NASDAQ OMX Plans Big Tick Market Data Cloud with Xignite
First Published Thursday, 5th August 2010 02:06 pm from Xand : Joel York
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The was plenty of href="http://www.securitiestechnologymonitor.com/news/-25731-1.html"
target="_blank" rel="nofollow">market data cloud buzz at the
2010 SIFMA Technology Conference and Exhibition with
NASDAQ and Xignite right in the center. Using the XigniteOnDemand
href="http://www.xignite.com/Solutions/On-Demand-Market-Data-Web-Services.aspx"
target="_blank">Market Data Cloud Platform, NASDAQ
plans to launch Data-on-Demand in the second half of 2010 to
provide easy and flexible access to large amounts of detailed
historical NASDAQ Level 1 trade and quote data for all
U.S.-listed securities. Tick data is increasingly in demand for
back testing of algorithmic trading strategies as the securities
industry pushes the limits of high frequency trading.
Randall Hopkins, NASDAQ OMX's Senior Vice President of
Global Data Products, is quoted in the press release as saying:
"Today our customers spend a large amount on technology
infrastructure, not the market data itself. With Data-on-Demand,
we want to drastically cut data management costs by running the
technology infrastructure on the cloud for our clients and
delivering to them the data they need, when they need it, and how
they need it."
>
NASDAQ discusses
it's market data cloud initiative with Max Bowie
/> of Inside Market Data at the 2010 SIFMA Financial Services
Technology Expo
Obtaining and collecting tick
data can be onerous and time-consuming as firms are required to
establish feeds and maintain large amounts of data on-hand.
On-demand market data distribution gives applications a way to
cherry pick the specific subset of data that the application
needs with pinpoint accuracy. Instead of combing through very
large data sets of historical tick data, developers will be able
to program their applications to select very specific data sets
and obtain them on-demand and process them instantly.
Data-on-Demand will also allow clients to download large tick
data subsets on a scheduled basis.
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