Episode 39: Jeff Yass - Founder and Managing Director of Susquehanna International Group
发布时间 2025-10-23 10:10:27 来源
以下是内容的中文翻译:
在这一集《创造阿尔法》节目中,主持人阿米尔采访了苏塞克斯国际集团(Susquehanna International Group)的创始人杰夫·亚斯(Jeff Yass)。苏塞克斯国际集团是一家成功的交易公司,以将扑克、概率论和决策理论应用于金融市场而闻名。本次对话的重点是预测市场,亚斯认为预测市场是理解真相和改善商业及政府决策的未来方向。
亚斯表达了他对预测市场的长期热情,强调它们在提供事件概率的最准确估计方面的价值。他认为,没有对这些概率的理解,就不可能做出好的决策,而预测市场是实现这一目标的最佳工具。他设想未来预测市场将在赌博和更广泛的社会背景下发挥关键作用。
关于未来十年预测市场的演变,亚斯指出了像必发(Betfair)这样的欧洲模式,个人之间可以进行交易。他认为这种系统更公平、更具成本效益,买卖价差可能会从大约5%降至1-2%。然而,亚斯支持预测市场的主要动机在于它们揭示真相的潜力,特别是在政客经常误导公众的领域。
他以伊拉克战争为例,当时布什总统最初的成本估计远低于实际支出。亚斯认为,如果有一个预测市场能够提供更现实的战争成本估计,可能会导致更大的公众抵制。他认为预测市场提供了一个客观、值得信赖的信息来源,由于错误预测会导致财务损失,因此它激励人们进行准确的分析。本质上,预测市场代表了人民版本的真相,而不是传播给公众的往往带有偏见的信息。
亚斯还驳斥了关于操纵的担忧,他指出操纵价格需要大量的资金投入,而且可能比误导性的广告宣传活动成本更高。他认为,竞争性市场将减轻任何潜在的操纵。
亚斯从他早期作为扑克和赛马职业赌徒的经历中得出结论,认为预测市场不存在系统性风险。相反,他强调了更大的透明度和理性、客观概率的好处。他将预测市场视为政治操纵的解毒剂。
亚斯解释了像苏塞克斯国际集团这样的公司如何将预测市场融入到他们的日常决策中。他以2015年纽约市选举为例,当时的预测市场准确地反映了比尔·德布拉西奥(Bill de Blasio)获胜的高概率,而传统媒体的报道则不太明确。对于那些正在就投资或搬迁到特定城市做出决策的企业来说,这些信息可能是非常宝贵的。他指出,苏塞克斯国际集团利用预测市场来衡量市场对政治事件的过度反应或反应不足。
他透露苏塞克斯国际集团已与Kalshi合作,作为其主要的做市商之一提供流动性。尽管机构参与目前有限,但亚斯预计,随着监管清晰度提高以及预测市场日益普及,更大的公司将开始在这些市场上进行对冲,而不是依赖外部金融工具。他设想未来华尔街规模的赌注将会押在诸如美联储加息等事件上。
亚斯还乐观地认为,预测市场有潜力彻底改变保险业,使其更易于获得且更实惠,特别是在传统保险不可用或价格过高的地区。
关于未来完全受监管的预测市场交易所的流动性来源,亚斯认为这将来自大型华尔街公司和散户投资者。他还设想了拥有专业知识的个人,例如天气专家,可以创建并从他们自己的市场中获利的机会。
亚斯驳斥了预测市场可以影响结果的神话,并举例说明了试图操纵价格的尝试被其他人反击的情况。他强调,更广泛参与的最大障碍是对潜在不利因素的恐惧,但随着人们获得经验并认识到预测市场的价值,这些恐惧将会减少。
关于应该刻意避免量化的决策问题,亚斯开玩笑地说,人们不应该围绕诸如“我应该和这个人结婚吗?”这样的个人选择创建一个市场。
他认为,预测市场最重要的潜力在于,它们能够通过迫使政客提供更准确的成本、时间表和伤亡人数估计来防止战争。他还强调了预测市场通过量化无人驾驶汽车的安全效益来加速其技术采用的潜力。
亚斯关于预测市场的关键信息是,它们是客观的,并为拥有卓越知识的个人提供了一个通过纠正市场错误定价来获利的机会。他鼓励人们参与,同时也承认市场可能比个人专家拥有更多的知识。
在向高中生提供建议时,亚斯强烈建议学习概率和统计,以培养在不确定性下做出决策的技能。他将此与美国教育体系过度强调微积分的情况进行了对比,认为概率和统计对大多数人的生活更具相关性。
最后,如果他可以给一个16岁的年轻人一条建议,那就是寻求朋友对恋爱关系的匿名反馈,因为他们可能会提供更客观的见解。他强调,人们往往将更多的注意力放在微小的决定上,而忽略了重大生活选择(例如人际关系)的重大影响。
In this episode of Generating Alpha, host Amir interviews Jeff Yass, the founder of Susquehanna International Group, a successful trading firm known for applying poker, probability, and decision theory to financial markets. The conversation centers around prediction markets, which Yass believes are the future of understanding truth and improving decision-making in business and government.
Yass expresses his long-standing passion for prediction markets, emphasizing their value in providing the most accurate estimations of event probabilities. He argues that good decisions are impossible without understanding these probabilities and that prediction markets offer the best tool for achieving this. He envisions a future where prediction markets play a crucial role in both gambling and broader societal contexts.
Regarding the evolution of prediction markets over the next decade, Yass points to the European model, like Betfair, where individuals trade amongst themselves. He believes this system is fairer and more cost-effective, with bid-ask spreads potentially dropping from around 5% to 1-2%. However, Yass's primary motivation for supporting prediction markets lies in their potential to uncover the truth, particularly in areas where politicians often mislead the public.
He cites the Iraq War as an example, where initial cost estimates by President Bush were far below the actual expenses. Yass suggests that a prediction market, providing a more realistic estimate of the war's cost, could have led to greater public resistance. He argues that prediction markets offer an objective, trusted source of information, incentivizing accurate analysis due to the risk of financial loss for incorrect predictions. In essence, prediction markets represent the people's version of the truth, as opposed to the often-tainted information disseminated to the public.
Yass addresses concerns about manipulation by noting that manipulating prices requires significant financial investment and would likely be more costly than misleading advertising campaigns. Competitive markets, he believes, will mitigate any potential manipulation.
Drawing on his early career as a professional gambler in poker and horse betting, Yass sees no systemic risks associated with prediction markets. Instead, he highlights the benefits of greater transparency and rational, objective probabilities. He views prediction markets as an antidote to political manipulation.
Yass explains how firms like Susquehanna incorporate prediction markets into their daily decision-making. He uses the example of the 2015 New York City election, where prediction markets accurately reflected the high probability of Bill de Blasio's victory, while traditional media outlets offered less clarity. This information can be invaluable for businesses making decisions about investing or relocating to a particular city. He notes that Susquehanna uses prediction markets to gauge market overreactions or underreactions to political events.
He shares that Susquehanna has partnered with Kalshi to provide liquidity as one of its primary market makers. While institutional involvement is currently limited, Yass anticipates that as regulatory clarity improves and prediction markets gain popularity, larger firms will begin hedging on these markets, rather than relying on external financial instruments. He envisions a future where Wall Street-sized bets are placed on events like Federal Reserve rate hikes.
Yass is also optimistic about the potential for prediction markets to revolutionize the insurance industry, making it more accessible and affordable, particularly in areas where traditional insurance is unavailable or overpriced.
Regarding the source of liquidity in future fully regulated prediction market exchanges, Yass believes it will come from both large Wall Street firms and retail investors. He also envisions opportunities for individuals with specialized knowledge, such as weather experts, to create and profit from their own markets.
Yass debunks the myth that prediction markets can influence outcomes, citing examples where attempts to manipulate prices were countered by others. He emphasizes that the most significant obstacle to broader participation is the fear of potential downsides, but as people gain experience and recognize the value of prediction markets, these fears will diminish.
On the question of decisions that should be deliberately avoided quantifying, Yass jokingly suggests that one shouldn't create a market around personal choices like "Should I marry this person?"
He believes the most significant potential of prediction markets lies in their ability to prevent wars by forcing politicians to provide more accurate estimates of costs, timelines, and casualties. He also highlights the potential of prediction markets to accelerate the adoption of technologies like driverless cars by quantifying their safety benefits.
Yass's key message about prediction markets is that they are objective and offer an opportunity for individuals with superior knowledge to profit by correcting market mispricings. He encourages participation, while acknowledging that the market may possess more knowledge than individual experts.
Offering advice to high school students, Yass strongly recommends studying probability and statistics to develop decision-making skills under uncertainty. He contrasts this with the overemphasis on calculus in the US education system, arguing that probability and statistics are more relevant to most people's lives.
Finally, if he could give one piece of advice to a 16-year-old, it would be to seek anonymous feedback from friends about romantic relationships, as they may offer more objective insights. He emphasizes that people often devote more attention to minor decisions and overlook the significant impact of major life choices, such as relationships.
摘要
This week on Generating Alpha, I’m joined by Jeff Yass — founder of Susquehanna International Group, one of the most successful trading firms in the world.
Jeff is a former professional poker player and horse bettor turned options trader. In 1987, he founded Susquehanna with five friends, and today it stands as one of Wall Street’s largest and most influential firms. Thanks to Susquehanna’s success and its early stake in ByteDance, Jeff is now the 26th wealthiest person in the world — yet remains one of the most private figures in finance.
In one of his first-ever podcast interviews, we spent 25 minutes focused entirely on prediction markets — why Jeff believes they represent the future of truth-seeking, how firms like Susquehanna will shape their evolution, and what obstacles still stand in the way of mass participation.
We also discussed whether some decisions shouldn’t be quantified, how to protect markets from manipulation, and Jeff’s advice for students on what to study in 2025.
Presented By: Rho.co/generatingalpha
GPT-4正在为你翻译摘要中......
中英文字稿 
This week on generating alpha in an episode unlike most, I'm joined by Jeff Yes. Founder of Susquehanna 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, 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 and 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.
本周,我们带来了一期与众不同的《生成阿尔法》节目,我邀请到了杰夫·耶斯。他是全球最成功的交易公司之一——Susquehanna International Group(锡古国际集团)的创始人。杰夫在金融界是个传奇人物,以将扑克、概率和决策理论的原则应用于市场而闻名。在过去的四十年中,他悄然在华尔街的幕后建立了一个全球强大的企业,涉及的交易从期权到加密货币,所有操作都以数学精确性和理性思维为基础。他也是现代金融界最具影响力且极为低调的人物之一,所以这次对话是他首次接受采访之一。在这简短的节目中,我们讨论了预测市场。杰夫为何相信预测市场是我们理解真相的未来,它们如何能在政府和商业中改进决策,以及它们揭示了激励、信息和人类行为的力量。我非常享受这次录音过程,希望你们也喜欢收听。感谢杰夫的参与,非常感谢您抽出时间。
Jeff 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 on prediction markets as a whole, and how are they significant to Susquehanna and yourself? Well, prediction markets have been a great passion of ours for years. They add tremendous value 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 tremendous benefits to society.
杰夫:这是我的荣幸,阿米尔。我们开始吧。为了给这次对话打下基础,我想从简单的问题开始。您目前对整体预测市场的看法是什么?它们对Susquehanna和您个人有何重要意义?
预测市场多年一直是我们的热情所在。它们为世界带来了巨大的价值。基本上,如果不清楚事件发生的概率,就无法做出良好的决策。预测市场是我们所知道的获取最准确预测的最佳方式。因此,我们认为这是一个能为社会带来巨大好处的绝佳工具。
In 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, 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 Betfair, where people combine sell amongst themselves is a much fair system. We'll reduce costs tremendously for customers. Currently, the big is somewhere around 5%. If you can trade amongst yourself on exchange, we think they'll go down substantially probably to 1% to 2%. So that will be a big win for people who want to engage in sports. But our real motivation for prediction markets is to get the truth out there.
从广义角度来看,您如何看待未来十年预测市场的发展,尤其是在法规和赌博立法方面的演变?关于赌博领域,我们仍不太确定。我认为世界正在逐渐认识到一个类似欧洲的系统,比如Betfair,那种让人们在彼此之间进行交易的系统,是一个更加公平的体系。这种模式会极大地降低消费者的成本。目前,手续费大概在5%左右。如果可以在这种交易平台上进行买卖,我们认为手续费可能会大幅下降到1%到2%。这对于想要参与体育活动的人来说将是一个巨大的胜利。但我们对预测市场的真正动机是想传播事实。
Our favorite example is during the Iraq war, when George Bush first went into Iraq, he said it would cost $20 billion. Lawrence Lindsay, his economic advisor, said, I think of my cost as much as $50. He was sort of punished for saying that. The true number has come in somewhere between $2 and $6 trillion. So had the people had a prediction market, what's the over on the line and how much this would cost? I don't think it would be anywhere near $2 to $6 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, it's going to lose money if they get their analysis wrong.
我们最喜欢的例子是伊拉克战争期间,当时乔治·布什首次进入伊拉克,他说战争会花费200亿美元。而他的经济顾问劳伦斯·林赛认为可能会花费多达500亿美元。由于他这么说,受到了某种程度的惩罚。然而,实际费用在2万亿到6万亿美元之间。如果当时有一个预测市场,人们可以预测战争的成本,我认为预测值不会达到2万亿到6万亿美元,但会远高于500亿美元。比如说,可能会被预测到5000亿美元。这样一来,人们可能会说,我们不想要这场战争。政治家总是告诉我们战争会便宜、迅速且短暂,但事实从来不是这样。所以我们需要一个值得信赖的来源,预测市场可以成为客观和值得信任的来源,因为任何下注的人,如果分析错误,就会亏钱。
So had we seen this gigantic number, I think there would have been much more pushback against this war. And prediction markets could be that powerful, where they can really slow down the lies that politicians are constantly telling us. And that's really sort of my number one reason why I want to see them thrive. It's almost the people's idea of the truth, rather than the kind of tainted idea of the truth. That's given to the general population. But also with experts. I mean, you may not know what wars course, the vast majority, 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.
如果我们当时看到了这个巨大的数字,我认为那场战争会遇到更多的反对声音。预测市场可以如此强大,以至于它们能够真正减缓政客们经常对我们撒的谎。这是我希望看到预测市场蓬勃发展的主要原因之一。这几乎是人民对真相的看法,而不是带有偏见的真相,被灌输给普通大众。除此之外,还有专家的参与。我是说,你可能不知道战争的代价,大多数人都不知道,但有一小部分人知道,他们会在这个市场下注,并把价格抬到一个合理的水平。
So the public who may not, you know, how the hell you're 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 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 the future that prediction markets can be used, and we'll be used to price more like financial instruments and support other decisions.
对于普通公众来说,你可能不知道,作为一个普通人,你怎么可能了解一场战争的成本。但是,如果你看到专家们根据预测市场的数据进行讨论和下注,那么你可以相信这个数字。通过观察预测市场,你甚至可以比那些可能随便编造数字或故意撒谎的政客更接近专家。我还认为,未来预测市场可以并将被用来像金融工具一样进行定价,并支持其他决策。
But how can we protect from prediction market manipulation? Well, in the same way you're protecting as any other manipulation, if you're manipulating the price, you're going to lose money. If there's enough players out there and you want to get a price up to something for some nefarious reason, you're going to have to lose a lot of money to do it. So if you want it a 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.
但是,我们如何保护自己不被预测市场的操纵影响呢?其实方法和防止其他操纵行为类似。如果你试图操纵价格,最终你会亏损。如果市场上有足够多的参与者,而你出于某些不良目的想要推高价格,就必须付出大量金钱来实现。所以,如果你想下注某项支出会低于500亿美元,那么我们会下注数亿美元来赌你错了。
So 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 my cost in the millions, this would cost in the hundreds of millions. So that will protect the integrity of the markets. And I want to take a step back for a moment. Early in your career, your professional gambler, specifically in poker and horse betting, what do you see as the parallels between gambling and prediction markets and what systemic risks and opportunities do you think are introduced as a result?
所以你的计划将会非常非常昂贵,可能比仅仅一个误导性的广告活动更为昂贵,广告活动的花费仅在数百万,而这个计划则将花费数亿。但这将保护市场的完整性。我想退一步,从更广的角度来看。早期在你的职业生涯中,你是一位职业赌徒,特别是在扑克和赛马下注方面。你认为赌博和预测市场之间有什么相似之处?你认为这会引入什么系统性风险和机会?
I don't really see any systemic risks. I see more truth, more rational objective probabilities getting out into the marketplace. And I see this systemic risk as politicians telling us stuff that they're trying to trick us. And this is the antidote to that. So I see, 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 now. Competitive markets will wipe out any problems that we may see.
我并不认为存在任何系统性风险。我看到的是,市场中有更多的真实信息和理性的客观概率在流通。而我看到的系统性风险其实是一些政客试图蒙骗我们的言论。这种新的发展正是对此的解药。当然,可能会有一些小规模的操控,但与目前我们所经历的大规模操控相比,这些都是微不足道的。竞争性的市场会消除我们可能面临的任何问题。
And from kind of like a broad overview, how do you think your firm infirms like yours will incorporate prediction markets into their daily decision making? Well, for example, there's an election in New York City in 2015. If you listen to TV, cable news, you get very hard to figure out what the probability is. Some people say, no, it's going to be too close. Come on, New York's not going to elect someone like Ma'am Dammy.
从一个广泛的视角来看,您认为贵公司以及类似的公司会如何将预测市场融入到日常决策中呢?举个例子,2015年在纽约市有一场选举。如果你通过电视或有线新闻了解情况,很难判断选举结果的概率。一些人说,选情会很胶着,认为纽约不可能选出像Ma'am Dammy这样的人。
But when you look at the prediction market, you see he's a little over 90% to win. If you're making a decision and you want to move to New York, you want to move to business to New York or whatever, you need to know that probability. It's very hard to know just by reading the newspapers or listening 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 is going to go down by a million dollars if Ma'am Dammy wins.
但是,当你查看预测市场时,你会发现他有超过90%的机会会赢。如果你在做决定,比如想搬去纽约或者把生意搬到纽约,那你就需要知道这个概率。仅仅通过看报纸或听新闻很难知道这些,但了解这个具体的数字对你的决策有很大帮助。另外,假设你是个房地产开发商,你认为如果Ma'am Dammy赢了,你的房地产价值可能会下降一百万美元。
You can 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 probability, you don't have to do all kinds of work, you don't have to read a million articles and call posters and posters 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 all your decisions.
你可以通过对冲来购买保险。但更重要的是,你可以迅速找到最有可能的结果。你只需查看价格,就能得到概率,而不必费力去做各种研究,也不用阅读大量文章或打各种电话。所有工作都已为你完成,你获得了最优的数字。这将指导你做出所有决策。
For Susquehanna, you know, we're constantly looking at what are the odds, let's say the 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 a stock has overreacted or underreacted to the political odds. And I imagine as 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.
苏斯奎汉纳(Susquehanna)一直在关注各种几率,比如说总统选举的几率。当股市因为谁将赢得或失去选举而上下波动时,我们利用这些几率来判断某只股票是否对政治几率反应过度或反应不足。我想,随着预测市场变得越来越大,交易量增加,更多的大型公司将开始参与,实际上会在预测市场上进行对冲,而不是使用外部金融工具来对冲。
So my question kind of around that is you recently joined forces with Kalshi 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 it's still a bespoke product. Institutions aren't really using it. There's a lot of action, but it's mainly relatively small bettors. No giant institution has really showed up and wanted a hedge.
所以,我的问题是,您最近与Kalshi合作,成为其主要做市商之一,为市场提供流动性。您认为像您这样的公司在市场中的作用会如何发展?这个问题很好。目前,Kalshi仍然是一个定制化的产品,很多机构还没有真正使用它。虽然市场活动频繁,但主要是由一些小规模的投机者参与。到目前为止,还没有大型机构进入并寻求对冲。
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 Street size bets placed on these things. But that has not yet happened. I mean, if you're, you know, an investment bank, if you go to the Saxon Morgan Stanley, you're a little cautious about betting on these things, which you haven't done it yet, but eventually they'll go away.
你知道,美联储是否会加息等等这些问题。但是我们认为,一旦这些事物获得监管明确性并随着其受欢迎程度的提高,机构投资者就会加入进来,届时会进行华尔街规模的投资。不过,这些事情目前还没有发生。我的意思是,如果你是一家投资银行,比如说摩根士丹利,你会对这些尚未投资的事物保持一些谨慎态度,但最终这些顾虑会消失。
What I really hope that prediction markets 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 ensure your home because the price is too low. But if we had insurance bets on prediction markets, you can live in an area we can put up a price and say, will the wins get above 80 miles per hour in the next two 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 about $10,000 on it to win $90,000. If it happens and now cover your cover most of your insurance costs, and you only have to buy it when there's a, you know, when there's a problem coming, they will take out all the adjustable claims, all the expense, all the advertising of insurance, making much, much cheaper, and much, more sort of bespoke to what you need to have happened.
我真的希望预测市场能够影响保险业务。你知道,有些地方的保险简直无法获得,因为政府限制了保险的售价。因此,很多保险公司已经退出了佛罗里达州,比如说,你不能给自己的房子投保,因为保险价格太低。但如果我们能够在预测市场进行保险投注,你可以住在某个地区,然后我们设定一个价格,比如说,未来两天内你所在地区的风速是否会超过每小时80英里?假设这发生的概率是10%。如果你认为一旦发生这种情况,你的房屋可能会遭受严重损害,那么你可以下注1万美元,赢得9万美元。如果事情真的发生了,这可以覆盖你大部分的保险费用,而且你只需要在问题即将来临时才去购买。这样的方式将去除所有的可调索赔、所有的开支以及保险的广告费用,使保险变得更加便宜和量身定制,以满足你的具体需求。
So, you know, there's enormous expense in insurance, and this would reduce, reduce a lot of it, making much easier for people to, to ensure what they really have. It won't be as perfect as an insurance claim where my roof low off, give me my money, it'll be more like, well, the win was really 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, you could much more easily hedge your risk than you can with typical insurance products. And it's so much more quantifiable. 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 markets kind of evolve in maturing to some day fully regulated exchange that I 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?
所以,你知道,保险费用是非常高的,而这个方法可以显著减少这些费用,使人们更容易对他们真正拥有的东西进行投保。这种方法不像传统的保险理赔那样完美,比如说我的屋顶被吹飞了,给我赔偿金。而是更像这样:风确实很大,我知道我的房子受到了损坏,但具体损坏到什么程度我并不十分清楚。不过因为这种方法成本更低,你可以比使用传统保险产品更容易地规避风险。而且这种方法的数据更易量化。保险公司当然会尝试评估你需要多少以及他们能给你多少之类的问题,而通过预测市场,这些因素会更加量化。当这些预测市场不断发展并成熟,最终成为我设想的完全受监管的交易所时,你认为大部分的流动性会来自华尔街的大型公司,还是来自普通投资者的资金流呢?
I think it's going to come from both. And I think that it's going to create tremendous opportunities. Let's say you're just a weather person that loves following weather and hurricanes and probabilities, and you live in Florida, and you can put out your own markets and say this area, I think is these are the odds of disruption, and in these areas, these are the odds, and you can have relatively small businesses who have expertise in this stuff, who now have no way to make any money from their expertise, and they can be putting out markets, and they can be making a lot of money and reducing the price for regular people. Yeah, I think it's incredible.
我认为这个将来自于两方面。而且我认为它将创造巨大的机会。假设你是一个热爱研究天气、飓风和概率的气象爱好者,并且住在佛罗里达州,你可以发布自己的市场预测,比如说你认为某个地区发生中断的几率是多少,而其他地区的几率又是多少。这样一来,那些在这方面有专业知识但目前没有赚钱途径的小企业就能发布预测市场,从中赚取丰厚的收入,同时降低普通人获取信息的成本。我觉得这很了不起。
And do you think at all in the future prediction markets can influence outcomes? No, that's like one of the myths that that someone's going to bet, there was that story on polymarket that the French guy was betting Trump, and it was just nonsense. We bet against them. If he bids it up, we'll bet it down. It's not going to influence anything. So all that's a fear that comes to mind, and it's not a zero probability that can happen, but it's really vastly overstated. And what do you think is the most significant obstacle to broader participation in prediction markets, and how can one go about removing that obstacle?
你认为未来预测市场会影响结果吗?不,这就像是一个神话,比如有人会下注改变结果。有个关于Polymarket的故事,说一个法国人赌特朗普获胜,但那纯属胡扯。我们押注反对他,如果他把价格抬高,我们就压低价格。这不会影响任何事情。这种担心可能会出现,但可能性非常小,而且被极大地夸大了。你认为广泛参与预测市场的最大障碍是什么?我们如何才能消除这一障碍?
The biggest obstacles, like as you ask these questions, you can see what could go wrong, what can go wrong, what can go 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 to it, will go away. It's going to take time, but people have fears, and they overstate the downside. But as the product takes place, and people learn how valuable it isn't how much money it can save them, those fears will dissipate. This may take years, but I'm very optimistic that we're going to get there.
最大的障碍在于,当你提出这些问题时,你会想到哪些事情可能会出错。这些可能出错的事情会立刻浮现在你的脑海中,确实有可能会出错,但事实上已经有些问题出现了。然而,随着我们逐渐适应,这些障碍会消失。虽然这需要时间,人们常常会有恐惧,并且夸大可能出现的问题。但是,随着产品的推出,人们会逐渐认识到它的价值,以及它可以为他们节省多少费用,这些恐惧将会消散。这可能需要数年时间,但我非常乐观,相信我们会达到目标。
Before we go back to the episode, I want to take a short break to talk about my sponsor, Row. The generating alpha podcast is presented by Row, the all-in-one banking platform for startups. Thousands of startups like their complexity, product tons, and more use Row. You get everything you need to manage your startups cash, fast banking setup, cards with a 2% cashback, a yield that turns company cash into extra runway. All super important in the early days of launching. But the thing founders really love about Row is their team. Their obsessed with helping founders disrupt the status quo, and will go to the end of the earth's health and the do so.
在我们回到这一集之前,我想利用一个短暂的休息时间来谈谈我的赞助商,Row。Generating Alpha 播客由 Row 提供支持,这是一家为初创公司提供一体化银行平台的公司。成千上万的初创公司,比如 Complexity、Product Tons 等,都在使用 Row。通过 Row,你可以快速设置银行业务,获得返现2%的卡片,以及将公司现金转换为额外资金的高收益,这些对于初创公司早期发展至关重要。但让创始人们特别喜欢 Row 的是他们的团队。他们专注于帮助创始人打破常规,愿意不遗余力地支持他们的事业。
And exclusively for generating alpha podcast listeners and viewers, you'll get a $1,500 statement credit plus a ton of exclusive perks when you manage your company cash with Row. Terms in condition to apply. To learn more, visit rho.co slash generating alpha. Row is a fintech, not a bank. Checking and card services provided by Webster Bank, member of FDIC. See your award terms for details. Thank you, and back to the episode.
专为“Generating Alpha”播客的听众和观众提供,当您使用Row管理公司资金时,您将获得$1,500的账单信用奖励,以及大量独家优惠。适用条款和条件。欲了解更多信息,请访问rho.co/generatingalpha。Row是一家金融科技公司,不是银行。支票和卡服务由Webster Bank提供,Webster Bank是联邦存款保险公司(FDIC)的成员。详情请查看您的奖励条款。谢谢,现在回到节目中。
And I know you come from a very probabilistic background, but with the rise of decision markets, there's under-prediction markets. Is there any type of decision, or even prediction that we should deliberately avoid quantifying? That's a good question. You could put up on a prediction market. Should I marry this girl or not? No. And maybe some, you know, your friends and your relatives might be more objective than you are. But I'd say that's going a bit too far. So my answer sort of would be no.
我知道你来自一个非常重视概率的背景,但随着决策市场的兴起,也出现了预测市场。那么有没有什么决定,或者预测是我们应该刻意避免量化的呢?这是个好问题。你可以在预测市场上提问,比如“我是否该和这个女孩结婚?” 不,这可能太过了。也许你的朋友和亲戚可能比你更客观,但我认为这种做法有点走得太远了。所以我的回答基本上是“不要这样做”。
And what is possible with prediction markets that no one is talking about right now? Or what do you think is possible prediction markets no one's talking about? I think the number one thing it will stop wars because every war is exaggerated. How quickly it'll be ended. It'll be ended. And how little it'll be cost. It will cost. And how many lives will be lost is always lied to us by our politicians.
在当前没人提起的情况下,预测市场还可能有什么用途?或者你认为预测市场有什么可能性是还没有被讨论的?我认为最重要的一点是它能阻止战争,因为每场战争的严重程度都会被夸大。战争会很快结束,它确实会结束。战争的花费和生命损失总是被我们的政客歪曲和隐瞒。
And Abraham Lincoln, you know, in the civil war in 1862, the war department, stop taking in the north, stop taking recruits. They said this war will be over in a couple of weeks. You know, he was off by 650,000 deaths and stuff. So he honestly believed that it was going to be a short, quick war. And obviously it wasn't. And it still reverberates now, 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 going to war.
亚伯拉罕·林肯在1862年的内战中,你知道吗,当时战争部停止在北方征兵。他们认为这场战争将在几周内结束。不过,他低估了战争的持续时间,结果战争造成了65万人的死亡。他真心相信这将是一场短暂而迅速的战争,然而事实并非如此。直到今天,这场内战的恐怖仍然给人留下深刻的印象。如果当时的人们知道战争会如此昂贵和灾难深重,他们可能会尝试找到其他解决方案,而不是诉诸战争。
Another example I can give is driverless cars. There's a lot of opposition to driverless cars because people can imagine a robot going crazy and killing somebody. But, you know, this year, in the next 12 months, about 40,000 Americans will die on their roads. If we had driverless cars, I'm guessing that number would probably be about 10,000. You know, down 75%, we'd say 30,000 lives. If we put that up in prediction markets and said how many lives, 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.
我可以举另一个例子,就是无人驾驶汽车。很多人反对无人驾驶汽车,因为他们能想象机器失控、伤人的场景。但是,你知道,今年和接下来的12个月里,大约有4万美国人会死于交通事故。如果我们使用无人驾驶汽车,我猜这个数字可能会降到1万左右。下降了75%,我们就能拯救3万条生命。如果我们在预测市场上预测,2030年会有多少人死于车祸,数字将比现在低很多,因为人们预计无人驾驶汽车会普及。
It would make policy makers hustle and hurry up and getting driverless cars there. But we're going to have this gain of tens of thousands of people who aren't going to die right now. You know, you so I say, 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 it is. And we move much, much faster. I think it's an incredible kind of use case of it, especially for quantifying things for policy makers to make decisions based off of.
这将促使政策制定者加快步伐,将无人驾驶汽车引入。然而,我们将因此拯救成千上万本可能面临死亡的人。我不确定无人驾驶汽车是好是坏,但如果我们有一个客观的数据,我认为我们会看到它有多好,从而加快推进速度。我认为这是一个令人惊叹的应用案例,尤其是在为政策制定者提供量化数据以便做出决策方面。
And before I move on to kind of a question or two about advice, what is the one message that Jeff Yass wants to tell the world about prediction markets? If you give one message to the world, if you were selling the world in prediction markets, would it be? It is my mother used to say to me, if you're so smart, how come you're not rich, the prediction markets are 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, which you'll get the price.
在我继续问关于建议的问题之前,Jeff Yass想要告诉世界关于预测市场的一个核心信息是什么?如果你要向全世界推销预测市场,你会怎么说呢?正如我母亲常对我说的,如果你真的很聪明,那你为什么还不富有?预测市场是客观的。如果你认为赔率不正确,那就去下注,把赔率调整到你认为正确的位置。如果你真的比市场聪明,你就会赚很多钱,同时也为社会提供了一个好处,那就是让价格回归合理。
You get the price 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 speculators battling it out every day in the market place will be vastly greater. It will insult the college professors, which as far as I'm concerned is a good thing.
你需要定价合理。如果你无法盈利,也许你应该考虑安静下来,可能市场比你懂得更多。这可能会让你遇到的每位大学教授感到愤怒,因为他们想成为专家,但实际上他们不是。每天在市场上搏斗的众多投机者的智慧要强得多。这可能会冒犯大学教授,但在我看来,这是一件好事。
I agree. I'm going to give you an example when my daughter was 12 years old. Obama was running against Hillary Clinton in the primary. One of the most famous political scientists in America was on TV saying, no, Obama Hillary Clinton is going to win. She's up by 30 or 40 points. My daughter said, go check trade sports. It was just the only place at that time to look. And she said, Obama has a 22% chance of winning.
我同意。我来给你讲一个例子,那是我女儿12岁的时候。当时奥巴马正在与希拉里·克林顿争夺总统初选的胜利。一位美国非常著名的政治学家在电视上说,希拉里·克林顿将获胜,她领先30到40个百分点。我女儿则说,要去看看TradeSports平台(当时唯一可以查看的地方)。她说,奥巴马有22%的胜算。
So the market place 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 as 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 polyps high. And that's the power of prediction markets. That's that's an incredible incredible incredible example.
所以市场知道奥巴马是个特别的人物。他很有魅力,但当时大家并不熟悉他,而大家都知道希拉里。所以他在几个月前落后35个百分点,这并不是真的有什么意义。我用这个例子说明,我12岁的女儿对谁将赢得初选的预测比世界上最顶尖的政治专家还要准。这就是预测市场的力量,这是一个非常非常非常了不起的例子。
And I'm going to ask two questions about advice. The first one being as a high schooler today, I'm a high schooler and I'm given all the success that you've had and given all the hiring that you've done. What should students today study? I would really strongly suggest. I mean, obviously, you know, computer science, you got to be computer literate and you got to you got to understand what AI is coming from. But if you really want to be a decision maker under uncertainty, which is what humanity is, you have to learn probability statistics so much of what happens, you know, in the world is you are making a decision.
我有两个关于建议的问题。第一个是,作为一名当今的高中生,我是一名高中生,考虑到您取得的所有成功以及进行过的所有招聘,今天的学生应该学习什么?我会非常强烈地建议。我的意思是,显然你要懂计算机科学,你必须具备计算机素养,理解人工智能的起源。但如果你真的想在不确定性中做出决策,也就是人类的实际情况,你必须学习概率和统计学。因为世界上发生的许多事情都是需要你做出决策的。
And if you're not really informed on the mathematics behind probability 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 there are always a lot of hurricanes? And what's the volatility around hurricanes is it vary by a lot? Is this such an outline? Does this prove this 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 some some knowledge and some learning, but you really can interpret events in the world unless you have a firm background in probability statistics.
如果你对概率统计背后的数学知识不够了解,你可能会做出错误的决定。例如,当你看到有飓风季节,并且出现了很多飓风时,你可能会问:这是不是一个大问题?还是每年都有很多飓风?飓风的变化性有多大?这是个例外情况吗?这能证明全球变暖的存在,还是这只是一个偶然现象?这就像是要分辨有用的信息和无关的信息。而要能够区分这些情况,需要一些知识和学习。事实上,除非你具备扎实的概率统计背景,否则很难正确解读世界上的事件。
And I'll give you another little anecdote that like the Russians in 1958, you know, had Sputnik and we were afraid that we're going to beat us to the moon. And they did beat us to the moon, but not a man on the moon. So the United States 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, get into a good college, you're going to have to learn calculus. Again, to med school, you have to learn calculus, which is absurd, but you're never going to use it.
我再给你讲一个小故事:1958年,苏联发射了人造卫星,让我们担心他们会在登月竞赛中超过我们。虽然他们确实在某方面超过了我们,但并不是指人类登陆月球。为了应对这一威胁,美国推出了科学教育计划,要求每个人都必须学习微积分。我听说过这个计划。于是,我们都必须学习微积分,因为我们不能让苏联超过我们。现在,为了进入好的大学,你必须学微积分;为了进入医学院,你也必须学微积分。这有点荒谬,因为你实际上从来不会用到它。
But no one learned how to use probability statistics, because it was not it was considered secondary to calculus. So we have a country that sort of knows, you know, fair amount of calculus, but very little probability statistics. And it's just not the way it's just not what's necessary to be a good decision maker to be a good 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 probability statistics.
没有人学会如何使用概率统计,因为它被认为是次于微积分的。因此,我们的国家在一定程度上了解微积分,但对概率统计了解甚少。而这并不是成为一个优秀决策者或好公民所需要的知识。改变这种状况几乎是不可能的,因此你需要自己努力,确保自己具备概率统计的素养。
And you certainly understand Bayesian analysis, because there's you know, all these studies done that they as Harvard kids in Harvard medical school who are going to be researchers, some basic questions after they got the data about about diseases and they were off by a factor of a hundred. I need to very, very smart people, but they didn't know Bayesian analysis and they were and they were ridiculous, but they 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. Oh, 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, but they're not trained that way.
你当然理解贝叶斯分析,因为曾有研究对哈佛医学院的学生进行调查,这些未来的研究人员在获得有关疾病的数据后,回答一些基本问题时,他们的结果偏差高达一百倍。这些人非常聪明,但他们不知道贝叶斯分析,因为这在医学院里没有教授过。如果你曾与医生交流时感到沮丧,问他们:“医生,我患这种病的几率是多少?”而他们回答:“哦,我不知道,可能有可能没有。” 你可能会想,希望他们能给出更明确的答案,但他们还没有接受过那样的训练。
And that's a tragedy. You have to make sure that you go out of your way to get that to get that training. I think that's a very valid point. And I'm currently learning calculus. I think I might get to do a little statistic education on my own. Calculus is wonderful. It's my favorite subject and it's great. It's beautiful. It's art. It's that's key to science and everything like that. But it's it's of limited value to most people.
这是一个悲剧。你一定要不遗余力地去获得培训。我认为这是一个很有道理的观点。我目前正在学习微积分,我想我可能会开始自学一些统计知识。微积分是很棒的,也是我最喜欢的学科。微积分很美,是一种艺术,是科学以及其他各个领域的关键。然而,对大多数人来说,它的实用性有限。
And I want to ask one more question that I do at the end of every interview. I think I asked it to 39 people so far. I'm 16 right now. If you would 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? I take it as romantic advice. I mean, I believe in markets. It's like, don't go out with somebody that your friends think is a nutcase. But you can get caught up. And if you say to my friends, be honest, I won't punish you, try and do it anonymously. Give me your marketplace. Am I making a gigantic mistake?
我要问一个我在每次采访结束时都要问的问题。目前为止,我已经问了39个人。我现在16岁。如果你能给今天的16岁孩子一条建议,可以是生活建议、职业建议,甚至是情感建议,那会是什么呢?我把它当作情感建议。我的意思是,我相信社会评价。就像不要和你朋友认为很奇怪的人出去约会。但你可能会被卷入其中。如果你对我的朋友们说,诚实点,我不会怪你,试着匿名告诉我。给我一些社会评价看看,我是不是犯了一个巨大的错误?
So many lives are ruined because you get involved with the wrong person. And no one wants to speak up. So you got to come up with a mechanism. Hey, friends, you're my friends. I trust you. And I'll do this anonymously. You know, should I should I know? Is this person too nutty for me to be going for me to going out with you could prevent a lot of horrible relationships from happening there? That would be my number one advice because one of the things that we do in reverse, the bigger the decision, the less time we think about it.
很多人的生活因为和不合适的人在一起而受到影响,而且没有人愿意说出来。你需要想出一个办法。“朋友们,你们是我的朋友,我信任你们。我会匿名问:‘我应该知道些什么吗?这个人是不是有些极端,以至于不适合和我约会?’”这样可以避免很多不好的关系。我的首要建议就是:越是重大决定,我们反而越少花时间去仔细考虑。
You know, if you're buying a selling a stock and it's basically irrelevant what you're doing with the markets of 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, as 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 worrying about the minor things and not enough time worrying about the big things.
你知道,如果你在买卖股票,而无论市场如何,其实这对你影响不大,你仍然会花费大量时间在这上面。而当你在决定和谁结婚、与谁建立关系时,基本上却往往没有经过太多思考就做了决定。而事实上,一个对你的人生有巨大影响,而另一个影响却很小。然而,我们常常在小事情上花费太多时间,却没有在大事情上投入足够的时间和精力。
I mean, from a living life experience, I think I agree. And I recommend anyone who's listening to this to listen to my episode with any you about decision making. I think it's an excellent compliment to this 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. It was fun. Okay. Bye.
我的意思是,从生活经验的角度来看,我觉得我同意这一点。我推荐正在听这个的人去听我和Ainy关于决策制定的那期节目,我认为它是对本期节目的很好的补充。但杰夫,非常高兴能邀请到你。感谢你的到来。我非常感激。祝好运。真的很感谢。很有趣。好,再见。