Spoofhouse.

Photographer: Simon Dawson/Bloomberg.

Why Is Spoofing Bad?

Matt Levine is a Bloomberg View columnist. He was an editor of Dealbreaker, an investment banker at Goldman Sachs, a mergers and acquisitions lawyer at Wachtell, Lipton, Rosen & Katz and a clerk for the U.S. Court of Appeals for the Third Circuit.
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Yesterday Navinder Singh Sarao was accused of spoofing S&P 500 E-mini futures in a way that might have contributed to the May 2010 flash crash. Prosecutors and the Commodity Futures Trading Commission claim that Sarao put in lots of big orders to sell futures, never intending to actually trade on those orders, to create the impression that there was a lot of selling interest and thus drive the price down. Here's how the CFTC describes the effect:

Many market participants, relying on the information contained in the Order Book, consider the total relative number of bid and ask offers in the Order Book when making trading decisions. For instance, if the total number of sell orders significantly outweighs the total number of buy orders, market participants may believe a price drop is imminent and trade accordingly. Similarly, if the balance of buy and sell orders changes abruptly, market participants may believe the new orders represent legitimate changes to supply and demand and therefore trade accordingly. Further, many market participants utilize automated trading systems that analyze the market for these types of order imbalances and use that information to determine trading strategies. Consequently, actions in the Order Book can, and do, affect the price of the E-mini S&P.

One reaction that a lot of people have is: Tough luck on them! If you're making your trading decisions based on the trading decisions that you think other people have made, you are a bad guy, and you deserve to be tricked. 

This is a reasonable intuition. John Arnold has endorsed it here at Bloomberg View, arguing that spoofers only harm "front-running" high-frequency traders who try to profit by trading ahead of other legitimate orders:

The battles between spoofers and front-runners are games being played between one computer and another in a tenth the time that it takes the human eye to blink. No human can see these trades, much less react to them in real time. The only party that is touched by the spoofer’s deception is the front-running HFT, whose strategies are harmful to every other market participant.

So ... what do we think? One framework that I often like to use in thinking about market structure is that high-frequency trading is controversial because it might make markets too efficient. This sort of depends on your definition of efficiency, but really simply, look at that CFTC description. If there are a lot of sellers at just above the current price, and not a lot of buyers at just below the current price, then that probably is an indication that sentiment is negative and the market will move down. Eventually some of that flock of sellers will get impatient and agree to sell at just below the current price, and down the price will go. If you recognize that fact faster than everyone else, you can make a bit of money by selling at the current price and buying back when the price drops. That is nice for you, but it also in some strict sense makes the market more efficient: If there are more sellers than buyers at (around) the current price, then the current price is "wrong," and your selling at the current price will help it move to the "correct" price more quickly. And by selling at the wrong price and buying back at the right price, you will make a bit of money to reward you for correcting the market.

That's sort of abstract and unsatisfying but basically true. Markets are more efficient when they move quickly to incorporate information. Order-book information is a kind of information. It is sort of second-degree information -- it reflects not, like, "what has changed in the fundamental value of this thing?", but rather "what has changed in people's perceptions of the fundamental value of this thing?" -- but it's still information, and incorporating it quickly makes the price more right.  This is what traditional market makers do -- if you are a market maker, and all your customers want to sell and none of them want to buy, you'll probably move your price down -- but high-frequency traders tend to do it faster and more mechanically.

Who cares if the price is right? Well, you might want the price to be right if you are an individual investor buying stock in your E*Trade account on your lunch break. You're buying at 12:45 not because you think the stock is unusually undervalued at 12:45, but because it's your lunch break. It would be reassuring if the market price was as accurate as possible, so that you'd know you've got a good chance of getting a fair price. Index funds, which are similarly value-agnostic, might have similar preferences. Accurate prices probably also make spreads smaller, so trading costs for both big and small investors are lower.

On the other hand, if you are a big fundamental investor looking to buy a lot of stock, you probably don't want a fair price. If you're a hedge fund manager who has spent months researching a company and come to the conclusion that its stock is undervalued, and you decide to buy 10 million shares, and you put in an order for 10 million shares at the current price, you will be sad if the price jumps up instantly. The whole point of all your research was to identify unfairly priced stocks; if high-frequency traders can just free-ride on your work by reacting to your order, then that feels like cheating. It feels like "front-running," actually, which is how you'd probably describe it.

The other day I said that "Norway's sovereign wealth fund wishes it could trade giant blocks of stock without impacting the price, which many large asset managers consider to be a fundamental human right." For a big fundamental investor, trading without moving prices is the goal of market structure, so anything that makes prices react more quickly to order information is bad.

And so a game exists in which big fundamental investors try to disguise their intentions so that the market doesn't efficiently incorporate those intentions into the price. They don't just blindly put in orders to buy 10 million shares at the current price. They break their orders into smaller pieces, and build (or rent from their brokers) algorithms to make their big orders harder to spot and less likely to move markets. John Arnold "spent millions of dollars developing a proprietary order-entry system to disguise and conceal strategies from external algorithms."

Okay, so, spoofing! Spoofing is about filling the order book with lies. Rather than just reflecting how much people want to buy and sell, and at what prices, the spoofed order book will be a more or less random collection of numbers. It will become un-informative. This is:

  • bad for the high-frequency traders who make markets based on order-book information;
  • bad for people who want prices to be maximally and instantaneously efficient, which may or may not include retail investors, index funds, etc.; and
  • good for people who don't want the market to instantly incorporate order information, which probably includes big fundamental investors.

So when regulators write and aggressively enforce rules against spoofing, they are in a sense favoring high-frequency traders over fundamental investors, sure. They are also making some other regulatory choices -- favoring market efficiency over rewarding research, punishing dishonesty regardless of its broader good or bad effects -- that are debatable but defensible. They are also creating gray areas, by banning a practice -- "spoofing," or lying about your trading intent -- that is dangerously close to another practice -- disguising your trading intent -- that is absolutely normal and ethical and even necessary.

There's a complication to this, though. Those algorithms that big funds use to disguise their intentions and avoid being "front-run" sometimes mimic the decision-making that high-frequency traders use. In particular, they rely on the information in the order book to decide how much to buy or sell, how fast, and at what price. Kipp Rogers:

These days, algorithmic trading tools are used by a wide class of traders. There is an entire industry, possibly larger than that of vanilla HFT, focused on creating and marketing these tools. Tremendous volume is executed via algorithms on behalf of traditional long-term traders. I’m not an expert on such algorithms, but my impression is that they tend to be much less sophisticated than a lot of vanilla HFT, and thus more likely to be tricked by spoofing. 

So while an equilibrium with lots of legalized spoofing might, as Arnold argues, be good for big fundamental investors, in the current equilibrium spoofing is probably bad for them: Their algorithms are often the ones that get spoofed.

Finally, what about spoofing and the flash crash? I obviously don't think that Navinder Singh Sarao caused the flash crash. For one thing, he turned off his spoofing algorithm a few minutes before the crash. Also, as Craig Pirrong puts it, "The complaint alleges that Sarao employed the layering strategy about 250 days, meaning that he caused 250 out of the last one flash crashes." But it's certainly possible that he contributed to it. I've heard a couple of theories on that. One, which I mentioned yesterday, is that his spoofing might have interacted badly with the algorithm that Waddell & Reed -- a big fundamental investor -- was using to sell E-mini futures. This is a story of spoofing tricking fundamental investors, with bad results for everyone. Another theory, which I heard from a high-frequency trader today, is that by spoofing high-frequency traders out of $879,018 -- Sarao's alleged profits on the day of the flash crash -- he might have caused them to hit their loss limits and shut off their own trading algorithms. Without the usual market-makers to provide liquidity, the market would have been more easily spooked than usual, and it would have been a lot easier for it to produce the wrong price. Which, for a few minutes on May 6, 2010, it definitely did.

  1. Arnold, like many commentators, uses the phrase "front-running" to describe trading on order information. Technically, "front-running" means trading on order information from your customers, and is illegal; a broker is not supposed to trade ahead of his customer's orders. But if I see an order to buy shares on the New York Stock Exchange, and I take action based on that order, that is not technically "front-running," nor is it illegal, though it might colloquially be "front-running" in many people's usage.

  2. I say this extreme generically, and it should not be taken as, like, investing advice, nor as an accurate description of how high-frequency trading algorithms work.

  3. We've talked about this before, but this discussion is (extremely) loosely based on this Austin Gerig paper. He notes the second-order-ness of the efficiency caused by high-frequency trading:

    Most HFT firms are run by scientists and engineers, and it is unlikely that they pay close attention to economic fundamentals and create a map of market structure that updates as fundamentals change. Instead, it is more likely that HFT firms are dependent on feedback mechanisms that punish them when the structure they enforce is incorrect.

  4. That said, you probably don't care about microsecond-level efficiency, so it's not clear, like, how much HFT efficiency you need.

  5. More consequentially, perhaps, it reduces your incentives to do that work, which might make prices less efficient in the long run.

    In this stylized description the big investors are trading, and the price is reacting, based on fundamental research. The investors might also trade based on fund flows, and the price might react more just due to the quantity of buying than to the fundamental signal that it sends. But those are sort of second-order versions of the same thing.

  6. Hurting, of course, retail investors who just want a fair price. Here's a great story about one such investor who had rotten timing.

This column does not necessarily reflect the opinion of Bloomberg View's editorial board or Bloomberg LP, its owners and investors.

To contact the author on this story:
Matt Levine at mlevine51@bloomberg.net

To contact the editor on this story:
Tobin Harshaw at tharshaw@bloomberg.net