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Algorithmic trading firms were put on notice last Monday
when Commissioner Bart Chilton of the Commodity Futures Trading
Commission (CFTC) said that high frequency trading (HFT) and
algorithmic trading firms should be made legally responsible for
maintaining a minimum set of testing and monitoring standards to
prevent future flash crashes.
The possibility
that algorithmic trading firms may need to support new regulatory
requirements highlights the rapidly growing importance of the
market data cloud and new cloud services like
href="http://www.nasdaqdod.com" target="_blank">NASDAQ
Data-On-Demand for back testing purposes.
In a bid to resuscitate the heroes of 1980's sitcoms,
Mr. Chilton declared, "I want to be like MacGyver. Remember, he
was always trying to prevent crime before it happened." So if
you're a criminally culpable algorithmic trading firm, you'd best
beware-especially if Mr. Chilton gets his hands on a paper clip
and a stick of chewing gum. Household items aside, Mr. Chilton
also plans to rely on tools such as a "kind of Good Housekeeping
Seal of Approval." He'd like algorithmic trading systems to be
tested by either exchanges or regulators before going live. And
after going live, he'd like algorithmic trading systems to be
monitored on an on-going basis.
So, if
you're engaged in algorithmic trading, you'll probably want to
make sure you've got systems in place to test your algorithms so
you're prepared for any regulatory requirements that might come
down the pike. That's where the market data cloud comes in. If
you want to future proof your algorithmic trading systems against
any possible testing requirements, you'll want to look into how
you can use the market data cloud to back test your algorithms
with minimal expense, time and effort put into building new
technology infrastructure.
On-demand market
data cloud services like NASDAQ Data-On-Demand offer a new way to
hold down both the cost and time investments of getting
historical tick data to back test algorithmic trading systems.
You can get only the slice of data you need for your specific
test conditions, and you only pay for what you use, not the
entire universe of data, which dramatically reduces your data
costs. On-demand cloud services also let you get highly
customized data sets in a variety of common formats (XML, CSV,
JSON and so on) which reduces your need to build new technology
infrastructure just to load the data into your algorithmic
trading systems.
So if Mr. Chilton knocks at
your door with the latest issue of Good Housekeeping under one
arm, never fear. Just check out NASDAQ Data-On-Demand and rest
assured you can handle any algorithmic trading regulatory
requirements for back testing that he might have in mind without
breaking the bank on new technology infrastructure.
(For more details on Mr. Chilton's public statements,
see the
href="http://www.securitiestechnologymonitor.com/news/algos-should-get-tested-first-chilton-26940-1.html"
target="_blank">recent Securities Industry
News
coverage.)
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