这些才是真正从预测市场赚钱的投机者

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你好。

Hi.

我是埃德·卢德洛。

I'm Ed Ludlow.

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彭博音频工作室。

Bloomberg Audio Studios.

播客节目。

Podcasts.

广播。

Radio.

新闻资讯。

News.

大家好，欢迎收听新一期的《Odd Lots》播客。

Hello, and welcome to another episode of the Odd Lots podcast.

我是吉尔·魏森塔尔。

I'm Jill Weisenthal.

我是特蕾西·阿洛韦。

And I'm Tracy Alloway.

特蕾西，我能分享一个我觉得挺‘老派’的观点吗？

Tracy, can I, reveal a very, boomer take of mine, so to speak?

请说。

Go on.

我真的很讨厌那些被称作暴富捷径的东西，还有把股票交易游戏化这一套

I actually really loathe anything that's sort of identified as get rich quick, or the gamification of stock trading, or

游戏化

Gamification.

比如说

Like

把股票交易游戏化

Gamification of stock trading.

那应该是另一回事

Gamification would be something different.

大概确实是另一回事

That would probably be something different.

我不明白自己为啥这么念这个词

I don't know why I pronounce it that way.

股票交易游戏化，还有赌博广告

Gamification of stock trading, gambling ads.

我特别讨厌那些暗示你一定能赢的赌博广告。

I really don't like gambling ads that imply that you're going be a winner.

虽然我对预测市场很感兴趣，但我不太喜欢大部分这类营销手段。

I really don't like, even though I'm very interested in prediction market, I generally don't like a lot of the marketing.

《华尔街日报》有篇很棒的文章讲了Polymarket和他们的广告，说什么人人都能赢，到处都是免费的钱，你只要用自己对降雨量之类的知识去交易就行。

There was a really good Wall Street Journal article about Polymarket and these ads that they had created, this idea that everyone's a winner and there's all this free money out there, you just have to trade your knowledge of whatever rainfall or whatever.

这些广告真的让我心里特别不舒服。

It really viscerally bothers me.

是的，我觉得这正是预测市场和传统市场的关键区别：这是零和游戏，你下注，就有人在对面赌相反的结果。

Yeah, I think this is the key difference with prediction markets is it's zero sum, If you make a bet, someone is on the other side taking the opposite of that bet.

这跟传统股市不太一样，传统股市里你能拿到分红，卖出时还能套现，有人接盘。

And that feels a little different to me than traditional stock markets where you would get some cash flow, some dividend, you sell, monetize whatever and you someone else buys.

没错。

No.

我完全同意。

I totally agree.

我的意思是，你看看。

I mean, look.

确实都是零和的。

There are certainly zero sum.

在我们说的常规交易里，零和市场多了去了。

There are all kinds of zero sum markets in what we'd call trad five.

对吧？

Right?

期货、期权，都是零和的。

Futures are zero sum options.

零和的，诸如此类。

There's zero sum, etcetera.

但另一方面，就算我们说期权、期货、互换这些零和游戏，那也不是投资。

But on the other hand, like but, yes, zero sum games, even if we're talking about, like, options or futures or swaps or whatever, don't that's not investing.

那是交易。

That's trading.

那就是交易。

That's trading.

而交易往往带有投机性质，很多人因此亏了很多钱。

And that's can often be speculation, and a lot of people lose a lot of money.

在这些市场环境中，我们很清楚，大多数人其实都会亏钱，虽然也有少数人非常专业，但很多人以为自己能进入这些新市场，比如期权或者加密货币，就能赚大钱。

And when we know in a lot of these environments, a lot of, like most people lose, some people are very sophisticated, but a lot of people think they're gonna go into some of these new markets or whatever.

不管是预测市场，还是在Robinhood上交易期权，幻想着一夜暴富，还是说加密货币——我觉得这本质上也是零和游戏——他们根本没搞明白。

Whether we're talking about prediction markets, whether we're talking about options trading on Robinhood and they have dreams of making a lot of money, or just talk about crypto, which is also zero sum, I think, and they don't.

是的。

Yeah.

完全正确。

Absolutely.

关于预测市场，还有一个有意思的地方，从市场结构的角度来看，我们之前和Susquehanna做过相关节目，就是流动性的问题。

The other interesting thing about prediction markets, just from a sort of market structure question, and we've done episodes on this with Susquehanna, is the liquidity aspect.

随着更多专业投资者入场，会不会逐渐消除那些早期交易者曾经拥有的优势？

And as more professional investors get in, does that start to maybe arbitrage some of the edge that certain traders have seen so far?

你读到这些故事，说普通老百姓在预测市场上赢了华尔街。

Because you read these stories, specific story, the average guys outsmarting Wall Street on prediction markets.

普通老百姓？我倒怀疑他们是不是真那么普通，但你可以想象，如果越来越多专业人士进入预测市场，想赢他们可能就越来越难了。

Average guys, I have a question over whether or not they're actually average, but you can imagine a scenario where more professionals get into prediction markets, and maybe it becomes harder to actually beat them.

没错。

Absolutely.

在听这个之前，我建议大家都回头去听听我们和杰里米·马利奇的那期节目，他在苏克兰证券负责预测市场业务。

Think everyone should actually go back and listen to our episode that we did with Jeremy Malich, who runs the prediction markets desk over at Susquehanna, before listening to this.

他还提到，即使是一些流动性很低的市场，参与者也会非常看重价格，因此敢基于价格做场外交易，这里面有不少有意思的东西。

Because the other thing he talked about is how even some of these low liquidity markets, they put a lot of stock in the price, and therefore they can feel comfortable doing OTC transactions based on what the price so there's interesting stuff going on.

你提到那篇《纽约时报》5月26日的文章，说普通人在预测市场上赢了华尔街。

Anyway, you mentioned this article, came out in The New York Times, May 26, the average guy is outsmarting Wall Street on prediction markets.

确实，有些人确实赚得不错。

And it is important, There are some people who are doing very well.

那些在其他领域被称为‘高手’的人，就像鲨鱼一样敏锐，水平非常高。

And if a handful of they would say sharps in various other contexts who are like sharks, very good.

我们大多数人都是小鱼，只有少数人能赚得不错。

Most of us are minnows and some people do really well.

而大多数人根本就是外行。

And they majority are total idiots.

对吧？

Right?

我要是去玩，肯定很快就把一千美元输光了，其中一部分归平台，大部分则会被那些最顶尖的交易员拿走，毕竟这是点对点的交易。

If I went on there, would quickly lose a thousand dollars and some fraction of it would go to the house and a bunch of it would go to some of the best traders, most likely, because it's peer to peer.

总之，我们这次要做一个特别复杂的专题节目。

Anyway, we have a very complicated special episode.

我都不知道这节目最后能做成什么样，但我觉得挺有意思的。

I don't even know how this is gonna work, but I thought it'd be fun.

这篇报道写得真不错。

So this was a great piece.

我们请来了报道的记者，还有几位顶尖交易员一起参与。

We have the reporter on the piece with us as well as a couple of the the Sharps.

他们都在一个Discord群里，好几个人在一起。

They are in a Discord together, a bunch of them.

我们今天只跟其中两位聊聊。

We're just gonna be talking with two of them.

那个Discord群叫‘Maga Kiwi俱乐部’。

The Discord is called The Maga Kiwi Club.

这名字听着挺有意思。

That sounds fun.

所以我们一会儿会跟记者亚当，还有Maga Kiwi俱乐部的几位成员对话。

So we're gonna be talking with Adam, the journalist, as well as some of the members of the Maga Kiwi Club.

我们请来了布莱恩·戈德温，就是文章里提到的那位。

We have Brian Golden, who is in the article.

他被认定为在交易通胀合约方面特别厉害的人。

He was identified as someone who's really top notch at trading inflation contracts.

还有丹尼尔·赖希曼，他平时用的名字叫Carnitas Taco，主要关注选举和政治话题。

We have Daniel Reichman, who also goes by Carnitas Taco, who does a lot of election and politics.

当然，我们这儿还有亚当，他是一名记者、记者兼制作人，住在纽约，最近加入了科技公司Notion——现在好多记者都可能去科技公司工作。

And of course, we have Adam here, who's a journalist, reporter, and producer here in NYC, recently joined the tech company Notion, which all journalists might end up working at tech companies.

确实如此。

Well, we do.

所以我们平时在播客里很少能跟Carnitas Taco聊上几句。

So We don't get to talk to a carnitas taco No.

真的很少。

That often on the podcast.

我对这一期特别期待。

I'm very excited about this episode.

谢谢你们三位，布莱恩、丹尼尔和亚当，来参加《Odd Lots》。

Thank thank all three of you, Brian, Daniel, and Adam, joining us on Odd Lots.

很高兴能来。

It's great to be here.

非常荣幸。

It's a pleasure.

谢谢。

Thanks.

我们先从你开始吧，亚当。

Let's just start, Adam.

说实话，我们其实是挺信任你的。

You know, I guess actually we're sort of trusting you.

我们已经把一部分判断权交给你了。

We've sort of delegated some of our judgment.

但你是怎么发现，世界上真有人一直参与预测市场的？

But you, you know, you reported out this story like, how did you like identify that there exist people in the world who consistently went on prediction market?

是的。

Yeah.

说真的，我一开始对这些市场感兴趣，是因为自己玩过。

I mean, I I think it started for me I got very interested in the in these markets because I was playing around in them.

对吧？

Right?

是的。

Yeah.

我当时输了很多钱。

And I was losing a lot of money.

也不是特别多，但对我来说已经不少了。

You know, not a lot a lot of money, but I for for me, it was a lot of money.

我就在想，我到底是在输给谁呢？

And I was wondering, who who the heck am I losing this this money to?

是市场做市商吗？

Am I losing to market makers?

还是像SIG这样的机构？

Am I losing to, you know, the the SIGs of the world?

是的。

Yeah.

我突然想到，也许外面真有一些人比我还更敏锐。

And it occurred to me maybe that maybe there are some people who are just a little bit sharper than me who are out there.

于是我开始到处打听，慢慢就开始留意，嗯，到处看看。

And And I started asking around and I sort of started, you know, looking around on, you know, just started

是的。

Yeah.

其实就是到处问一问。

You know, just just asking around basically.

一个人引荐一个人，不知不觉你就进了个Discord群，里头一堆人，水平高得吓人，远超一般人。

And one person sort of leaves the next and and suddenly you find yourself in a Discord with a lot of guys who are just really crushing it sharper than anybody else.

其中就有两个人，叫布莱恩和丹尼尔。

And, you know, two of those folks are are Brian and Daniel.

那布莱恩和丹尼尔，跟我们说说这个Discord群吧。

Well, Brian and Daniel, tell us about the Discord group.

对。

Yeah.

根据我从文章里看到的，好像一群做预测市场的交易员聚在一起，互相分享信息。

Because from what I can tell from the article, you know, a bunch of prediction market traders get together, share information.

你们会不会分享一些实际的盈亏数据？

Maybe you share some actual p and l.

听起来像是一个多策略基金。

It kind of sounds like a multistrat

是的。

Yeah.

对，就是那种对冲基金分销商，多策略类型。

Hedge fund Distributor multistrat.

每个人各自管理自己的投资组合。

Where everyone's, like, in charge of their own portfolio.

不过还是跟我们说说这个Discord群组吧。

But tell us about the Discord group.

对。

Yeah.

首先，‘Maga Kiwi Club’这个名字其实是个讽刺。

Well, the first thing is the Maga Kiwi Club name is ironic.

这根本不是什么Maga俱乐部。

It's not a Maga Club.

但群里的大多数名字，都是聊天过程中自然冒出来的内部笑话。

But most of the names of the group end up being some form of inside joke that emerges during the conversation.

因为我们几乎每天一整天都在聊市场，从经济到文化，再到体育。

Because we spend almost all day, every day talking to each other about markets ranging from economics to culture to sports.

这么说吧，有点像复仇者联盟的模式，群里每个人都有自己的专长。

And it is sort of like that, I would describe it almost as an Avengers model where there are different people in the group that have different specialties.

每个人都有自己的投资组合，但信息交流的方式有种社区精神——我知道，如果我给丹尼尔他们提供关于通胀的有用建议，他们也会反过来给我一些我擅长但不够精通的领域的建议。

And everyone has their own portfolio, but there is kind of a spirit of community in the way that information is exchanged and that I know that if I am giving helpful tips to Daniel and others on inflation, that they're going to give me helpful tips back on things that I may be adequate at but not expert at.

我们就是这样互相配合的。

And we sort of work together in that way.

是的，我们很多人其实从2016、2017年PredictIt还是主流预测市场的时候就认识了。

Yeah, so a of us actually know each other dating back all the way really to 2016, 2017 when PredictIt was the dominant prediction market.

我们最初是通过政治话题认识的，因为那时候预测市场主要玩的就是政治。

And we mostly know each other through politics originally because that was the prediction market game.

我们大多数人一开始就很关注政治，甚至可以说非常热衷。

Pretty And much all of us had some interest in politics or very large interest in politics to start with.

预测市场这个领域现在规模大了很多，投入的资金也越来越多。

And the prediction market space has grown very large and the money has gotten larger.

但其实很多事我们本来就会做，比如分析选举、寻找真相、一起解开各种谜题。

But a lot of us would be doing a lot of this stuff anyway, would be unpacking elections, trying to find the truth of things, trying to solve puzzles together.

只是恰好这个圈子现在变大了，而我们做的事跟以前没什么两样。

And it just so happens that the space has grown large around us, but we're kind of doing the same thing we've always been doing.

我认识布莱恩和丹尼尔的过程是这样的：我认识了一个特别喜欢研究选举的交易员。

The way I found myself, you know, talking to Brian and Daniel was, you know, I met another trader who who loved elections.

说起来，这算是我这段经历的起点。

You know, this is sort of where where the journey began for me.

我们一开始只是聊选举，大概过了六周，不断交流、积累信息，他才突然说：哦，对了。

And, you know, we were just talking about elections and, you know, it was after maybe six weeks of of talking and source building that finally he says, oh, yeah.

我其实一直在和另外好几个人保持联系。

I'm actually talking to all of these other people.

我不是一个人在做这件事。

I'm not just doing this alone.

我不是一个人在地下室埋头建模型。

I'm not just building models alone in my basement.

我是跟一大群人一直在交流，真的。

You know, I'm like, I'm talking to all of Yeah.

我所有的同事都是这样。

All of my colleagues really.

我说，同事？

And I said, colleagues?

你在对冲基金工作？

You're at a fund?

不是。

No.

不是。

No.

不是。

No.

不是。

No.

不是。

No.

不完全是。

Not quite.

我们其实都在一个Discord群里。

We're actually all in a Discord together.

是的。

Yeah.

我得说，听起来确实挺有意思的。

I have to say it does sound pretty fun.

等等。

Wait.

咱们私下说，这个群是百分百男性吗？

Let's just between us, is it a 100% male?

这个群确实是。

This one is.

对。

Yes.

明白了。

Okay.

谢谢。

Thanks.

我本来就觉得应该是这样。

I sort of assumed as such.

我问你们个问题。

Let me ask you guys a question.

我就像个EMH兄弟。

I am like an EMH bro.

我觉得总的来说，各个市场里大多数资产的价格都还算合理。

I think that generally across all markets, most people, markets are generally well priced.

至于预测市场，我觉得想靠它赚钱其实挺难的，但股票市场不一样——虽然我也觉得股价总体上反映得很充分，可还是有人能持续赚钱，不管是像巴菲特那样的长期投资，还是做多空策略的从业者。

And I think that with prediction markets too, in the specific sense that I think it is difficult to make money, but evidently in stocks, even though I think stocks are efficiently priced, some people seem to consistently make money in stocks, whether they're a Warren Buffett strategy or whether they work at a long short.

显然，也有人能在预测市场上持续获利。

And evidently, some people consistently make money in prediction markets.

你们怎么看待市场的有效性？价格到底能在多大程度上反映真实信息？

How do you guys think about market efficiency generally and how high quality that signal is on a price?

像我们媒体人，经常引用预测市场的数据，你们觉得这些数据靠谱吗？还是说，其实到处都是明显的套利机会？

Would you say those of us in the media who sometimes increasingly quote prediction market quotes, like these are do you find are they decent or when you look at them, are they just like, there's just easy pickings everywhere?

如果所有价格都完全有效，那这个圈子里的人也不可能拿到这么高的回报了。

Well, I think if they were all efficiently priced, you wouldn't be able to get some of the returns that some people in this group have gotten.

要是价格信号真那么精准，想反复打败市场会难得多。

I think it would be much harder to enter and sort of crush markets repeatedly if the price signal were better.

我觉得现在有不少预测市场的推崇者，总爱说预测市场是未来，是超级精准的价格信号，比其他所有方式都准。

I guess where I see it is that there is a lot, who I would call kind of prediction market evangelists, would like to go out and say, Oh, prediction markets are the future, they're this incredible price signal, and they're more accurate than all these other places.

我不太信这个，我见过太多市场明显严重偏离了。

I don't really believe that, I've just seen too many markets that are way, way off.

我觉得预测市场有价值，是因为错了有代价，对了也有回报。

The reason that I think prediction markets have value is because there are consequences when you're wrong, and there are consequences when you're right.

世界上有太多所谓专家，嘴上说得很响，但说错了、误导了人，却不用承担任何后果。

And we have so much kind of expertise in the world that says a lot of things under the expert banner, but then doesn't really have any bills to pay when they mislead people or when they're wrong.

所以对我来说，这个体系最吸引人的地方就是：你错了，就得付出代价。

And so really the most appealing part of this ecosystem for me is that when you're wrong, you pay a price.

如果媒体在报道经济和政治时也能这样，我觉得我们国家的专家文化会更好。

And I think that we might have a better expert culture in this country if if that were true in media that covers economics and politics.

这得看具体市场，价格的准确性因市场而异。

It depends on the market, certainly, in terms of how correct these prices are going to be.

但回到乔在开头提到的，预测市场本质上是零和游戏，我们押注的大多数事件都是零和的。

But going back to what Joe was talking about in the intro about the zero sum nature of these prediction markets, a lot of the events, most of the events that we're betting on are zero sum.

比如一场选举，两个阵营砸重金，最后只有一个赢，另一个只能认输回家。

We have an election and two campaigns spend a ton of money and then one wins and one goes home.

而这个国家的政治本质，乃至全球各地的政治，都是人们生活在完全隔绝的环境里，信奉截然不同的东西，甚至以完全相反的方式看待现实。

And the nature of politics in this country, especially but all over the world, is that people live in totally siloed environments and believe different things and often engage with reality in totally opposite ways.

通过某种机制来为自己的信念下注，试图逼近真相，虽然不可能完美高效，但目前来看，它至少比我们现有的其他方式都要强。

And having a mechanism to essentially bet your beliefs and try to find real truth is, know, it's not going to be a perfectly efficient way, but at the moment it seems to be better than at least anything else we've got.

我觉得，正如丹尼尔提到的，和通胀不同，政治牵动的是情感，更容易陷入这种信息孤岛效应。

Well, I think to Daniel's point, you know, unlike inflation, politics brings out matters of the heart and is, I think, much more subjected to that siloed effect.

就拿刚刚结束的洛杉矶市长初选来说，斯宾塞·普拉特的胜选赔率被炒得离谱，高得不可思议。

I mean, can look back at the Los Angeles mayor primary that just happened, and Spencer Pratt's price to not just make the top two, but to actually win the the mayorship of Los Angeles got so unbelievably high.

当时，右翼媒体圈，甚至一些主流媒体，都在隐隐约约地试探：这事儿真能成？

And there was this right wing media ecosystem, and sometimes even a mainstream media place that was, like, sort of flirting with this idea, like, can this happen?

我认识的每个人都在说，这事太离谱了。

Everyone I know is is is saying that that this is live.

我认识的圈子里，没人不押注斯宾塞·普拉特不会当选洛杉矶市长，因为根本没那个数学上的可能性。

And there wasn't a Sharp that I knew that didn't have one of the biggest positions of their lives on Spencer Pratt not winning the mayorship of Los Angeles because the math was just not there to be mathing.

洛杉矶是个民主党领先42个百分点的城市。

Los Angeles is a Democrat plus 42 city.

共和党人不可能赢下这场选举。

A Republican is not gonna win that race.

但这种信息茧房——人们只关注推特上的某些账号、只看特定媒体——会让人误以为某件事发生的证据多得不得了。

But this this sort of siloed media of people sort of only following certain accounts on Twitter and watching certain media can lead to what feels like to them an o- an abundance of evidence in a certain thing happening.

从这个角度看，我认为选举永远是最容易定价错误的市场，因为人们并不会真的对‘我希望通胀是3.6%而不是3.8%’这种事产生情感上的投入。

And in that sense, I think that elections will always be some of the most mispriced markets because, you know, people don't really have a heart connection to, gosh, I really believe I want inflation to be 3.6x instead of 3.8x.

我觉得未来经济市场可能会趋于收紧，但像丹尼尔这样的人运气不错，因为我觉得选举市场总会相对更模糊一些。

I do think that the future of economics markets is probably a tightening, but people like Daniel are fortunate because I think elections will always be a little softer.

上一次选举时，我就遇到过这个问题。

This was my problem in the last election.

我花了太多时间刷Reddit，结果以为哈里斯会赢，最后大吃一惊。

I spent way too much time on Reddit, and so I thought Harris was going to win, and then I was very surprised.

再深入一点，当咱们说你们在这个市场有优势时，很多人，尤其是投资者，总会说自己有优势，但其实往往只是运气好过几次，然后硬是编出一套故事来。

Just to press on this further, when we talk about you guys having an edge in this market, you know, a lot of people will say, a lot of investors will say that they have an edge, and usually it's like they got lucky a few times and then they built a whole narrative around it.

那你们能说说，你们的做法到底跟别人有什么不一样吗？

But how would you describe what you are doing differently to others?

你刚才提到要理性看待数据，别让情绪干扰，还要避开社交媒体的回音壁之类的。

So you mentioned looking rationally at the numbers, keeping feelings out of it, social media echo chambers, that sort of thing.

但你们同时也做实地调研。

But you're also doing some original on the ground reporting.

你们有自己的模型。

You have your own models.

那你们具体的优势到底在哪里？

What is the edge exactly?

很大程度上，就是我们投入的大量工作。

A lot of it is really just work that we put in.

比如保持开放心态，愿意改变想法，试着量化并验证自己的假设。

So it's being open to changing your mind, trying to quantify and test your assumptions.

在政治领域，很多东西都有历史可循。

With politics, it's a lot of history.

其实就是知道，这种事情以前发生过。

Mean, it's just knowing this has happened before.

这就是趋势。

This is the trend.

我们觉得，这次的趋势可能比上次大得多，上次只有一半那么大，现在看到数据出来，就要不断调整自己的预判，无论赢了选举还是赌注。

We think the trend might be this big this time when it was only half as big last time and then seeing numbers come in and trying to stay calibrated with your assumptions when you win an election or win a bet.

你不能只说，赢了就完事了。

You don't just say, Yay, I won.

你要问，我到底赢了多少？

You say, How much did I win?

我当初对概率的判断是多少？

What was my belief in the probability?

就是要深入挖掘，彻底拆解清楚。

Just like really digging in and unpacking it.

最近资金规模变大了，我们也开始更认真地学习。

And then the money has gotten bigger recently, we've started trying to learn more.

我们尝试做过一些民意调查。

We tried to do some polling.

德克萨斯州初选时，我们自己开展了电话民调。

And the Texas primary commissioned our own phone polls.

团队里有些人做过实地上门 polling，那次我们和亚当一起做了更大规模的走访，文章里有详细记录。

Some of the guys in the group have done this live door to door polling, which we did a bigger trip with Adam that's written about in the article.

但关键还是踏实做事、开放接受数据，并愿意调整自己的判断。

But the edges it's mostly just work and openness to data and changing your mind.

我觉得丹尼尔还没把我们团队在选举分析上的实力说够。

I think Daniel's even underselling how good the elections team is in our group at elections and what they do.

举个例子，洛杉矶市长选举那会儿，这些人早就建好了模型，预测选举夜各区域的早期投票和现场投票情况，算出普拉特需要多少票才能胜出。你知道加州的选票很多都是后半夜才统计的，要准确预判这些票的走向特别难。

I mean, can tell you for the Los Angeles mayor's race, these guys had a model built of, on election night, what certain areas should look like in terms of the early vote, the in person vote, what it would take for Pratt to have what he needed, you know, what we know from California is that so much vote comes in late, that really predicting what that vote is going to look like.

所以这些人之前就按选区和区域做了大量历史数据分析。

So these guys did historical work by precinct and region.

选举当晚，妮莎·拉曼在向支持者致意时都哭了，以为自己输了，但丹尼尔和团队却在赌她能进入前两名——他们对她的胜算判断，比她自己的竞选团队还要乐观。

And on election night, when Nithya Raman was in tears speaking to her supporters because she thought she'd lost, Daniel and the crew were betting on her to make it to the top two, because they had a better vibe on her chances than I think her actual campaign did.

真厉害。

Wow.

我觉得，其实根本不可能高估这个选举团队在数据分析上的能力——他们不需要等好几天才出结果，而是能根据实时涌入的数据立刻做出判断。

So, I really, I think he's it would be hard actually to oversell how good this elections crew is with data, and not just needing days to solve it, but being able to really solve on the fly based on incoming numbers.

你好。

Hi.

我是巴里·里特尔茨，欢迎收听我的《商业大师》播客。

I'm Barry Ritholtz inviting you to join me for the masters in business podcast.

每周，我都会邀请塑造市场、投资和商业格局的人物来对话。

Every week, we bring you conversations with the people who shape markets, investing, and business.

我会和首席执行官、诺贝尔奖得主、市场创新者，以及传奇投资者畅谈。

I speak with CEOs, Nobel laureates, market innovators, and legendary investors.

不管你投资的是股票、债券、房地产、大宗商品，还是加密货币，这些对话你都绝对不能错过。

Whether you own stocks, bonds, real estate, commodities, even crypto, these are discussions you absolutely need to hear.

请在苹果、Spotify，或你常用的任何平台订阅《商业大师》播客。

Subscribe to the Masters in Business podcast on Apple, Spotify, or anywhere you listen.

虽然我原本觉得价格大体上是有效的，但我在选举夜注意到，由于不同批次选票的陆续公布，市场会涌现出大量噪音。

Even though, like, my assumption was that prices are somewhat efficient, I do notice that on election nights, there's a lot of noise based on timing of vote batches with multiple elections.

比如最近加拿大总理选举时，我们就看到过这种情况——因为一些早期投票数据明显不具代表性，导致Polyev的得票率突然飙升。

We even saw it in the recent Canadian prime minister election, for example, where there was a spike for Polyev on election night because of some early votes that were clearly not representative.

所以这总让我怀疑，我是不是根本不该引用这些数据。

So that always does make me sort of question whether I should ever be quoting these things.

但布莱恩，在亚当的文章里，还有亚当你自己，能不能谈谈你们的通胀模型？有些经济学家说你们是通胀领域的‘诺stradamus’。

But Brian, in Adam's article, and maybe Adam, you could talk about this, your inflation models are described by some economists as quote being Nostradamus of inflation.

先给我们大概讲讲你们在做什么，再解释一下：既然你们被称作通胀界的预言家，为什么不去管理一个几十亿美元的利率对冲基金呢？马特·莱文在他的通讯里就提过这个问题，这说不通啊。

Give us a general overview of what you're doing and explain to us why you are not working at a I think Matt Levine talked about this in his newsletter, it doesn't make sense if you're like an inflation Nostradamus, why aren't you managing a, you know, multi billion dollar rates hedge fund or something?

不过得澄清一下，没人真这么叫过我们，但

Well, to be clear, nobody's called, but

我来叫。

I will.

我做的第一件事是研究劳工统计局计算通胀数据的公式，他们是怎么处理所有价格输入的。

The first thing that I did was the BLS has a formula to the way that they take all of their price inputs to calculate the inflation number.

我知道你们的听众可能已经了解，但为了方便大家理解，我得说明一下：通胀数据不是单一数字，而是由两百多个子类目组成的‘一篮子商品’价格变动构成的。

As I know your audience knows, but just to set the table, it's not one big number, it's 200 plus subcategories of how prices have moved, which we call the basket of goods.

每个月，这个商品篮子中各个子类别的权重都会根据美国人实际支出的变化而调整。

And the basket of goods changes what percent each subcategory is worth every month based on how much Americans are spending on it.

说到这个公式，说实话，我本科读的是戏剧，纯粹是个来自中西部的戏剧生。

So this formula to me, I mean look, my degree, I have an undergraduate degree in drama, I'm just a theater kid from the Midwest.

这玩意儿太复杂了，我敢说，我对宏观经济的了解，可能比你们请过的任何嘉宾都少。

Like this is very complicated, I'm sure that I know less about the macro economy than any guest you've ever had.

但我还是用Excel把他们的公式重新做了一遍。

But I rebuilt their formula on Excel.

花了差不多三个月，我才搞清楚他们到底是怎么算的，好在BLS有不少热心的公务员，耐心回答了我关于计算细节的各种问题。

It took me like three months to figure out exactly how they math the formula, and a lot of really helpful public servants at the BLS answered my questions about just how the math works.

接下来就是预测价格了，有些类别有公开数据，比如汽油、天然气，偶尔还有汽车，但大部分还得靠分析趋势、猜走势，看看过去六个月价格大概往哪个方向走。

And then you go from there to predicting the prices, there are some price categories that have public data, like gas and natural gas and sometimes cars, but most of it is just trend work and guessing, and looking at the last six months and sort of where prices seem to be heading.

但对我来说，真正说明问题的不是我有多准，而是那些投行和机构预测者们的预测本身有多不靠谱。

But the the real thing for me is I just think that this says a lot more about the sort of softness of the people, the investment banks and people who predict this in the institutional end than it does about me.

因为当你在预测通胀的时候，其实你根本不是在预测未来——你只是在复盘过去。

Because when you predict inflation, it's not even a prediction, it's in the past.

这些都是已经发生过的数据。

It's data that has already happened.

自从我进入这个领域以来，最让我惊讶的是，那些靠通胀预测来指导数十亿美元资金配置的机构，竟然做得这么差。

And it has been very surprising to me since I entered this space that the places who advise billions of dollars of capital with their inflation forecasts aren't better at this.

这正是我想问的，顺便说一下，劳工统计局的工作人员

Well, this is what I wanted to ask because, by the way, BLS employees

非常乐于帮忙。

Very helpful.

非常乐于帮忙。

Very helpful.

你真的可以打电话给他们

You can actually call them on

打电话

the phone

他们会很耐心地帮你一步步解释。

and they will, like, walk you through stuff.

但说到这个，当你去研究劳工统计局的公式，打电话问他们这些数据是怎么算出来的，为什么没人这么做呢？无论是预测市场还是传统金融领域？

But on that note, when you describe just, like, you know, working out the BLS formula, calling some people up and asking them how it all works, why aren't more people doing this, either in the prediction market or in traditional finance?

你得去问他们才行。

I mean, you'd have to ask them.

说实话，让我惊讶的是，过去两年里，我靠直觉预测通胀的平均绝对误差，居然比彭博的市场共识还小。

You know, it's shocking to me when, you know, it just really shouldn't be the case that my average absolute error on predicting inflation is better over the last two years than the Bloomberg consensus.

我就是一个人，用个Excel表格，而他们却有几乎无限的资源去获取这些数据。

I'm just one guy with Excel and they are, have pretty much unlimited resources to find this data.

这不仅让人震惊——他们到底在干什么？为什么不用心点？我觉得在经济学和选举中，专家的预测往往左右公众预期，而这会深刻影响舆论走向和大众反应。

It's, you know, not just shocking from a kind of what are they doing and why aren't they trying harder, but I think we find in both economics and elections that expert forecasts really shape expectations, and that can play a big role in narrative creation and and how the public responds to that.

我见过太多次了，彭博在通胀数据发布前二十分钟的头条，还写着‘通胀将显示XXX’，仿佛板上钉钉，因为高盛、摩根大通和美国银行都那么说了。

I mean, I've seen many times the headline on Bloomberg twenty minutes before the inflation number will say inflation to show blank as if it's a foregone conclusion because Goldman and JPMorgan and Bank of America have said so.

结果数据一出来，跟预测不一样，他们立马改头条，好像之前那条根本没存在过。

And then when the inflation number is wrong, they just change the headline like that never happened.

市场却还是根据这个本来就不靠谱的预期，对数据是高了还是低了做出反应。

And the market reacts to it either being above or below that expectation, which maybe wasn't that good of an expectation in the first place.

所以我真不明白他们为什么不够努力。

So I don't know why they're not trying harder.

他们手里的资源显然比我要多得多，用来追踪这些数据完全不成问题。

I mean, they certainly have more resources to chase down these numbers than I do.

说句公道话，我们认识的那些最懂通胀的人，全都跟你一样，Brian，是通过亲自钻研公式、从底层一点点搞明白的，真正顶尖的通胀分析师都是这样。

For what it's worth, like, the best inflation people we know all did it the same way you did, Brian, in terms of, like, actually the bottoms up approach to learning the formula, like, all the best inflation.

比如奥默·沙里夫就是个典型例子。

And, of course, like someone like Omer Sharif comes to mind.

没错。

Yeah.

他确实厉害。

He's great.

其实就那么几个人，真正做到了极致。

There's a handful of people who, like, really yeah.

这正是我想说的——不只是Brian，我接触过的所有高手，不管是在预测通胀、选举，还是天气，比如纽约下个周末会下多少雨，都是这么做的。

And this is what I mean, this is what not just Brian, but all of the sharps that I talked to, whether they're doing inflation or they're doing elections or they're doing meteorology, how much is it gonna rain next weekend in in New York City, whatever.

他们都在不断打电话，亲自跑现场，跟人交流，收集大量数据。

They're all just making calls and going on the ground and talking to people and gathering so much data.

他们联系气象学家，联系地球物理学家，很多时候还联系彭博社的记者。

They're calling meteorologists, they're calling geophysicists, they're calling, you know, Bloomberg reporters in many instances.

我认识几个行家，他们就说，没错，我天天都在跟彭博社的记者通电话。

You know, I talked to a few sharps who were like, yeah, I'm on the phone with Bloomberg reporters all the time.

不过我觉得，这些行家基本上就是不停地打电话，搜集信息，这很合理。

But, you know, I think these a lot of these sharps are just, you know, they're constantly on the phone gathering information, which makes sense.

对吧？

Right?

如果你在基金公司工作，做法也是这样。

This is also what you do if you're at a fund.

是的。

Yeah.

我能问个问题吗？我一直很好奇，这更像是个操作层面或者市场结构方面的问题。

Can I ask I've always this is more of like a sort of, I don't know, of a tactical question or market structure question?

可能是两件相互关联的事情。

Maybe it's two interrelated things.

有时候发生一件事，之后会有一段等待结果的时间。

So sometimes an event happens, and then there is a period of time before it resolves.

Kelsius 和 Polymarket 在结果判定上采取了不同的方式。

And Kelsius and Polymarket have different approaches to resolution.

Polymarket 依赖一个第三方的所谓‘预言机’，其实就是个模糊的机制。

Polymarket is based on a sort of third party, quote, Oracle, unquote, that is also sort of like whatever.

而 Kelsius 则更集中化一些。

And then Kelshi is more centralized.

我想知道你的交易思路是怎样的，比如你押中了洛杉矶市长人选。

And I'm curious, what your trading philosophy is, it's like, okay, you get the LA mayorship right.

你是等到最终确认才出手，还是在价格到 99% 的时候就平仓，转而去盯下一个大机会？

Do you wait until resolution or do you sell it when it hits 99% and then move on to the next big thing?

在从 99% 到 100% 的这段等待期内，有没有可能赚到超额收益？

And is there alpha or profits to be gained in holding from the 99 to 100 during that period of resolution?

那两边的情况有区别吗？

And is it different on either of the two sides?

我觉得这要看离结算还有多久，以及有没有其他更值得做的交易。

I I think it depends how much time it is and what other plays are available.

一般来说，如果一个市场马上就要在48小时内结算，那基本都会从99%持有到100%，但有些选举结果早就明了，却要等一个月才能拿到 payout。

I mean, usually, you know, if if if a market is gonna resolve in the next forty eight hours, I mean, you're pretty much always gonna hold that from 99 to a 100, but there are certainly elections that the answer is clear, and then you know you're not getting that payout for a month.

一个月里，你用这99美分去干别的，可能赚得比干等着还多。

And I mean, can turn 99¢ into $1 over a month faster doing something else than waiting.

不过，这还得看具体情况。

But I suppose it depends on the context.

我也说不准。

I I don't know.

丹尼尔可能有不一样的做法。

Daniel might have a different approach.

搞清楚市场是98%还是99%，关键在于它要花多久才能最终结算，这点特别重要。

It's really important to know the difference between is your market 98 or 99 just because of the time it's going to take to resolve?

还是说它有1%到2%的可能性会朝相反方向发展？

Or is there a 1% or 2% chance of it actually going the other way?

我尽量避开这类规则争议和棘手的市场，免得最后变成一场争论。

I try really hard to avoid these rules disputes and these thorny markets where it ends up kind of a debate.

我觉得Polymarket的系统问题很大。

I think Polymarket's system is very problematic.

他们基本上已经削弱了自己的预言机制，现在每个市场都靠Polymarket怎么解释来结算。

They have basically undermined their oracle, and now every market just settles on how Polymarket clarifies.

总的来说，我对Kalshi的结算方式还是比较满意的。

I have generally, for the most part, been happy with Kalshi's resolutions.

但当你交易像‘内阁成员能否获得确认’或者‘谁会赢得选举’这类问题时——

But when you trade in stuff like, will a cabinet member get confirmed or who wins an election?

几乎从来不会有争议。

It is almost never up for debate.

除了2020年那种特殊情况，其他时候答案都很明确。

You know, 2020 notwithstanding, you have clear answers.

所以这完全看情况。

And so it just depends.

我现在把钱押在秘鲁1999年到1月的选举上，只是因为没别的地方可投。

I'm I'm holding the Peruvian election right now from '99 to January because I don't have anywhere else to put the money.

但如果我找到更想投的选项，想把钱腾出来，我立马就会平仓，转投别的机会。

But if I had another play that I liked and I wanted the money freed up, I would sell it in a second and, you know, put it in in whatever else there was.

我们挂了电话再聊。

Let's talk when we get off the call.

我有几个地方可以推荐给你。

I got some places for you.

既然我们在谈概率变化，我想提一下这个。

Since we're talking about probabilities changing, I wanted to bring up this.

一直有个长期争议，就是预测市场在预测选举结果时，到底比传统民调更准，还是只是因为能更快更新数据，看起来更准。

There's a long running debate, I guess, about whether prediction markets are actually better than traditional polls when it comes to forecasting election results or whether they just look better because they're able to update faster as the results come in.

丹尼尔，我很想听听你的看法。

And, Daniel, I'd be very interested in getting your take on this.

这些市场真的能给出更准确的概率，还是只是因为更新更快？

Are these genuinely producing better probabilities or is it just a matter of speed?

是的，但这取决于有多少资金流入各方。

Yes, but it depends on how much money is coming into each side.

一个特别值得注意的选举，我觉得是去年十一月的新泽西州长竞选，当时所有民调都显示这场选举非常胶着。

A really noteworthy election, I think recently last November, was the New Jersey governor's race, where the polls really all said this was a pretty close race.

两、三、四、五。

Know, two, three, four, five.

我们频道上有个人做了一个非常简单的模型，其实都算不上模型，他只是说，卡马拉当时以五到六个百分点的优势赢了这个州。

One of the guys on our channel had made a very simple model, not even really a model, had basically just said, you know, Kamala won the state by, I forgot, five or six.

从那以后，特朗普的支持率可能下降了八到九个百分点。

Trump's approval had fallen maybe eight or nine points since then.

要知道，那时候当总统的是特朗普，不是拜登。

You know, Trump was president instead of Biden.

所以卡马拉或者谢丽尔现在大概能赢十四个百分点。

Kamala or Cheryl's probably going to win by about 14.

这不过是三周前，有人在餐巾纸上随手画了个先验分布而已，那时候连 polls 都还没出来。

And this was just sketched out on Priors on a napkin very quickly, three months before any polls.

后来一堆民调陆续出来，都说这是一场势均力敌的选战。

And then all these polls came in showing this close race.

几乎没几个民调显示哪一方有明显领先。

Very, very few polls showed a big margin.

我们其实并没有忽视这些民调。

And we actually wouldn't ignore the polls.

我们试着把所有民调都统一标准来处理。

We kind of tried to standardize them all.

但我们频道里的人真真切切地相信，这场选举的差距应该是十二、十三、十四个百分点，这跟民调完全对不上。

But we did genuinely believe in our channel that this was a twelve, thirteen, 14 race, that the polls didn't show at all.

可我们没法让预测市场的价格反映出这个观点，因为另一边的资金实在太多了。

Now, we couldn't make the prediction market prices reflect that because there was so much money on the other side.

所以，说到底，预测市场的价格虽然比民调显示的要高一些，也更倾向更大的胜幅，但还是远低于最终的实际结果。

So, you know, ultimately the prediction markets, I think, were higher than the polls, you know, pointing to a higher margin, but still well below what it would eventually come out to.

所以你知道，在流动性足够强的选举中，预测市场的价格还是会出错。

So, you know, on an election where the liquidity on the, you know, the Square side is large enough, the prediction market prices are still gonna be wrong.

你可以再看看普拉特的情况。

I mean, you can look at Pratt again.

普拉特当市长的赔率从来就不是27%，实际上一直低于5%。

Pratt's price was never 27 to be the mayor.

但27%这个数字，相比其他人的臆测，还是要准确得多。

It was less than 5 always in truth, but it was also still that 27 was so much more accurate than anybody's bubble who would have said.

不过这让我想起之前想问的关于泡沫的问题。

But actually, this brings me to a question I wanted to go to the bubble question again.

亚当，你的那篇文章写得非常好。

Adam, obviously your piece was great.

去年还有一篇关于预测市场的优秀报道，讲的是艾伦·科尔，他押上了全部积蓄，认为埃隆·马斯克根本不可能大幅削减赤字——他非常了解赤字问题，觉得这根本不可能发生。

There was another great piece of prediction markets journalism in the last year about Alan Cole, who had bet his life savings that Elon Musk wouldn't actually reduce the deficit very much, and he knows the deficit very well, and he's like, This is never gonna happen.

那篇文章里最精彩的一句话，来自艾伦的妻子：我看了预测市场里的评论区，里面的人看起来全都是傻子，至少跟我丈夫比是这样。

And the money quote in that article is from Alan's wife, who said, I read through the comment section in the prediction markets, and they all seem like idiots, at least relative to her husband.