Panther Energy Trading: The Orders Were Built to Disappear

In the Panther Energy spoofing case, Panther Energy Trading LLC and its owner agreed to a $1,400,000 civil penalty and the same amount in disgorgement to resolve Commodity Futures Trading Commission allegations of programmed spoofing. The agency alleged that they used large orders to draw other traders toward smaller orders they actually wanted filled, then canceled the large ones. If you know how a trading strategy was specified, coded or monitored, this case shows why the instructions behind the orders can matter as much as the orders themselves.

The agency’s July 22, 2013 settlement order covered the Red Bank, New Jersey trading company and its manager and sole owner. The agency alleged that the strategy operated from August 8 through October 18, 2011 on Globex, CME Group’s electronic trading platform. The agency described trading in 18 futures contracts across four CME-owned exchanges.

Can the Commodity Market Be Manipulated?

Yes. The Panther allegations show how displayed orders can create a false impression of demand and induce other traders to buy at the price the spoofer wants. The agency described a program that used that reaction to sell, then reversed the pattern to buy back at a lower price.

In the order’s crude-oil example, the algorithm first offered 17 contracts for sale at the best available selling price. Within a fraction of a second, it placed larger buy orders on the other side of the market, at progressively higher prices. Those bids suggested that demand was building and that prices might rise. Another trader seeing that apparent demand had a reason to buy the small sell order already waiting there.

The agency alleged that the large bids were intended to be canceled before execution. Once the small sell order filled, they disappeared. The program then reversed direction: a small order to buy, accompanied by large sell orders at progressively lower prices. The apparent buying pressure became apparent selling pressure, serving the same trader on both sides of the cycle. The agency said the algorithm sometimes ran hundreds of times in an individual futures contract in a single day.

We see the deception in the alleged strategy. Other traders were being asked to price a market around buying and selling interest that the program was built to withdraw. The small order got a trade. The large orders got an exit.

What Evidence Is Required to Prove Fraud?

In this spoofing prosecution, the government had to prove that the owner intended to cancel the orders when he placed them. The criminal trial evidence connected his instructions and software design to the actual orders, fills and cancellations. The Seventh Circuit’s account of the criminal trial explains how the trading results supported the conclusion that he intended to cancel the large orders when he placed them.

The opinion reports that on the Chicago Mercantile Exchange, 35.61% of the small orders filled, compared with 0.08% of the large orders. That difference mattered because the large orders were supposed to move other traders toward the small ones. The behavior in the market matched the different jobs assigned to the orders.

Their lifetimes also differed sharply from other high-frequency traders’ orders. A study presented at trial found that only 0.57% of the owner’s large orders stayed open for more than one second, compared with 65% of other high-frequency traders’ large orders. For an insider, that is the useful connection: what the strategy was told to do, what it showed the market, and what it actually bought or sold.

Algorithmic Spoofing and the Instructions Behind It

The criminal trial evidence described software designed to avoid filling the large orders. According to the court’s account, the owner commissioned two programs, Flash Trader and Quote Trader, and the programmer testified that the owner wanted a decoy that would provoke reactions from other algorithms.

The cancellation triggers made that purpose concrete. Large orders would be canceled after an interval measured in milliseconds, after a partial fill of the large orders, or after the small order filled completely. The program therefore connected withdrawal to both the risk that the displayed order would trade and the success of the smaller trade it was meant to help.

The opinion also recounts the owner’s earlier testimony to the Commodity Futures Trading Commission. Asked why the program canceled large orders when they risked filling but treated small orders differently, he said it was just how the program worked:

We see a deliberate instruction being passed off as a quirk of the software. The programmer’s account put the decision back with the person who commissioned it.

The instructions also reached the choice of market conditions. In its announcement of the criminal indictment, the Justice Department alleged that the programs looked for stable prices, low volume at the best prices and a narrow gap between buying and selling prices. They sometimes placed a one-contract test order to check whether conditions suited the strategy. The indictment account also described use of the programs on ICE Futures Europe, beyond the CME Group markets.

That charging account alleged that the large orders canceled automatically even when market conditions moved in their favor. It described a program built to withdraw the displayed interest, including when execution might otherwise have been attractive.

These are decisions a developer or trading employee may recognize in strategy instructions and cancellation settings. The trial evidence joined those decisions to the fills and cancellations. The person who understands why a condition was written into the program may explain something a trading log only records.

The CFTC Settlement and the Trading Profit

The civil penalty matched the approximate net profit the agency attributed to the strategy. The separate disgorgement obligation required the company and owner to surrender the gains the agency alleged. The agency also imposed a one-year trading prohibition tied to full payment of the civil penalty and disgorgement obligations.

Can CFTC Prosecute Criminal Violations?

No. The Justice Department brings criminal prosecutions. The Commodity Futures Trading Commission brings civil and administrative enforcement actions. In Panther’s case, the federal criminal prosecution was against the owner.

The Justice Department’s verdict announcement reports that a federal jury in Chicago convicted him on November 3, 2015 of six counts of commodities fraud and six counts of spoofing. It was the first federal prosecution under the anti-spoofing provision added to the Commodity Exchange Act by the Dodd-Frank Wall Street Reform and Consumer Protection Act.

What Public Trading Data Leaves Out

Public order data can reveal suspicious behavior while leaving the trader’s identity hidden. The 2016 Futures and Derivatives Law Report paper The Exercise of Anti-Spoofing Authority in U.S. Futures Markets: Policy and Compliance Consequences explains the gap:

The paper explains that exchanges, and the CFTC using exchange data, can identify the trading firms behind the orders. It also describes surveillance technology that can follow an order through submission, modification, cancellation and execution. That full sequence matters in a strategy where the orders meant to influence other traders disappear before becoming trades.

This is where knowledge inside a trading business adds something different. A market observer can see the sequence. A developer may understand the cancellation trigger. Someone who reviewed the strategy may know what explanation was given for it. We connect those accounts to the trading evidence.

When Surveillance Sees the Pattern

JPMorgan’s later CFTC settlement illustrates why the response inside a firm matters too. Its order covered alleged spoofing in precious-metals and Treasury futures and supervision failures despite surveillance alerts, inquiries and internal allegations.

Panther’s criminal trial evidence showed how instructions became programmed behavior. The JPMorgan civil allegations concerned, among other things, what supervision failed to address after warning signs appeared. Someone who knows the strategy’s design and someone who knows how the business responded to an alert can explain different parts of the conduct.

How Much Is a Whistleblower Claim Worth?

Under the Commodity Futures Trading Commission whistleblower program, eligible whistleblowers can share 10% to 30% of the money collected in a qualifying enforcement action. Your role and the information you can explain are where our assessment begins.

A whistleblower case under the False Claims Act can pay 15% to 30% of what the government recovers. The CFTC has its own whistleblower program for commodity-market information. We work with you to understand the conduct, the evidence and the program that fits your information.

You Know Why the Orders Disappeared

If you know who specified the cancellation settings, what the program was meant to do or how the desk answered surveillance questions, talk with our whistleblower experts about the strategy. We develop your information into a CFTC whistleblower submission with you, bring in CFTC whistleblower lawyers who understand electronic trading, and stay beside you throughout the process.