Chicago Fed calls for tighter control of high-speed traders

Chicago Fed calls for tighter control of high-speed traders

The Chicago Federal Reserve is calling for tighter controls on high frequency trading after finding that many firms are skirting the rules in the interests of speed-to-market.

Researchers at the Chicago Fed interviewed more than 30 firms at every stage of the trade lifecycle and found that many firms fail to implement best practice recommendations or rely on other firms in the trade cycle to catch an out-of-control algorithm or erroneous trade.

Some of the firms studied by the Fed do not have stringent processes for the development, testing, and deployment of code used in their trading algorithms, preferring instead to deploy new trading strategies quickly by tweaking old code and placing it into production in a matter of minutes.

"In fact, one firm interviewed had two incidents of out-of-control algorithms," says the Fed. "To address the first occurrence, the firm added additional pre-trade risk checks. The second out-of-control algorithm was caused by a software bug that was introduced as a result of someone fixing the error code that caused the first situation."

Chicago Fed staff also found that out-of-control algorithms were more common than anticipated prior to the study and that there were no clear patterns as to their cause. Two of the four clearing BDs/FCMs, two-thirds of proprietary trading firms, and every exchange interviewed had experienced one or more errant algorithms.

The Fed says that regulators should seek to adopt more stringent controls on traders, including:

  • Limits on the number of orders that can be sent to an exchange within a specified period of time;
  • A 'kill switch' that could stop trading at one or more levels;
  • Intraday position limits that set the maximum position a firm can take during one day;
  • Profit-and-loss limits that restrict the dollar value that can be lost.
In addition, trading firms should have access controls defining who can develop, test, modify, and place an algorithm into production, as well as quality assurance.

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