly and in the next few years are going to represent
  249. 24:00meaningful portions of the volume.

  250. Edge: Where Knowledge Becomes a Market

  251. 24:05So, uh, my name is Joel. I am a full-time prediction market trader and content creator only for the last six
  252. 24:10months. So, still very [music] new to this. I trade a variety of markets, but I'm most wellknown for mentioned markets, which are markets on what
  253. 24:16someone will say in a speech and [music] within that even more so focused on kind of Trump speeches. Being an accountant
  254. 24:22and following, you know, [music] companies very closely, loving to read like a 10K or 10 Q. And I realized that
  255. 24:27like I can't really compete uh the equities market, right, in terms of like picking [music] stocks or something like
  256. 24:32that because who is my counterparty? Who am I up against? It's going to be a hedge fund or just a much more
  257. 24:38sophisticated investor. [music] So seeing prediction markets was a huge draw to me because I'm like okay here's
  258. 24:43something that I believe is very inefficient for the [music] time being and that's why it was a natural draw is I felt like I could get an edge I guess
  259. 24:50made in the past year just over uh 200k trading but since going full-time back
  260. 24:55[music] in end of September uh I've made about 170,000 in the last 5 months or so
  261. 25:00uh trading when I'm trading [music] I'm doing heavy kind of research like for for Trump um I'm looking at you know as
  262. 25:06many historical speeches that he's given to kind of try to gain an edge of what is this [music] guy going to say? I'm
  263. 25:11very very in tune to talking points of the administration as new news is breaking out. How is this going to impact what he's going to talk about in
  264. 25:17his next speech? I will watch every single one of Trump or Manny or Powell every single one of his speeches.
  265. 25:22[music] So the intuition I've been able to build up over kind of what he's going to talk about in a given day and then
  266. 25:27staying [music] very very in tune with what's happening around the world and how that's going to impact talking points. uh have uh [music] a database
  267. 25:34that I use of historical speeches for for anyone that I'm I'm trading in. So,
  268. 25:40I'm not going to like rewatch all of his past speeches, but [music] anytime he's going to go live for a speech, I'm
  269. 25:46always watching it. It started as a very kind of quantitative thing where you're looking [music] at historical speeches,
  270. 25:53things like that. and it's evolved into a lot more intuition [music] based where I just know I can trust my intuition
  271. 25:58when it comes to someone like Trump because I've watched hundreds of his speeches. I'm Brandon Fiend. I'm a
  272. 26:0425-year-old in Bucks County, Pennsylvania and I am a public school
  273. 26:09teacher. I teach sixth graders at an elementary school and direct the school plays. So, I have $150,000
  274. 26:19um that I have made from Kouchi. I just hit that milestone today. I went downstairs to my parents and I said,
  275. 26:25"Mom, dad, I just made like $8,000." And I'd been very quiet about koshi like
  276. 26:32beforehand cuz I wasn't having success with it ever since I was in 8th grade. I've studied the music charts. I have
  277. 26:38overanalyzed them. I've tracked them in the little notes app on my phone. Travis Scott was selling CDs for his single
  278. 26:464x4. If you copied the HTML page source and you looked in the code of it, you
  279. 26:51could actually see the inventory for how much was stocked. I bought very low
  280. 26:56stakes, paid out [music] $8,000. That was crazy that just looking at the source code of a website that's
  281. 27:02public to everyone. You can just hit source code. It's right there. I made $8,000 off one click.
  282. 27:09My name is Shannon. I work at Koshi in operations and I am originally from
  283. 27:14Alabama. I started trading on Kouchi back in 2021. I went to school for meteorology and so some friends that I
  284. 27:20went to school [music] with had said, "Did you know that you can trade on high temperatures?" And I thought that was
  285. 27:26super [music] interesting. My first deposit was $50. From there, I mean, it was just kind [music] of like, "Let's
  286. 27:32see what happens with this." Uh, I wrote out Hurricane Ivan back in 2004, Hurricane Katrina [music] in 2005,
  287. 27:39Hurricane Michael in 2018. I have a lot of experience with tropical storms,
  288. 27:45tropical cyclones, hurricanes, things of that [music] nature. I think it's really important from a climatological
  289. 27:52perspective [music] to utilize those weather markets in a way that is almost
  290. 27:58like insurance. But whenever I did live on the Gulf Coast, my homeowner's insurance deductible for a hurricane was
  291. 28:04over $10,000. So essentially it if a hurricane were headed to my house, the
  292. 28:10way I would hedge that is with buying yes that a hurricane would hit. So let's
  293. 28:15say that that's a 10. I take $1,000 and put that on yes that a hurricane is
  294. 28:21going to hit. So if I bought $10,000 I get $10,000. So a $9,000 return. I would
  295. 28:27then use that to pay the homeowner's insurance deductible [music] to recover
  296. 28:32things, you know, from the loss from the hurricane at my house.

  297. Scale: From Niche Market to Global Infrastructure

  298. 28:40Well, I think the company has grown a lot since we last spoke. I mean, I think the the way that consumer marketplaces
  299. 28:45work is there's [music] network effect aspect to them. They compound over time. It's a bit like an exponential. and the exponential things
  300. 28:52grow but you don't really notice that growth up until it starts getting to big numbers and all and then an exponential
  301. 28:58basically becomes big very [music] big very quickly and I think that's what happened with Koshi in the last 2 years I think the company has gone mainstream
  302. 29:04we've grown a lot in size percentage of Americans now are active on the product whether they're trading actively or
  303. 29:11they're getting informed about the forecasts they use it a bit like a news feed and I think we now have a global
  304. 29:16recognizable brand one of the places that we really want to invest in is essentially defining ing what the brand stands for and explaining to [music]
  305. 29:22people who we are, who we're not, what we want to do and what we want to achieve. And I think there's a lot of work to be put on the brand. Basically
  306. 29:27explaining [music] to people what that brand means. We want to go international. We want to diversify our customer base. And you know, we feel
  307. 29:33like we're in a very very early inning of people using prediction markets actively. Even though the numbers have grown a lot, I think they could really
  308. 29:39grow significantly more. You know, we get into basically every corner of the internet. If you have an interest or a
  309. 29:44passion or you care about something, there will be a market that you can relate to or engage with or you can get
  310. 29:50informed about because that's whole the whole vision. The whole thing was people feel like Wall Street is rigged against them. Most people don't relate to the
  311. 29:56stock market or understand options or or complicated [music] financial instruments, but they read the news. They follow trends. They are on X. They
  312. 30:03care about politics. They care about culture. They care about sports. And this is a market where they can find a place for topics that they're passionate
  313. 30:09about with other people that have the same similar passion. and then you know debate on the opinions about these things. [music] So we we have a long way
  314. 30:14to go. We really want to go more into the institutional use case. When we started the company it was the idea of causing
  315. 30:20how we how we first encountered this this type of [music] couch behavior was in institutions right it wasn't a
  316. 30:25Goldman Sachs a Bridgewater five rings a citadel and for us it's kind of full circle we actually that is where we want
  317. 30:31to really land it's like these extremely liquid markets that everyone from retail to [music] a massive institutional bank
  318. 30:38is trading on. And I think that in five years, if we're very successful, I think that prediction markets are the size of the stock market. The participation of
  319. 30:44like the types of users participating [music] in it are similar to that. And it's just a very more a way more mature
  320. 30:50market. But yeah, I [music] just hope Couch grows even even more.
They Made $0 for 4 Years. Then Built a $22B Startup | The Kalshi Story — Transcriptly