ADVERTORIAL
Data is in the DNA of our EMS
TRADETech Daily talks to Chris Hollands , head of European sales and account management at TradingScreen ( TS ), about the increasingly pivotal role of the EMS in the capture , aggregation and accessibility of data across the order life cycle .
How does the EMS help the buy-side trader to manage the proliferation of data ? Chris Hollands : As electronic trading has proliferated across the asset classes , the data requirement to inform each step of the order life cycle has increased . The role of the EMS in aggregating and consolidating data is essential across multiple categories , starting with referential data , which often can be a massive challenge especially as it relates to integrating to downstream systems supporting different symbologies , such as PMSs or OMSs and execution counterparties and venues .
A key advantage that our SaaS ( Softwareas-a-Service ) infrastructure provides us with is an embedded multi-asset class product master , which means potential symbology issues , and the sourcing of the product data itself , disappear . The next category is real-time market data ranging from centrally provisioned , specialist vendor feeds , to local pricing APIs leveraging existing data sources down to IOIs , RFQs and streaming prices from liquidity providers and venues in the OTC world . Managing this complexity , and all of the associated connectivity in an efficient and cost-effective manner is a constantly evolving challenge but one where the right EMS can clearly provide the solution .
Best execution requirements under MiFID II have extended the focus from equities into the other asset classes , such as listed derivatives , fixed income and even FX , outside of spot . So inherently data has become a broader theme . There ’ s also the downstream implications , i . e . communicating all of this order and execution data into the OMS , where under MiFID II , the buy-side ’ s record-keeping and reporting obligations have multiplied .
What other significant changes have there been to the way data workflows are managed under MiFID II ? CH : The use of broker and specialist vendor pre- , in- and post-trade analytics and their close interaction with the buy-side trader ’ s book of orders is driving the active pursuit of best execution . MiFID II requires the buyside to maintain a seven-year audit trail of all relevant information regarding the placement , the handling and the execution of orders . This encompasses the feedback loop between the centralised dealing desk and the portfolio managers explaining exactly how and why the order is being worked . All of this data needs to be captured . The EMS is uniquely positioned to fulfil this function and to feed this information to other systems such as the OMS .
In that in-trade and post-trade sphere , how important a part does data visualisation play now ? CH : With the proliferation of data , the ability to visualise it and to derive meaning from it in a timely manner becomes more critical . For in-trade analytics , configurable exception-based alerting mechanisms are becoming the norm . For post-trade , we have embedded Tableau , a market leading reporting and data visualisation package , which syncs up with both our transaction database and our tick-by-tick database . Clients can then use these out-of-the-box tools to create their own customised TCA reports to fit their precise needs , rather than us providing standard , box-ticking type reports .
Are you seeing new applications of data to help drive decision-making ? CH : A current and growing trend in equities is the Algo Wheel , a best execution tool to make sure that order flow is allocated ‘ appropriately ’ across the selected counterparties and to provide a way to review that . Here the post trade execution data from Algo Wheel-generated order flow can be used to determine the selection of the future counterparties and the algo tactic ( s ) themselves .
Given these developments , how is TS approaching the development of its offering ? CH : That brings us to the whole open and broker neutral nature of our platform , our propensity to integrate to third parties and not try ourselves , to be all things to all people . We don ’ t profess to be specialists in some of the quantitative analytics , which are of interest to the buy-side , hence we partner .
TRADINGSCREEN
“ With the proliferation of data , the ability to visualise it and to derive meaning from it in a timely manner becomes more critical .”
We are partnering on the OMS side with a well-documented alliance with SimCorp and are a preferred EMS partner for Avaloq , the core private banking system . In the world of analytics , we have fully integrated with OTAS Technologies . Hot off the press , we are pleased to be the first EMS to integrate to BondCliQ , a central market system for US corporate bond trading ’ s posttrade data . These integrations equip our buy side clients with the ability to extract and use data precisely as they want to without restricting them .
The launch of our enterprise application programming interface ( API ) website gives buy sides a new way to extract data . We have recently launched a REST API , which is a very quick and flexible way of bringing order data into our platform and extracting execution data .
There are a myriad of ways we can help , but most prominently by being genuinely broker neutral and by being open , we offer the broadest range of options and the maximum flexibility .
Issue 1 TheTradeNews . com 31
A DV E RTOR IAL
Data is in the DNA of our EMS
TRADETech Daily talks to Chris Hollands, head of European sales and account
management at TradingScreen (TS), about the increasingly pivotal role of the EMS in
the capture, aggregation and accessibility of data across the order life cycle.
How does the EMS help the buy-side trader to
manage the proliferation of data?
Chris Hollands: As electronic trading has
proliferated across the asset classes, the
data requirement to inform each step of the
order life cycle has increased. The role of
the EMS in aggregating and consolidating
data is essential across multiple categories,
starting with referential data, which often
can be a massive challenge especially as it
relates to integrating to downstream systems
supporting different symbologies, such as
PMSs or OMSs and execution counterpar-
ties and venues.
A key advantage that our SaaS (Software-
as-a-Service) infrastructure provides us with
is an embedded multi-asset class product
master, which means potential symbolo-
gy issues, and the sourcing of the product
data itself, disappear. The next category is
real-time market data ranging from centrally
provisioned, specialist vendor feeds, to local
pricing APIs leveraging existing data sources
down to IOIs, RFQs and streaming prices
from liquidity providers and venues in the
OTC world. Managing this complexity,
and all of the associated connectivity in an
efficient and cost-effective manner is a con-
stantly evolving challenge but one where the
right EMS can clearly provide the solution.
Best execution requirements under MiFID
II have extended the focus from equities
into the other asset classes, such as listed
derivatives, fixed income and even FX, out-
side of spot. So inherently data has become
a broader theme. There’s also the down-
stream implications, i.e. communicating all
of this order and execution data into the
OMS, where under MiFID II, the buy-side’s
record-keeping and reporting obligations
have multiplied. relevant information regarding the place-
ment, the handling and the execution of
orders. This encompasses the feedback loop
between the centralised dealing desk and
the portfolio managers explaining exactly
how and why the order is being worked. All
of this data needs to be captured. The EMS
is uniquely positioned to fulfil this function
and to feed this information to other systems
such as the OMS.
What other significant changes have there
been to the way data workflows are managed
under MiFID II?
CH: The use of broker and specialist vendor
pre-, in- and post-trade analytics and their
close interaction with the buy-side trader’s
book of orders is driving the active pursuit of
best execution. MiFID II requires the buy-
side to maintain a seven-year audit trail of all Given these developments, how is TS ap-
proaching the development of its offering?
CH: That brings us to the whole open and
broker neutral nature of our platform, our
propensity to integrate to third parties
and not try ourselves, to be all things to all
people. We don’t profess to be specialists in
some of the quantitative analytics, which are
of interest to the buy-side, hence we partner.
In that in-trade and post-trade sphere, how
important a part does data visualisation play
now?
CH: With the proliferation of data, the
ability to visualise it and to derive meaning
from it in a timely manner becomes more
critical. For in-trade analytics, configurable
exception-based alerting mechanisms are
becoming the norm. For post-trade, we have
embedded Tableau, a market leading report-
ing and data visualisation package, which
syncs up with both our transaction database
and our tick-by-tick database. Clients can
then use these out-of-the-box tools to create
their own customised TCA reports to fit
their precise needs, rather than us providing
standard, box-ticking type reports.
Are you seeing new applications of data to
help drive decision-making?
CH: A current and growing trend in equities
is the Algo Wheel, a best execution tool
to make sure that order flow is allocated
‘appropriately’ across the selected coun-
terparties and to provide a way to review
that. Here the post trade execution data
from Algo Wheel-generated order flow can
be used to determine the selection of the
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