Last month, we started looking at the signature 111-contract trading pattern of Igor Oystacher identified in some court filings in the CFTC’s civil action against him. Our initial take was that the pattern alleged looked so similar to legitimate trading that it would be difficult to infer that his orders were manipulative.

Having spent more time with the data, we did find some slightly more incriminating order sequences, but not enough to change our initial view. The CFTC will need to produce more compelling examples of manipulative intent to win this case.

Before getting into the granular order message details, some context is useful. Oystacher was trading one of the most heavily traded symbols, ZN, the 10 year treasury note, which is CME’s 3rd most active contract across all products. ZN usually trades over a million contracts a day, and almost always has a one-tick spread and 2000-3000 contacts quoted at each tick tier.

Oystacher’s trading pattern, as alleged in the CFTC’s court papers, and as reflected in the actual quote data in ZN on February 1 and 2, was as follows:

1. Oystacher quoted around 500 contracts at the best bid or offer (the “Side 1 Orders”), accounting for about 1/4 to 1/2 of the total contracts quoted market-wide at that price tier;

2. After several whole seconds, during which the best bid and offer did not change price, Oystacher entered a single large order (the “Side 2 Order”) on the opposite side of, and at the same price level as, his Side 1 Orders;

3. CME’s wash trade prevention logic automatically cancelled the Side 1 Orders before executing the Side 2 Order (so they did not execute against one another);

4. The Side 2 Order executed against the remaining non-Oystacher quotes at the same price level as the Side 1 Orders, clearing that price level.

Here’s what this pattern looks like in Surveyor (click images to enlarge; you can also view this data dynamically by accessing the free Surveyor web viewer here and entering ZNH6:US FU on February 1, 2016 and zooming in to the times indicated in the static images):



Note that CME’s wash trade prevention logic, viewed in microsecond resolution, actually cancels the Side 1 Orders at different times, creating a distinctive staircase pattern in the order volume graphs just before the executions. It is not hard to manually find more of these events by scrolling through the print list and looking for large prints immediately preceded by this staircase cancellation pattern.

Is this spoofing?

Spoofing is defined as entering orders at the best bid or offer with the intention of inducing other traders to react to those orders, and then trading against those other traders and cancelling the earlier orders.

The above pattern clearly satisfies some elements of this definition. Oystacher entered orders at the best bid or offer, and then traded against other traders and canceled his earlier orders. But did his earlier orders induce other traders to react?


What makes this pattern harder to call spoofing is the fact that the best bid and offer remain at the same price levels for the duration of the sequence. In most spoofing and layering cases, the Side 1 Orders cause a change in either or both of the best bid and offer, enabling the Side 2 Order to execute at a more favorable price than was quoted before the Side 1 Orders were entered.

From a strict microeconomics perspective, it shouldn’t matter whether the price moved as a result of the Side 1 Orders. All changes in published supply and demand have some effect on the equilibrium price, even if that effect is not enough to move prices by a whole price tier. The rigidity of the 1/32 minimum tick size in this contract masks the effect on price of small changes in supply and demand, but that does not mean there is no effect on price.** As the CFTC put it in its classic formulation of market manipulation in the 1982 Indiana Farm Bureau case, “when a price is effected by a factor which is not legitimate, the resulting price is necessarily artificial. Thus, the focus should not be as much on the ultimate price, as on the nature of the factors causing it.”

But from a practical courtroom litigation perspective, the absence of a price change is more significant. Where a fact finder is shown evidence of a trader repeatedly entering Side 1 Orders that are seldom executed but that consistently push prices in the direction of Side 2 Orders, and the Side 2 Orders consistently execute at prices more favorable than what was quoted in the absence of the Side 1 Orders, the fact finder can reasonably infer that the purpose of the Side 1 Orders was to induce other traders to react in a way that favored the Side 2 Orders. Why else was he doing it? The most logical purpose for such a sequence is that the trader wanted to push prices in his favor. There is an inference of manipulative intent, which makes the case for spoofing.

But where, as in the above ZN examples, the Side 1 Orders do not move prices, and the Side 2 Orders execute at prices that were already quoted before the Side 1 Orders were entered, another more benign explanation is possible. The trader may simply have changed his outlook on the direction of the market, and decided to replace his bids at a particular price level with offers. So long as this explanation is at least as logically sound as any other explanation, a fact finder should not infer manipulative intent, and the trader should win the case.

This is not to say the CFTC can’t win here with better evidence. The CFTC has put forward affidavits from algo designers at Citadel and HTG Capital Partners complaining that Oystacher’s trading patterns distorted their analysis of fair market value, “which caused [HTG] to place orders that we wouldn’t have otherwise placed.” As a market maker, HTG saw Oystacher’s Side 1 Orders as “strong and sudden interest from multiple market participants, which is an important factor that we use to make trading decisions.” “The build-up of orders created the false impression of market demand on which [Citadel] programmed our algorithms to make trading decisions.” 

This testimony is conclusory, but if it is supported by trading data showing that Oystacher was able to fill his Side 2 Orders in larger size than if he had not first entered his Side 1 Orders, against liquidity (provided by Citadel, HTG and their peers) that was otherwise not available, the CFTC can win this case. In the ZN examples above, Oystacher’s Side 1 Orders were a minority of the Side 1 liquidity, and he likely could have obtained his Side 2 fills without them. To succeed, the CFTC will need to present instances where the non-Oystacher Side 1 liquidity was more clearly coaxed out of the woodwork by Oystacher than in these ZN examples.

** Corollary: For the same reasons set forth above, widening minimum tick sizes, which the SEC is pursuing in its planned pilot, would make it more difficult to detect spoofing, and narrowing tick sizes would make it easier. If stocks and futures contracts were allowed to be quoted at smaller tick sizes, smaller Side 1 Orders would have a measurable effect on price that could be used to demonstrate manipulative intent. More on some other benefits of sub-penny pricing in the equity markets here.