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Luana Lopes Lara

Things Luana Says on Podcasts

Where to Find Them

Luana Lopes Lara writes CNBC Changemakers and Power Players . They have also been a guest on Interviews with Max Raskin (2 times) , Silicon Valley Girl: AI, Tech and Career Growth , Billboard On The Record , Cheeky Pint , Masters in Business , Coin Stories with Natalie Brunell , The Investor's Podcast (We Study Billionaires) - The Investor’s Podcast Network , What's Your Problem? and Masters of Scale .

Recently: “Kalshi vs. Everyone: Co-Founder Luana Lopes Lara on the lawsuits and the long game” on Masters of Scale (October 2026); “Top 1% Career Playbook: How to Get Hired in the AI Era” on Silicon Valley Girl: AI, Tech and Career Growth (September 2026); “How Music Superfans Are Cashing In On Kalshi w/ Luana Lopes Lara” on Billboard On The Record (April 2026); “Luana Lopes Lara: Youngest Self-Made Woman Billionaire on Kalshi, Bitcoin & Beating the Feds” on Coin Stories with Natalie Brunell (April 2026); “Creating prediction markets (and suing the CFTC) with Tarek Mansour and Luana Lopes Lara” on Cheeky Pint (March 2026); “She's the world's youngest self-made female billionaire 3/10/26” on CNBC Changemakers and Power Players (March 2026).

What They Said

“A sports book is actually completely different. … Their revenue is equal to customer losses. The more the customers lose, the more money they make.” — Luana Lopes Lara, Masters of Scale

Lopes Lara was answering a question about states suing Kalshi as an unlicensed gambling operation. Her defence is that Kalshi is an exchange where users trade against each other and the company takes a fee, so it does not profit when users lose. The host pointed out afterwards that most of Kalshi's volume is sports and that sportsbooks regard it as a competitor.

Masters of Scale · 2026-10-06 Permalink → Listen →
Masters of Scale Around 06:46 into the episode
Speaker 3

I actually would say it's a very good thing that it happened like so fast because, in a lot of ways, we keep the mentality of very, very early stage, right? And I think it's like when companies, I think they're just like compounding at a kind of like very normal rate. I think it's easier to kind of start thinking, like, oh, I'm a bigger company, I need to hire more people. And you kind of like, you don't realize like you can start making a lot of mistakes and it take a long time for you to realize you're making that many mistakes. For us, because we grew so fast, we also our mentality and our kind of like way that we look at the company hasn't changed as fast. So, because of that, we're able to, for example, have and operate with way fewer people. We just had to like really keep going on like building the product as fast as we could. Early stage team and early stage mentality, very intense in time of like work intensity, keeping the speed, which I think is the most important thing for startups is the speed. You're definitely right that sometimes we'll look at the numbers and like two years ago, like before the election, we were making like way less than $10 million a year, right? Now, in a day, we transact way, way more than we used to do in a year, like two years ago, you know, and it's just like just the transaction volume. And it is crazy, like the numbers we're talking about. And we're very grateful for where we are. But we really, really try to keep the mentality on we're still underdogs. Everyone have a lot to prove it to grow.

Speaker 4

I mean, the success you've had has put a bullseye on your back. There, states are coming after you, you know, for being an unlicensed gambling operation. Federal appeals court just ruled that Ohio and Tennessee can regulate Calci through their gambling laws. Like, is that kind of an existential threat? I mean, New York alone is suing you for $36 billion, the state where you're headquartered.

Speaker 3

We are very, very confident analysis. And of course, as you said, the appeals court that we enters, but we also won the Third Circuit. What all of these lawsuits are saying is like each of them has a different legal thesis. The more important part, if you take a step back, is that like the mechanics of how Cal Shi operates in a sports book is completely different, right? And that's why they are regulated different ways. That's why we are federally regulated, right? We are an exchange, which means that you trade against someone else. We don't set the price. We don't set the odds. We don't trade against the users. The users are just trading against each other and we take a transaction fee. What matters the most here is liquidity and making sure that we have like national liquidity right to build upon. Imagine if you have, for example, the New York Stock Exchange, but you could only buy stocks in the New York Stock Exchange if you're in New York. The prices would be significantly worse. It would not be a liquid market. It would just be worse for every participant. And also, the market just wouldn't work well. On the sports book, on the other hand, it operates completely different, right? Like, for example, in the exchange, because we also don't trade against our users, we don't make money when users lose. A sports book is actually completely different. They make money, their revenue is equal to customer losses. The more the customers lose, the more money they make. For us, it's not the same. The incentive is not to make people lose because we don't make money when people lose. Because of that as well, we don't cap our winners. So, you know, if you go to a sports book or a casino, you start making money, they'll make sure that you cannot participate anymore. That's the opposite. We want winners. We want people to come and bring price and we want price competition. And all of those kind of like really, there's no like price competition, right? The sports book has a monopoly on the price and they're going to put their margins on top because like they're having a bad month. So they're going to make the prices a little worse or whatever. And because of that, it's like it, they are very fundamentally different mechanics and very fundamentally different products and they need to be regulated in different ways, which is how the federal regulation for exchanges develop a certain way. And, you know, we're growing a lot because an exchange is a fair, fair, more accessible, more transparent way to trade. You can see all the prices. You can see the competition in the order book in real time. And that's why users like it so much. And I think it's fair and it should be that the consumers at the end of the day pick what's better for them.

Speaker 4

Something like 75% of the volume of your business is sports. And for some users' point of view, it can seem like it sort of serves the same function for them. And, you know, the draft kings and fandals of the world look at you as competition, even if the engine behind operates in a different way.

Speaker 3

Well, the thing is, speculation happens in all financial markets. You know, crypto, stocks, options, futures, there's speculation in all of them. And speculation is actually very important because it drives liquidity, right? If you obviously every market that we're talking about, and it's actually one of the biggest growing parts of Cal Shi right now, is the hedging and kind of small business hedging. And hedging is very important for financial markets. And it is a differentiator from gambling. But speculation is very important. And it happens in every market. And it should happen. And it's fine. There's nothing wrong with speculation, but the mechanics being different really matters. You know, the house always wins. Like, that's not the case of an exchange. And on the DraftKings defendable point, it's actually interesting because Jason, CEO of DraftKings, actually, in their latest earnings, said that they're seeing no cannibalization between sports betting and prediction markets because they are fundamentally different. Users understand they're different and they engage with them in a different way. And because that I think both models can coexist, they are coexisting. And at the end of the day, the users will pick what's best for them. But it's not the same. And I think the users kind of know that.

Speaker 4

You mentioned hedging. I did love during the Knicks NBA championship run, there was a bar here in New York that used Cauchy as a hedge so it could offer free drinks to everyone if the Knicks won. And these are great counterpoints to all the betting talk. Do you look for those opportunities to tell those kinds of stories?

Speaker names from our own diarization · position estimated from where the line sits in the episode
“You can go on TV and say there's a recession tomorrow, and you're going to get a lot of clicks. Everyone's going to watch because you're doomsday and whatever. But it doesn't really matter if you're not right. But on markets, it really, really matters if you're right.” — Luana Lopes Lara, Masters of Scale

The host asked why prediction markets forecast as well as studies say they do. Lopes Lara had explained that money at stake gets people to do research and then compete on price. She is a co-founder of the prediction market Kalshi, so she is describing her own product.

Masters of Scale · 2026-10-06 Permalink → Listen →
Masters of Scale Around 12:24 into the episode
Speaker 3

No, that's a good question. Because we're federally regulated, we don't allow markets on war, terrorism, assassination, and any of that. The reason we decided to extend market, same thing with the Maduro, is that actually there are a lot of different ways that a person can be out of power, right? And an example is Maduro, for example. He wasn't assassinated or anything like that. And you could see like the impact, the clear economic impact that had, for example, in like price of oil. So what we do for these markets is actually we let that market operate. But what we do is if there is an assassination or a terrorism or a case or something like that, what we do is we void every trade. So no one can profit from it. And we kind of like, that's kind of how we draw, we drew the line in this case. I think that the reason we did the reimbursement was actually not because we thought there was anything wrong, but I think that we didn't do a good enough job in the product to explain to users how that voiding would work. And I think that that's what got confused. Now, after this market, we actually have been way more selective with the markets that we list.

Speaker 4

I've seen some Federal Reserve studies that say that prediction markets are more accurate than almost any forecasting method. When money's on the line, people are incentivized to tell the truth in a different way. Like, why do they work?

Speaker 3

If I ask you right now, if you think it's going to rain tomorrow, you might say, oh, maybe it's going to rain. Yes, it's going to rain. But if I tell you, I'll give you $100 if it's going to rain tomorrow. The first thing you're going to do is you're going to open your phone and you're going to open the website like the weather.com. You're going to look outside. You're going to maybe call your, you know, your mom and ask, like, you know, do you think it's going to rain tomorrow? What do you think? And there is. Up their first layer, which is if you're incentivizing people that you will make money if you're right or lose money if you're wrong, they will go out and do research and get more information to bring to the market. So, that's layer number one. And also, why, like, yeah, they're layer number one. Layer number two is that you actually have now competition between these people, right? Like, I went and asked my mom and did all my research. You did the same. And now we are both going to try to compete on the market for the best price so that we're going to match with someone that's willing to trade against us. So, now there's price competition and that price competition, that trading of price competition, really makes the market get to the best forecasted value. That is, everyone in the market kind of agrees that that price is fair. Because if someone doesn't agree with it, they're going to trade and they're going to move the price, right? So, that combination of the incentives for people to bring like more information to the market incentive to make money and the price competition makes that number the best forecast that you can because it's basically everyone that did a lot of research is agreeing that that price is the best one. Um, and you can track it with time, right? Like, because the markets are open 24/7, every second there's some news, maybe that fair value change, and now there's an incentive for someone to come and move and trade to make money. And because of that, markets become kind of efficient and they become the best forecast and the real-time forecast of what's going to happen in the future. You can go on TV and say there's a recession tomorrow, and you know, you're going to get a lot of clicks. Everyone's going to watch because you're, you know, doomsday and whatever. But it doesn't really matter if you're not right. But on markets, it really, really matters if you're right. We actually put out our own calibration study. And what calibration really means is like if a market says there's a 70% chance of something happening, is it actually true that seven out of 10 times something will happen? And the results were very, very, very good. That calibration and prediction marks is very good. And as you get closer and closer to the date or the resolution date, they get even like high 90s on calibration and kind of accuracy.

Speaker 4

Prediction accuracy in the high 90s is pretty darn good. One of the benefits of deploying market dynamics. So, what does Calci reveal about the upcoming U.S. midterm elections? And what about Timothy Chalamet's strange dentist chair ad for Calci? We'll talk about that and more after the break. Stay with us.

Speaker 1

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Speaker 4

Before the break, Kalchi's Luana Lopes Lara talked about what makes prediction markets better and broader than sports betting. Now she talks about election predictions as we near the midterm, plus insider trading surveillance, how Calci is like ballet, and Timothy Chalamet's strange dentist chair ad. Let's jump back in. Election polling has become kind of unreliable. What does Calci's current data say about the midterms? Is that 70% accuracy? Or like at what point does it start to move toward 90%?

Speaker names from our own diarization · position estimated from where the line sits in the episode

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