Episode 39: Jeff Yass - Founder and Managing Director of Susquehanna International Group

This week on generating alpha in an episode unlike most, I'm joined by Jeff Yas, founder of Saskahana International Group, one of the most successful trading firms in the world. Jeff is a

legendary figure in finance known for applying the principles of poker, probability, and decision theory to markets. Over the past four decades,

markets. Over the past four decades, he's built a global powerhouse, quietly operating behind the scenes of Wall Street, trading everything from options to crypto, all grounded in mathematical

precision and rational thought. He's

also one of the most influential and private figures in modern finance, making this conversation one of his first interviews ever. In this short episode, we talk about prediction markets, why Jeff believes they're the

future of how we understand truth, how they can improve decision-making in business, in government, and what they reveal about the power of incentives, information, and human behavior. I

really enjoyed recording this episode, and I hope you guys enjoy listening.

Thank you, Jeff, for coming on. I really

appreciate you making the time.

>> It's my pleasure, Amir. Let's go.

>> So, to set a foundation for this conversation, I'd love to kind of start simple. What's your current perspective

simple. What's your current perspective on prediction markets as a whole and how are they significant to Suskahan and yourself?

>> Uh well prediction markets have been a great you know passion of ours for years. They add uh uh tremendous value

years. They add uh uh tremendous value to to the world. You basically can't make a good decision without knowing the probabilities of events happening.

Prediction markets are the best way we know how to get the most accurate guess of what those predictions are. So we

think it's a fantastic tool that will add uh you know tremendous benefits uh to uh to society >> and from a broad perspective how do you

see the kind of evolution of prediction markets playing over the next decade especially in terms of regulation and gambling legislation?

>> Well in the gambling world uh uh you know we're really not uh uh we're really not sure. I think the world is coming to the conclusion that a

system like the one they have in Europe like Bet Fair where people can buy and sell amongst themselves is a much fairer system will reduce costs tremendously

for uh uh uh for for customers. You know

currently uh the VIG is somewhere around 5%. If you can trade amongst yourself on

5%. If you can trade amongst yourself on exchange we think that'll go down substantially probably to to one or two%. So that will be a uh a big win for

two%. So that will be a uh a big win for uh for for people who want to uh engage in sports. But our real motivation for

in sports. But our real motivation for prediction markets is to get you know

the truth out there. Our favorite

example is uh uh during the Iraq war uh when we when George Bush first went into Iraq uh he said it would cost $20 billion. uh Lawrence Lindsay his

billion. uh Lawrence Lindsay his economic advisor said I think it might cost as much as 50. He was sort of punished for saying that the true number has come in somewhere between two and $6

trillion.

So had the people had a prediction market what's the over underline and how much this would cost now I don't think it would be anywhere near 2 to6 trillion but it would have been substantially

higher than 50 billion let's say it would have been 500 billion then the people might have said look we don't want this war politicians always tell us that the wars are going to be cheap and

quick and fast and they never are. So we

need a trusted source and prediction markets would be an objective trusted source because anyone betting on them uh you know is going to lose money if they uh if they get if they get their

analysis wrong. So had we seen this

analysis wrong. So had we seen this gigantic number, I think there would have been much more push back against this war and and something as p you know

predictions markets could be that powerful where they can really slow down the lies that politicians are uh are constantly telling us and that's really

sort of my number one reason uh why I want to see them uh you know thrive.

It's almost the people's idea of the truth rather than the kind of tainted idea of the truth that's that's given to it's given to the general population. Um

and I want to kind of >> exactly but but also with experts. I

mean you may not know what wars course the vast majority of people don't know but there's a small group of people who do and they would be betting it and they would be bidding it up to a price that makes sense. So the public who may not

makes sense. So the public who may not you know how how the hell you going to be informed about what a war is going to cost if you're a regular person. But if

you see experts battling it out and betting on it, then uh then you can you can trust that number and you could be more of an expert by looking at a

prediction market than a politician can who's just either making up a number or purposely lying. And I also assume in

purposely lying. And I also assume in the future that prediction markets can be used and will be used to price more like financial instruments and support

other decisions. But how can we protect

other decisions. But how can we protect from prediction market manipulation?

>> Uh well, in the same way you you protect against any other manipulation, if if you're manipulating the price, uh you're going to lose money if there's enough,

you know, uh players out there and you want to get a price up, you know, to something uh uh uh you know, for for some nefarious reason, you're going to

have to lose a lot of money to do it.

So, uh, if you wanted us, you know, bet that it's going to be under $50 billion spending, well, we will bet you hundreds of millions of dollars, that you're

wrong. So, uh, your plan is going to be

wrong. So, uh, your plan is going to be very, very expensive and it'll probably be more expensive than just a misleading advertising campaign, which is just, you know, might cost in the millions. This

would cost in the hundreds of millions.

So, that will protect the integrity of the uh of the markets. And I want to take a step back for a moment. Um, early

in your career, you're a professional gambler, specifically in poker and horse betting. What do you see as the

betting. What do you see as the parallels between gambling and prediction markets? And what systemic

prediction markets? And what systemic risks and opportunities do you think are introduced as a result?

>> Uh, I don't really see any systemic uh uh uh uh risks. uh I see more truth,

more uh rational objective uh probabilities getting out into the marketplace and I see the systemic risk as politicians telling us stuff that

they're trying to trick us and this is the antidote to that. So uh you know I I see you know obviously there could be some tiny amounts of manipulation but that's going to be trivial compared to

the amount of manipulation that we have uh we have now competitive markets will wipe out that uh will wipe out any problems that uh that we may see.

>> And from kind of like a broad overview how do you think your firm and firms like yours will incorporate prediction markets into their daily decision-m?

Well, for example, uh you know, uh there's an election in New York City in uh two in 15 days.

>> Okay.

>> Okay. Uh you know, if you listen to TV, uh you know, cable news, you get, you know, it's very hard to figure out what the probability is. Like some people say, "Nah, it's going to be too close.

Come on. Uh New York's not going to uh elect someone like Maami." Uh but when you look at the prediction market, you see he's a little over 90% to win. So,

if you're making a decision and you want to move to New York, you want to move the business to New York or or or whatever, you need to know that probability, and it's very hard to know

just by reading the newspapers or listening to to the to the news. And to

have that actual number helps you dramatically in that decision. Plus,

let's say you're a real estate developer and you think that your value of real estate's going to go down by a million dollars if uh if mom dami wins, you can hedge it. So you can buy insurance but

hedge it. So you can buy insurance but more importantly you can get you know you can find out what the best guess is and you can do it in an instant. You

just look at the price you have the the probability. You don't have to do all

probability. You don't have to do all kinds of work. You don't have to read a million articles and call posters and post pollsters and do all the work. All

the work is done for you and you get the best possible number you can and that will guide you through your you know through all your decisions. in uh you know for for for Saskuana you know we're constantly looking at what are the odds

uh let's say of a presidential election and stocks are going up and down based on who's going to win and who's going to lose and we use that number to determine if we think you know uh a stock has

overreacted or underreacted to the uh political uh odds >> and I imagine as kind of prediction markets become bigger and bigger and there's more volume that larger firms will start participating and actually

hedging on the prediction markets rather than using outside financial instruments to hedge. So my question kind of around

to hedge. So my question kind of around that is you recently joined forces with Kshi to provide liquidity as one of its primary market makers. How do you believe the involvement of firms like

yours will evolve with the markets?

>> Yeah, that's a great question. We right

now uh it's still a bespoke product. Uh

institutions aren't really using it.

There's a lot of action but it's mainly uh relatively smallers. No giant

institution has really showed up and wanted to hedge, you know, will the Fed raise rates or not yet on these things.

But we think as they get regulatory clarity and as they grow in popularity, institutions will show up and there will be Wall Streetsized bets uh placed on

these uh placed on these things. Uh but

that has not yet ha not yet happened. I

mean, if you're, you know, a an investment bank, if you're Goldman Sachs or Morgan Stanley, you're a little co cautious about betting on these things, but you haven't done it yet. But

eventually, that'll go away. What I

really hope that uh uh prediction markets uh could could uh uh could influence is the insurance business. You

know, insurance in some places is impossible to get. The government caps the rate that you can sell it at. So, a

lot of insurance companies have left Florida, for example, and you can't insure your home because the price is is too low. But if we had uh insurance bets

too low. But if we had uh insurance bets on prediction markets, you can live in a, you know, in an area, we can put up a price and say, will will the winds get

above 80 miles per hour in the next 2 days in your area? And let's say there's a 10% chance of it happening. If you

think that if that happens, you're, you know, you may suffer serious damage to your home, you might want to bet $10,000 on it to win $90,000.

Uh I I if it happens, and that'll cover your or cover most of your insurance costs. And you only have to buy it when

costs. And you only have to buy it when there's a uh you know when when there's a problem coming they will take out all the uh adjustable claims all the expense

all the advertising of insurance make it much much cheaper and much more sort of bespoke to what you need to have happen.

So uh you know there's enormous uh expense in insurance and this would reduce m reduce a lot of it make it much easier for people to uh to ensure what they really have. It won't be as perfect

as an insurance claim where my roof blew blew off. Give me my money. It'll be

blew off. Give me my money. It'll be

more like, well, the wind was really bad. I know my house is messed up. How

bad. I know my house is messed up. How

messed up? I don't I don't exactly know.

But because it's so much cheaper, you could uh you can much more easily hedge your risk than you can with typical insurance products.

>> And it's so much more quantifiable. The

the insurers will obviously try to see how much you need and how much they'll give you and stuff like that. And with

prediction markets, it's so much more quantifiable. And as these prediction

quantifiable. And as these prediction markets kind of evolve and mature into someday fully regulated exchanges, I'd imagine, do you think the majority of liquidity will come from large Wall

Street firms or do you think they're going to come from retail flows?

>> I think it's going to come from both.

And I think that it's going to create tremendous opportunities. Let's say

tremendous opportunities. Let's say you're just a weather uh person that loves following weather and hurricanes and probabilities and you live, you know, in Florida. You can put out your

own markets and say this area I think is you know uh uh these are the odds of of disruption and in these areas these are the odds and you can have uh uh you know

you know relatively small businesses uh who have expertise in this stuff who now have no way to make any money from their their expertise and they can be putting out markets and they could be making a

lot of money and reducing the price for uh for regular people.

Yeah, I think it's incredible. And and

do you think at all in the future prediction markets can influence outcomes?

>> No. Uh, you know, that's like one of the myths that uh that someone's going to bet, you know, there was that story on poly market that the French guy was betting uh Trump and he was, you know,

that was just nonsense. You know, we bet against him. You know, if he bids it up,

against him. You know, if he bids it up, we'll we'll bet it down. It's not going to influence anything. Uh so all that that's a fear that comes to mind and

it's not a zero probability that can happen but it's really uh it's really vastly overstated.

>> And what do you think is the most significant obstacle to broader participation in prediction markets and and how can one go about removing that obstacle? uh the the the biggest

obstacle? uh the the the biggest obstacles I like as you as you ask these questions you can see what could go wrong, what can go wrong, what can go wrong. Those things psychologically come

wrong. Those things psychologically come right to your mind that these things could go wrong and yes something could go wrong but something is already going

wrong. So that obstacle as we get used

wrong. So that obstacle as we get used to it will uh uh will go away. It's

going to take time, but people have fears and they overstate the the downside. But as the product takes, you

downside. But as the product takes, you know, takes place and people learn how valuable it is and how how much money it can save them, those fears will dissipate. This may take this may take

dissipate. This may take this may take years, but I'm very optimistic that we're going to get there. Before we go back to the episode, I want to take a short break to talk about my sponsor,

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terms for details. Thank you. And back

to the episode. And I know you come from a very kind of probabilistic background, but with the rise of decision markets kind of there's underprediction markets.

Is there any type of decision or even prediction that we should deliberately avoid quantifying?

>> Uh that's a good question. Uh you know, you could uh I remember you could put up on a prediction market uh uh should I marry

this girl or not? you know, uh, and maybe some, uh, you know, your friends and your relatives might be more objective than you are. Uh, but I'd say that's going a bit too far. Uh, so my

answer sort of would be no.

>> And what is possible with prediction markets that no one is talking about right now? Or what do you think is

right now? Or what do you think is possible prediction markets no one's talking about? Uh I think the uh the the

talking about? Uh I think the uh the the number one thing it will stop wars because every war is exaggerated uh is

uh how quickly it'll be ended it'll be ended and how little it will be cost it will cost and how many lives will be lost is always lied to us by our

politicians. uh and uh Abraham Lincoln,

politicians. uh and uh Abraham Lincoln, you know, in the in the Civil War in 19 in 1862, the War Department stopped taking uh in the North stop taking

recruits because they said this war will be over in a couple of weeks. Uh you

know, he was off by 650,000 deaths and stuff. So, he honestly believed that it

stuff. So, he honestly believed that it was going to be a short quick war. And

obviously, it wasn't. and the rever, you know, it still reverberates now. Uh, uh,

you know, the horror of the civil war.

If the people knew how expensive it's going to be and how disastrous it's going to be, they will try and come up with other solutions besides uh besides

going to uh going to war. Another

example I can give is driverless cars.

There's a lot of opposition to driverless cars because people can imagine, you know, a robot going crazy and killing somebody. But uh you know this year in the next 12 months about

40,000 Americans will die on the roads.

If we had driverless cars, I'm guessing that number would probably be about 10,000. You know, down 75% we'd save

10,000. You know, down 75% we'd save 30,000 lives. If we put that up in

30,000 lives. If we put that up in prediction markets and said how many lives uh you know in 2030, how many people will die in car accidents and the

numbers vastly lower than it is now because people expect driverless cars to happen. It would make policymakers

happen. It would make policymakers hustle and hurry up and getting driverless cars there because we're going to have this gain of tens of thousands of people who aren't going to

die right now. You know, you sort of say, "Oh, I don't know. Maybe driverless

cars will be good. Maybe they won't." If

we had an objective number on it, I think we would see how great how great it is and we'd move much much uh faster.

I I think it's an incredible kind of use case of it, especially for quantifying things for for policy makers to make decisions based off of. And before I move on to kind of a question or two

about advice, what is the one message that Jeff Yas wants to tell the world about prediction markets? If you had to give one message

markets? If you had to give one message to the world, if you were selling the world on prediction markets, what would it be?

>> It is uh my mother used to say to me, if you're so smart, how come you're not rich? the prediction markets are

rich? the prediction markets are uh objective. If you think the odds are

uh objective. If you think the odds are incorrect, then go bet it and go put it go put it back into where in line where it should be. If you really are smarter than the markets, you'll make a lot of

money. You'll do society a favor because

money. You'll do society a favor because you'll get the price you get the price right. And if you can't make money, you

right. And if you can't make money, you may want to consider being quiet like maybe the market knows more than you do.

Now, this is going to infuriate every college professor you're ever going to have because they want to be the experts. But they're not. A bunch of

experts. But they're not. A bunch of speculators battling it out every day in the mark in the marketplace will be vastly greater. It will insult the

vastly greater. It will insult the college professors, which as far as I'm concerned is a good thing.

>> I agree.

>> Let me give you an example. When my

daughter was 12 years old, Obama was running uh uh you know uh against Hillary Clinton in the primary. And one

of the most famous political scientists in America was on TV saying, "No, Obama, you know, Hillary Clinton's going to win. She's up by 30 or 40 points." My

win. She's up by 30 or 40 points." My

daughter, I said, "Go check trade sports," which is the only place at that time to look. And she said, "Obama has a 22% chance of winning." So the marketplace knew that Obama was special,

that he was charismatic. He didn't have any name recognition, and Hillary did.

So the fact that he's down by 35 with months to go doesn't really mean anything. So, I use that in an example

anything. So, I use that in an example that my 12-year-old daughter had a better guess of who's going to win that primary than the world's foremost expert in in polyai. And that's the power of

prediction markets.

>> That's that's an incredible incredible anecdote, incredible example. Um, and I want to ask two questions about advice.

The first one being as a high schooler today, I'm a high schooler and um given all the success that you've had and given all the hiring that you've done, what should students today study?

>> I would strongly suggest I mean obviously you know uh you know computer science you got to be computer literate and you got to you got to understand where AI is coming from. But if you

really want to be a decision maker under under uncertainty which is what humanity is, you have to learn probability and

statistics so much of what happens uh you know in the world is you are making a deci a decision and if you're not really informed on the mathematics

behind probability and statistics you can make a terrible decision. So, when

you see that there's a hurricane season, there's a lot of hurricanes. Like, well,

is this a big deal or are there always a lot of hurricanes and what's the volatility around hurricanes? Does it

vary by a lot? Is this such an outlier?

Does this prove there's global warming or is this just a blip? So, it's sort of the signal versus the noise. And to be able to distinguish which is which takes some uh some some knowledge and some

learning. But you really can't interpret

learning. But you really can't interpret events in the world unless you have a firm uh background in probability and statistics. And I'll give you another

statistics. And I'll give you another little anecdote that like the Russians in 1958 land you know had Sputnik and we were afraid they were going to beat us to the moon. Uh and they did beat us to

the moon but not a man on the moon. So,

the United States, you know, put in a science program where everybody has to learn calculus.

>> I've heard about that.

>> Okay. So, we all got to learn calculus, which we can't let the Russians beat us.

So, now everyone has to, you know, to get into a good college, you're going to have to learn calculus. To get into med school, you have to learn calculus, which is absurd, but you're never going to use it. Uh, but no one learned how to use probability and statistics because

it was not, it was considered secondary to calculus. So we have a country that

to calculus. So we have a country that sort of knows you know a fair amount of calculus but very little probability and statistics and it's just not the way uh it's just not what's necessary to be a

good decision maker to be a good uh to be a good citizen but it's almost impossible to change these things. So

you have to take the effort yourself to make sure that you are literate in in probability statistics and you certainly understand basing analysis because there's uh you know all these studies

done that uh they asked Harvard uh kids in Harvard medical school who are going to be researchers some basic questions after they got the data about uh about diseases and they were off by a factor

of a hundred. These are very very smart people, but they didn't obey the analysis and they were and they were ridiculous because it was not taught to them in medical school. And if you've ever had the frustration of talking to a

doctor and saying, "Doc, what's my chance of having this?" He goes, "Oh, I don't know. You may or may not have it."

don't know. You may or may not have it."

It's like, "I'd like you to I'd like you to tighten that market up a little bit, doc." Uh, but they're not trained that

doc." Uh, but they're not trained that way. And that's a uh and that's a

way. And that's a uh and that's a tragedy. You have to make sure that you

tragedy. You have to make sure that you go out of your way to get that uh to get that training.

>> I I think that's a very valid point. And

uh I I'm currently learning calculus. I

think I might do a little statistics education on my own. Probably statistics

education on my own.

>> Calculus is wonderful. It's my favorite subject and it's great. Uh it's

beautiful. It's art. It's the key to science and and everything like that.

But it's it's of limited value to most people.

>> And I want to ask one more question that I do at the end of every interview. Um I

think I've asked it to 39 people so far.

>> I'm 16 right now. If you were to give one piece of advice to a 16-year-old today, it can be life advice, career advice, even romantic advice. What would

it be?

>> Uh uh I tell if it was romantic advice, I mean, I believe in markets. It's like

don't go out with somebody that your friends think is a nutcase. Okay? You

know, but you can get caught up and if you say to my friend your friends, be honest. I won't I won't punish you. Try

honest. I won't I won't punish you. Try

and do it anonymously. Give me a marketplace. Am I making a gigantic

marketplace. Am I making a gigantic mistake? So many lives are ruined

mistake? So many lives are ruined because you get involved with the with the with the wrong person and uh no one wants to speak up. So you got to come up with a mechanism. Hey friends, you're my

friend. I trust you and I'll do this

friend. I trust you and I'll do this anonymously. You know uh should I should

anonymously. You know uh should I should I you know is this person too nutty for me to be going for me to going out with and you could prevent a lot of uh

horrible uh relationships from happening there. Uh that would be my uh number one

there. Uh that would be my uh number one advice because because one of the things that we do in reverse, the bigger the decision, the less time we think about it. You know, if you're buying or

it. You know, if you're buying or selling a stock and it's basically irrelevant what you're doing because the markets are fair, you'll spend a lot of time on it. If you're deciding who to marry or who to have a relationship or

whatever is you basically just plop into it without much thought and one has a gigantic impact on your life and one has a very small impact on your life yet we

spend much more time uh worrying about the minor things and not enough time worrying about the big things.

>> I I I I mean from my limited life experience I think I I agree and I I recommend anyone who's listening to this to listen to my episode with any Duke about decision-making. I think it's a

about decision-making. I think it's a it's an excellent uh compliment to this episode. But Jeff, it was an absolute

episode. But Jeff, it was an absolute pleasure having you.

>> Thank you for coming on. I really

appreciate it.

>> Good luck. I really appreciate it, too.

It was fun. Okay. Bye.