I.H.119.Warren Buffett.Long-short Strategy
多空策略和高频交易是相互伴生的，巴菲特反复否定这样的投资策略，他用了很多生动的例子，这跟数学上的幂律分布有关，幂律分布在任何可观察的尺度上都是成立的，比如，房地产，以一个长期的视角观察，开发商赚的没有屯房子、屯地皮的多，相比于屯房子开发商赚了高频交易的钱，最典型例子是李嘉诚，以下是我们自己的总结。
1、未来发展不是线性的，10笔交易9笔赚钱，其中1笔巨亏（套利业务可能都有这个问题，特别是某些戏剧性的变化，比如政策）；
2、机会成本，对一些“简单并且长期”的价值失去正常的感受能力。
1、《2002-05-04 Berkshire Hathaway Annual Meeting》
46. Ben Graham and the long/short model
本·格雷厄姆和多空策略模型
WARREN BUFFETT: Six?
沃伦·巴菲特：第六区？
AUDIENCE MEMBER: Hi, I’m Steve Rosenberg (PH). I’m 22, from Ann Arbor, Michigan. It’s a privilege to be here.
听众：你好，我是斯蒂夫·罗斯本（PH），22岁，来自密歇根州安娜堡。能在这里真是荣幸。
First, I’d just like to thank you both for serving as a hero and positive role model for me and many others. Much more than your success, itself, I respect your unparalleled integrity.
首先，我要感谢你们俩作为我的英雄和正面榜样，不仅仅是你们的成功，更重要的是我敬佩你们无与伦比的诚信。
I have three quick questions for you. The first is how a youngster like myself would develop and define their circle of competence.
我有三个简短的问题。第一个是像我这样的年轻人如何发展和定义自己的能力圈。
The second involves the role of creative accounting in the stories of tremendous growth and success over many years. GE, Tyco, and IBM immediately come to mind for me, but I was hoping you could also discuss that issue in relation to Coke.
第二个问题是关于创造性会计在多年巨大增长和成功故事中的作用。通用电气、泰科和IBM立刻让我想起了，但我希望您也能讨论一下与可口可乐相关的这一问题。
Some people have said that their decision to lay off much of the capital in the system onto the bottlers, who earn low returns on capital, is a form of creative accounting.
有人说，他们将系统中大量资本转移给那些资本回报率低的瓶装商的决定，是一种创造性会计。
On the flip side, others counter that Coke’s valuation, at first glance on, say, a price-to-book metric, is actually less richly valued than it seems because they earn basically all the economic rents in the entire system.
另一方面，另一些人反驳说，初看可口可乐的估值，例如基于市净率的估值，实际上比看起来的更不昂贵，因为他们基本上在整个系统中赚取了所有的经济租金。
My final question is, if you could comment on the A.W. Jones model, the long/short equity model. I understand that it doesn’t make sense for capital the size of Berkshire’s to take that type of a strategy.
最后一个问题是，您能否评论一下A.W.琼斯模型，多空股票模型。我理解对于像伯克希尔这样规模的资本来说，采取这种策略没有意义。
But it just seems to me that playing the short side in combination also seems incredibly compelling, even giving the inherent structural and mathematical disadvantages of shorting. And I was wondering if you could talk a little bit more about why you would have lost money on your basket of a hundred frauds.
但在我看来，结合做空策略似乎也非常具有吸引力，即使考虑到做空的固有结构性和数学上的劣势。我想知道您能否再多谈谈为什么您在做空一百只“欺诈”股票时会亏钱。
WARREN BUFFETT: Yeah, it’s an interesting question. And we’ll start — we’ll go in reverse order.
沃伦·巴菲特：嗯，这是一个有趣的问题。我们从后往前回答。
Many people think of A.W. Jones, who was a Fortune writer at one time, and who developed the best-known hedge fund, whenever it was, in the early ’60s or thereabouts, maybe the late ’50s even.
许多人都会想到A.W.琼斯，他曾是《财富》杂志的作者，并在1960年代初期（或者说是1950年代末）发展了最著名的对冲基金。
And for some of the audience, the idea originally with A.W. Jones is that they would go long and short more or less equal amounts and have a market-neutral fund so that it didn’t make any difference which way the market went.
对于一些观众来说，最初A.W.琼斯的理念是他们将以多空大致相等的比例进行投资，建立一个市场中性基金，这样无论市场如何波动，都不受影响。
They didn’t really stick with that over time. And I’m not even sure whether A.W. Jones said that they would. But they, you know, sometimes they’d be 140 percent long and 80 percent short, so they’d have a 60 percent net long, or whatever it might be.
但随着时间的推移，他们并没有始终坚持这一策略。我甚至不确定A.W.琼斯是否曾表示他们会这样做。但你知道，有时他们会做140%的多头和80%的空头，所以他们会有60%的净多头，或者其他的。
They were not market-neutral throughout the period, but they did operate on the theory of being long stocks that seemed underpriced and short stocks that were overpriced.
他们并不是始终保持市场中性，但他们确实遵循了多头投资被低估的股票，空头投资被高估的股票的理论。
Even the Federal Reserve, in a report they made on the Long-Term Capital Management situation a few years ago, credited A.W. Jones with being sort of the father of this theory of hedge funds.
甚至几年前联邦储备委员会在一份关于长期资本管理的报告中，将A.W.琼斯视为这种对冲基金理论的奠基人之一。
As Mickey Newman, if he’s still here, knows, I think it was in 1924 that Ben Graham set up the Benjamin Graham Fund, which was designed exactly along those lines, and which even used paired securities.
正如米基·纽曼（如果他还在这里）知道的那样，我认为本·格雷厄姆于1924年设立了本杰明·格雷厄姆基金，基金设计正是沿着这种思路，它甚至使用了配对证券。
In other words, he would look at General Motors and Chrysler and decide which he thought was undervalued relative to the other, and go long one and short the other.
换句话说，他会比较通用汽车和克莱斯勒，决定他认为哪个相对于另一个被低估，然后做多一个，做空另一个。
So, the idea — and he was paid a percentage of the profits. And it had all of the attributes of today’s hedge funds, except it was started in 1924.
所以，这个理念——他按利润比例获得报酬。它拥有今天对冲基金的所有特征，除了它是在1924年启动的。
And I don’t know that Ben was the first on that, but I know that he was 30 years ahead of the one that the Federal Reserve credited with being the first, and that many people still talk about as being the first, A.W. Jones.
我不知道本是否是第一个采用这种方法的人，但我知道他比联邦储备委员会称之为第一个的A.W.琼斯早了30年，许多人仍然认为A.W.琼斯是第一个。
Ben did not find that particularly successful. And he even wrote about it some in his — in terms of the problems he encountered with that approach.
本并没有发现这种方法特别成功。他甚至在他的著作中提到过他遇到的一些问题。
And my memory is that a quite high percentage of the paired investments worked out well. He was right. The undervalued one went up and the overvalued — or the spread between the two narrowed.
我记得配对投资中有相当高的比例是成功的。他是对的，低估的股票上涨了，而高估的股票——或者说两者之间的差距缩小了。
But the one time out of four, or whatever it was, that he was wrong lost a lot more money than the average of the three that he was right on.
但每四次中的一次，或者不管是多少次，当他错的时候，损失的金额远远超过了他对的三次的平均数。
And you know, all I can say is that I’ve shorted stocks in my life, and had one particularly harrowing experience in 1954.
你知道，我唯一能说的就是我一生中做过空头，并且在1954年有一次特别令人惊慌的经历。
And I have — I can’t — I can hardly think of a situation where I was wrong, if viewed from 10 years later.
而我——我几乎无法想到任何一个我错过的情况，如果从十年后回看的话。
But I can think of some ones where I was certainly wrong from the view of 10 weeks later, which happened to be the relevant period, and during which my net worth was evaporating and my liquid assets were getting less liquid, and so on.
但我能想到一些情况，在十周后的视角下，我肯定是错的，那恰好是相关的时期，期间我的净资产蒸发了，流动资产变得更加不流动，等等。
So, it’s — all I can tell you is it’s very difficult.
所以，我能告诉你的是，这真的很难。
And the interesting thing about it, of course, is A.W. Jones was a darling of the late 1960′s.
当然，有趣的是，A.W.琼斯曾是1960年代末的宠儿。
And Carol Loomis is here, and she wrote an article called “The Jones Nobody Keeps Up With.” And it’s a very interesting article, but nobody’s writing articles — nobody was writing articles about A.W. Jones in 1979.
卡罗尔·卢米斯（Carol Loomis）在这里，她写过一篇文章叫做《没有人能追得上琼斯》。这是篇非常有趣的文章，但在1979年没有人再写关于A.W.琼斯的文章了。
I mean, something went wrong, and there were spin-offs from his operation. Carl Jones spun off from his operation, Dick Radcliffe spun off from his operation.
我的意思是，出了问题，他的业务有分支出来。卡尔·琼斯从他的业务中分出来，迪克·拉德克利夫也从他的业务中分出来。
There were — you can go down the list.
有很多，你可以列出一长串。
And out of many, many, many that left, they — a very high percentage of them bit the dust, including suicides, cab drivers, subsequent employment — the whole thing.
而且，许多许多离开的人——其中很高比例的都失败了，包括自杀、开出租车、后来找工作——一切都发生了。
There was a book written in the late ’60s, it had a lot of pictures in it. I don’t remember the name of it, but it showed all these portraits of all these people that were highly successful in the hedge fund business, but they didn’t bring out a second edition.
在60年代末有一本书，它有很多照片。我记不清书名了，但它展示了这些在对冲基金行业非常成功的人的肖像，但他们没有出版第二版。
So, it’s just tough.
所以，这真的很困难。
Logically, it should work well, but the math of only — you can’t short a lot of something. You can buy till the cows come home if you’ve got the money. You can buy the whole company if need be, but you can’t short the whole company.
从逻辑上讲，它应该行得通，但数学上只有一个问题——你不能做空很多东西。如果你有钱，你可以买到天荒地老。如果有需要，你可以买下整家公司，但你不能做空整家公司。
A fellow named Robert Wilson, there’s some interesting stories about him. He’s a very, very smart guy, and he took a trip to Asia one time, being short, I think it was Resorts International or maybe it’s Mary Carter Paint, it was still called in those days.
有一个叫做罗伯特·威尔逊的人，有一些有趣的故事。他是一个非常非常聪明的人，有一次他去亚洲，他在做空，我认为是度假村国际，或者是玛丽·卡特涂料，当时还是叫这个名字。
And he lost a lot of money before he got back to this country. He’s a very smart guy, and he made a lot of money shorting stocks, but it just takes one to kill you.
他在回到美国之前损失了很多钱。他是一个非常聪明的人，他通过做空股票赚了很多钱，但它只需要一个错误就能致命。
And you need more and more money as the stock goes up. You don’t need more and more money when a stock goes down, if you paid for it originally and didn’t buy it on margin. You just sit and find out whether you were right or not.
随着股价上涨，你需要越来越多的钱。当股价下跌时，如果你是原价买入且没有使用保证金，你就不需要更多的钱。你只需要静坐，看看自己是否正确。
But you can’t necessarily sit and find out whether you’re right on being short a stock.
但你不能简单地坐在那里，看看自己是否做空股票是对的。
I think I’ll let Charlie comment on that before I go to your other two questions.
我想在回答您的其他两个问题之前，让查理评论一下这个问题。
2、《2008-05-03 Berkshire Hathaway Annual Meeting》
17. Long-short strategy wasn’t a big money maker
多空策略并不是一个大赚的策略
WARREN BUFFETT: Thank you. Number 2.
沃伦·巴菲特：谢谢。2 号。
AUDIENCE MEMBER: Hi. My name is Henry Pattener (PH). I’m hailing from Singapore, most recently.
观众成员：你好。我的名字是亨利·帕特纳。我来自新加坡。
In one of your older letters, you — your older partnership letters in 1964 — you introduced a fourth investment method called “Generals — Relatively Undervalued.”
在你的一封较早的信中，你——你在 1964 年的较早合伙信中——介绍了一种投资方法，称为“普通股——相对低估”。
In your description you say, “We have recently begun to implement a technique which gives promise of very substantially reducing the risk from an overall change in valuation standards.
在您的描述中，您提到：“我们最近开始实施一种技术，这种技术有望大幅降低整体估值标准变化的风险。
“We buy something at 12 times earnings when comparables or poor-quality companies sell at 20 times earnings, but then a major revaluation takes place so that the latter only sell at ten times.”
“我们以12倍的收益购买某种股票，而可比或劣质公司则以20倍的收益出售，但随后发生了重大重新估值，使得后者仅以10倍出售。”
Is this technique pair trading and, if so, how did you think about and calculate the ratio of longs to shorts?
这种技术是配对交易吗？如果是这样，您是如何考虑和计算多头与空头的比例的？
WARREN BUFFETT: Yeah. I didn’t remember we started as early as ’64, but certainly in the ’60s we did some of what, in a very general way, would be called pair trading now, which is a technique that’s used by a number of hedge funds, and perhaps others, that go long one security and short another, and often they try to keep them in the same industry or something.
沃伦·巴菲特：是的。我不记得我们在 64 年就开始了，但可以肯定的是，在 60 年代我们确实做了一些现在被称为配对交易的事情，这是一种被许多对冲基金和其他人使用的技术，即买入一种证券并卖空另一种证券，通常他们会尝试将它们保持在同一行业或类似的领域。
They say that British Petroleum is relatively attractive compared to Chevron or vice versa, so they long one and short the other.
他们说，与雪佛龙相比，英国石油相对有吸引力，反之亦然，所以他们做多一个，做空另一个。
And actually that technique was employed first by Ben Graham in the mid-1920s when he had a hedge fund, oftentimes — I read articles all the time that credit A.W. Jones with originating the hedge fund concept in the late ’40s, but Ben Graham had one in the mid-1920s — and he actually engaged in pairs trading.
实际上，这种技术最早是由本·格雷厄姆在 1920 年代中期使用的，当时他有一个对冲基金。我经常读到一些文章，将对冲基金概念的起源归功于 A.W.琼斯，认为是在 40 年代末，但本·格雷厄姆在 1920 年代中期就已经有一个对冲基金了——而且他实际上参与了配对交易。
And he found out it worked modestly — very modestly — well because he was right about four times out of five but the time he was wrong tended to kill him on the other four.
他发现这种方法有效——非常有限地有效——因为他在五次中对四次是正确的，但他错误的那一次往往会让他在其他四次中遭受损失。
We did — we shorted out the general market for about five years in the partnership, to a degree. We borrowed stocks directly from some major universities. I think we were probably quite early in that.
我们确实——在合伙企业中，我们在一定程度上做空了大约五年的大盘。我们直接从一些主要大学借入股票。我想我们可能在这方面相当早。
We went to Columbia and Harvard and Chicago and different places and actually arranged for direct borrowing. They weren’t — it wasn’t as easy to facilitate in those days as it is now.
我们去了哥伦比亚大学、哈佛大学、芝加哥大学和其他不同的地方，并实际安排了直接借用。在那些日子里，这并不像现在这样容易促成。
And so we would take their portfolios and we would just say, “Give us any of the stocks you want, and then we’ll return them to you after a while and we’ll pay you a little fee.”
所以我们会拿他们的投资组合，然后我们就说：“把你想要的任何股票给我们，然后过一段时间我们会还给你，并支付你一点费用。”
And then we went long things that we thought were attractive. We did not go short things that we thought were unattractive; we just shorted out the market generally.
然后我们就会做多那些我们认为有吸引力的股票。我们并没有做空我们认为不吸引的股票；我们只是做空了整体市场。
It was always kind of interesting to me, when I would visit the treasurer of Columbia or something like and I’d say, “We’d like to borrow your stocks to short,” and, you know, he thought his stocks were pretty good at that point.
我总是觉得有点有趣，当我去拜访哥伦比亚的财务主管或类似的人时，我会说：“我们想借用你的股票来做空。” 你知道，他当时认为他的股票相当不错。
And he’d say, “Which ones do you want?” And I said, “Just give me any of them — (laughs) — I’m happy to short your whole damn portfolio.” (Laughter)
他会说：“你想要哪一个？”我说：“随便给我一个——（笑）——我很乐意做空你整个该死的投资组合。”（笑声）
I needed the Dale Carnegie course to get me through that kind of thing, you know.
我需要戴尔·卡耐基课程来帮助我度过那种事情，你知道的。
We didn’t have any specific ratios in mind. We were always limited by the number of institutions that would give us the stocks to short.
我们并没有心中设定任何具体比例。我们总是受到愿意借给我们股票的机构数量的限制。
So it was not a big deal, but we probably made some extra money on it in the ’60s. It’s not something that would fit our — what we do these days at all.
所以这不是什么大事，但我们可能在 60 年代从中赚了一些额外的钱。这完全不符合我们现在所做的事情。
And, generally speaking, I think if you’ve got some very good ideas on businesses that are undervalued, it’s really unnecessary to do any shorting out of the market.
一般来说，我认为如果你有一些关于被低估的企业的好想法，实际上没有必要在市场上做空。
There’s a — for those of you who are in the field — I mean, there’s a — kind of a popular proposal — money managers always have some popular proposal that’s being sold to the potential investors — and now there’s something called 130-30, where you’re long 130 percent long, short 30 percent.
对于那些在这个领域的人来说，我的意思是，有一个——一种流行的提议——资金管理者总是向潜在投资者推销一些流行的提议——现在有一种叫做 130-30 的东西，你是 130%做多，30%做空。
That stuff is all basically a bunch of stuff just to try and sell you the idea of the day. It doesn’t really have any great statistical merit.
那些东西基本上就是一堆东西，只是为了向你推销当天的想法。它实际上并没有什么很大的统计价值。
But the fish bite, as Charlie says. Charlie can elaborate on that.
但鱼咬钩了，正如查理所说。查理可以详细说明。
CHARLIE MUNGER: Yeah. We made our money by being long some wonderful businesses. We didn’t make it by a long-short strategy.
查理·芒格：是的。我们通过持有一些优秀的企业赚到了钱。我们不是通过长短策略赚到的。
3、《2024-12-02 Hedge Fund Paloma Partners Offers IOUs to Fleeing Investors》
Founded in 1981 by Sussman, a onetime Democratic megadonor, Paloma trades across asset classes and hedge-fund strategies, with an emphasis on computer-driven algorithmic investing. The firm has also been a prolific early backer of other hedge funds, most notably industry giant D.E. Shaw.
由曾是民主党大金主的苏斯曼于 1981 年创立，Paloma 在资产类别和对冲基金策略上进行交易，重点是计算机驱动的算法投资。该公司也是其他对冲基金的早期支持者，最著名的是行业巨头 D.E. Shaw。
Lately, though, Paloma’s quant business has been a drag on returns and lost money so far in 2024. Through November, Paloma generated returns of about 4%, which is on par with the firm’s average annualized return over the past three years, people familiar with the matter said.
不过，最近 Paloma 的量化业务拖累了收益，截至 2024 年，已经亏损。知情人士表示，截至 11 月，Paloma 的收益约为 4%，这与该公司过去三年的平均年化收益率相当。
A broad hedge-fund index returned 8.5% through October, according to the most recent data compiled by research firm PivotalPath. The S&P 500 is up 27% so far this year.
根据研究公司 PivotalPath 编制的最新数据，一个广泛的对冲基金指数截至 10 月回报率为 8.5%。标准普尔 500 指数今年迄今上涨了 27%。
“We must begin by acknowledging that our performance over the last few years has not met our high standards,” Sussman wrote in the Nov. 22 letter. “As a result, we have received significant withdrawal and redemption requests from investors.”
“我们必须承认，过去几年的表现未能达到我们的高标准，”苏斯曼在 11 月 22 日的信中写道。“因此，我们收到了投资者大量的撤资和赎回请求。”
SEC: Two Sigma SEC：Two Sigma
Quantitative hedge funds and proprietary trading firms employ researchers whose job is to find trading signals. A trading signal is some rule of the form “when you see X, that means that Stock Y will probably go up.” X is something observable — some other security’s price or volume or some other market event, or some accounting item, or something happening on social media, or some satellite photos of parking lots, or whatever — and the researcher has found that, when X happens, then there is statistically significant increase in the probability that Stock Y will go up. So the researcher will go to her boss and say “good news, I discovered that X predicts that Stock Y will go up, so whenever X happens we should buy some Stock Y.”
量化对冲基金和自营交易公司雇佣研究人员，他们的工作是寻找交易信号。交易信号是一种规则，形式为“当你看到 X 时，这意味着股票 Y 可能会上涨。”X 是可观察的——可能是某种其他证券的价格或成交量，或某种市场事件，或某项会计数据，或社交媒体上的某些动态，或某些停车场的卫星照片，等等——研究人员发现，当 X 发生时，股票 Y 上涨的概率在统计上显著增加。因此，研究人员会去找她的上司，说：“好消息，我发现 X 可以预测股票 Y 会上涨，所以每当 X 发生时，我们应该买入一些股票 Y。”
“Not so fast,” her boss will say. “You have found that, when X happens, Stock Y will outperform the market by 0.1% the next day, 54% of the time. That’s good work, and I am impressed. But we can’t run a hedge fund off that fact. For one thing, we have transaction costs to trade Stock Y, which will eat up much of the expected profit. For another thing, we have like 500 other signals that your colleagues have found. Sometimes, when your signal predicts Stock Y will go up, our other signals predict it will go down, and we should actually sell it, not buy it, if those other signals are better. Other times, when your signal predicts Stock Y will go up, our other signals also predict it will go up, so your signal is not that useful. No, we cannot run a strategy that is just ‘when X happens, buy Stock Y.’ Instead, what we will do is add your signal into our big trading model. The big trading model looks at all the signals and combines them in some appropriate way to get our firm’s combined best guess about what stocks will go up and down. Your signal will be added to the big trading model, which will make the model a bit smarter about Stock Y, some of the time. But the big trading model will never be reducible to a rule as simple as ‘when X happens, buy Stock Y.’ The big trading model knows many other things.”
“没那么快，”她的老板会说。“你发现当 X 发生时，股票 Y 在第二天有 54%的概率跑赢市场 0.1%。这很不错，我很欣赏你的工作。但我们不能仅凭这个事实来运营对冲基金。首先，交易股票 Y 会产生交易成本，这将吞噬大部分预期利润。其次，你的同事们已经找到了大约 500 个其他信号。有时候，当你的信号预测股票 Y 会上涨时，我们的其他信号预测它会下跌，如果那些信号更可靠，我们实际上应该卖出而不是买入。还有时候，当你的信号预测股票 Y 会上涨时，我们的其他信号也预测它会上涨，因此你的信号并不那么有用。不，我们不能仅仅依靠‘当 X 发生时，买入股票 Y’来制定策略。相反，我们会把你的信号加入我们的大型交易模型。这个大型交易模型会分析所有信号，并以某种合适的方式将它们结合起来，以得出我们公司对哪些股票会上涨或下跌的最佳判断。你的信号将被添加到大型交易模型中，这将在某些时候让模型对股票 Y 的判断更聪明一些。” 但是，大型交易模型永远不会被简化为一条简单的规则，比如“当 X 发生时，买入股票 Y。” 大型交易模型还了解许多其他信息。
And so the researcher’s signal will get added to the model. Generally speaking, the signal will be worth more — will have more influence on the model — if:
因此，研究员的信号将被添加到模型中。一般来说，该信号的价值更高——对模型的影响更大——如果：
1.It is strong: “When X happens, Stock Y goes up by 5%, 90% of the time” is better than “When X happens, Stock Y goes up by 0.1%, 54% of the time.” The higher the Sharpe ratio of a strategy, the better it is.
它是强的：“当 X 发生时，股票 Y 在 90%的情况下上涨 5%”比“当 X 发生时，股票 Y 在 54%的情况下上涨 0.1%”更好。一个策略的夏普比率越高，它就越好。
2.It is uncorrelated to the model’s other signals. If you find a signal like “companies underperform when their chief executive officers have nice suntans,” but the model already incorporates a signal like “companies underperform when their CEOs have low golf handicaps,” and golf skill and suntans are highly correlated, then your signal is not adding very much to the model, even if it is pretty good on its own.
它与模型的其他信号不相关。如果你发现一个信号，比如“当公司的首席执行官晒得很黑时，公司表现不佳”，但模型已经包含了一个信号，比如“当公司的首席执行官高尔夫差点较低时，公司表现不佳”，而高尔夫技能和晒黑程度高度相关，那么即使这个信号本身相当不错，它对模型的贡献也不会太大。
In fact, if your signal is too correlated to other signals, the model might ignore it or even trade against it. Michael Isichenko writes:
事实上，如果你的信号与其他信号的相关性过高，模型可能会忽略它，甚至与之对冲交易。Michael Isichenko 写道：
What is less intuitive, if the correlation of two performing books gets high enough, … the optimal weight … for the lower-Sharpe book gets negative, even though the book is profitable by itself. This observation emphasizes an important role of correlations in combining, and also poses an interesting question of pnl attribution … for the purposes of compensation of quants working for a combined portfolio. ...
如果两本表现良好的书籍之间的相关性足够高，较低夏普比率的书籍的最优权重会变为负值，即使该书籍本身是盈利的。这一观察强调了相关性在组合中的重要作用，同时也提出了一个有趣的问题，即在合并投资组合的情况下，如何归因盈亏以用于量化分析师的薪酬计算。
Positively correlated forecasts compete for weight in the mix. Many weights can end up zero or even negative. … Forecasts contribute to the optimal bottom line in a complicated, nonlinear way, and the sum of the contributions, however computed, does not normally add up to the total.
正相关的预测在组合中竞争权重。许多权重最终可能为零甚至为负。……预测以复杂的非线性方式对最优底线做出贡献，而贡献的总和，无论如何计算，通常都不会等于总数。
Isichenko is discussing the most important question in quantitative finance: “How much is my bonus?” Generally speaking, the more value a researcher adds to the overall trading model, the more she gets paid. The way you add value to the overall trading model, crudely speaking, is (1) the model trades on your signals and (2) the stocks that it buys on your signals go up.
Isichenko 正在讨论量化金融中最重要的问题：“我的奖金是多少？” 一般来说，研究员对整体交易模型贡献的价值越大，薪酬就越高。粗略来说，增加整体交易模型价值的方式是：(1) 模型根据你的信号进行交易，(2) 它根据你的信号买入的股票上涨。
If you are a quantitative researcher, you could imagine gaming this. One form of gaming is:
如果你是一名量化研究员，你可以想象操纵这一点。其中一种操纵方式是：
1.You find a signal. It’s pretty good, not amazing, but pretty good.
你找到一个信号。还不错，不算惊艳，但还不错。
2.You hand it off to your boss and it goes into the big trading model.
你把它交给你的老板，然后它进入大型交易模型。
3.The big trading model doesn’t make much use of it, because it is too correlated with other signals.
大型交易模型并不会大量使用它，因为它与其他信号的相关性太高。
4.Therefore, you do not get paid very much for the signal you found.
因此，您发现的信号并不能为您带来太多报酬。
5.You find those other signals and break their kneecaps.
你找到那些其他信号并打断他们的膝盖。
6.Now the big trading model stops using the other signals and uses yours instead.
现在，大型交易模型停止使用其他信号，而改用你的信号。
7.Yours is pretty good, so it makes money, so you get paid.
你的很不错，所以能赚钱，所以你能得到报酬。
The problem with this is that you can’t really break the kneecaps of statistical models of stock price returns. What you could do, maybe, is trick the big trading model into thinking that your signal is uncorrelated with the other signals. Then the big trading model will use your signal a lot — it will trade a lot of stock based on your signal — because uncorrelated signals are very useful. And you will get paid a lot.
问题在于，你无法真正打断股票价格回报统计模型的膝盖。也许你可以做的是欺骗大型交易模型，让其认为你的信号与其他信号不相关。然后，大型交易模型会大量使用你的信号——它会基于你的信号大量交易股票——因为不相关的信号非常有用。而你将获得丰厚的报酬。
Is this bad? Well, sure, I mean, the big trading model was optimized to achieve high risk-adjusted returns, and by tricking it into using more of your signal, you break that optimization. The model will achieve lower risk-adjusted returns. But maybe higher absolute returns; who knows? By breaking the model in this way, you cause it to double down on your signal, to put more money into your signal than it deserves. If your signal works pretty well, then for a while this could actually be good for the model’s performance; it is taking more risk but possibly earning higher returns.
这很糟糕吗？嗯，当然，我是说，这个大型交易模型被优化以实现高风险调整回报，而通过欺骗它使用更多你的信号，你破坏了这种优化。模型将实现较低的风险调整回报。但也许会有更高的绝对回报；谁知道呢？通过这种方式破坏模型，你让它加倍依赖你的信号，投入比应得的更多资金。如果你的信号效果不错，那么在一段时间内，这实际上可能对模型的表现有利；它承担了更高的风险，但可能获得更高的回报。
Anyway this is not any sort of advice about anything, and in general if you are a researcher at a quant firm, tricking your firm’s trading models in this way is (1) a bad idea and (2) probably not all that feasible. They will try not to let you do that. But … maybe? Here’s an SEC case from last Thursday against Two Sigma Investments LP:
总之，这并不是关于任何事情的任何建议，通常来说，如果你是量化公司的研究员，以这种方式欺骗公司的交易模型（1）是个坏主意，（2）可能也并不那么可行。他们会尽力阻止你这样做。但是……也许？以下是美国证券交易委员会（SEC）上周四对 Two Sigma Investments LP 的案件：
According to the SEC’s order, in or before March 2019, Two Sigma employees identified and recognized vulnerabilities in certain Two Sigma investment models that could negatively impact clients’ investment returns, but Two Sigma waited until August 2023 to address the issues. Despite recognizing these vulnerabilities, Two Sigma failed to adopt and implement written policies and procedures to address them and failed to supervise one of its employees who made unauthorized changes to more than a dozen models, which resulted in Two Sigma making investment decisions that it otherwise would not have made on behalf of its clients.
根据美国证券交易委员会的命令，早在 2019 年 3 月或之前，Two Sigma 的员工就发现并认可某些 Two Sigma 投资模型中的漏洞，这些漏洞可能会对客户的投资回报产生负面影响，但 Two Sigma 直到 2023 年 8 月才解决这些问题。尽管认识到这些漏洞，Two Sigma 未能制定和实施书面政策和程序来应对这些问题，并且未能监督其一名员工，该员工对十多个模型进行了未经授权的更改，导致 Two Sigma 代表客户做出了本不会做出的投资决策。
We talked about this situation in 2023, when it was first reported that “a researcher at Two Sigma Investments adjusted the hedge fund’s investing models without authorization.” Apparently he “was trying to improve the firm’s performance, which would have benefited his career and potential pay.” And, in an obvious sense, it worked: The SEC says that his “changes resulted in certain funds and [separately managed accounts] overperforming by more than $400 million and other funds and SMAs underperforming by approximately $165 million.” So he added more money than he subtracted, but in a bad way.
我们在 2023 年讨论过这种情况，当时首次有报道称“两家西格玛投资公司的一名研究员未经授权调整了对冲基金的投资模型。” 显然，他“试图提高公司的业绩，这将有利于他的职业生涯和潜在薪酬。” 从某种明显的角度来看，他的做法奏效了：SEC 表示，他的“更改导致某些基金和[单独管理账户]的超额收益超过 4 亿美元，而其他基金和 SMA 的表现则下降约 1.65 亿美元。” 所以他增加的金额多于减少的金额，但方式不当。
The SEC order lays out the bad way. Two Sigma’s trading code was off limits to researchers: “Two Sigma’s live trading system uses Model code that is stored in a secure file called the ‘Jar,’” and researchers couldn’t mess with it. But there was a separate database, called celFS, “to store certain Model parameters that were too large to be stored in the Jar,” and the researchers had more ability to change that.3
美国证券交易委员会的命令阐明了错误的做法。Two Sigma 的交易代码对研究人员是禁区：“Two Sigma 的实时交易系统使用存储在一个名为‘Jar’的安全文件中的模型代码，”研究人员不能对其进行更改。但还有一个名为 celFS 的独立数据库，“用于存储某些过大而无法存储在 Jar 中的模型参数，”研究人员对其有更大的修改权限。
To get a signal or strategy — called a “Model” in the SEC order — approved, researchers had to submit a white paper and other documentation explaining the model, and Two Sigma decided if it was strong and uncorrelated enough. “Two Sigma management then reviewed these documents and forms, and Models could be approved where, among other things, the modeler’s documentation reported that the proposed Model’s correlation to existing Models was below a specified threshold.”
要获得信号或策略（在 SEC 命令中称为“模型”）的批准，研究人员必须提交白皮书和其他文件来解释该模型，而 Two Sigma 决定其是否足够强大且不相关。 “Two Sigma 管理层随后审查了这些文件和表格，并且在模型开发者的文档报告所提议模型与现有模型的相关性低于指定阈值的情况下，模型可以获得批准。”
But once it was approved:
但一旦获得批准：
Between November 2021 and August 2023, Modeler A, a TSI employee who had used celFS to store certain Model parameters for years, made dozens of unauthorized changes to Model decorrelation parameters stored in celFS for fourteen different Models that Two Sigma used in live trading. These Models included both Models that Modeler A developed himself as well as Models developed by Modeler A’s direct reports and with which Modeler A assisted. …
在 2021 年 11 月至 2023 年 8 月期间，TSI 员工 Modeler A（多年来一直使用 celFS 存储某些模型参数）对存储在 celFS 中的模型去相关参数进行了数十次未经授权的更改，涉及 Two Sigma 在实盘交易中使用的十四种不同模型。这些模型包括 Modeler A 本人开发的模型，以及由 Modeler A 的直接下属开发并由 Modeler A 协助的模型。
By adjusting these Model parameters, in many cases to zero (i.e., nullifying the parameter), Modeler A increased these Models’ expected correlation to Two Sigma’s other Models without detection. ...
通过调整这些模型参数，在许多情况下将其设为零（即使参数失效），模型师 A 在未被发现的情况下提高了这些模型与 Two Sigma 其他模型的预期相关性。
These changes caused the Models to perform differently than expected such that Two Sigma made investment decisions that it otherwise would not have made. Specifically, Modeler A’s unauthorized changes resulted in Two Sigma buying or selling more or less of specific securities than it otherwise would have, which caused certain funds and SMAs to overperform by more than $400 million and other funds and SMAs to underperform by approximately $165 million. Modeler A received millions of dollars of additional compensation from Two Sigma as a result of the net overperformance attributable to these changes.
这些变更导致模型的表现与预期不同，使得 Two Sigma 做出了本不会做出的投资决策。具体而言，模型师 A 的未经授权的更改导致 Two Sigma 购买或出售特定证券的数量多于或少于原本应有的水平，导致某些基金和 SMA 的超额收益超过 4 亿美元，而其他基金和 SMA 的表现则下降约 1.65 亿美元。由于这些变更导致的净超额收益，模型师 A 从 Two Sigma 获得了数百万美元的额外报酬。
I think that means, roughly, that this researcher cranked up how much Two Sigma’s overall trading engine relied on his models. You have some signal, it spits out trade recommendations, and then the trading engine ignores or scales back those recommendations to the extent they correlate with the firm’s other signals. The decorrelation parameter tells the engine how much to scale them back. If you set that parameter to zero, then the engine takes more of your signal’s recommendations — even if they are highly correlated with other signals — and, if your signal is good, you get more performance attributed to you.
我认为这大致意味着，这位研究员提高了 Two Sigma 整体交易引擎对其模型的依赖程度。你有一些信号，它会输出交易建议，然后交易引擎会忽略或缩减这些建议的影响程度，具体取决于它们与公司其他信号的相关性。去相关化参数告诉引擎应该缩减多少。如果将该参数设为零，那么引擎会更多地采纳你的信号建议——即使它们与其他信号高度相关——如果你的信号质量好，你就会获得更多的业绩归因。
The business of a big quantitative hedge fund is to get a high risk-adjusted return, but in any particular year, if you are an employee of that hedge fund, you might care more about a high absolute return. Probably that gets you a bigger bonus. Quant funds aim for a low volatility of returns, but quant fund employees benefit from a high volatility: If the returns are high you get a big bonus, if they’re mediocre you need to find a new job, and if they’re catastrophic you need to find a new job, so a 50/50 chance of high or catastrophic is better, for you, than a 100% chance of mediocre.4 If you can secretly turn the dial to take more risk, you might.
大型量化对冲基金的业务是获得高风险调整回报，但在任何特定年份，如果你是该对冲基金的员工，你可能更关心高绝对回报。可能这会让你获得更高的奖金。量化基金的目标是回报的低波动性，但量化基金的员工则受益于高波动性：如果回报高，你会得到丰厚的奖金；如果回报平平，你需要找一份新工作；如果回报灾难性，你也需要找一份新工作。因此，对你来说，50/50 的高回报或灾难性回报的机会比 100% 的平庸回报更好。如果你能偷偷调整风险水平以承担更高风险，你可能会这样做。
Long 1x MSTR short 2x MSTR
做多1倍MSTR，做空2倍MSTR
Roughly speaking the two big MicroStrategy Inc. trades are:
大致来说，两大MicroStrategy Inc.交易策略是：
1.MicroStrategy is a pot of Bitcoin, and its stock trades at a large premium to the value of its Bitcoin, so you can go long Bitcoin and short MicroStrategy stock to bet on convergence. This trade is pretty tricky for most investors (what if the premium gets bigger?), but it is a great trade for MicroStrategy (it can print as much stock as it wants, and buy more Bitcoin), so MicroStrategy has done it in enormous size.
1.MicroStrategy就像一个比特币宝库，其股票的交易价格远高于其所持比特币的价值，因此你可以做多比特币，同时做空MicroStrategy的股票，以押注两者价格趋于收敛。对于大多数投资者来说，这笔交易相当棘手（如果溢价进一步扩大怎么办？），但对MicroStrategy来说，这是一笔极好的交易（它可以无限量增发股票并购买更多比特币），因此MicroStrategy已经大规模执行了这项策略。
2.MicroStrategy is a very volatile stock, and you can buy its volatility at a discount to fair value, so a lot of volatility investors do. This mostly takes the form of convertible arbitrage funds buying MicroStrategy’s convertible bonds in large size: MicroStrategy gets more money to buy Bitcoin by selling its volatility to people who can use it. The arbitrageurs buy the bonds, short the stock, and profit by adjusting their hedge as the stock moves around.
2.MicroStrategy是一只非常波动的股票，你可以以低于其公允价值的价格购买其波动性，因此很多波动性投资者会这样做。这主要表现为可转债套利基金大规模购买MicroStrategy的可转换债券：通过向那些能够利用波动性的人出售波动性，MicroStrategy获得更多资金来购买比特币。套利者购买债券，同时做空股票，并通过在股票波动过程中调整对冲策略获得利润。
The nuance with the second trade is that the convertible arbitrageurs are, in effect, buying volatility not just from MicroStrategy (which is selling convertibles) but also from retail investors in levered MicroStrategy exchange-traded funds. Retail investors buy those funds to get extra returns on MicroStrategy stock, but because those funds rebalance every day — buying more stock when it’s up, selling stock when it’s down — they (1) amplify MicroStrategy’s volatility and (2) lose money on that volatility: The more the stock bounces around, the worse the funds are at tracking MicroStrategy’s long-term returns. (This is called “volatility drag,” and here is Kris Abdelmessih on “the gamma of levered ETFs.”)
第二笔交易的细微之处在于，可转换债套利者实际上不仅从MicroStrategy（正在出售可转换债券的公司）那里购买波动性，还从杠杆化MicroStrategy交易所交易基金中的散户投资者那里购买波动性。散户投资者购买这些基金以获得MicroStrategy股票的额外回报，但由于这些基金每天都会再平衡——股价上涨时买入更多股票，股价下跌时卖出股票——它们（1）放大了MicroStrategy的波动性，并且（2）在这种波动性上亏损：股票波动越大，这些基金在追踪MicroStrategy长期回报时就表现得越糟。（这被称为“波动性拖累”，以下是Kris Abdelmessih关于“杠杆ETF的伽马”的解读。）
This suggests another way to do the second trade: Not “buy volatility from retail investors by buying convertible bonds and shorting the stock,” but rather “buy volatility from retail investors by buying the stock and shorting the ETFs.” Here’s David Einhorn:
这表明实现第二笔交易的另一种方法：不是“通过购买可转换债券并做空股票从散户那里购买波动性”，而是“通过买入股票并做空ETF从散户那里购买波动性”。下面是David Einhorn的看法：
Greenlight Capital’s David Einhorn thinks speculative behavior in the current bull market has ascended to a level beyond common sense.
Greenlight Capital的David Einhorn认为，当前牛市中的投机行为已经上升到超出常识的水平。
“We have reached the ‘Fartcoin’ stage of the market cycle,” Einhorn wrote in an investor letter obtained by CNBC. “Other than trading and speculation, it serves no other obvious purpose and fulfills no need that is not served elsewhere.” …
“我们已经进入了市场周期中的‘Fartcoin’阶段，”Einhorn在一封被CNBC获得的投资者信中写道。“除了交易和投机之外，它没有其他明显的用途，也无法满足其他地方已有的需求。”……
Greenlight took advantage of the craziness around crypto during the fourth quarter by betting against some popular exchange-traded funds linked indirectly to bitcoin.
Greenlight利用第四季度围绕加密货币的疯狂行情，通过做空一些与比特币间接相关的热门交易所交易基金来获利。
The two funds the firm focused on were the T-Rex 2X Long MSTR Daily Target ETF (MSTU) and the Defiance Daily Target 2X Long MSTR ETF (MSTX). Those funds use derivatives to try to achieve two times the daily returns of MicroStrategy, a software company that has turned itself into a bitcoin treasury vehicle in recent years.
该公司关注的两个基金分别是T-Rex 2X Long MSTR Daily Target ETF (MSTU)和Defiance Daily Target 2X Long MSTR ETF (MSTX)。这些基金利用衍生品试图实现MicroStrategy每日回报的两倍，MicroStrategy近年来已经转型为一个比特币国库工具的软件公司。
The funds have at times struggled to achieve that goal due to MicroStrategy’s volatility and little supply of the derivatives most easily used to get the leveraged returns.
由于MicroStrategy的波动性和最容易用于获得杠杆回报的衍生品供应有限，这些基金有时难以实现这一目标。
The letter said Greenlight took short positions against those funds during the quarter, partially offset by owning MicroStrategy stock in an arbitrage trade that was a “material winner.”
信中提到，Greenlight在本季度对这些基金采取了空头仓位，部分通过持有MicroStrategy股票的套利交易进行对冲，而该套利交易成为了“重要赢家”。
The big picture is that a lot of institutional investors are lining up to take the other side of MicroStrategy retail trades.
大体而言，许多机构投资者正排队做多MicroStrategy的散户交易的反面头寸。
网友：你好，段总。deepseek的创始人梁文峰，听说是做量化交易的。
他说过，量化交易可以赚到今天技术层面的钱，未来也会赚到基本层面的钱。如何看待此问题，价值投资在量化面前还有优势吗？
段永平：我不那么了解量化交易，感觉上其实就是高级的看图看线，但他们是用ai看也许加一点点人工干预。量化交易大概率是个猎人和猎物的零和游戏，投资则像农夫种田，两者其实互不干扰。量化交易赚的是韭菜的钱，投资赚的是企业成长的钱。我对量化交易持中性看法，毕竟那也是合法生意。
这个看法有些问题。
7、《2025-03-17 Matt Levine.Merger arb》
Merger arb
合并账户
Here’s a little puzzle. In 2023, Chevron Corp. agreed to acquire Hess Corp. in an all-stock merger. The merger price is 1.025 Chevron shares per Hess share. About a year ago, Exxon Mobil Corp. filed for arbitration to try to stop the deal: Hess’s most important asset is a minority interest in an oil project in Guyana operated by Exxon, and Exxon claims that it has a right of first refusal to buy that stake. Hess and Chevron disagree, arguing that the right of first refusal applies to a sale by Hess of its interest, but not a merger of Hess itself. We talked about the case last year, and it is “scheduled to be heard in May with a decision by September.”
这里有一个小谜题。2023 年，雪佛龙公司同意以全股票合并的方式收购赫斯公司。合并价格为每股赫斯股票 1.025 雪佛龙股票。大约一年前，埃克森美孚公司申请仲裁，试图阻止这笔交易：赫斯最重要的资产是埃克森在圭亚那经营的一个石油项目中的少数股权，埃克森声称它有优先购买权。赫斯和雪佛龙不同意，认为优先购买权适用于赫斯出售其权益，但不适用于赫斯本身的合并。我们去年曾讨论过此案，"计划在 5 月进行听证，9 月做出裁决"。
So (1) the closing of the Chevron/Hess deal is still a ways off and (2) it is not certain, because Exxon might still block it. So Hess trades at a discount to the deal price. This past Friday, Chevron closed at $157.02, implying a price of $160.95 per Hess share. Hess, however, closed at $148.13, about an 8% discount to the deal price.
因此，(1) 雪佛龙/赫斯交易的完成仍遥遥无期，(2) 这并不确定，因为埃克森仍有可能阻止交易。因此，赫斯的交易价格较交易价格有折扣。上周五，雪佛龙的收盘价为 157.02 美元，这意味着赫斯的每股价格为 160.95 美元。而 Hess 的收盘价为 148.13 美元，比交易价格折价约 8%。
I don’t know who will win the arbitration, but let’s say you do. Let’s say you are an expert in international oil project litigation and you are highly confident that Chevron is right and will win in arbitration. What should you do with that information? An obvious thing to do would be the merger arbitrage trade: Buy a share of Hess for $148.13, sell short 1.025 shares of Chevron for $160.95, pocket the $12.82 difference and close out the trade in September when the deal closes as you expect. Obviously this trade can backfire if you’re wrong, but if you’re confident in it it’s free money.3
我不知道谁会赢得仲裁，但假设你知道。假设你是国际石油项目诉讼方面的专家，你非常确信雪佛龙公司是正确的，并将在仲裁中获胜。你应该如何处理这些信息？一个显而易见的办法是进行合并套利交易：以 148.13 美元买入一股赫斯公司股票，以 160.95 美元卖空 1.025 股雪佛龙公司股票，将 12.82 美元的差价收入囊中，并在 9 月份交易如期完成时平仓。很明显，如果你做错了，这笔交易可能会适得其反，但如果你有信心，这就是一笔免费的钱 3。
And in fact I assume a lot of merger arbitrageurs have analyzed the situation and done either this trade (long Hess, short Chevron to bet on the deal closing) or else the opposite (betting on Exxon winning). (The spread being only 8% suggests mostly the former.) And you could imagine them getting new information that would change their minds: Perhaps they might read Exxon’s or Chevron’s brief in arbitration, or learn something about one of the arbitrators, that caused them to update their beliefs and become more or less confident that the deal will close. For instance, the spread widened last July when the market learned that the arbitration hearing wouldn’t happen until this May, a slower schedule than the market expected.
事实上，我认为很多兼并套利者已经分析了形势，并做了这样的交易（做多赫斯，做空雪佛龙，赌交易完成）或相反的交易（赌埃克森获胜）。(价差仅为 8%，这表明大多数情况下是前者：也许他们会阅读埃克森公司或雪佛龙公司在仲裁中的辩护状，或者了解到仲裁员的一些情况，从而更新他们的看法，或多或少地相信交易会达成。例如，去年 7 月，当市场得知仲裁听证会要到今年 5 月才举行，比市场预期的要慢时，价差就扩大了。
You know who probably has better information about the state of the arbitration than you do? Chevron. So here’s a trade:
你知道谁可能比你更了解仲裁的现状吗？雪佛龙公司所以我们来做个交易：
Chevron Corp. bought nearly 5% of Hess Corp. as a show of confidence that it will win the arbitration battle with Exxon Mobil Corp. that has delayed the Hess takeover for more than a year.
雪佛龙公司收购了赫斯公司近 5%的股份，以此表明它有信心赢得与埃克森美孚公司之间的仲裁战，这场仲裁战已使赫斯公司的收购计划推迟了一年多。
Chevron bought 15,380,000 Hess shares between January and March this year, the Houston-based company said in a statement, and the stake is worth about $2.3 billion at today’s price. The purchases were made at a discount to the price implied by Chevron’s $53 billion all-stock takeover of Hess agreed in 2023.
总部位于休斯顿的雪佛龙公司在一份声明中说，雪佛龙在今年 1 月至 3 月间购买了 1538 万股赫斯股票，按目前的价格计算，这部分股份价值约 23 亿美元。雪佛龙公司将于 2023 年以 530 亿美元的价格全股收购赫斯公司。
The purchases “reflect Chevron’s continuing confidence in the consummation of the pending acquisition of Hess,” the company said.
雪佛龙公司表示，这些采购 "反映出雪佛龙公司对完成即将进行的对赫斯公司的收购仍然充满信心"。
Here’s the announcement, which notes that Chevron bought the shares “at prevailing market prices in open market transactions.”4
公告指出，雪佛龙公司是 "在公开市场交易中以现行市价 "购买这些股票的 4。
Is that … allowed? Is it insider trading? Well, not legal advice, but a few points here:
这是......允许的吗？是内幕交易吗？嗯，不是法律建议，但这里有几点：
Chevron has, in some sense, told you everything that it knows: It has consistently said it is confident in its position and expects the merger to close. You might not believe it; you might not ascribe as high a probability to the deal closing as Chevron does. You might therefore sell Hess’s stock at a discount to the deal price. But that’s not Chevron’s problem! To the extent insider trading is about fairness, Chevron hasn’t done anything unfair: It has told everyone that the deal will close, and then it has acted accordingly.5
从某种意义上说，雪佛龙公司已经把它所知道的一切都告诉了你：它一直说它对自己的立场很有信心，并希望合并能够完成。你可能不相信；你可能不像雪佛龙公司那样认为交易完成的可能性那么高。因此，你可能会以交易价格的折扣出售赫斯的股票。但这不是雪佛龙公司的问题！就内幕交易的公平性而言，雪佛龙公司并没有做任何不公平的事情：它告诉所有人交易将会完成，然后就采取了相应的行动。
But let’s say that Chevron does have some material nonpublic information that merger arbitrageurs don’t know about. Let’s say Chevron knows some hard facts that make it very confident in the deal closing, and if it disclosed those facts — rather than its generic statements of confidence — Hess’s stock would go up. (Maybe Chevron went to a closed-doors confidential arbitration hearing and the arbitrators winked at Hess’s lawyers.) But insider trading law, in the US, is not exactly about fairness. The question is not just “do you know something the market doesn’t know” but also “do you have some duty to someone to keep that information confidential and not trade on it?” Here it is not clear. Companies aren’t supposed to trade their own stock while they have material nonpublic information (because they have fiduciary duties to their shareholders), but Chevron didn’t trade its stock; it traded Hess stock.6 Did Chevron have some duty to Hess not to trade?7 Does it have some obligation to, like, the arbitration process not to use any information it learned? I dunno; this kind of feels like my rule of thumb that you are allowed to trade on nonpublic information about your own intentions, which in this case means Chevron’s information about its intention to close the merger.
但是，假设雪佛龙公司确实掌握了一些并购套利者不知道的重大非公开信息。假设雪佛龙公司知道一些确凿的事实，使其对交易完成非常有信心，如果雪佛龙公司披露这些事实，而不是其一般的信心声明，赫斯公司的股票就会上涨。(也许雪佛龙公司参加了秘密的闭门仲裁听证会，仲裁员对赫斯的律师眨了眨眼睛）。但在美国，内幕交易法并不完全关乎公平。问题不仅在于 "你是否知道一些市场不知道的信息"，还在于 "你是否对某人负有保密义务，不得利用该信息进行交易？这一点并不明确。公司在掌握重大非公开信息时不应该交易自己的股票（因为公司对股东负有受托责任），但雪佛龙公司并没有交易自己的股票，而是交易了赫斯的股票。我不知道；这有点像我的经验法则，即允许交易有关自己意图的非公开信息，在本案中指的是雪佛龙公司有关其打算完成合并的信息。
On the other hand, if Chevron was shorting Hess’s stock to bet against the deal closing, that would obviously be bad! But it’s not.
另一方面，如果雪佛龙公司做空赫斯的股票，赌交易不会完成，这显然是不好的！但事实并非如此。
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