Government Focuses on Old-School and New-School Techniques
In the last year, we have seen a noticeable uptick of charges involving market manipulation brought by the Department of Justice (DOJ), the Securities and Exchange Commission (SEC), and the Commodities and Futures Trading Commission (CFTC). Those charges have focused on manipulative acts from both the old school, such as matched trading, and the new, such as spoofing and layering. The spike in market manipulation enforcement is poised to continue, particularly in light of the first successful prosecution for spoofing, which concluded last week with a three-year sentence for the defendant, Michael Coscia. In this alert, we summarize these trends and discuss their implications for participants in the financial markets moving forward.
Market Manipulation Generally
In the context of a securities transaction, a manipulative act is one that sends “a false pricing signal to the market” and therefore does not reflect the “natural interplay of supply and demand.” It is typically undertaken to create a false image that the security’s value is based on supply and demand, and thereby induces unwitting investors to buy the security. Market manipulation is regulated under a number of statutes and rules. Most notably, Section 9(a)(2) of the Securities and Exchange Act (Exchange Act), titled “Manipulation of Security Prices,” prohibits transactions in certain securities that create “actual or apparent active trading in such security, or raising or depressing the price of such security, for the purpose of inducing the purchase or sale of such security by others.”  Section 9(a)(2), however, does not apply to all securities; for instance, it is not applicable to over-the-counter securities. Section 10(b) and Rule 10b-5 of the Exchange Act are more broadly worded, and thus more broadly applied, including, prohibiting any act, practice or course of business that operates or would operate as a fraud or deceit upon any person.
Section 9 of the Commodity Exchange Act (CEA) also proscribes manipulation of the price of any commodity in interstate commerce. Section 4c(a)(2)(B) of the CEA further prohibits any price from being reported, registered or recorded that is not a bona fide price. In 2010, the Dodd-Frank Wall Street Reform and Consumer Protection Act amended the CEA’s Section 4c(a), adding a section that specifically prohibits spoofing, making it unlawful to engage in trading that is “of the character of, or commonly known as, spoofing,” which is defined as “bidding or offering with the intent to cancel the bid or offer before execution.” In addition, self-regulatory organizations, such as FINRA and the exchanges, promulgate rules designed to guard against manipulative conduct.
Manipulative conduct is often divided into two categories: “Traditional Manipulation” and “Open Market Manipulation.” Traditional manipulation requires a “bad act” explicitly proscribed under Section 9(a)(1) of the Exchange Act, such as fictitious trading, a “pump and dump” scheme, or wash sales. Under Rule 10b-5, the fraudulent conduct alone is indicative of the manipulator’s deceptive intent. In open market manipulation, the trades themselves are not objectively fraudulent but, when taken in context, may constitute a manipulative practice. An example is “painting the tape,” or “marking the close,” which involve engaging in a series of transactions on a public facility, typically at the end of a trading day, in order to give the impression of activity or price movement in a security. Each transaction may individually appear legitimate, making the manipulator’s intent in the overall open market scheme more difficult to prove.
Enforcement agencies have sought to target market manipulation as far back as 1934 when the Exchange Act was enacted. Since that time, the complexity behind manipulative schemes has steadily increased, as has the zeal of enforcement agencies responsible for curbing manipulative practice. The government’s stated goal is to protect the integrity of the open market, and individuals who engage in market manipulation fundamentally undermine legitimate investors’ ability to value the market.
In its most general terms, matched trading is a form of traditional market manipulation. A matched order occurs “when an individual enters an order or orders for the purchase or sale of a security registered on a national securities exchange with the knowledge that an order of substantially the same size, at substantially the same time and at substantially the same price, for the sale or purchase of such security, has been or will be entered by or for the same or different parties.”  The purpose of this strategy is to create “a false or misleading appearance of active trading in such security or a false or misleading appearance with respect to the market for such security.”
Over the last couple of years, a number of notable securities fraud cases included matched trading charges. For example, in September 2015, the DOJ and SEC both brought actions in the Southern District of New York against Benjamin Wey, the CEO of New York Global Group, a private equity firm, for allegedly engaging in this kind of market manipulation, among other offenses. After obtaining shares of CleanTech (one of his firm’s clients) through the use of foreign nominees (and allegedly failing to report that his beneficial ownership interests exceeded five percent), Wey allegedly sought to unload those shares through prearranged trading. For instance, after CleanTech made a public offering of $3.00 per share, Wey—with the assistance of his Swiss broker, co-defendant Seref Dogan Erbek—matched a trade of 1,000 shares of CleanTech at $5.10 per share, a 70 percent price increase. Soon thereafter, Wey allegedly touted the increase to potential investors. As evidence of the matched trading, the DOJ and SEC cited emails such as the following: “Dogan, Cleantech just traded at $4.50 per share. Please make sure the trader buys the stock at $5 per share, stay at $5 per share bid price, not less. Please make sure this happens right away.” As the government alleges, Wey orchestrated these transactions, locking down the buyer and the seller and predetermining the price and the timing of the sale, in an effort to drive the stock’s price upward.
The charges against Wey are not unique. The DOJ—particularly the United States Attorney’s Office for the Southern District of New York (SDNY)—has been steadily pursuing market manipulation cases. Similar allegations can be found in the case against Edward Durante, and various co-conspirators, unsealed earlier this year, regarding trading in shares of VGTel Inc. The government alleges that Durante, who held a majority of the publicly traded stock of VGTel, recruited a broker to fraudulently buy his shares. Durante and the broker would match the transaction, coordinating on date, number of shares and price. These sales artificially inflated the price of VGTel from $0.25 per share to as much as $1.90 per share, as well as inflated the trading volume.
Perhaps the clearest example of matched trading can be found in the case against Jason Galanis and six other co-conspirators, brought in the SDNY last September, involving the manipulation of the price of Gerova Financial Group, a publicly traded reinsurance company. Like Durante, Galanis was looking to unload a large block of Gerova shares and recruited (and compensated) brokers to buy the shares from him. The SEC alleges that Galanis caused his orders to sell Gerova stock to be matched with buy orders placed by the brokers “at exactly the same times, prices, and amounts.” The government further alleges that Jason Galanis’s brother, Jared Galanis, coordinated both sides of the matched trades, placing the sell orders and then calling or emailing the brokers to place the parallel buy orders. Through the matched trading, the Galanis’ are alleged to have reaped over $20 million in profits.
The cases above demonstrate that the SDNY is increasingly focused on investigating and charging market manipulation based on matched trading. The SDNY, however, is not alone. Over the last few years, regulators have pursued matched trading charges in a number of districts across the country.
Spoofing and layering—both forms of open market manipulation—continue to occupy the recent attention of regulators and commentators alike. What conduct falls under the header of spoofing has been debated, but it can be defined generally as the placing of non-bona fide orders in an attempt to induce other market participants to buy or sell in order to move the market price. The CEA provides a simpler definition of spoofing: bidding or offering with the intent to cancel the bid or offer before execution. Layering is simply a type of spoofing, where the trader places several orders to improve the price of a trade in the opposite direction. No matter the definition, spoofing is typically accomplished through complex algorithms that quickly cancel or withdraw a bid or offer after creating the appearance of demand.
As high-frequency traders (HFT) have found themselves under the regulatory microscope, the number of spoofing investigations has risen. The most notable case is that of Michael Coscia, the founder and owner of Panther Trading, an HFT firm. In November 2015, Coscia was convicted after trial of six counts of commodities fraud and six counts of spoofing in the first criminal charges filed under Dodd-Frank’s anti-spoofing provision to the CEA. On July 13, 2016, Coscia was sentenced to three years in prison.
At trial, the government proved that Coscia made over $1 million in illegal profits by engaging in thousands of spoof trades using a variety of futures contracts, including gold, copper, euros, British pounds, soybean oil and soybean meal. The government’s case included Coscia’s programmer, who testified that Coscia directed him to design a trading algorithm that would “pump up the market” by placing a large volume of “quote” orders several ticks away from the best bid or offer to generate price movement. A separate algorithm was then designed to create smaller orders on the other side of the market to capitalize on the small, but predictable, price movements. Once these orders were executed, the “quote” orders were canceled. In his own defense, Coscia testified that he intended to trade on every order. He also said that by causing momentarily lopsided markets, he “improved the market for everyone” by creating liquidity.
The Coscia verdict shows that the jury was unconvinced by Coscia’s innocuous explanations for why orders were canceled. It did not matter to the jury that there is nothing unlawful about placing large orders, that HFTs execute more large orders than most, or that any of his orders could have been filled. As such, Coscia showed that proving fraudulent intent can be done not only by emails, instant messages, audio recordings and historical trading data (which are the traditional bases for deceptive trading claims), but also from less conventional sources such as the code used to program trading algorithms and testimony from programmers and other non-trading personnel. In short, Coscia provided a playbook, for both the DOJ and the CFTC, to prosecute spoofing cases and hold individuals accountable under Dodd-Frank’s anti-spoofing addition to the CEA.
Since Coscia, there have been a number of significant spoofing cases brought in the Northern District of Illinois. Most notably, in September 2015, Navinder Singh Sarao, a British day trader, was indicted on 22 charges of spoofing and market manipulation that allegedly contributed to the 2010 “flash crash.” In March 2016, a British judge authorized Sarao’s extradition to the United States. The government alleges that Sarao used layering to create the appearance of supply in the market. He modified the orders so they stayed close to the market prices, and eventually canceled them. When the price dropped, he sold futures contracts only to buy them back at lower prices. Sarao allegedly acknowledged his spoofing in emails to his programmer, such as: “I need to know whether you can do what I need, because at the moment I’m getting hit on my spoofs all the time and it’s costing me a lot of money” and “If I am short I want to spoof it [i.e., the market] down.” (emphasis added).
One other notable case is that of Igor Oystacher, the founder of 3Red Trading LLC. In June 2015, the CME and ICE exchanges penalized and banned Oystacher for his alleged spoofing. Then, in November 2015, the CFTC accused Oystacher of spoofing on 51 days from December 2011 through January 2015. The CFTC alleged that, rather than moving the price of the contracts he was trading, Oystacher created a “false impression of market depth and book pressure” with his initial orders that he later canceled. Oystacher’s defense is that his reasoning skills (99th percentile; he was a speed-chess champion) and customized computer equipment made him faster than most humans at executing trades. Unlike the other spoofing cases involving traders using an algorithm, he has argued, his trades required the “click of a mouse.”
Insider trading cases—even before the Second Circuit’s landmark decision in United States v. Newman—have dominated the headlines in recent years. And while spoofing cases have also received attention, the overall increase in manipulation charges has flown under the radar. Whether it be spoofing or simply matching buyers and sellers outside the open market to influence the price of a stock, the government is clearly focused on pursuing and charging market manipulation. The government’s position is summed up in the comments of US Attorney Zachary Fardon after the Coscia sentencing: “Guess what? A lie is a lie. Deceit is deceit. Using technology or algorithms to facilitate that kind of age-old crime doesn’t make it anything other than what it is.”
It is important to recognize that every trader is potentially vulnerable to an allegation, after the fact, that their actions intended to deceive the market—either that they intended to cancel their bids or offers before they were executed (spoofing), or that in unrecorded conversations with brokers they agreed to match a trade seeking to affect the market price (matched trading). With Oystacher, traders are on further notice that suspected spoofing is not restricted to use of algorithms or instances when the market price was actually manipulated.
Traders and their firms need to take this trend seriously. Placing and canceling a bid here, or an offer there, may appear to be inconsequential or something that only pertains to niche algorithmic traders. Similarly, it may seem that only blatant matched trading, such as bribing brokers to execute both sides of a trade at a desired price, will get a trader caught. But the rise in the number, and sophistication, of both old-school and new-school manipulation investigations creates a new source of trading risk. The SEC and CFTC continue to roll out new technology, along with the SEC’s development of a comprehensive database of trading information across all trading platforms, to identify and investigate suspicious trading. Thus, even if the conduct does not result in charges, it may be the subject of a potentially damaging investigation.
The key, as it often is, is for firms to implement robust, prophylactic compliance and surveillance measures that can help detect manipulative trading activity before a regulator makes contact. In short, as the regulatory landscape continues to evolve and enforcement agencies strive to keep pace with traders, firms need to develop ways to stay one step ahead, such as heightened surveillance programs around the timing of orders and cancellations.
 In re Barclays Liquidity Cross & High Frequency Trading Litig., 126 F. Supp. 3d 342 (S.D.N.Y. 2015).
 See 15 U.S.C. § 78i.
 See 17 C.F.R. § 240.10b-5.
 S.E.C. v. Wilson, No. 04-CV-1331 (JCH), 2009 WL 2381954, at *1 (D. Conn. July 31, 2009).
 See United States v. Wey et al., 15 Cr. 611 (AJN) (SDNY) and SEC v. Wey et al., 15 Civ. 7116 (PKC) (SDNY).
 See United States v. Durante, Cervino, Werbel, and Khan, 15 Cr. 171 (ALC) (SDNY); SEC v. Edward Durante, et al., 15 Civ. 9874 (S.D.N.Y).
 Likewise, market manipulation allegations can be found in the case involving Kit Digital, a publicly traded software/media company, and the company’s former chief executive officer, Kaleil Isaza Tuzman. See United States v. Tuzman and Smyth, 15 Cr. 536 (PGG) (SDNY). The indictment, which focuses mainly on accounting improprieties, alleges that Tuzman orchestrated purchases and sales of Kit Digital stock, through a co-conspirator at a hedge fund, for the purpose of “manipulating the stock price” and “creating the illusion of greater volume” in Kit Digital shares. At Tuzman’s direction, the hedge fund would have two of its accounts take both sides of a transaction to artificially inflate the trading volume in, and bolster the price of, Kit Digital stock.
 See United States v. Jason Galanis, et al., 15 Cr. 641 (PKC) (SDNY); SEC v. Jason Galanis, et al. (SDNY).
 See, e.g., United States v. Kevin Brennan, et al., 562 F. App’x 914, 917 (11th Cir. 2014), 12 Cr. 60064 (RSR) (S.D. Fla.) (defendants convicted of paying kickbacks to a hedge fund manager who misappropriated clients’ funds in order to buy stock at predetermined, inflated prices); SEC v. Mikhail Galas, et al., 14 Civ. 5621 (RBL) (W.D. Wash. 2014) (promoters of marijuana-related, penny-stock companies conducted pre-arranged, manipulative matched orders and wash trades to create the illusion of an active market in the stocks); SEC v. Douglas Furth, 14 Civ.7254 (LDW) (E.D.N.Y.) (defendant charged with paying kickbacks to investment advisor in exchange for buying 52 million shares of stock per the defendant’s instructions concerning the size, price and timing of the purchases); SEC v. Samula Delpresto and MLF Group, LLC, 15 Civ. 8656 (PGS) (D.N.J. 2015) (engaged in manipulative trading whereby an investment advisor was paid kickbacks to steer transactions to an alternative trading system in order to match purchasers with known sell orders, often at a predetermined price and volume).
 See United States v. Coscia, 14 Cr. 551 (HDL) (N.D. Ill.).
 See United States v. Sarao, 15 Cr. 75 (N.D. Ill.).
 See CFTC v. Oystacher, 15 Civ. 9196 (N.D. Ill.).
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