The SEC and Data Analytics: An Action Centered on 3,000 Securities

A key focus for the Commission in recent years has been the development of its capabilities in data analytics. Following the market crisis, the agency focused in part on adding staff members and developing its expertise in areas tied to the analysis of data, statistics and economics. This has resulted in a continued outflow of cases based in whole or in part data on and tech. The cherry-picking cases brought largely against investment advisers are one example. Another group of actions focused on aberrational performance metrics.

Perhaps the most visible aspect of these efforts are the insider trading and manipulation cases brought by the agency. While the SEC has always had the ability to quickly gather trading data using blue sheets, which at one time were paper records and now are electronic, breaking that data down, sifting it, and identifying those who are violating the insider trading and/or market manipulation prohibitions has always been a challenge. Big data, coupled with ever increasing data analytics capabilities, has over the years dramatically increased the capabilities of the Commission in this area. The result is cases like SEC v. Chen, Civil Action No. 1:19-cv-12127 (D. Mass. Filed Oct. 15, 2019)(here) in which the SEC named 18 largely foreign based defendants in an international market manipulation case involving about 3,000 securities over $32 million in trading profits over about four years. The action is paralleled by a case filed by the U.S. Attorney’s Office for the District of Massachusetts.


The complaint names 18 persons as defendants along with six others as relief defendants. All are based either in China or tied to that country. As early as 2013 Defendant Jiali Wang, a China resident, began trading in the U.S. markets. Although he had compliance issues at times, Mr. Wang persisted. Eventually he began working in concert with others and opened accounts using those names to conceal his trading. For example, he used accounts such as one for Forest (HK) Co., Ltd.

Defendant Xiaosong Wang, a resident of China and Massachusetts, took similar steps. He held brokerage accounts in the names of others which helped to conceal his trading. In 2018, for example, he opened an account in the U.S. in the name of relief defendant Jomgri Zjao. In doing so he used altered documents, deleting his name from bank records and substituting that of Jingru Zhai. While he also had compliance issues, Defendant Xiaosong Wang persisted and continued to trade in the U.S. markets.

An analysis of IP addresses, computer identifiers and banking transfers demonstrates that Defendants Jiali Wang, Xiaosong Wang, and other individual Defendants, were coordinating their efforts and working in concert. These identifiers link the accounts of fifteen persons to Defendant Jiali Wang.

The actual market manipulation scheme, while massive and conducted across international boarders, was built using traditional manipulation building blocks keyed to manipulative trading such as cross trades and wash sales. For example, in June 2014 Miali Wang, Forest (HK) and a relief defendant were involved in the manipulation of Institutional Financial Market Inc. (NYSE) shares. On June 16th several manipulative techniques were employed to generate about $941 in profits. Similarly, on September 27, 2018 Defendants Xiaosong Wang and Shun Sui used multiple accounts to manipulate the share price of Craft Brew Alliance (NASDAQ), generating $6,003 in illegal profits.

Over the period Defendants repeatedly manipulated the share price of thousands of securities, typically using the following steps:

1) Orders were placed on an exchange to sell a thinly traded security at prices below the prevailing offer to lower the price;

2) One or more of the accounts intended to profit from the trades would then place buy orders, frequently using a variety of accounts, while the sell orders were still being executed, although the orders seldom crossed;

3) Once the profit or winner accounts had acquired sufficient quantities of the stock, the sell orders were cancelled, and the price would increase to an artificial level; and

4) The profit or winner accounts would then sell their respective holdings, reaping profits based on a manipulated price.

While there were variations of this pattern, essentially it was replicated over and over for years. The SEC’s complaint details a number of examples showing the trade dates and times drawn from an analysis of the individual account brokerage records. Those trades were placed as recently as May 1, 2018 as early as September 28, 2014.

During the period a number of the accounts received warnings from the brokerage houses regarding possible wrongful and manipulative trading being conducted in violation of the firm’s policies and procedures. In each instance the trader controlling the account proffered a fabricated excuse. For example, in March 2014 a U.S. brokerage firm sent a warning to Jiali Wang about transactions that appeared to involve cross trades or wash orders. He responded by claiming that the stocks had been selected by his stock screener software and that the transactions went out of his “pre-judgment,” requiring him to take certain steps to stem losses. Other accounts received similar warning. More excuses were proffered. These excuses helped conceal the on-going, years long manipulation. The transmission of proceeds among accounts aided the concealment efforts.

The complaint alleges violations of Exchange Act Sections 9(a)(2) and 10(b) and Securities Act Sections 17(a) and (c). The action is pending.


While this case is still being litigated, the complaint is a good example of the Commission’s data analysis capabilities. The scheme here is alleged to have lasted for about four years, involved about 3,000 stocks and was conducted through numerous accounts. Despite the massive amounts of data involved the staff was able to distill details linking the accounts together and quantify the impact of the trading on the market price of the securities. This kind of massive effort reflects the capabilities developed over the years to analyze transactions and trading in the markets by individual traders and market professionals. It also helps reassure retail investors who may be concerned about entrusting their hard-earned retirement dollars in the markets while serving as a warning to all traders.

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