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Next is whether the data truly represents executable
bids and offers available at the time.
“This is critical for algo modellers and for users
looking to do trade validation,” Brittan points out.
“For users storing tick-by-tick data, managing the
sheer volume of data can be a challenge and requires
special consideration in itself. That said, the cost of
mass storage has plummeted in recent years.”
There are also many issues in terms of data rights,
licences to actually store the data and use the data in an
historical environment or even a real-time environment.
In terms of handling, managing and processing huge
volumes of data, Doe points out: “Simple queries in
that scenario can take an extremely long time as you
are dealing with a certain amount of computing
power. And, when trying to calculate terabytes of
data, high performance engines are required to
calculate this type of analysis if you are looking at a
year of data, let alone a decade or more of data.”
In this regard, Thomson Reuter’s acquisition of Vhayu
in August 2009, will help in fulfilling client needs.
Vhayu provides a high-performance engine for clients
to store, analyse and process this data, as well as
undertake real-time analysis of Thomson Reuters’ feed
and send real-time messages to trade upon. Doe
confirms that the firm is “investing heavily” in their
historical Quant business and the FX space in
particular. They view it as a growth area and also want
to stay ahead of the curve.
Streamlining access
On efforts that providers are making to streamline the
process of accessing historical FX price data, ICAP’s
Kohler says: “As with all our offerings we’re trying to
make it as painless as possible for our customers to use
our [FX] data as well as offering them the best possible
service.” The reduction in time slicing on the EBS
platform to 10x/second is illustrative of the improvement
in their service. He adds: “People know how to write to
it. And, every single market participant who is present in
the FX space is reading a market data element from
ICAP EBS, whether real time or historical.” Further
enhancements - as yet undisclosed - are in the pipeline to
improve the quality of data quality for ICAP EBS feeds
as well as the real-time element, Kohler reveals.
FXall’s Huffman says: “We make an effort to give our
clients access to the data they are looking for. For
example, our customer savings reports have market
data built directly into it and included with the
analysis, such as the rates at the time of trades.”
72 | january 2010 e-FOREX
Philip Brittan
“For users storing tick-by-tick data, managing the
sheer volume of data can be a challenge and requires
special consideration in itself. That said, the cost of
mass storage has plummeted in recent years”
At Bloomberg, Brittan explains that they are making
it easier for users to find the vendor’s data through
functions like ‘FXTF’. They also offer an evergrowing
range of tools to undertake data analysis right
within the terminal, including functions like ‘VOLC’,
‘XCRV’, ‘XDSH’, ‘FXFM’, and ‘CIX,’ as well as a
whole suite of charting functions. “This all means
that users don’t have to deal with exporting, storing,
and providing their own analysis tools, for a wide
range of analytical applications,” Brittan says.
Distribution formats
Turning to the kinds of data distribution formats that
are available and what factors may influence how
firms choose to integrate data into their research and
FX trading infrastructures, FXall’s Foster says: “For
live market data, FXall offers a proprietary format
(Accelorate), using very compact messages to keep the
transmission and processing time on the client side
extremely low” For historical data, the firm offers a
format, which is claimed “can easily be imported into
client systems.”
Bloomberg offers several enterprise-level data
products, but also makes it easy for individual users
carry out ‘desktop analysis’ via their Excel API.
ICAP’s Kohler notes here: “I’ve found in this
particular space, that even if it is extremely