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e-Forex-Nov-23

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Next generation FX analytics: Bringing transparency and more to the FX execution process<br />

TRADING OPERATIONS<br />

“The historical approach of simply adding LPs via an EMS is<br />

no longer adequate because each LP and their effect on the<br />

pool needs to be understood.”<br />

benchmark from outside the system. It<br />

is from this information that the trader<br />

can create an execution methodology<br />

for each trade.”<br />

FairXchange’s Hopkins acknowledges<br />

the importance of independent data<br />

sources but stresses that analysis is<br />

just as critical. “It is important to<br />

differentiate between independent<br />

analysis and independent data,” he<br />

says. “Independent data analytics firms<br />

like FairXchange provide objective,<br />

neutral analysis of trading firms’ data.<br />

This gives firms valuable insights into<br />

their trading business that they might<br />

otherwise miss, and it also removes<br />

the perception of “marking your<br />

homework”. Indeed certain types of<br />

analysis only make sense when based<br />

on a particular firm’s data – their<br />

unique liquidity, for example,” he<br />

states.<br />

Paul Lambert<br />

When does incorporating a benchmark<br />

or ruler (as Lambert explained)<br />

hold water? “There are times when<br />

it is helpful to combine this with<br />

independent data sources,” Hopkins<br />

responds. “Particularly when the<br />

analysis is intended for third parties,<br />

such as clients, counterparties, or<br />

regulators. This gives a useful degree<br />

of standardisation, and can remove<br />

the potential for a given firm’s trading<br />

activity to leave a signature on the<br />

reference data against which trades are<br />

measured. It is also helpful for creating<br />

a level playing field, using objective<br />

data that counterparties can agree<br />

on.”<br />

COMBINING DATA WITH<br />

ANALYTICS TOOLS FOR MORE<br />

TRANSPARENCY<br />

“Data alone is quite useless without<br />

analytics,” Bloomberg’s Shevelenko<br />

says, “as analytics are a vehicle that<br />

make sense of your data and uncover<br />

meaningful conclusions. Therefore, data<br />

and analytics go hand in hand helping<br />

to constantly reshape the execution<br />

process, making it clearer and more<br />

transparent.”<br />

Hopkins believes data standardisation<br />

is a critical first step firms must invest<br />

time into. “Standardise the data into a<br />

format that permits firms to compare<br />

across different venues, trading<br />

platforms, and counterparties,” he<br />

says. “The analytics then need to be<br />

powerful enough to allow firms to<br />

quickly identify areas of interest, in real<br />

time if possible. This now extends to<br />

using AI to detect anomalies or issues<br />

that require attention.”<br />

He also points out that these analytics<br />

must be accessible to as broad a<br />

constituency of users as possible.<br />

“Data and data analysis are now part<br />

of everyone’s daily working life, it is no<br />

longer the province of a small number<br />

of highly qualified specialists,” he notes.<br />

Lambert counters that firms must<br />

look earlier in the cycle and focus<br />

on sourcing enough data. “Almost<br />

no buyside users can consume and<br />

analyse their available liquidity,”<br />

he says. “They are shooting in the<br />

dark without the data to understand<br />

their feeds and act accordingly. Most<br />

analysis available today is based on<br />

‘dead’ data, which offers little in terms<br />

of live execution problems.”<br />

He explains that using such data with<br />

algos doesn’t make sense. “The use of<br />

a historic database of algo executions<br />

to guess which algo to use now is like<br />

driving from A to B using last week’s<br />

traffic conditions when roadworks<br />

may have moved, and the weather<br />

may have changed. This challenge is<br />

what led New Change to build its<br />

Data Processing as a Service (DPaaS)<br />

offering. NCFX, under an ordinary<br />

platform agreement, can take feeds<br />

from banks and process them to<br />

produce live analytics for its clients.<br />

Clients can create their live midrate,<br />

see how a trade or algo execution<br />

with a bank affects the prices at every<br />

other institution, and triangulate their<br />

midrate with the independent midrate<br />

from NCFX and their own micro-price.”<br />

Lambert adds that while these feeds<br />

are built on live data, clients can store<br />

James Knoop<br />

“Being able to highlight areas where LPs are struggling<br />

against their peers or being deliberately toxic with their flow<br />

can lead to a closer collaboration between Bank and LP.”<br />

24 NOVEMBER 20<strong>23</strong> e-FOREX

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