Much has been made of the 32MB of Goldman Sachs’ proprietary algorithmic trading code (“trading secrets”) allegedly stolen by Sergey Aleynikov, now portrayed in the financial media as the new Julius Rosenberg, Aldrich Ames, Robert Hanssen and John Walker all rolled into one. That may prove to be true; but while it makes for a great news story at this point in time, it highlights the new significance of high-frequency trading — which is built on this technology — in the marketplace.
We are all keenly aware that electronic routing and execution has become the mechanism by which our capital markets operate. Algorithms account for more than 25% of all shares traded by the buy side today — a number steadily rising for several years now. However, the incredible capabilities offered by technology have given meteoric rise to a relative few high-frequency proprietary trading firms that now wield far greater influence on the markets today than most people recognize. The familiar names of Lehman, Bear and Merrill are being replaced by less familiar ones like Wolverine, IMC and Getco.
For example, high-frequency trading firms, which represent approximately 2% of the 20,000 or so trading firms operating in the U.S. markets today, account for 73% of all U.S. equity trading volume. These companies include proprietary trading desks for a small number of major investment banks, less than 100 of the most sophisticated hedge funds and hundreds of the most secretive prop shops, all of which operate with one thing in mind — capture profit opportunities by being smarter and faster than the closest competition.
They are, as a rule, secretive, stealthy, smart, and relatively unknown. The key to being smarter is their unique technology that enables them to profit on a number of these quantitative strategies, which they will protect at all costs.
The Value of High-Frequency Trading Strategies
Proprietary trading takes in a number of unique strategies, including market making, arbitrage (ETFs, futures, options), pairs trading and others based on the linked trading of more than one asset class, e.g., futures index and cash equities. In fact TABB Group estimates that annual aggregate profits of low-latency arbitrage strategies exceed $21 billion, spread out among the few hundred firms that deploy them. While we know all the large investment banks such as Goldman Sachs are committed to prop trading profitability, the hundreds of smaller, private high-frequency prop shops extend much greater influence in the marketplace by providing liquidity that keeps activity flowing.
While none of us knows the ingredients of Goldman’s “secret sauce,” we can say that any algorithmic code in and of itself is precious but has limited value until placed in the right circumstances. Those circumstances are not available to just any Tom, Dick or Sergey, but represent the core strategy of the fast-rising high-frequency trading firms.
First, strategies that optimize the value of high-frequency algorithmic trading are highly dependent on ultralow latency. The right decisions are based on flowing information into your algorithm microseconds sooner than your competitors. To realize any real benefit from implementing these strategies, a trading firm must have a real-time, colocated, high-frequency trading platform—one where data is collected and orders are created and routed to execution venues in sub-millisecond times.
Next, since many of these strategies require transacting in more than one asset class and across multiple exchanges often located hundreds of miles apart, i.e., New York to Chicago, that infrastructure will often require round-trip long-haul connectivity between the data centers.
Last and most important, this code has a limited shelf life, whose competitive advantage is diluted with each second it is outstanding. While a prop desk’s high level trading strategy may be consistent over time, the micro-level strategies are constantly altered — growing stale after a few days if not sooner — for two important reasons. First, because high-frequency trading depends on ridiculously precise interaction of markets and mathematical correlations between securities, traders need to regularly adjust code — sometimes slightly, sometimes more — to reflect the subtle changes in the dynamic market. The speed and volatility of today’s markets is such that the relationships forming the core of our algorithm strategies often change within seconds of our ability to implement the very strategies that exploit them. Second, competitive intelligence is so good across all rival trading firms that each is exposed to the increasing susceptibility of their strategies being reverse-engineered, turning their most profitable ideas into their most risky. As a result, any firm acquiring the “stolen” code would gain benefit from it for no more than a few days before that firm would need to adjust the code to the dynamic conditions. Since these changes build on themselves, in a matter of weeks that code would look quite different from that which was originally “stolen.”
There’s no doubt that Goldman Sachs, or any other proprietary trading firm, could indeed lose tens of millions of dollars from its proprietary trading if their strategies are stolen — and that is very serious. The competitors that obtain access to these trading secrets could (and would) use it to front-run or trade against it, ruining even the most well-planned tactics. This news story contains many very important subplots: trading espionage, the necessity for a trading firm to have sophisticated security systems built around its technology, the requirements for risk management, and even the potential for proprietary trading software to be targeted on a wider scale for terrorist activity; but more than anything else it highlights the critical role played by high-frequency prop trading in this new market.