Co-Location Strategies Evolve
Need to execute across multiple exchanges drives decisions.
Firms implementing high-frequency trading strategies are faced with decisions on where to physically locate the servers that receive data and execute trades.
It’s not simply a question of co-locating within a few feet of an exchange’s matching engine within a data center, but must take into account multiple matching engines and data centers.
“If a firm is executing a multimarket strategy, it needs to be able to capture data with microsecond precision, and be able to manage data storage in multiple locations,” Roji Oommen, senior director of business development, financial services at Savvis, told Markets Media.
Savvis hosts trading systems and matching engines for many liquidity venues, including traditional equities and derivatives exchanges, dark pools, crossing networks, and ECNs.
Over 200 securities and trading firms are located in it NJ2 data center in Weehawken, N.J., including investment banks, broker-dealers, market makers, prop and quant traders, and service provides.
Matching engines for five of the nine largest U.S. equity dark pools are located in NJ2, which is responsible for half of average daily volume traded in U.S. equities dark pools.
Selerity, a provider of event data to high frequency traders, has had to face the issue of deciding where to be located to get access to the most financial services servers.
Selerity clients also have to deal with figuring out the best location to be in, so that they have the fastest, most direct access to exchanges.
“Anybody running a trading strategy has to be as close as possible to that market, but they may also need to coordinate between multiple markets,” Andrew Brook, chief technology officer at Selerity, told Markets Media.
Selerity’s ultra-low latency platform delivers machine-readable event data immediately as events are breaking.
Its product offering is aimed at programmatic traders looking to incorporate market-moving events into their automated trading and risk management models, for whom speed is paramount.
When placing orders to an exchange, a firm will want to do so from a server in close proximity to the exchange’s matching engine. However, many trading strategies will involve placing orders on multiple exchanges, in which case the firm needs to consider the travel times to two separate matching engines.
“If you’re executing a pairs trading strategy involving trades on companies that have similar characteristics but trade on separate exchanges, then the optimal geographic location is somewhere between the exchanges’ matching engines,” Brook said.
The New York metropolitan area is unique in its concentration of matching engines: NYSE’s matching engine is in Mahwah, N.J., in the northern part of the state, and Nasdaq’s is in Carteret, to the south.
Secaucus, located approximately midway between Mahwah and Carteret, is therefore a logical point from which to execute a trading strategy.
“We have clients who will make trading decisions from Secaucus, and fire off trading signals to Carteret and Mahwah,” said Brook.
The result is an “ecosystem where you have a collection of markets in close proximity,” he said.
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