Risk Management: In the Eye of the Storm
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Keep Out, At Your Own Risk
December 15, 2010
This kind of breadth allows NYSE Euronext to “aggregate” the risk being engaged in by a broker’s customer. A high-speed trader may well have order-transmitting servers co-located with those exchanges in each of those data centers If the broker has established a limit for trading by that trader of 10 million shares a day, say, the gateway, as a system, can stop the trading when the threshold is crossed.
The gateway also provides the broker with a series of trading tools that lets a broker watch the flow of orders that its clients with direct access to markets are sending out and search for particular orders, as needed. This helps monitor both risks and compliance. The broker, using a Web browser, can see an aggregate view of each participant’s trading activity as well as how various filters have been applied. Through the browser, limits can be set for different customers or even specific traders at a trading firm. And the controls, Boytim points out, can be updated within a trading day.
NYSE Euronext has invested $250 million in the Mahwah data center and, in theory, it could be used as an industry laboratory to test for market risks. After all, it’s been built to host and handle the activity for all existing national exchanges as well as all those that can be expected to be launched over the next 20 years, NYSE Euronext officials say.
NYSE Euronext already provides comprehensive data, charting and historical analysis tools for all National Market System-listed securities, through its SuperFeed of market data and historical information from OneTick.
Mahwah also is set up with plenty of space for adding storage and computing capacity through another two decades. Each pod can hold 600 cabinets of computing power, with each cabinet holding more processing power with each passing generation of microchip technology.
Even in flat markets, the number of messages generated by trading activity is soaring, notes Steve Rubinow, NYSE Euronext’s chief information officer. This is driving innovation in storage, which is now measured in petabytes, or quadrillions of numbers and characters.
But Tuskey said throwing present or past data at algos is not necessary, if risk controls are used properly. Defining what constitutes a “good” algorithm and a “bad” algorithm is hit or miss. Past conditions don’t necessarily predict how the math will perform in new circumstances. If a particular algo shows a propensity to get stuck in a loop, spitting out orders repeatedly, a risk gateway can simply stop orders that look very similar, in their tracks.
Defining algorithms could be “error prone,’’ said Tuskey. “Whereas, risk management, it’s defined.”
And manageable. “As long as everybody’s applying it,’’ he said.