On March 16, 2011, the Southern District of New York denied former Goldman Sachs programmer Sergey Aleynikov’s motion to dismiss his conviction for theft of trade secrets under the Economic Espionage Act (“EEA”). The court held that the evidence was sufficient to show that Aleynikov had stolen trade secrets and transported them across state lines, and further held that the stolen source code from Goldman Sachs’ high frequency stock trading system was a “good, ware or merchandise” under the National Stolen Property Act (“NSPA”). Aleynikov’s trial was one of two recent cases involving theft of source code for high frequency trading systems, both of which were tried in New York’s Southern District under the Economic Espionage Act.
High Frequency Trading
High frequency trading involves the use of computerized algorithms and highly sophisticated programs to trade securities. Firms that engage in such trading hold onto positions for seconds at a time, and generally end a trading day with no net positions. Decisions are made through high-speed mathematical analysis of market data, taking advantage of trading opportunities that open up for fractions of a second. The field is technologically complex, highly competitive, and very lucrative. High frequency trading systems require significant time and resources to develop and maintain. Court documents in the Aleynikov case estimate that it would cost roughly $10 million and two years to build a high frequency trading system from scratch.
Aleynikov – Theft, Subversion, and Espionage
Goldman Sachs employed Sergey Aleynikov as a programmer from May of 2007 to June of 2009, when he accepted an offer from a Chicago-based startup called Teza. About two months prior to his last day at Goldman Sachs, Aleynikov began uploading proprietary data to a subversion site on a German server. He went out of his way to avoid detection, deleting his encryption key and attempting to clear his bash history. The files he stole included, in the court’s words, components “connecting to the various securities exchanges; reading the incoming price data; pricing algorithms; trading strategies; the infrastructure for routing the trading decisions back to the exchanges; and applications for monitoring the performance of all of these intricate parts of the trading system.” Continue reading


