Практика Shadowing: The Youngest Self-Made Female Billionaire Behind Kalshi - Изучайте разговорный английский по видео

Выберите режим практики

Каждый режим открывает полноэкранную комнату практики.

764 предложений

Если предложения слишком короткие или длинные, нажмите Edit, чтобы их изменить.

Prediction markets, they can be bigger than the stock market

and we think they will be bigger because it actually relates to way more people.

Prediction markets are growing far faster than previously expected.

What do you think it is that's driving this hyper growth?

We always knew that, you know, if we actually made this work, every one of their moms would want to come and compete with us because it's just such a massive market, right?

If you look at our growth this year, we're trading over a billion dollars a week.

Who is trading on CalShake?

A lot of people expect that it's just the Wall Street people and things like that, But actually some of the most profitable traders are people from very, very different backgrounds.

We have like meteorologists that are some of the most successful weather traders out there.

So what would you say to a critic who said that what we're seeing in prediction markets is a bubble?

We don't really spend time thinking about the critics, so.

I'm Sammy Cohen and this is Social Currency, a podcast that unpacks the stories that are shaping business, culture, and the intersection of the two.

Today I'm speaking with a founder who's building one of the most fascinating and for some controversial companies in fintech right now.

Luana Lopez Lara is the co -founder of Kalshi, the CFTC -regulated prediction market that lets you trade on the outcome of real -world events.

And I also have some huge news to share with you all.

Last week, the news broke that Luana is officially the youngest female self -made billionaire in the world.

And I filmed this interview with her right before the news came out, so I am extra excited for you guys to listen.

And if you've seen prediction markets suddenly pop up everywhere this year, Luana's work with Kelshi is a huge reason why.

Kelshi is one of the fastest growing tech companies in the country.

Luana and I get into the stats in this episode and they are very impressive.

But what makes this story even wilder is

that they had to build a regulatory moat the size of a fortress to even get here, becoming the first and only prediction market fully approved by the CFTC,

which Luana tells me was as brutal as it sounds.

In our conversation, Luana gets into the ripple effects of the 2024 election on the business, how they decide which events are tradable, the booming new Labuba market, the psychology of their users,

and why she thinks prediction markets might rival stock exchanges sooner than anyone expects.

This is Luana Lopez Lara's Social Currency.

Luana Lopez Lara, welcome to Social Currency.

Thank you for having me.

I have interviewed so many founders and CEOs on the show, but your background specifically and your experience really stands out to me.

Just to name a few things, and we're going to get into this during the show, but you're a classically trained dancer.

You pivoted to finance and that's where you worked.

And now you're building one of the most complex corners in tech and markets.

So I wanted to call that out.

Thank you.

Pretty impressive background.

Thank you.

And so we're going to dig into it a little bit more.

So you were a ballerina growing up what lessons from the

world of dance do you apply to what you're doing today yeah

and first of all thank you

so much for having me I'm very excited to chat my

sister's a big fan of your podcast in Brazil I'm from Brazil born

and raised it's very normal for kids

when they're like two years old to start doing ballet classes

so that's how I started and from the start I just fell in love with it

and just throughout the years just started doing more and more

and more and more that was in a professional school pretty much training eight hours a day

when I was in high school.

And I think that realistically, ballet is probably one of the things that impacted my life the most and impacted Kaoshi and everything I've done since.

I think that one of the biggest lessons there really has been the discipline side.

Kaoshi has been a very hard company to build in terms of the amount of ups

and downs and years of regulatory battles and things of the sort.

And the discipline that you get from ballet to be able to wake up even with terrible news

and just you have to do it every day you have to go and get your goals done and everything like that.

This helped a lot.

And the other side is like ballet is very good at teaching about the late gratification in a way, which is kind of tied to discipline, but it's like being able to be,

it's going to be very painful and very hard for X period of time.

But the long -term, the vision, what we're trying to build is very important.

And I think this concept of delayed gratification in ballet, a lot of it is tied to like, you're injured, you need to dance anyway.

And how do you deal with like the pain, but actually to not lose your role and things of the sort.

So I think those two things probably what I got the most from ballet.

Yeah, a lot of long term thinking, especially in your space and how long you guys have been doing this.

But I want to back up a bit and really set the tone, especially for someone who's listening to this conversation, may have heard of Kelshi, they don't really know what it's all about.

Let's get the P0 beginner version out there.

And then of course, we'll dive deeper.

But for someone who's hearing about Kelshi for the first time, Can you describe it in the most simplest way?

The thing about Cauchy is the stock market, but for everything.

So in terms you go to the stock market, you can buy and sell stocks.

You go to Cauchy and you can buy and sell what's going to happen in the future, in any future event.

So things from who's going to win an election, you can buy and sell shares of different candidates, who's going to be the top Spotify artist of the year, and things of the sort.

So we're really letting people trade on everything.

I love that definition.

And in creating the company, so you were studying at MIT.

And that's where you met your co -founder.

Can you describe how you first met your co -founder and second, how you went from, OK,

we're we're talking about ideas in different spaces to, OK, we are going to start this company together?

Yeah.

So we met actually in the first year of school.

And a part of it was because I'm born and raised in Brazil.

Tarek, he's actually American, but he grew up in Lebanon.

So all the internationals kind of like bundled together.

So we became friends from the very start

and we have very very similar interests

So we took the same classes we even intern both at Citadel

and a five rings Just a small prop shop in New

York together actually like deciding to start a company was a very together was a very organic thing It wasn't one day.

We woke up and it's like, oh my god, you're my perfect co -founder.

Let's do it It was actually like throughout years of college

We were noticing a lot of behaviors in in finance and things that

we were noticing in common and talking about it and there was a day that we were spending like

hours and hours and hours talking about it in the beginning of our master's

and we were like well

if someone's gonna do it it should be us let's just

let's just go to this hackathon try to start it

and it was very organic because we just were

so in love with the same idea

and we really was like three years of all of our

finance experience building up to this to the idea to to get it was the idea

that pulled us and really was very organic way to start

100

if that makes sense yeah And how old were you guys at the time?

101

We started the company with 22.

102

So yeah, a long time ago.

103

Time flies.

104

That's amazing.

105

And so the world of prediction markets was very different than it is today.

106

I don't know if I can say non -existent, but very different from where it is today.

107

When you were deciding on this is the market that we're going to go after, this is the company that we want to build.

108

What was it like speaking with initial investors?

109

Because now there's so much hype around it.

110

It's easier to raise money in this space.

111

But what was that like?

112

Well, prediction markets themselves are not necessarily a very new idea, right?

113

They've been studied for a very long time.

114

Is this like information markets, markets, a wisdom of the crowds, better forecast the future.

115

All of the ideas have been there for a long time, but no one has actually been able to do it in a regulated way and, you know, in a big, you know, mainstream way.

116

There are two types of investors.

117

There are investors that really want to be like, what are the numbers and what is the traction

118

and all those things and for those investors didn't want to talk to us really

119

but then there was a lot of the other investors

120

that were more like there's a very small chance is gonna

121

work you guys are gonna even be able to launch but

122

if it does gonna be very big

123

and I think that's those are the investors that

124

that we talked to you from the start

125

and they invested in us even before before we got regulated

126

because it was a hard business to invest in

127

because it took us from starting the company to being able

128

to launch a product in the US took us three years without anything

129

so it was very important to get these the support from the right investors from the start.

130

And when you were at the very beginning raising your first round of capital, were you even able to go to VCs or was it Angels?

131

We started the company in Y Combinator, which is this big startup accelerator in California.

132

So that helped us quite a bit because we got the money from YC

133

and at the end of the like demo day, everyone raises capital.

134

So that helped.

135

For a lot of investors, I think when they're thinking about Angel, like Angel checks on like a seed round, they think a lot about what's the background, what's the team and i think that they liked both tark

136

and i so that helped after

137

that we raised a couple rounds to today we're still raising money yes yes i saw

138

that you guys recently raised or announced the raise a month ago

139

or a few months ago right the race was like i think before august

140

so like yeah it was just delayed the announcement

141

but yeah at a five billion dollar valuation yep damn girl okay all right

142

and so you mentioned the regulation piece and so cal she's very unique in the way that it operates, it's CFTC regulated.

143

How difficult was it to go through that regulation process?

144

Honestly, like we look back and we're like, how did we do it?

145

It was it was very difficult because it was it was three years.

146

It was a very binary decision that took us a very long time to get there.

147

Like if we didn't get regulated, the company would be worth zero.

148

And for us, it was almost like very hard, like psychologically to think about.

149

we are you know 22 to 25 years old

150

and like we're betting our entire careers pretty much like all

151

of our friends are going to Citadel they're going to do all these things into this thing

152

that most people say it's lower than 1 % chance it's gonna work

153

so it was very tough on that sense but also

154

because what we're doing is round of questions from the government

155

so the government will say these markets are easy to manipulate

156

they are bad they're bad for this reason they don't fulfill this principle

157

or whatever and we'd have to go back and do the analysis and say like, no, you're wrong.

158

Like, this is why all of your concerns are not real.

159

And send it back.

160

And they're like, okay, out of these 20 questions, we accept the answer to three, we have follow up on 17, and we have another 10.

161

I think a lot of the work we've done at the time really helped

162

and are in the kind of cornerstone of the company too today on the compliance side.

163

But my co -founder likes telling the story.

164

It's like, you think you're like climbing a mountain?

165

and you think that the top of the mountain is like closed and you're like, oh, I can get there.

166

So you keep going.

167

And when you get there, you're like, oh, damn, it's actually like twice as high.

168

And you keep going and it's actually like twice as high.

169

And I actually think that helped, though, because I think from the start, we knew it was going to be three years.

170

I think it would have been harder, but we always thought we were six months away.

171

So it made it a little easier.

172

I actually am realizing, too, as you're describing all of this, a lot of people may not be aware of the differences between the CFTC, the FTC.

173

Can you provide a little bit more background?

174

So the SEC regulates everything to do with like securities trading.

175

So things like stocks and things like that.

176

The CFTC is the sister agency that pretty much regulates everything that has to do with commodities.

177

So events and things like prediction markets are regulated by the CFTC.

178

There are other agencies in D .C that do like consumer protection and things like that, but they're not actually like financial regulators.

179

So there's these main two that are relevant to us and the CFTC is our regulator.

180

And when you finally got that regulatory approval,

181

did you find that users really felt as though this was a step change in perhaps reputational trust?

182

Or I'm curious from the user perspective, what that really means to them?

183

There's a lot of things that help, right?

184

If you think about power users that have been thinking about prediction markets, trying to trade like small experiments and nonprofits have tried to do these things before.

185

For them, it's like it was the first time they saw a chance of their hobby

186

or what they do or what they believe in to become real and mainstream.

187

But for the vast majority of users, it really was like, OK, like, I don't think my money is going to be taken from me because the federal government's regulated.

188

It's regulating them.

189

I can actually access pay with a debit card

190

and access an app and all of those things that make a big difference.

191

Because there have been prediction markets like the offshore type prediction markets that have existed before, but they have so many risks.

192

And I think the other regulation helped is establish

193

that as a mainstream real product in the US that everyone could use in a safe way.

194

And I think it really, really helped, especially compared to a lot of the crypto stuff that people get scammed and things like that.

195

And I think that being regulated really helped establish this different and safe.

196

I think it helps.

197

The CFTC regulation is a point of differentiation, right?

198

When we're looking at other players in the space, because there are other behemoths that we're aware of, right?

199

Pauli Market being the first one that comes to mind.

200

How does the regulation work for someone like them?

201

Because I think for the prediction market, they're also a name that people think about.

202

The way I understand it is Kalshi is the only predictions player that is regulated by CFTC.

203

And so earlier you had mentioned that if you weren't regulated, the company valuation would be zero, right?

204

So can you walk me through how it works and how they're able to do it?

205

I don't want to speak about other players in the space that much, but it's basically the way that we think about it is being safe

206

and regulated is very important for what we've wanted to build.

207

What we want to build is the Everything Exchange, right?

208

It's allowing people to trade on everything that's going to happen in the future.

209

The only way to do that, in our mind, is to have a safe and regulated space.

210

And you see like why so many partners have chosen to work with us from, you know, Robinhood, WeBull, PrizePix, and also like a lot of other folks in the space are choosing to work with us is

211

because we actually have the safeguards and things in place.

212

And in the US, if you're offering contracts and trading to US participants, you need to have a license to do these things and do these things legally.

213

And that's why we think it was a kind of a necessary step for us to achieve our mission.

214

We're not going to be as big as we want to be

215

and have all the players we want trading if we're not a safe space, a safe market.

216

That's why we were like, let's go to the elephant in the room first, which is let's make this thing legal, let's make this thing safe, and then we know we're going to be able to grow it

217

because it's just going to have open a whole new space.

218

So that's kind of how we think about it.

219

I think nowadays the way that we see our future is really about we have the best product.

220

I think we have, as you said, pretty much one of the only viable products in the U .S.

221

And I think that what I tell the team all the time is our goal, we think we have like six months to two years of a lead time.

222

How do we increase that time?

223

What work do we do?

224

What strategy do we do?

225

We need to work harder so that we increase that lead time.

226

And, but you know, the two years become five years.

227

And how do, how do we think about we're reading

228

because we have a better product and our job is to make sure we have a better, better, better product.

229

And from a brand awareness perspective too, I am seeing Kelsey everywhere right now.

230

I follow this Instagram account.

231

That's like, they do memes that they do a bunch of stuff called kale salad.

232

And I see, and I see, I see Kelsey on there all of the time talking about, you know, how Kelsey is doing what you're doing.

233

And I think from a top of funnel brand awareness perspective, in my opinion, Kelsey is winning right now.

234

So it's really exciting to see because obviously you've done all of this work on the regulation side.

235

You've put literally countless meetings to get this over the line.

236

And now actually that you're there, it's...

237

Yeah, totally about market penetration.

238

It's interesting because we've really started putting a lot more focus on on marketing.

239

I think in marketing like a year and a year and a half ago.

240

Mm -hmm.

241

And we've been learning so much about it.

242

And it's just it's just marketing is very fun to think about it.

243

Like, how do we think of like strategy, like which demographics we want to go after?

244

Like, we are very lucky that our product is very easy for us to create markets that are relevant to everyone.

245

Like today, we just announced we actually have labable markets now.

246

How high the prices are going to go and things of the sort.

247

And like from Dancing with the Stars to things like sports,

248

to things like elections, we really have such a broad range of markets that we can really advertise and market to everyone.

249

And almost at every point in time, they're very relevant markets.

250

So for us, it's really building that operation, that almost marketing operation of like, what's relevant today?

251

What's in the news?

252

How do we target?

253

How do we market it?

254

And kind of having that motion every day.

255

And we're going to get into some of the areas that you can trade on in Kelshi.

256

But since you've done all this work, do you envision, is it something that your team ever talks about?

257

The new players that have seen you go through, they know that regulation is now allowing this.

258

Are you starting to see all of these competitors, even though they're probably tiny, crop up now?

259

Yeah, we always knew that, you know, if we actually made this work, everyone and their moms would want to come and compete with us because it's just such a massive market.

260

Right.

261

If you look at our growth this year, we're trading over a billion dollars a week we want competition.

262

Let's go and make this market as big as we can be.

263

And so, yeah, there's a lot of people coming into the space from very established players to smaller players.

264

But what I told you is we really focus on product.

265

We just need to have the best product, the best liquidity.

266

And I think that the rest and the best marketing, as you said, and the rest will go from there.

267

Yes.

268

And just yesterday, it sounds like there's a lot of news popping up for Kelsey.

269

Just yesterday, there was an article in Bloomberg that said prediction markets are growing far faster than previously expected,

270

and they will rival stock exchanges in just a few years.

271

First off, like, moment of silence for that.

272

That is crazy.

273

I know.

274

It's insane.

275

Do you guys envision that the market would grow that quickly?

276

What do you think it is that's driving this hyper growth?

277

Now we're seeing the result of five, six years of work we've been putting to really seeing this hit mainstream now with South Park mainstreaming us

278

and the volumes we're Prediction markets, they can be bigger than the stock market.

279

And we think they will be bigger than the stock market because it actually relates to way more people.

280

If you sit down at dinner, you're talking about Costco financials or, you know, what's going to happen to the CEO of this company.

281

You're not.

282

You're talking about, you know, what happened in culture, what's happening in health.

283

Are we going to see another pandemic?

284

He's talking about these things.

285

And what prediction markets are is a way to actually get information and price all these things about the future.

286

And that's why we think it's going to be a lot bigger.

287

Like we think that like the the 2020 election should be bigger than a trillion dollar market

288

And it's just a matter for us of like how do we keep growing

289

and make sure we're building the systems building the engineering and all of that To to get there.

290

We always say that we're biased

291

because this is our our child This is like we want

292

we want prediction markets to be the biggest thing it can be but we really

293

We really don't see a way and it's not as big

294

or not bigger than the stock market if that makes sense

295

So what would you say to a critic who said that because all of this growth is happening so quickly right now, that what we're seeing in prediction markets is a bubble?

296

What would you say?

297

I think it's just a bad way to look at it.

298

I think people look at anything that's growing and there's always someone that wants to be like, oh, this happens with AI.

299

Happens with every very, very big technology that is going and growing a lot.

300

There's going to be critics trying to claim the other side.

301

I think the benefits to the world from prediction markets, we saw it in the elections, we're seeing in so many places, is here to stay.

302

And more and more people are mentioning and using and trading these markets.

303

We don't really spend time thinking about the critics.

304

And actually, on that note, because I saw this is actually from the Calci blog.

305

We've already talked about this, but Calci's become one of the fastest growing tech companies in the U .S

306

and the fastest growing company outside of the AI industry.

307

In the past year alone, trading volume has grown 200x, and this is probably a little bit outdated.

308

And user base has grown 20x.

309

Kalshi now accounts for over 60 % of global prediction market activity, despite previously being confined to the U .S.

310

I read that, and I think that was the moment for me where I was like, this is real, it's coming, and it's going to, I think,

311

infiltrate back to what you said around what people are talking about at their dinner table, right?

312

Right.

313

Because this is something that people feel a lot more, I think, also emotionally connected to.

314

Even if you're not in the finance space, I think there's an emotional level around being able to make these predictions around everyday events.

315

Right.

316

So previously, Kelsey was just in the US in terms of what could be predicted on.

317

What international markets are you the most excited about now?

318

The point is that everyone is an expert on something, right?

319

And I think that that's the difference.

320

You're in the dinner table and you're talking about culture and pandemics and things of the sort.

321

But it's not just about talking about it.

322

It's also because a lot of people have deep knowledge about things that they actually can come and monetize.

323

If you think about Uber, you could go and, you know, you know how to drive a car.

324

So you can make money driving a car or Airbnb.

325

You have a house.

326

You can become a host.

327

With us, really, it's like what prediction markets will get that big is because everyone, any knowledge they have, any hobby they have, they're able to turn their passions into profit.

328

And really, like, if you think you're an expert on something, you can actually monetize that.

329

And we have so many examples of people that are doing this.

330

There's this one specific user that Ariana Grande is superfan.

331

That's actually, like, the best way to describe it is like an Ariana Grande superfan.

332

I heard about Couch because of the elections, wasn't very interested in the elections, but found out we had music charts and, you know, what's going to top the charts and started,

333

you know, trading and making money and learning about markets and has made over $60 ,000, paid back all their student loans.

334

Now their new girl is like making enough money to buy a house.

335

That is actually available to everyone because we have so many markets and everyone can make money on it.

336

And that's the other side of making it so broad that is important.

337

It's the topic of conversation, but also that like we're just democratizing or opening access to ways to make money to a lot more people.

338

But yeah, back to the international question.

339

So we are excited about a lot of different countries.

340

And I think a lot of what we're doing now is actually, you know, mapping out the world and what partners we want in different countries.

341

I think there's different countries with different strategies and things like that.

342

It's not our number one focus.

343

Our number one focus is still winning the U .S market and growing here.

344

We are going to be way more aggressive about growing internationally in the coming months and years.

345

I know we spoke a little bit earlier about the demographics of people who are using it, but I wanted to actually double click into this around the ages.

346

Are you seeing that age dispersion across really anyone from Gen Z to boomers and above?

347

Yeah, pretty much across the board.

348

We actually have a lot of users that are like obviously on the 20 to 30 range, but also a lot of users that are like 70

349

and are thinking about it as risk mitigation and things of the sort.

350

So it really has been like across the board.

351

Is it mostly men now?

352

I think it's over 50 percent men.

353

But we actually have like a lot of women in the platform.

354

It's very intuitive to get started.

355

And I think that that it's very transparent and safe.

356

And I think that the women appreciate that.

357

And I think we have a lot of markets that women are excited about and like like trading as well.

358

So compared to other folks in similar industries, we're way higher percentage, but I think men are still over 50%.

359

And you mentioned briefly the election.

360

So that seemed to be the watershed moment for your company.

361

Yeah.

362

So how did the entire election cycle change your business?

363

The elections actually have an interesting, a funny background story because I told you it took three years to get regulated.

364

And when we got regulated and launched, there was actually still another elephant in the room, which were the election markets.

365

and we worked with the CFTC for one to two years

366

and they were saying no no no no no we had like big comment periods

367

which is normal for when they asked the public to opine

368

and everything was very positive but the CFTC did not let us list it

369

so we had to sue them

370

because we knew we were right on the law like legally you're able to offer

371

and trade election markets so we had to sue our own regulator

372

and we won the lawsuit actually one month before the election

373

and people thought it was like a partisan thing and it really wasn't.

374

You know, all the judges decided that said we were right on the law were Democrats and we have support.

375

It's always been a bipartisan thing that everyone kind of supports these markets, but the CFTC at the time.

376

And we were able to list these markets and there had been a ban for over 100 years in the US.

377

Election markets were legal

378

and they on election day used to be bigger than the stock market trading volume back in like 1920s

379

and then with the great depression they bent election markets with a lot of other things

380

and we were last year it would bring them back a

381

hundred years later the last two weeks we had like over

382

two billion dollars traded millions of new accounts number one in the app store

383

and he was reading this like vindication moment

384

because a lot of the critics again we're saying

385

that like would destroy democracy it was very bad for for everyone

386

and things like that and actually if you look at what happened

387

markets were the best way to forecast what was going to happen.

388

The entire time we were saying Trump was around 65 % chance of winning, while the polls were saying it was 50 -50.

389

And it was that insane moment that we saw, see the value of these markets are here.

390

You can see why the markets were better at forecasting what was going to happen.

391

After the polls closed on election night, it was around 30 minutes, it was like 6 .30 or something,

392

that Trump was already at 95 % chance of winning because of early votes.

393

It really was, even in the media, you see this kind of change in behavior, how they were talking about the markets.

394

They were very skeptical before, then they were like, wow.

395

This is actually valuable.

396

And I think in this election cycle this year, same thing.

397

Mondani was quoting the Couchy odds on stage in multiple rallies and talking about them and everything.

398

And it's just great to see it as kind of mainstream now in the political world to use these markets

399

and use these odds to do it.

400

And I think that every growth we've had is kind of like that election market, being able to list it and seeing what happened after was just so important for us.

401

I think on that note around the elections, I believe that Kelshi is actually going to take out the voter polling surveys.

402

You know, before an election, they'll say like, oh, the, you know, the surveys are saying blah, blah, blah.

403

They're always wildly inaccurate.

404

It's like, who is doing these surveys and who are they asking?

405

Do you know anyone that's ever answered?

406

I don't.

407

No. And obviously we'll get to the Mamdani numbers and all of that.

408

Going away from elections, But how does CalShit decide which events are even tradable in the first place?

409

We try to list as many markets that users suggest and ask for as we can.

410

Obviously, there's a very strict compliance procedure to make sure the markets aren't easy to manipulate, they aren't on prohibited categories, things of the sort.

411

But we really tend on like, it's better to have markets.

412

Because even if it's fewer people, like reliable futures, maybe not that many people are interested in it,

413

but it's still valuable information for a group of people to trade and get the price and see what's going to happen.

414

We have a market seam in house that pretty much writes the legal contract that is the

415

base of every one of these markets, writes them down and passes through compliance and all of that.

416

There's three things that define great markets.

417

The first one is disagreement.

418

Is it something that people actually disagree on?

419

The second one is volatility.

420

Is there actually going to be news that move prices up and down?

421

And the last one is like, are these actually important questions, right?

422

If you think about a lot of markets that we had that were very big, like will TikTok be banned in the US?

423

It was actually a very important question.

424

There was a lot of disagreement on whether it should or should be banned or whether it would be banned.

425

And also a lot of volatility.

426

And it's a very important question for us to price and have like a forecast of what's going to happen.

427

So we try to list as many markets as we can.

428

But these are the three kind of categories that were like, if the market hits these three points, we need to have it.

429

One key differentiator as well for CalSHE is the world of sports.

430

So I'm sure that has been a very, well, first, very successful for CalSHE, the fact that you can make these predictions on sports.

431

But what pushback have you gotten from the sports world?

432

Because I'm sure especially the sports betting world is thinking, damn, I wish I was CalSHE now.

433

That is a good question.

434

I think that for us, it's important to have sports markets.

435

And the way that we frame new markets again is

436

because we want to have markets on everything and we want everyone to find markets that they are interested in.

437

And there's so many people that are interested in sports

438

and there's just like another demographic that we can open the platform to.

439

In terms of pushback, like, look, we operate like a stock market, right?

440

We're not a casino.

441

You know, you're not trading against, you're not betting against Scalshy.

442

You're not trading against Scalshy.

443

We just facilitate trading between different people.

444

And that's why we are federally regulated and all of that.

445

There's a lot of problems with the sports betting model.

446

I think we're very different from that model.

447

I think there's a lot of almost unquestionable problems with that model, which is there's no fairness in price.

448

You only have one, like the house setting the odds for you, and there's no competition on the price.

449

There's no fairness or transparency on the price.

450

You don't actually know if the price that someone's getting is different from yours and things like that.

451

After that, if you start winning money, they can cap you, and they can be like, you can't participate anymore.

452

There's a lot of unfairness in the way that sports betting works, than I think exchanges are better models for.

453

But again, we're just fundamentally different, right?

454

We function more like a stock market.

455

Sports is just another category we're excited to expanding to because we want people to be able to train on anything.

456

There's a lot of experts on sports out there.

457

Oh, yeah, yeah.

458

Outside of elections, is that one of the most popular categories?

459

Yeah, for sure.

460

Sports are very popular.

461

Elections and things, politics, very, very popular.

462

We actually have markets on mentioned markets that we call them, which is basically what people are going to say in different events.

463

I have also been very very popular entertainment

464

and culture have been growing a lot Now have markets on like reality TV and things of the sort,

465

but also like charts Oscars Grammys all of that stuff I would say those are probably the biggest categories, but we have everything from like, you know

466

Like research papers being published

467

and things of the sort to to a bigger market Are there any topics or categories that you wouldn't list?

468

We don't do anything related to terrorism assassination or all of

469

that stuff It's we wouldn't do it anyway and it's also not allowed to be done in the US.

470

There's clear regulation on that and also things that like one person can really impact the results.

471

So for example, we have markets on hurricanes

472

or other type of natural disasters because humans cannot impact a hurricane happening in any way.

473

But we don't have markets on wildfires, for example.

474

because that's easier to manipulate.

475

So that's kind of how we draw the line there.

476

Clear categories, we never go even close.

477

And otherwise, just are these important questions, that information is actually valuable, and whether a single person can impact the outcome, then we don't list them either.

478

What's so interesting about this, and as I was thinking about the differences between traditional stock market investing and something like Kelsey, everyone's an expert in something, right?

479

Maybe I'm an expert in Libuboos.

480

I'm obsessed with Popmart.

481

I know all of the different varieties.

482

I'm not, but let's just say hypothetically.

483

And then you can be this, like, as close to the foremost expert in a space.

484

And then you can actually create some value out of your expertise when you come to Kalshi.

485

And that's exactly, you can't really do that in any other space, right?

486

Exactly.

487

For example, Ariana Grande's super fan.

488

That's exactly what happened to him.

489

But also, I guess I'll ask you a question.

490

Who do you think is one of the most profitable traders on inflation?

491

Oh, gosh.

492

Profitable traders on inflation?

493

You've stumped me.

494

I have no idea.

495

Right.

496

It's actually a news junkie from Kansas that has never traded, you know, financial markets, any of that before.

497

And he just reads the news, reads like all everything around it, and he's been able to, you know, beat the markets trading inflation for the past year.

498

They've made like millions of dollars doing that.

499

And it's also just like there is the aspect of, you know, everyone can be an expert in something and everyone is an expert in something.

500

And this is really a way for you to monetize it.

501

And I think a lot of the demographics behind who's trading on CalShake is actually very surprising to a lot of people.

502

OK, so I need to hear more about that.

503

Who is trading on CalShake?

504

It's everyone.

505

And I think that that's kind of like the crazy thing, because a lot of people expect that it's just the Wall Street people and things like that.

506

But actually some of the most profitable traders are people from very, very different backgrounds that have just been like, this has been my hobby for the past X number of years.

507

And now I'm going to find a way to monetize.

508

We have like meteorologists that actually have are some of the most successful weather traders out there.

509

There's also a lot of people that use the markets to see how good they are or something.

510

So it's almost like a validation of, OK, I think I'm good at music or I think I'm good at politics.

511

So I'm actually going to use the markets to validate if I'm actually correct about a lot of things, which is another use case.

512

Our most successful traders come from a very, very wide variety of places and backgrounds and everything.

513

That's interesting.

514

And also, I think, empowering, too, because people feel, and I'm speaking for myself, I feel intimidated by the idea of day trading, right?

515

Because you have to really be up to date on the latest and greatest that's going on with the company.

516

Right.

517

And it's nice to know that your expertise can help you in other ways.

518

The stock market is very, very, very competitive, right?

519

If you think about it, there's all these hedge funds and everyone trading.

520

It's very hard for you to actually have a winning strategy over the long term.

521

But with Couch, we have so many markets that you can really like a lot of different strategies, like people that have full -time jobs are actually two jobs.

522

They're able to have strategies that they are like trading very long -term things.

523

So then they actually don't need to be like actively monitoring everything.

524

And it's just because it's a new space, there's more opportunity to make money.

525

And a lot of like new funds are starting to trade on couch and things like that.

526

There's a couple of people trading certain things.

527

So I think there's more opportunity on that end too.

528

We've talked a lot about these big moments

529

that bring a lot of people to the platform because they want to weigh in.

530

What have you seen from the user behavior standpoint around these big macro events?

531

Have you seen anything interesting that surprised you?

532

People think that very big events are going to have bias in some way or another.

533

And what we've realized is that like, and what research has said as well, is that there is no bias in the markets.

534

And that I think is very interesting for us to see, because if you are biased in one way or another on like this party or this team or something,

535

there is just money left on the table for sharper traders to come and bring the mark, the price back to what a fair value is.

536

So the market self -corrects to a fair value very quickly.

537

It's a very common misconception that these markets can be prone to bias

538

or manipulation when actually all the research points to the other side.

539

And they're actually less prone to any of this than the very big markets that everyone talks about, like the stock market and things like that.

540

On the potential to manipulation point that people talk about

541

that I think is interesting on user behavior is that folks talk about how, oh, if there's one piece of news, it's going to really move the markets and things like that.

542

And there was a very interesting point on this last election that Decision Desk HQ, which is a great platform.

543

We love them.

544

You know, everyone makes mistakes.

545

They called the Seattle mayor election too early to the wrong person.

546

And that didn't move the markets at all because the markets were, you know, they are trying to price incorrectly price the future.

547

So even something at that size doesn't actually manipulate the markets.

548

So I think a lot of the like disconnect there is

549

that people think these markets are more prone to bias and manipulation than they are.

550

They're very, very resilient because people are putting money.

551

where their mouth is.

552

And if you're putting money where your mouth is, you're incentivized to do research, to think more rationally about what you think is going to happen and all of that.

553

And then it becomes a way better forecast of what's going to happen in the future

554

because people are putting money where their mouth is.

555

How do events with very asymmetric outcomes, like a catastrophe scenario, right?

556

You said that you can predict something around a hurricane or some kind of natural disaster.

557

How does that affect risk or liquidity on the platform?

558

The risk part of these contracts is what we actually see

559

a lot of people do on Calashita different from making money on what they know

560

and things like that is people actually hedging concerns that they have about the future.

561

Hurricane is a great example, but another great example is student loans.

562

There was that forgiveness or forbearance at the time, and we actually saw people buying that, buying that as a hedge in a way that like,

563

if the Supreme Court would take down student loan forgiveness, they would get paid and they could use that to pay their student loans.

564

Oh, wow.

565

So you see a lot of people actually using prediction markets

566

as a way to mitigate risk in their own lives on top of getting information.

567

Hurricane is another example that we see a lot of people being like, well, my insurance has massive deductibles and there's all these issues.

568

I live in Florida and they actually buy prediction markets so

569

that if they do need to evacuate and there's a high deductible,

570

they can use the winnings from the market to cover their deductibles or cover their evacuation costs and things like that.

571

So it is a very good risk mitigation tool for a lot of people.

572

In the individual level, also, a lot of companies are using it from the government shutdown.

573

There was this big startup called Arrived, actually, that used prediction markets on the government shutdown length to hedge a lot of the risk

574

because they work with regulators that were just not working for so long.

575

And there was a lot of delay in the roadmap.

576

Risk mitigation, actually prediction markets are a great new tool for risk mitigation from businesses and individuals across the board.

577

We're seeing that a lot.

578

In terms of liquidity, after having a market on a certain topic, liquidity is the most important thing.

579

And right now we're the most liquid prediction market by far.

580

And it means that you're able to buy a big size of what you want.

581

So if you want to buy, I don't know, Gavin Newsom, when the election, you buy like $1 ,000 or $10 ,000.

582

And it's actually a lot of our focus on how to make the long tail of markets very, very liquid.

583

So we have a lot of different market makers

584

and we have a lot of retail market makers like day traders like I talked about.

585

All they do is actually provide liquidity on these markets and things like that.

586

For long term and kind of asymmetric markets like you mentioned, we also give interest on the positions you're holding.

587

So if you buy something at like 1 % or 2%, the other person that's locking in 99%, they're actually getting interest on that money.

588

So that helps.

589

All right.

590

So now we're going to go to some industry hot take questions.

591

All right.

592

So bring your hottest takes.

593

So what is your hottest take on how people misunderstand prediction markets?

594

I would have to say back to the to the bias

595

and manipulation point that I think it's one thing that's very funny that we see is whenever, for example, there's an election.

596

Whoever is ahead on the election really likes the markets and who's not ahead thinks the markets are being manipulated.

597

It goes from like the presidential election on one side to like, for example, the New York election on the other side.

598

And I think it's just there's a lot of coping going on, if that makes sense.

599

And people try to blame the markets versus looking into their campaigns and what they're saying and things of the sort.

600

What category of markets will explode in popularity within the next five years?

601

I would have to say the entertainment markets.

602

They are growing a lot and we're very excited about them.

603

And they have such a broad range, right, from like music to movies to video games.

604

I think they're going to be very, very big.

605

Prediction markets reveal how people think, obviously but are there any biases

606

that we haven't talked about in terms of how people use the platform that you think are super interesting?

607

There are people trying to do research right now to see

608

if there's a bias on yes versus no and who's actually buying more yeses versus more nos.

609

I don't think the research is done yet

610

but I'm very curious to see what are the results of

611

that research there and who what demographic is more biased to taking a yes versus a no

612

but nothing comes to mind outside of that research right now.

613

Okay.

614

And we've talked a ton about CalSHE as a business, operationally how it works, the larger industry.

615

But I want to ask a few questions about you as a founder and leader of this massive company.

616

With all of the very high highs, the very low lows, especially as you were working to get the regulation over the line,

617

how do you personally manage that and really handle the stress of entrepreneurship?

618

Yeah, it's a great question.

619

I really think for me, it's like the support system I have.

620

It's my family, my fiance, my parents, my sister, my fiance, my dog are always there for me.

621

And I think that that helps a lot.

622

A very hard thing is that you need to be there for the team and be like, we're going to figure this out and we're going to win this.

623

Even if you're upset about something and you're questioning things, the amount of times that I was being very upset about something, I just called my fiance.

624

I was like, can you just come walk around the block with me and things like that so I can relax?

625

And then he goes.

626

And I think the level of support I get from these four people is just insane.

627

And I wouldn't be here without them.

628

From a founder perspective, because I talked to so many entrepreneurs, CEOs of companies that even if their companies are doing massively well,

629

there's always something that keeps them up at night with their business?

630

Is there anything right now that's keeping you up at night?

631

For me, it really is how can we build the best team so that we can keep, not just keep our lead, but increase our lead.

632

That's what's in my mind.

633

It's like, if we think we have six months to two years ahead of everyone else in the space, who are the right people we need to hire?

634

And what is our strategy to make that three, four, five years so that when people blink, they're like, it's impossible to catch up to Kalshi.

635

And I think it's just these questions.

636

It's building the right team and having the right culture, execution, and strategy in place so that we can extend that.

637

And hiring people to join your team.

638

Also, it's such a new space.

639

It's moving very quickly.

640

When you're growing your team, I mean, you're also growing across everything, right?

641

Marketing, the behind the scenes operationally.

642

Of course, I would imagine you also have a pretty large team that's actually on like engineering slash data science side.

643

Yeah, a lot of you.

644

Yeah.

645

Yeah.

646

Yeah.

647

And one strategy we've used is like, when we're hiring for a specific team, we find the company that is best at that thing that we're doing.

648

So what is the best company at design that we really look up to?

649

How do they hire and build the team in that department?

650

So how do they actually structure and hire people for design

651

and try to copy what they're doing and bringing people sometimes from that place?

652

And I think a lot of different teams in the company actually mimic different structures from, we want engineers from Wall Street.

653

So how do they actually hire these engineers?

654

What background they look for?

655

What structure?

656

What incentives versus a design team versus a marketing team?

657

So you probably see if you look at at Kaoshi employees

658

that different teams are kind of look like they're a little bit mimicked to different Companies, but I think that we just have to learn from from people

659

that did better than us Have done it very well in the past

660

so that we can kind of learn from their learnings

661

and avoid the similar mistakes and and go from there so

662

that a lot of what we do is like study very good companies

663

and see what their best teams are and what actually made this company very good.

664

And then what's the best team?

665

How do we mimic it?

666

How do we learn from that?

667

I think more people need to be doing that because I think people will study companies from a holistic level,

668

but I loved how you broke it down of you'll actually go to the function that you need.

669

So design, you'll go to the best design agency.

670

And that's a really cool way to look at it.

671

And I think more companies should structure their hiring process like that?

672

It's actually not hard to see the difference, right?

673

If you see like companies that are more design driven, you see there's going to be like a creative department with creative directors

674

and there's like very clear programs and design is like kind of an independent part inside of the org.

675

It doesn't report to product or marketing.

676

And other companies that you think are worse than design actually is just there's no design team, they're all embedded in other, there's no coherent design culture.

677

And there's all these things that if you actually just study specific companies and how they structure their best teams, you can learn and kind of like leapfrog a lot of possible mistakes.

678

Yeah.

679

Okay.

680

So we're going to the questions I ask every guest.

681

All right.

682

First is, can you share a system that you have in place that benefits your career or business?

683

And it can be truly a system for anything.

684

I operate better if I have an extremely structured day and things from like the time I eat, the time I wake up, the time and days I go to the gym

685

and like even at work having meetings in a very specific like morning versus the afternoon

686

and things like that because I think

687

that taking a lot of the decision making

688

and randomness out of the day lets you focus on on kind of like deep thinking that you need to do.

689

And it's funny, my co -founder is the opposite.

690

He really like cannot do well with routine or structure or anything like that.

691

So we're very different in that way.

692

But for me, it's like it's very clear

693

if I'm in the office in New York and having my day structured as I want, I'm like infinitely more productive.

694

So the next question comes from the social currency corner where I get your input on a trend

695

or story that's impacting business and culture.

696

And so we've already brought him up.

697

But the Mamdani of it all for Kelshi was a massive moment.

698

Yes.

699

Kelshi was being being spoken about from Mamdani himself.

700

The voters before the election results were were announced were also referencing Kelshi.

701

So my question for you here is,

702

do you think that there's any level of almost like a self -fulfilling prophecy when you have results?

703

Because you can see on Kelshi how things are looking well in advance of the announcement.

704

So do you think that there's any element there where it just kind of then convinces not on the on your side, but on the voter side where they're hearing, oh, well all right, he has a 90 % lead,

705

like, guess, I guess I'm not even going to go to the polls today.

706

It's an interesting question because you can actually argue for almost both sides, right?

707

You can argue if you're a Mondani voter, you're not going to want to go because it's a 90 % chance also.

708

So you can actually argue that, like, if you were a Cuomo voter, you would be like, oh, he's not going to vote, like, win anyway, why am I going to waste my time?

709

But you can also make the argument if you're a Mondani voter and you're like, there's 90 % chance it's going to win, why would I even go?

710

There's been a lot of research that proved that no, there actually is no impact.

711

People don't change their votes.

712

People don't do these things because of prediction markets.

713

They function in people's heads or like how they interpret future very similar to polls.

714

Right.

715

And I think that the difference is they are similar to polls and bringing information, but they're better.

716

They're better than polls.

717

On the other point, it's like you can argue for a lot of different things.

718

Like Mondani said, you know, my odds are over 90 percent.

719

But there's been elections in the past that actually Elon Musk was like, guys, it's really, let's everyone go vote because there's a 10 % chance and we need to win.

720

So actually he was using it on the other side.

721

I think it's just very important for the public to have access to unbiased information about the future

722

and kind of not polarized and, you know, by different news sources and things of the sort.

723

And that's what the function that the markets really bring.

724

So it's like better data about the future kind of bringing better than polls.

725

All right, let's end with a listener question.

726

So this question comes from Julia.

727

Could prediction markets actually become a tool that companies use internally, like forecasting product launches, revenue targets, or even whether a marketing campaign will work?

728

Absolutely.

729

And there's actually quite a few companies that try to do this.

730

I don't know if I'm right, but I think Google actually ran prediction markets internally.

731

I don't think they did with real money, but they used to do it to forecast different release dates and things like that.

732

We also use them at Kalshi.

733

Is this going to be released on time or not?

734

We actually do markets on a lot of things.

735

It's almost like a way to summarize a lot of what we're talking about, because you can see if you have your team and you run these markets,

736

how the bias is going to go down.

737

Even someone's like, oh, we're definitely going to meet this target.

738

You're like, OK, are you actually going to put money in the line?

739

We're going to we're going to write it down.

740

You're going to have this position and we're going to see what's going to happen.

741

And you see the kind of polarization go down.

742

It's like, oh, but maybe this external partner is going to be delayed here or things like that.

743

And you just see this kind of decrease in polarization and people are more rational about things.

744

So I definitely see that happening.

745

Wow.

746

Okay.

747

Well, that is a great note to end on.

748

Luana, thank you so much for coming on today.

749

Thank you.

750

Thank you for having me.

751

I'm really excited for my audience, especially whoever hasn't checked out Kalshi to definitely open up your phone right now and go explore because this is the future,

752

whether or not you're participating in it or not.

753

My audience is really excited about being on the cutting edge of whatever's happening in business and Kalshi's leading the way.

754

So thank you.

755

Well, thank you so much.

756

Thank you so much for listening to today's episode of Social Currency.

757

I've been wanting to launch this show for so long, I can't tell you how excited I am to do this.

758

And how thrilled I am that you're actually here listening.

759

It means the world to me.

760

If you liked what you heard today, please rate and review the podcast, because it massively helps to support the work I do to bring the show to life.

761

And if you want to keep up with the hottest business lore in real time, follow me on Instagram at sammycohentalks, and subscribe to my newsletter,

762

Social Currency, which is linked in the show notes social currency is a production of social currency media

763

and money news network the podcast is hosted

764

and executive produced by me sammy cohen social currency is produced by the money news network team see you next time

Скачать приложение

Всё для свободной речи

ИИ-оценка произношенияОценка каждой фразы

Практика IPAОсвойте каждый звук

СловарьСоберите свой словарный запас

Игра со словамиУчитесь играя

Сканировать QR

Download on theApp Store Get it onGoogle Play

FOR YOU

О данном уроке

В этом уроке вы познакомитесь с интервью Луаны Лопес Лары, основательницы платформы Kalshi — первой и единственной прогностической биржи, одобренной регулирующим органом CFTC. Вы научитесь понимать разговорный английский в контексте бизнеса, технологий и финансов, а также проанализируете лексику, связанную с рынками, инновациями и личным опытом предпринимателя. Практика будет включать в себя работу с интонацией, темпом речи и специфическими терминами, что поможет улучшить навыки аудирования и говорения.

Ключевые слова и фразы

Prediction market — Прогностический рынок (рынок, где торгуются контракты на исходы событий)
Regulatory moat — Регуляторная преграда (защита компании от конкурентов через сложные лицензии)
CFTC — Комиссия по товарным биржам и товарным контрактам США (регулирующий орган)
Hyper growth — Гиперрост (экстремально быстрое развитие)
Discipline — Дисциплина (ключевой навык, который Луана переняла из балета)

Советы для практики

Этот диалог отличается естественным темпом и эмоциональной окраской, поэтому идеально подходит для shadow speech (техники повторения за говорящим). Вот как практиковать:

Сначала прослушайте отрывок длиной 10–15 секунд, затем остановите и повторите его, копируя интонацию и паузы. Особое внимание уделите фразам, где Луана переходит от личных историй к бизнес - аспектам (например, о балете и дисциплине).
Обратите внимание на сокращения и разговорные формы, такие как "it's just such a massive market" или "we don't really spend time". Эти выражения часто используются в повседневном английском, и их повторение поможет сделать речь более естественной.
Используйте shadowing site для записи своего повторения и сравните его с оригиналом. Это поможет заметить различия в темпе и акцентировке.

Практика разговорного английского с таким материалом не только улучшит ваши языковые навыки, но и познакомит с современными трендами в бизнесе и технологиях. Не бойтесь повторять сложные фразы — дисциплина, как и в балете, приведет к результатам!

Грамматика в этом видео

Конструкции, которые говорящий использует чаще всего, с точными словами из видео:

Конструкция	В видео
Present Perfect Continuous have/has been + -ing — действие началось раньше и продолжается	have been doing · have been thinking · we've been learning
Условные предложения if + предложение, will/would + глагол — условие и его результат	if the Supreme Court would take
«Used to» used to + глагол — прошлая привычка или состояние, которых больше нет	used to be · used to do
Present Perfect have/has + причастие прошедшего времени — прошлое действие, важное сейчас	you've seen · have interviewed · I've done

Что такое техника Shadowing?

Shadowing — это научно обоснованная техника изучения языка, изначально разработанная для подготовки профессиональных переводчиков и популяризированная полиглотом доктором Александром Аргуэльесом. Метод прост, но эффективен: вы слушаете аудио на английском от носителей языка и немедленно повторяете вслух — как тень, следующая за говорящим с задержкой в 1–2 секунды. В отличие от пассивного прослушивания или грамматических упражнений, Shadowing заставляет мозг и мышцы рта одновременно обрабатывать и воспроизводить реальные речевые паттерны. Исследования показывают, что это значительно улучшает точность произношения, интонацию, ритм, связную речь, понимание на слух и беглость речи — что делает его одним из самых эффективных методов для подготовки к IELTS Speaking и реального общения на английском.

Техника шедоуинга: читать полное пошаговое руководство →

Практика Shadowing: The Youngest Self-Made Female Billionaire Behind Kalshi - Изучайте разговорный английский по видео

Выберите режим практики

Скачать приложение

Рекомендуемое видео

This 25-Year-Old Built a 2-Year Moat Nobody Can Bet Against | Corgi, Nico Laqua & Emily Yuan

What Chrishell Stause Has Learned From Million Dollar Deals | Richer Lives | Episode Four

Trade, tech and geopolitics: what you need to understand about China today

KSI Accidentally Exposes His Crypto Scams

A Tale of Two Markets

Private Credit: The Secret Industry Taking Over Wall Street

Everything we learned in 29 minutes at Harvard Business School (part 1)

Shark Tank Australia | 21-Year-Old Entrepreneur Stuns The Sharks With Her Huge Monthly Sales

Pavel Durov on manifesting reality and hard work | Lex Fridman Podcast Clips

CEO of Addepar Eric Poirier on Lesson from $6 Trillion in Assets

5 Stages to Getting Rich in 2026: Which One Are You?

Why Chinese Bubble Tea Chains Are Brewing Billions

О данном уроке

Ключевые слова и фразы

Советы для практики

Грамматика в этом видео

Что такое техника Shadowing?