Money Stuff: Knowing the Future Isn’t That Helpful

BloombergOpinion Money Stuff

Matt Levine

Cheat codes Some of my all-time favorite insider traders are the hackers who "allegedly stole approximately 150,000 confidential press releases from the servers of the newswire companies" and made more than $100 million trading on advance knowledge of the news. It's just a whole different game from the usual sort of CEO-tips-his-golf-buddy-about-a-merger insider trading. If you get a merger tip on the golf course, your approach to insider trading is obvious: You go buy as much target stock as you can. You will almost definitely make money, and the trick is to make as much money as possible. Probably you buy short-dated out-of-the-money call options on the target, to maximize your profits when the deal happens. Then you get caught, oops, that's how this goes. (It's the Second Law of Insider Trading.) You are just doing a crime. But when you get every piece of corporate news in advance, your approach is radically different.[1] For instance, on a really simple level, if you have 150,000 press releases, how do you choose which ones to read? In the normal merger-tip insider trading cases it is obvious that buying stock of the target before the merger is announced will be profitable: The merger is big news, the merger price is a premium to the current price, the stock will move toward the merger price, it is easy stuff. But some press releases are like "the oldest member of our board of directors has decided to retire." Is that material? Will it move the stock? Which way? You've got to focus. Obviously if you have merger press releases you should trade on those, but they'll be rare even in your enormous corpus of press releases.[2] The more common kind of market-moving news comes from earnings announcements: If you know a company's earnings before anyone else does, you can make money. Not always: Sometimes the company will just meet earnings expectations, or beat or miss them by a teeny tiny bit, with lower-than-expected revenue growth but positive signals for future quarters, etc. etc. etc., it can all be pretty noisy and you might not know which way the stock will trade. But you could skip those. With 150,000 press releases, you can focus only on the really clear ones, the large clean earnings beats and misses. If you just buy stocks that did way better than expectations, and sell stocks that did way worse, you should do okay. And in fact the Securities and Exchange Commission's case against some of the hackers alleged a 77% success rate: Plenty good enough to get rich, but far from perfect.[3] The point here is that your trading strategy, when you get all the market's news in advance, will look less like "doing crime" and more like "being a regular stock trader, only on the very easy setting." Plenty of investors will be doing more or less the same thing you are doing: Reading the earnings release, trying to digest what it means and how it compares to Wall Street expectations, and then, if the release is significantly positive or negative, buying or selling the stock to profit from the news. You'll be doing it before them, but the basic approach is the same.  And so in a sense these hacker insider traders were conducting a deep empirical experiment about market efficiency. They were answering questions like: If you know every company's earnings in advance, how reliably can you make money from that knowledge? How much can investors learn from earnings announcements that isn't already built into the stock price? Can investors tell, by reading an earnings announcement, that it will affect the price—does the announcement contain the meta-information that it contains information? What theories of market efficiency are true, and how, and why? Obviously these traders were doing this secretly and criminally and to make money, rather than out of a disinterested commitment to science, but still, they were doing their part to push the frontiers of knowledge forward. Also fortunately Chloe Xie of Stanford's Graduate School of Business went and wrote up their results in a paper called "The Signal Quality of Earnings Announcements: Evidence from an Informed Trading Cartel." The whole thing is in the same academic deadpan as that title: To empirically estimate the signal quality of quarterly earnings announcements of US public companies, I examine a natural experiment in which informed investors made predictions of stock price responses to earnings announcements. For her it's a natural experiment. For them it was just an experiment. Like, they had to go out and hack the press releases. Presumably they didn't get approval from an institutional review board first. Anyway: From 2011 through 2015, an international hacker group illegally obtained access to the servers of three commercial newswire companies. These servers stored hundreds of thousands of confidential firm press releases awaiting dissemination to the public. The hackers sold this illegal access to a cartel of sophisticated investors (e.g. ex-hedge fund managers, asset managers, and more). These investors knew the earnings announcements in advance and profited through informed trade. Using transcripts from court proceedings and Freedom of Information Act (FOIA) requests, I gathered data on 1,029 informed-traded earnings announcements over this five-year period. From the archives of the hacked newswires and Factiva's database, I also gathered the set of 10,100 press releases that were disseminated on the same day via the same newswire. The traders had access to these press releases but forwent trading on them. The informed traders were selective: they chose to trade 9.25% of the illegally obtained earnings announcements. My empirical strategy is to use the informed traders' performance to recover earning announcement signal quality. The economic intuition is that the profitability of informed traders depends on how well the information in earnings announcements predicts stock price responses to earnings. The empirical test is straightforward: controlling for liquidity, to what extent were these informed traders identifying the earnings announcements with the largest ex-post returns? In other words, how well were these sophisticated traders able to predict stock price responses from their foreknowledge of the content of earnings announcements? They were okay. The earnings releases definitely helped. The hacker-traders focused on more liquid stocks, which might be a matter of convenience or of not pushing the prices around so much as to be suspicious. But they also did focus on the stocks that were going to go up the most. That is, their advance knowledge of earnings did give them some ability to predict price moves: The informed traders chose earnings announcements with larger ex-post returns. A one standard deviation increase in the magnitude of realized stock returns increases the probability of trade by 19%. This finding confirms the joint hypothesis that informed traders could identify, and preferred to trade on, earnings with larger returns. Furthermore, on the intensive margin, the informed traders more aggressively traded earnings announcements with higher returns. Conditional on a stock that is informed-traded, a one percentage point increase in realized stock returns increases the informed traders' price impact by 8.5 bps.  But they weren't great at picking the stocks that would move the most. Xie sorted all of the available press releases based on the actual stock returns from the announcements; trading the 10% of stocks that went up the most in a given day, or the 10% that went down the most, would give you the highest returns. But only about a third of the hackers' trades were in those biggest winners and losers: Their performance is statistically significantly greater than that of random choice. However, the difference is economically small. For example, only 31% of earnings announcements traded by the informed traders fell within the tail deciles. About 70% of their informed trades missed the biggest stock price return opportunities. They traded earnings announcements with an average absolute return of 5.15%. The average earnings announcement return in the tail deciles is 11.3% (median 9.2%). There is a whole intuitive model here of how you might behave if you knew every earnings announcement in advance. So for instance you'd be more likely to trade on earnings if they're more surprising: If every analyst thinks a company will announce bad earnings, and you know it will announce good earnings, that's a good trade; if analyst opinions are mixed then it's less clear how the market will react. And in fact they traded more where analysts were in agreement: When analysts differ in their forecasts of expected earnings and revenue, there is more pre-announcement private information. Empirically, I find that a one standard deviation increase in analyst disagreement is associated with a 22% decrease in the probability of informed trade, compared to the unconditional mean of informed trade of 9.25%.  Or, you'd be more likely to trade on earnings if a company beats (or misses) expectations on both the top and the bottom line. If a company beats revenue expectations but misses earnings, that might be good or bad, depending on the circumstances and what the market cares about and so forth. If you have all the news in advance, you might skip those and focus on the unambiguous ones: Controlling for the average surprise, if earnings surprise conflicts in direction with revenue surprise, then there is more scope for heterogeneous interpretations. Empirically, I find when signals for earnings and revenue are in the same direction, informed trade is 40% more likely. Obviously the lessons here aren't just, or mainly, about insider trading. It will be hard to replicate this experiment; the newswires probably won't let anyone steal 150,000 press releases again. But other investors will read press releases (at the normal time), and companies will write them, and prices will react to them, and markets will incorporate information from earnings releases, and people will debate how informative they are. And the answer is, meh, they're okay: This unique natural experiment reveals a general fact that earnings announcements are noisy signals of subsequent market reactions. The informed traders had "perfect foresight" from stolen earnings announcement press releases, but they were only able to enjoy mixed success in predicting next-day stock returns. Their poor performance implies that capital market participants have difficulty mapping earnings information to stock price reactions. The contributions of this paper are to empirically quantify the limited informativeness of quarterly earnings announcements to individual investors, provide evidence on the likely sources of signal noise, and shed light on how this noise affects the behaviour of capital market participants. People are worried about unicorn porn One thing that SoftBank Group Corp. Chief Executive Officer Masayoshi Son is amazingly good, or maybe amazingly bad, at is being photographed in front of PowerPoint slides that can be used out of context to make fun of him. Here is a Wall Street Journal article titled "SoftBank Shareholders Criticize Company After WeWork Wipeout" that starts with a picture of Son standing in front of a big arrow pointing down and to the right. Here is a Bloomberg News article titled "After WeWork, SoftBank's Startup Bookkeeping Draws Scrutiny" that features four different photographs of Son, one of which has him standing in front of a big slide saying "25 - 4 = 9?" The context for that slide was not, like, Son asking a room full of investors for help with basic arithmetic. But when your bookkeeping is under scrutiny it is just an irresistible picture. Anyway! The bookkeeping is under scrutiny because of a core component of SoftBank's investing strategy, which is: Invest a lot of money in a buzzy startup at an aggressive valuation. Wait a little while. Invest some more money in that startup at a higher valuation. Profit! Literally profit, as Bloomberg notes: When SoftBank buys shares in a startup and then invests again at a higher valuation, Son says he has made a profit. That is legal under accounting standards, but SoftBank receives no money. The only change is that SoftBank has boosted the value of its original stake from, say, $1 billion to $2 billion by raising the value of the startup. In SoftBank's income statements and return calculations, at least some of the additional $1 billion can be counted as profit. "They pump up valuations to get higher returns to look good to investors," says Eric Schiffer, chief executive officer of Patriarch Organization, a Los Angeles-based private equity fund. "That kind of fundraising apparatus is essentially unicorn porn." We have talked about this strategy before, and actually reading the article mostly assuaged my concerns about SoftBank's bookkeeping. In fact, SoftBank says that it doesn't aggressively mark up its unicorn portfolio (and take accounting profits) every time it pumps in more money on its own. When it invests in later rounds alongside other investors, providing some external validation for the new valuation, it will mark up its stakes (but "only after taking into account future cash flows and public market proxies, as well as private market funding prices"). But, for instance, SoftBank and its associated Vision Fund "never took profits from WeWork by marking it all the way up to $47 billion," since it was the only investor in at those levels; instead it marked WeWork at levels that other investors also paid. And in its even sillier Oyo deal—in which the company's founder borrowed $2 billion to invest more money in his own company at a higher valuation—while "Son himself personally guaranteed the loans" to the founder and "SoftBank did not disclose Son's personal role in the deal," nonetheless "the Vision Fund decided it wouldn't mark up its Oyo stock to the $10 billion valuation because the latest funding did not include independent investors." It is the case that SoftBank makes a lot of profits by marking up its investments to later fundraising rounds also led by SoftBank, but, you know, given that, it's not as bad as it could be.  The Journal article, meanwhile, is largely about how outside investors in SoftBank wish that SoftBank wouldn't lend its executives millions of dollars to buy stakes in the Vision Fund. "In conversations with SoftBank executives and investor-relations staff, those shareholders and others—including AllianceBernstein LP and Odey Asset Management—have criticized the loans as risky and said they could create conflicts of interest between the executives and investors."  A common thread in the two articles is "25 - 4 = 9?" Here's Bloomberg: In February, he opened an event with a slide that showed: "25 – 4 = 9?" The point he was making is that SoftBank held assets worth 25 trillion yen—including a 12.5 billion yen stake in Alibaba—and had only 4 trillion yen in debt. Yet investors bestowed a value of 9 trillion yen on SoftBank, a discount of more than 60%. "It's just beginner math," Son said. "This is too cheap." And the Journal: Many value-oriented funds, who try to buy shares on the cheap, invested in SoftBank because its shares are worth just $80 billion, far below the value of the company's assets. SoftBank's stake in Alibaba alone is worth $125 billion. The two articles present two obvious potential explanations of the missing value. One is: If your assets are valued based only on what you pay for them, and you are famous for aggressively overpaying for assets, then the market is going to give you a bit of a haircut. Another is: If you are constantly doing weird risky stuff over the objections of your big shareholders, then those big shareholders are not going to give you full credit for the assets you already have. Elsewhere in unicorn porn: Once Silicon Valley's highest-flying darlings, companies from WeWork to Uber Technologies Inc. have collectively lost about $100 billion in value this year, prompting some startup executives to talk up profitability over growth as venture-capital investors grow more cautious about spending. ... "We've been in the middle of a rollicking party that's gone on for five years and someone has snapped on the light switch,'' said Chris Douvos, whose firm, Ahoy Capital, invests in venture-capital firms and startups. "We are all adjusting our eyes and no one has any idea how the rest of the night is going to go. That's how Silicon Valley feels right now." The crypto Is there anyone more trusting than a Bitcoin investor? At Vanity Fair, Nathaniel Rich has the amazing story of Gerald Cotten, the founder of Canadian crypto exchange Quadriga CX. Cotten kept most of Quadriga's Bitcoins in cold wallets that could only be accessed using private keys only he knew, and then he went and died of Crohn's disease on his honeymoon in India. Millions of dollars' worth of Bitcoins owed to Quadriga's customers have vanished. Or that is the story, but lots of aggrieved Quadriga creditors suspect that Cotten is still alive. Rich does not really take a position one way or the other on that question, though he is open to the possibility; he notes that "the RCMP and the FBI have refused to comment, but some of their interview subjects have gotten the impression that they believe Cotten might not be dead." But honestly reading this story made me care less about that particular mystery, because the whole story of Quadriga is so insane. When we have previously discussed it, I was pretty harsh about Quadriga investors. I wrote: "If you are a believer in the power of cryptocurrency, if you like its promise of trustless decentralized money, why did you entrust millions of dollars of your money to one guy with a laptop?" But it is actually way, way worse than that. Cotten was not just a random guy with a laptop. If you chose a random guy with a laptop to hold all your money, 99% of the time you'd choose a better guy to hold your money than Cotten. Cotten, it turns out, was a serial operator of "exit scams: Ponzis that, after reaching a critical volume, abruptly close up shop." He ran his first pyramid scheme at age 15. Cotten and his partner in Quadriga, Michael Patryn—an alias!—met on a message board for Ponzi schemers, where they bonded by running Ponzi schemes on each other: Patryn would tell friends that they'd first met in a con artist meet-cute, like the thieves in an Ernst Lubitsch film who fall in love while picking each other's pockets. Cotten tried to scam Patryn; Patryn tried to counter-scam Cotten. Soon they were responding to each other's public posts with inside jokes. And most of Quadriga's cold wallets were empty before Cotten's suspicious death:  Cotten, it turned out, had transferred the funds into personal accounts on competitor exchanges. At least some of those accounts had also been emptied. The operator of an exchange on which Cotten opened accounts told Ernst & Young that Cotten had squandered most of his holdings on reckless trades. On one particular margin account, he conducted 67,000 individual trades alone, placing enormous bets on fledgling currencies like Dogecoin, OmiseGO, and Zcash. The article suggests that there are two possibilities: Either Quadriga was a failed exit scam (Cotten took the money, but then lost it trading Dogecoin, and then had the bad luck to die on his honeymoon), or it was a really good exit scam (he took all the money, laundered it with Dogecoin trading, and then faked his death). Neither one is exactly great for trust in crypto exchanges. Meanwhile here is "Cryptoqueen: How this woman scammed the world, then vanished." The woman is Ruja Ignatova, the scam was a cryptocurrency called OneCoin, and … and … and: It took McAdam three months to go through it all, but questions were starting to form. She started asking the leaders of her OneCoin group if there was a blockchain. At first she was told it was something she didn't need to know, but when she persisted she finally got the truth in a voicemail in April 2017. "OK Jen… they don't want to disclose that kind of information, just in case something goes wrong where the blockchain is being held. And plus, as an application, it doesn't need a server behind it. So it's our blockchain technology, a SQL server with a database." But by this stage, thanks to Curry and Bjercke, she knew that a standard SQL server database was no basis for a genuine cryptocurrency. The manager of the database could go in and change it at will. "I thought, 'What???' And literally my legs just went, and I fell on the floor,'" she says. The inescapable conclusion was that those rising numbers on the OneCoin website were meaningless - they were just numbers typed into a computer by a OneCoin employee. Far from putting an end to their financial worries, she and her friends and family had thrown a quarter of a million euros away. Imagine calling up the people running Bitcoin and being like "wait is there a blockchain" and them being like "you don't need to know that information at this time." (Imagine there being people who run Bitcoin, imagine that being a question you'd have, etc.) That's like the one thing you need to know! I have previously mentioned my plan for a cryptocurrency called ExcelCoin, in which the coins would be tracked not by a decentralized blockchain but instead by a trusted central counterparty (me) in a secure database (a Microsoft Excel spreadsheet). This is the same basic idea, except it was an SQL database and nobody should have trusted the central counterparty. But they did anyway! Elsewhere: "Bitcoin Matches Record Losing Run in Fall to Six-Month Low." Things happen In a $0 Fee World, Charles Schwab Muscles Its Way to the Top. Charles Schwab's $26 billion deal for TD Ameritrade is an aggressive play for size that was set in motion before brokers started slashing commissions. Investment Advisers Fear Losing Out in Schwab-TD Ameritrade Deal. Inside the Mass-Tort Machine That Powers Thousands of Roundup Lawsuits. An Activist Investor Tries to Oust a Trump Confidant. Activist Investor Takes Stake in CVS. Google Fires Four Workers, Including Staffer Tied to Protest. SEC Moves to Overhaul Rules on Mutual Funds' Use of Derivatives. EBay to Sell StubHub in Deal to Create Global Tickets Giant. Repo: How the financial markets' plumbing got blocked. Even the Hottest Traders Face Bleak Bonuses in 2019. Westpac Banking CEO and Chairman Depart Amid Money-Laundering Probe. Hoard of Baroque Jewels Stolen in German Museum Heist. "Not OK, Boomer": Younger CFOs Curb Older CEOs' Earnings Management? "The rank correlation between hours worked and conscientiousness across countries is negative, though statistically insignificant." "In perhaps the most brutal rule, you are allowed to rip your bills in half so that your money goes a lot further." Musk to testify in own defense in defamation trial, his lawyer says.  If you'd like to get Money Stuff in handy email form, right in your inbox, please subscribe at this link. Or you can subscribe to Money Stuff and other great Bloomberg newsletters here. Thanks! [1] It hardly seems necessary to add that this post is all especially not legal advice. Do not insider trade! Do not hack all the press releases! Everything in the text assumes a hypothetical world without law, or a world where you do not care about law. In the real world you should do none of this. [2] In part just because mergers are relatively rare (once in the target's lifetime) compared to earnings releases (four times a year). But also the way the whole thing works is that companies sometimes put their draft press releases on a newswire's servers hours  or even days before they actually hit the button to publish them, and you hack into the servers during that delay. With bland scheduled announcements this is relatively easy, and companies might upload them early so they can hit the button exactly at 4 p.m. With mergers everything, including the press release, tends to be negotiated right down to the wire, and the idea of uploading a merger press release onto the newswire's server and just leaving it there for hours or days sounds unimaginably luxurious.  [3] The SEC said: "Despite this illegal advantage, it is not surprising that the Trading Defendants did not trade successfully based on this information 100% of the time. This is so because, unlike some other corporate announcements, it is not always predictable how the market will react to a given earnings announcement. For example, an earnings release may contain a combination of positive and negative news, may match analysts' preexisting expectations, or the market may focus on a particular aspect of a release at the exclusion of other information that points to a contrary conclusion." I, meanwhile, said: "In my former lives as a banker and a lawyer, I would often have to plan things for after an earnings release: The earnings release would go out on Tuesday, and we'd launch a deal on Wednesday, and it would be helpful to know in advance if the stock would be up or down. So on Monday I would ask the company's CEO or CFO or the relationship banker — who had seen the draft earnings release, knew what it said, knew what Wall Street expectations were, knew the company well, had a good feel for the markets — whether the earnings release would be good or bad for the stock. They would invariably — invariably! — say 'I have no idea, could go either way.' This is called 'strong-form market efficiency,' I think, or it may just be evidence that investment bankers and corporate executives should not be stock traders."

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