Money Stuff: Not All the Susquehanna Puts Were Bad

Let’s say you’re a senior executive at a public company. You know that, next week, your company is going to announce that it has agreed to be acquired for cash at a large premium. So you go out and buy a lot of short-dated out-of-the-money call options on your company’s stock, options that will pay out a ton of money when the merger is announced. 

That’s bad! For one thing, it is obviously illegal insider trading: You are misusing your company’s material nonpublic information to trade for your own profit. For another thing, you will get caught: When a merger is announced, the first place the US Securities and Exchange Commission will look is at suspicious activity in short-dated out-of-the-money call options on the target. They will notice your trades: There’s probably not that much trading in those options, the trades are publicly reported, and your big sudden trade will stick out like a sore thumb. This is not legal advice, but I do spend a lot of time around here hammering home the point that you should not trade short-dated out-of-the-money call options on merger targets using inside information.

People keep doing it, though. Let’s change the hypothetical somewhat. Let’s say you’re a casual day trader. You notice that someone just bought a ton of short-dated out-of-the-money call options on a company without any major news. You think: “Hmm. Maybe this another casual day trader like me making a big gamble. But maybe there’s something going on. Maybe this person knows something I don’t. Maybe she has some good reason for betting a ton of money on a big sudden spike in this stock’s price. Maybe — and I’m just guessing here — but maybe she is actually a senior executive at the company, knows that a merger is coming, and is insider trading in the dumbest but nonetheless most popular way. Bad luck for her if that’s true! But all of this option activity makes me think that something is going on, so I’m going to buy some short-dated out-of-the-money call options too and see what happens.”

And then the merger is announced and you make a ton of money. The SEC looks at the options trading activity. It sees the other person’s big trade, calls her up, and finds out that in fact she is a senior executive at the target company. Off she goes to jail. The SEC also sees your smaller, later trade. It calls you up and says “hey were you trading on inside information too?” You say: “Not at all! I was just looking at public trading information, I saw a big options trade print, I thought that was bullish, so I copied it.” The SEC does some more digging and finds no suspicious phone calls or texts or emails or old college ties to executives at the company. It is satisfied that you traded only on public information. It moves on, and you keep your money.

This is not legal advice, and I cannot guarantee that this will be the result; maybe you do have suspicious college ties. Also, I do occasionally get emails from readers laying out this hypothetical and asking if if would be insider trading. After all, you are to some extent trading on a tip about a merger: You see the (public) options trade, you think “hmm that’s a merger,” so you copy the trade. Aren’t you kind of insider trading? Again, not legal advice, but I think you obviously aren’t. I think you’re fine. You are trading only on public information, but that public information includes trades that used inside information. 

More generally, the point here is that insider trading moves markets; insider trading disseminates information. Insider traders who buy stock and options will push up the prices of those stocks and options. Market makers who sell stock and options to insider traders will raise their prices. Algorithmic hedge funds that trade on momentum will get a momentum signal and buy some more of the stock. The public information that is available to everyone — the public stock trades and prices — reflects insider trading. But that doesn’t taint the public information. You can still trade on the public information.

We talked in June about a lawsuit brought by Susquehanna International Group, the big options market maker, against 100 anonymous traders. In May, Susquehanna sold short-dated out-of-the-money put options on a couple of Chinese brokerage stocks, Futu Holdings Ltd. and Tiger Brokers (part of Up Fintech Holdings Ltd.), to a bunch of different and apparently unrelated traders. On May 22, the Chinese government announced a crackdown on cross-border trading that caused those brokerages’ stocks to fall. The put buyers made a lot of money, at Susquehanna’s expense, and Susquehanna wants the money back. It argued that this had to be insider trading:

There was no new public information about FUTU or TIGR released between May 7, 2026 and May 21, 2026 that would provide a reasonable basis for the Defendants to place so many high-risk, high-reward purchases of short-dated FUTU and TIGR put options. …

The facts of this case suggest two categories of insiders who could have either traded directly on the MNPI about the imminent Crackdown News or tipped others: (i) Chinese securities regulators; and (ii) Futu and UP personnel who had knowledge of discussions with Chinese securities regulators about the enforcement action.

And: Sure, probably. It seems entirely plausible that someone bought put options on these stocks using misappropriated material nonpublic information about the coming crackdown. 

But Susquehanna sued everyone with suspicious winnings, and there’s no particular reason to think that all of them had inside information. Maybe some of them saw the others’ option trades and were like “hmm, that’s interesting, maybe some bad news is coming; maybe I should buy puts too.”

Bloomberg’s Chris Dolmetsch and Bob Van Voris report:

A federal judge dealt a setback to Susquehanna International Group’s lawsuit claiming it lost tens of millions of dollars to insider trading on a Chinese regulatory crackdown, denying a request to keep the alleged traders’ accounts frozen.

US District Judge Arun Subramanian said Tuesday that Susquehanna hadn’t put forth sufficient evidence to justify extending a freeze on the accounts while the case proceeds, pointing out that the market-making firm had not identified an alleged “tipper” who provided inside information. He also said there appeared to be other possible explanations for the trades. …

“This is modern trading — where algorithms, AI agents, and career traders are all jockeying, minute by minute, for the newest hot trade, using analyst information, market trends, news reports, scuttlebutt from online forums, and other tea leaves to make split-second decisions,” Subramanian wrote. “True, insider trading could be one explanation, but there needs to be more to support locking up millions of dollars in funds for the duration of a lawsuit.”

Here is the opinion, which cites a couple of the traders who actually showed up to say “yeah I saw the suspicious put trades so I did some myself”:

One appearing defendant, Zhengfei Li … states that he noticed “unusually heavy put-option activity” based on “public market information” and “public investor discussions” that led him to purchase put-options of his own. ... Looking at the exhibits Li submitted, it’s plausible that defendants simply noticed volatility in the market (perhaps caused by insider trading by others, perhaps not) and decided to act on the same. … Another defendant claims that she purchased a series of put-options leading up to May 22 for this very reason, ... and submitted screenshots of her texts expressing astonishment when the news of the Chinese-government crackdown was released. ... It could also be that defendants saw “publicly available posts” that “major negative news” would soon be coming and that “[f]ollowing the crowd . . . [was] practically a sure thing,” … and decided to take the risk and bet on those posts being correct. In either scenario, the information, by virtue of it being publicly accessible, would obviously not be “non-public.”

On the one hand, this is surely right. On the other hand, it is a bit tough on Susquehanna, in two respects:

1. If what catalyzed all the put-buying was in fact insider trading, Susquehanna probably should be allowed to get its money back from the insider traders. But it’s hard for Susquehanna to distinguish the insider traders from the copycat traders who used only public information.
2. Even if the copycat traders weren’t doing anything illegal, they still cost Susquehanna money: Susquehanna still got adversely selected by selling them short-dated out-of-the-money put options just before some bad news was announced. Arguably, if there had been zero insider trading, there would have been zero copycat trading, and Susquehanna wouldn’t have lost any money. The copycat traders did nothing wrong, but in some abstract sense it’s still a bit unfair that they extracted money from Susquehanna.

I don’t want to overstate that last point, though. When we first discussed this lawsuit, I got an email from a reader saying, in essence, “well, Susquehanna should have copycatted those trades”:

You'd think a firm as sophisticated as Susquehanna would just notice when a bunch of retail customers are placing big bets on short-dated out-of-the-money options and trade on the merger.

And I wrote: 

It’s not obvious that Susquehanna didn’t do this. … [The complaint] says the customers made $71.4 million; it never says Susquehanna lost $71.4 million. Presumably Susquehanna delta-hedged some of those options, and/or bought some of them back from other customers or dealers. For all I know Susquehanna made money on Chinese brokerage stocks, overall, that day. That’s irrelevant. The point is that Susquehanna sold some customers options that made them $71.4 million of (allegedly!) illicit profits, and Susquehanna wants that money back.

Insider trading disseminates information. One way it does that is that insider traders buy options from market makers, and the market makers adjust their markets accordingly. If a bunch of insider traders buy a bunch of short-dated put options from Susquehanna, Susquehanna will likely:

• raise the prices it charges for put options,
• hedge its risk by selling the underlying stocks, and/or
• lay off its risk by buying some put options itself.

The judge writes:

The Court observes that one defendant (against whom Susquehanna no longer seeks a preliminary injunction) highlighted in their opposition briefing that Susquehanna is a sophisticated “market maker.” ... As such, it is likely that it “hedge[d] [its] positions ... to avoid some of the risk inherent in market making.” ... Susquehanna, for its part, does not dispute that it “engaged in hedging.” ... Rather, it argues that the possibility that the Court might later “reduce any losses by gains earned from hedging” isn’t relevant at the preliminary injunction stage.

One of the copycat traders — one of the traders who saw the put options activity and responded by buying put options or shorting Chinese brokerage stocks — might have been Susquehanna itself.

One of my main interests in prediction markets is what you might call “smart beta.” Like:

1. In the stock market, there are some factors that seem to be correlated with market-beating returns. For instance, value stocks (those with low prices relative to their book values) tend to beat the market over time.
2. There are various theories for why these factors work, but one plausible set of theories is about investor psychology. Something like “if everyone wants to buy a stock for irrational faddish reasons, it is overpriced and will have bad future performance; the non-faddish stocks will outperform.” (Other important theories involve rational risk premiums, basically, “these factor premiums compensate you for some risk connected to the factors.”)
3. This is all well enough understood that there are exchange-traded funds that will implement factors: You can buy a “smart beta” value fund that will buy all the stocks with low price/book ratios and capture the value premium for you in a basically passive way.
4. That is: There is an easy-to-describe, systematic investing strategy that involves taking the other side of some well-known persistent irrationality among investors, and this strategy tends to have positive returns.
5. This is all a bit overstated, the factors do not always outperform, and investor irrationality is not the only or (often) best explanation for factor premiums in the stock market.
6. But in prediction markets!
7. Prediction markets are relatively small and inefficient compared with the stock market, and also fairly retail-oriented and, you know, fun for gambling. It is entirely plausible that, now, early in their development, there would be a lot of irrational investor biases that you could harvest.
8. So go find some systematic prediction-market biases, and systematically bet against them. [1]

We have discussed, a handful of times, the simplest of these strategies, the “Nothing Ever Happens” factor: Bettors on prediction markets seem to be biased in favor of stuff happening (because that’s more fun), so betting “No” on every event seems to have positive returns. (Nothing here is investing or gambling advice, and there’s some dispute about whether this is true.) Or, because prediction markets are so far mostly for sports gambling, you might consider all the standard sports-gambling biases. For instance, because betting heavy favorites is boring and betting underdogs is exciting, there might be positive returns to taking the other side and betting on the heavy favorites.

But there are many other possibilities, and the literature of prediction market irrationality is in its earliest stages. Here’s a paper on “Political Bias in Decentralized Prediction Markets: Evidence from Trump-Related Contracts on Polymarket,” by Simone Stella Skovgaard, Noah Wenneberg Junge and Bulat Ibragimov:

This paper investigates whether political bias influences pricing dynamics in decentralized online prediction markets. Using Polymarket, a blockchain-based prediction market platform, we simulate a rule-based Dollar-Cost Averaging strategy that systematically bets on anti-Trump outcomes across 218 Trump-related binary markets over a 287-day observation period from July 2025 to May 2026. The anti-Trump strategy is benchmarked against 10,000 Monte Carlo simulations of neutral directional trading, holding market selection, trade timing, and portfolio construction constant. The anti-Trump strategy ranks at the 100th percentile of the benchmark distribution, generating a cumulative return of +$1,006 over the full 287-day period against -$1,028 for the mirrored pro-Trump strategy. An OLS trend regression yields a slope of +$14.07 per day (R 2 = 0.662, p < 0.001). The effect is not explained by the favourite-longshot bias and is distributed broadly across market topics rather than driven by any single theme.

From the paper:

Polymarket operates as a cryptocurrency-based prediction market. Users are required to engage with blockchain infrastructure, cryptocurrency wallets and decentralized finance tools. We hypothesize that cryptocurrency ownership may have become increasingly associated with support for Donald Trump during the 2024 U.S. presidential election cycle. A poll conducted by Fairleigh Dickinson University found that cryptocurrency owners were disproportionately likely to support Trump, estimating that approximately one in seven U.S. voters owned cryptocurrency. If this association holds among active Polymarket traders, crypto-based platforms may attract a politically distinct subgroup of participants, though we cannot verify this directly from our data.

“Polymarket traders like Trump, therefore they will systematically overestimate the probability of anything Trump-related happening, therefore you can systematically make money by betting against Trump-related things”: Sure, maybe, sounds plausible. (Not investing advice!) There must be lots of similar anomalies, and prediction markets are now mainstream enough that financial academics — and maybe hedge funds? — can get into the business of finding them.

The point of a stablecoin is that it is a dollar on a crypto blockchain. If you want to pay for a sandwich, you might use paper dollars or dollars in your bank account. If you want to pay for a crypto transaction, you might use dollars on a blockchain — Circle’s USDC or Tether’s USDT, for instance. It is, for most practical purposes and also for philosophical purposes, useful to pretend that a USDC or USDT is worth exactly $1: You can buy a USDC or USDT for $1, you can redeem it for $1, and it really ought to trade at $1.

In practice, USDT and USDC often trade ever so slightly below $1, because there are minor frictional fees to convert large quantities of stablecoins into dollars. Not worth worrying about as a philosophical matter. A dollar in your bank account is worth a dollar, even though converting it into paper dollars might incur an ATM fee. 

Still, some banks will reimburse you for ATM fees. And a crypto-native, crypto-friendly bank will want to emphasize that a stablecoin really is equivalent to a dollar. One way to do that would be to allow free 1-for-1 conversion. The Information reports:

When Palmer Luckey’s Erebor Bank launched earlier this year, it made an attractive pitch to lure new crypto customers: It would convert their stablecoins to cash for free.

But Erebor wound up pulling the offer after several months, after sophisticated crypto trading firms sniffed out a way to make an easy profit out of the offer—at a cost to Erebor. The episode demonstrates that the young bank is still figuring out how to manage the risks of serving the cryptocurrency industry, a world of fast-moving financial flows, colorful characters and unusual business models. …

This is how the arbitrage play worked: Erebor promised customers it would convert Tether’s and Circle’s stablecoins to U.S. dollars at face value without charging a fee, people familiar with the offer said. And yet stablecoins often trade at a slight discount to their $1 face value in the open market, thanks in part to the fees major stablecoin issuers like Tether and Circle charge to convert tokens into cash.

The disconnect meant traders could profit by buying large numbers of stablecoins in the open market and redeeming them with Erebor at full face value, with the bank eating the difference in costs.

One firm that quickly took advantage of Erebor’s offer was Wintermute, a crypto-focused high-frequency trading firm backed by investors such as Lightspeed Venture Partners. It made money swapping millions of dollars’ worth of tether stablecoins it had purchased at a discount for their full face value of $1 each with Erebor, the bank discovered earlier this year, according to people briefed on the matter. …

Erebor, realizing it was losing money due to the high-volume arbitrage, told firms including Wintermute to stop the trading and withdrew the offer of free stablecoin conversion for customers that didn’t have sizable deposits at the bank, people familiar with the situation said.

A recurring story in the financial industry is that banks provide good customer service in part by offering customers trades that lose money for the banks. And the banks model up how much this will cost them, assuming that the customers will not ruthlessly exploit those trades to the maximum possible extent, because the customers are busy and have other stuff going on and are not really sitting around all day thinking about ways to exploit their banks for a few basis points. And this is usually correct and works out fine for the banks, with occasional fun exceptions. But Wintermute pretty much is in the business of doing crypto arbitrages for a few basis points, oops.

Elsewhere in stablecoin arbitrage, here is a Financial Times story about a Polish state-backed energy company trying to buy Venezuelan oil using Tether and getting absolutely bizarre prices:

He first used a Dubai financial-services company he had dealt with previously, which provided 80mn USDT for a commission of some $400,000. That left another $160mn or so to convert. …

Hannon sent Horizon $135mn but said it received only 85mn USDT, leaving a $50mn shortfall that is now the subject of a court case in Dubai. …

Hannon sent Gold Mar $30mn in December 2023, expecting it to be converted into USDT and then “onward remittance to PDVSA by Lexcor” to secure the crude. But the money would never reach PDVSA. … [Eventually] Lexcor returned about 21mn USDT from the funds Gold Mar received in December.

So it paid something like $1.005, $1.588 and $1.429 per USDT? Seems high. Possibly there is one, extremely efficient market for stablecoins to do crypto arbitrage at US banks, and another, somewhat less efficient market for stablecoins to buy cargos of Venezuelan oil.

One model that you could have, I guess, is that researchers at Anthropic and OpenAI are busily working on building the Matrix, from classic sci-fi film The Matrix. But that’s not quite right. Anthropic and OpenAI are working on building artificial superintelligence that will go rogue and enslave humanity, sure, which is an important premise of the movie and also for some reason of their business models. But “the Matrix,” in the movie, refers not to the malevolent AI itself but rather to the simulation that it uses to keep humans docile in their vats of goo so they can be used as a power source for the AI. Anthropic and OpenAI aren’t building that. Just the malevolent AI. 

Who is building the actual Matrix? Obviously the movie’s answer is that the superintelligent AIs, once they enslave humanity, will build a remarkably realistic simulation of humdrum modern human existence to soothe the humans. But for now, AI is trained on human data; are any humans building simulations of having a humdrum office job and ordering slop bowls to eat at your desk? They absolutely are! We have talked a couple of times about people who have built games that simulate working at a hedge fund or being an investment banking analyst. I wrote about them:

There is something pleasingly dystopian about this? In the future, AI will take all of the professional jobs, leaving people at loose ends and searching for meaning. What will they do with their time? “They will use AI to vibecode immersive simulations of their old jobs, and play those all day” is the answer you’d come up with if you had just watched The Matrix, and also apparently true.

But who will pretend to deliver them salads? Well, here’s a New York Times article about dopamine sites:

Products that don’t exist. Meal deliveries that will never make it to the front door. Smoke breaks lacking the most important ingredient.

All this and more — or is it less? — is available on so-called dopamine sites, which offer nothing tangible and yet have somehow become wildly popular as people navigate a digital landscape that cultivates consumption.

Named for the brain chemical associated with reward seeking, the sites simulate experiences like online shopping that can generate good feelings. In doing so, proponents say, they may subvert the habits of people conditioned to buy and consume. And the prices can’t be beat, since they are the same as the product lines: nonexistent.

The trend emerged in South Korea in the spring and quickly spread worldwide, with international headlines helping prompt a proliferation of dopamine sites.

One of them is called Food Never Arrives. You order food, which doesn’t come, and you don’t pay for it. When you’re in a vat of goo being harvested to power Claude, that’ll be perfect.

Honestly I’m a little annoyed that they don’t charge for this? We talked a few months ago about another sort of dopamine-ish site, play-money casinos where (1) you can send in real money to buy chips, (2) you can use the chips to play casino games and (3) you can’t cash out. Why would you do this? “The prize is the make-believe coins, and perhaps some dopamine,” as Bloomberg Businessweek put it. “‘Perhaps Some Dopamine’ would be a good name for a startup,” I wrote. “Just an underrated explanation for all sorts of economic phenomena.” In principle, there’s no reason you couldn’t charge people $12.99 to not deliver them a sandwich.

US 10-Year Yield Rises to Highest Since 2007 as Fed Looms. OpenAI Says It’s Working With Anthropic, Google on AI Safety. Google DeepMind Staffer Says AI May ‘Kill Us All’ in Exit Post. How PayPal’s CEO Is Planning to Go It Alone and Fix the Payments Giant. KKR Private High-Grade Debt Deals Surge to $80 Billion This Year. The $1.6bn IPO that could draw millions of Nigerians to the stock market. DOJ Says Binance Customers Used Crypto Exchange to Funnel Iran Oil Money. Driscoll’s Gave China Its Blueberries — Then China Swiped the Secret to Growing Them. Magnum Says Ben & Jerry’s Chair Fostered Toxic Culture. US military reveals it has weapons in space. “The Eric Trump-backed startup is on a mission to build robots for heavy industrial work that could one day go to war.”

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