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ISSUE 38 | MAY 2025 WWW.FXALGONEWS.COM FOLLOW US AT:

TOP STORIES

FX Connect launches automated OMS

algo ticket submission

State Street’s FX Connect has automated

the FX algo submission direct from a

client’s Order Management System (OMS)

streamlining the process with a no-touch

workflow in what is believed to be at

market leading offering . The feature was

developed in partnership with one of the

platform’s sophisticated algo clients in

an effort to reduce the complexity and

cost of algo trading, says Darren Smith,

Global Head of FX Connect Product. “One

of the big challenges we hear from our

advanced FX algo clients is that although

the algo execution is fully automated, the

submission process for those algos is

still a fairly tedious and time-consuming

process. Now, algo users can plug in

their algo wheel directly or create rules

within the OMS so the user still has full

control, but we then perform all the

validations required prior to submitting

to the bank, which is where the full

value of this offering comes into play,”

Smith adds. FX Connect also recently

added the ability to trade NDF algos on

the platform and will be rolling out a

new basket algo offering in the coming

months, he adds. See page 3.

Darren Smith

Trading Technologies unveils TT Strategy

Studio for multi-asset algo trading

Trading Technologies International has

announced the broad introduction

of its TT Strategy Studio multi-asset

algorithmic trading offering for

institutional trading firms. A featured

offering of TT Quantitative Trading

Solutions (QTS), TT Strategy Studio

provides a framework for developing,

testing and deploying complex multiasset

automated trading strategies

while keeping a firm’s intellectual

property within its own control.

Joe Signorelli

Joe Signorelli, TT’s EVP Managing

Director, QTS, said: “TT Strategy

Studio is a powerful, commercialgrade

offering that can save the

largest, most sophisticated firms

hundreds of developer hours. It

enables them to build alpha with

access to full tick-by-tick backtesting

with complete depth of market,

live simulation through a built-in

simulator and production trading

for the most complex automated

trading strategies on the market. They

can leverage our hosted ultra-lowlatency

infrastructure, easy-to-use

interface and advanced tools to

create, hone and execute their unique

trading strategies at a substantial

cost savings, while protecting their

proprietary code – the intellectual

property that is most treasured by

trading firms.” TT Strategy Studio

ingests market and execution venue

data from leading providers in

equities, options, futures and foreign

exchange markets.

IN THIS ISSUE

p4. MARKET WATCH

FX algos counter liquidity mirage claims

p6: PROVIDER PROFILE

Further FX algo developments at Westpac

p8: INDUSTRY VIEWS

What’s influencing FX algo providers?

p16: DEQUANTIFICATION

The Nightjar algo from Societe Generale

p18: BUYSIDE INTERVIEW

With Tatu Kallio at OP Asset Management

p22: PANEL DISCUSSION

Practitioner and buyside perspectives

p22: INDUSTRY REPORT

FX Trading in 2025

p28: EXPERT OPINION

Buying vs building trading architectures

p30: ALGOTECH

Delivering data for FX algo trading

NOW AVAILABLE ON VELOCITY 3.0

DYNAMIC ALGOS

• Access on our web app designed for both corporate & professional investor clients

• Execute NDF Algos

• Additional Liquidity venues

• Enhanced internalization through the Citi franchise

• Engineered with next generation market making technology

• Increased client parametrization and controls

STILL INNOVATING

Contact your Digital FX salesperson to learn more

FX Connect expands

FX algo functionality

State Street’s FX Connect has always supported the maturing FX algo market with its

cutting-edge offering, supporting client workflows while reducing cost and complexity

across the board. Darren Smith, Global Head of FX Connect Product, shares some of

the latest developments which have been recently unveiled on the platform in light of

client demand, including a new NDF algo offering, automated OMS algo selection and

the upcoming introduction of basket algo functionality.

FX algo use on FX Connect has continued

to increase significantly, resulting in a

recent focus on increasing efficiency and

flexibility on the platform, Smith says.

This led to the recent roll out of key new

features and functionality in response

to client demand. The first significant

development was the launch of NDF algo

functionality on the platform, which is an

important development given that NDFs

were until recently only available as part of

a single dealer offering, Smith explains.

He adds: “Part of the reason for this was

the significant amount of work required

to integrate with the liquidity providers

in a way that is both efficient and which

does not add additional risk to the users

of the system. But in light of increasing

demand for NDFs and emerging market

currencies, we have worked in partnership

with our liquidity providers to enable

access to NDF algo strategies through

FX Connect.” Users can now trade non

deliverables using specific strategies

that the different liquidity providers

support, Smith says, while the team is

working closely with additional banks

to ensure that the maximum number

of algo strategies are supported. “We

are expecting to have the support of 12

liquidity providers within the year,” he

adds. “Both clients and liquidity providers

wanted to see this functionality become

available. It has filled a gap in the multidealer

space which was only becoming

bigger as more attention turns to EM

currencies.”

AUTOMATING ALGO USE

At the same time, FX Connect has also

introduced automated FX algo selection

from the OMS, in what Smith describes

as a significant step forward in evolving

the FX algo space to catch up to what

is already widely available for equity

algo users. “On our platform, we scored

somewhere around 250 strategies for

liquidity providers and we are constantly

adding new algos to the platform,” he

says. “Each one of those strategies in turn

has its own algo ticket that needs to be

populated before it could be submitted

to the bank, often with upwards of 20

parameters. Clients were losing the

benefits of automation when using FX

algos as a result so we wanted to focus on

eliminating that complexity by simplifying

their workflows.”

In what is believed to be a new market

leading offering, FX Connect worked

in close partnership with one of its

sophisticated algo clients to build out a notouch

workflow for the platform. Buyside

clients can now create rules with the

OMS directly or plug in their algo wheel,

creating Quick Tickets which populate the

static fields for that strategy. Smith notes

that any non-static, dynamic fields are

provided within the Fix message itself. He

adds that the most tangible benefit for

buyside clients is that FX Connect will then

perform all the validation required prior to

submitting to the bank. “The algo space is

constantly changing, so having this offering

is a big step up for algo clients and ensures

that everything matches seamlessly with

the bank’s own single dealer platform,

where clients have the ability to directly

manage algo execution via the LINK

application,” Smith explains.

TOP STORIES

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The coming months will also see the roll

out of a new basket algo offering on the

platform, allowing clients to submit a

multi-currency, multi-value basket of algos

for the first time, adds Smith. “This ties

into our over-arching theme of maximising

efficiency, automation and capabilities

for our algo users, while simultaneously

minimising risk. That is our philosophy

at FX Connect and one which continues

to drive our strategy going forward,” he

concludes.

© 2025 Citigroup Global Markets Inc. Member SIPC. All rights reserved. Citi Velocity, Citi Velocity & Arrow Design, Citi, Citi with Arc Design, Citigroup and CitiFX are service

marks of Citigroup Inc. or its subsidiaries and are used and/or registered throughout the world. This product is offered through Citibank, N.A. which is authorised and

FX Connect operating within LINK, GlobalLINK’s interoperability product

regulated by the Financial Conduct Authority. Registered Office: Canada Square, Canary Wharf, London E14 5LB. FCA Registration number 124704. VAT Identification Number

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(30201501598T, 11201505904S), and design registrations in the EU (0027845156-0001/0002, 002759266-0001).

2 May 2025 May 2025

3

MARKET WATCH

FX algos counter

liquidity mirage claims

Reports citing the potential of a ‘liquidity mirage’ in the FX market and the availability

of liquidity during times of crisis prompted concerns among some algo clients. Dr

Ralf Donner, Head of Marquee Execution Solutions at Goldman Sachs, argues that

recent volatility has served to demonstrate that the opposite is true and leading algo

providers are in fact successfully ensuring that liquidity provision for algo execution is

more robust now than ever before.

Dr Ralf Donner

The claims, which surfaced in March,

stem from concerns about the impact

of the ongoing migration away from

the primary FX markets and declining

volumes on these venues, which

Donner explains is correct and is borne

out of the data with no sign of a let

up. But the reports go on to suggest

that this can then lead to a problem

for traditional banks if they are then

forced back to these traditional sources

of liquidity during volatile periods, only

to find that it is not possible to trade

there in the same sizes as before.

While Donner agrees that primary

markets have dwindled, he encourages

taking a step back to observe the true

FX liquidity landscape as it stands

today. “We can see that the secondary

markets have stayed stable, or grown

slightly, but have not plugged the gap

that is left by the reduction in primary.

So far, it does look as if there might

be a problem,” he says. “But what

is also happening is that the more

sophisticated banks have responded

by addressing this liquidity gap. Algo

providers are creating bespoke pools

of liquidity by selecting liquidity

providers, thus ensuring good KYC and

therefore a very good ability to offset

risk. In our case we have chosen to

use FXSpotStream as a home for this

bespoke liquidity, but it can be done

in a variety of different ways and there

are now a number of venues that offer

firm liquidity.”

LIQUIDITY CURATION

The benefits of banks using these

venues are that, contrary to the

reported claims, it can actually make

the market more stable, argues

Donner. “The banks can be sure that

we are not dealing with HFTs on

the other side, or participants who

are not signatories to the FX Global

Code,” he adds. “We have chosen

our counterparties ourselves. There

are other benefits, such as being able

to create bespoke liquidity pool for a

particular currency pair. For example,

we can partner with regional banks to

specifically address any areas where

we need additional liquidity. This adds

strength to our offering rather than

diminishes from it.” Donner notes

however that this is definitely not the

picture across the whole market and

that only certain select banks currently

offer this level of bespoke, curated

liquidity. “This is because it requires

significant investment in terms of

resources to be able to set up and

monitor the pool,” he says.

“In addition, the reports came out

prior to Trump’s Liberation Day and the

subsequent market volatility allowed us

to put the theory to the test,” Donner

adds. “We had extremely high volatility

and very, very high volume days, with

some of the largest daily volumes in

the past 10 years recorded. Even during

this period of very high volatility we

were finding that FX liquidity was

actually very robust. There was no flight

back to the reduced primary markets.

We can see that the additional volume

that was needed on those very, very

busy April days did not come from

the primary markets, but in fact came

from having better internalisation and

curated liquidity on bespoke venues.

That is where the additional volume

happened.”

From an algo perspective, Donner

believes that there are now far more

robust systems in place than ever

before. Signalling risk now occurs

more when interacting with the more

traditional markets, he explains, while

newer FX venues offer reduced mark

outs which have proven to be more

robust in a time of crisis, resulting in

overall better algo performance as

well. “Markets were generally high

volume but orderly in this period and

everything was fine in terms of off-

The evolution of FX volumes across venues (aggregated into groups) that can be used by algos, which clearly shows the reduction

in primary market share

setting risk,” Donner says. “Then in

terms of internalisation what worked

well during April, but also has served

us well this year in general, has been

employing a franchise skew in order

to help fill an algo, allowing the algo

to trigger the skew in streaming prices

from the bank in order to help fill the

algo.”

FOCUS ON PERFORMANCE

Looking ahead, Donner expects further

volatility and reason to continue to

expect high volumes beyond the March/

April market crisis. “There is a lot

happening in the world that is peaking

volumes and we are seeing that higher

activity in our algos as well,” he adds.

“Although everything gets wider, so in

absolute terms may be less good, there

is also a general risk aversion, desks

are pricing wider and so some of that

premium can be captured through

algos.”

At Goldman Sachs, Donner says that

algo development is continuing on two

fronts. “We offer highly exotic, cuttingedge

functionality for algos. For example,

we already have knock-ins on algos,

Algo providers are creating bespoke pools of liquidity by selecting liquidity providers who

offer very good KYC and therefore a very good ability to offset risk

and now we offer a double knock-in on

an algo so it is possible to watch two

different levels simultaneously, each with

its own limit price,” he says. “The main

focus however is 100% on our algo

performance, that is our top priority. It is

more likely to be measured pre-trade via

various third-party TCA tools integrated

into multi-dealer platforms and

elsewhere, so we just need to be certain

that we are over-performing.”

Donner adds that the desire for live-

TCA is also important, but that many

pre-trade tools have been largely historic

in nature. “That is now a key focus for

clients who want TCA that is immediately

useful at the point of trade,” he says.

“We also offer a risk-filled Stop Loss

level, which takes away a lot of the

hassle for our algo clients. They might be

debating whether or not to use an algo

in case they take their eyes off the algo

and the market gets worse. By offering

tools that allow an automatic Stop Loss

in such an event, then we can take away

that risk and our client can just fire and

forget.”

A final area of interest is the trend

towards smaller banks using algos. “ A

smaller bank can trigger a skew in our

franchise with an algo that could allow a

much greater opportunity to get out of

risk than by attempting to do something

with their own franchise,” he adds.

4 May 2025 May 2025

5

PROVIDER PROFILE

Westpac unveils algo

rolls and access to

the WMR Fix

Westpac is uniquely positioned to offer the FX market a compelling algo offering,

supported by strong internalisation rates, access to the Asia open and a cuttingedge

approach to innovation. Gin Devoy, Executive Director, Head of Platform

Distribution, Financial Markets and Joel Marsden, Director, Systematic Trading,

Analytics & Quants at the bank share why a fiercely client-centric approach has

helped it support the further development of its algo suite to meet the increasingly

sophisticated needs of users.

Gin Devoy

Has Westpac introduced any recent

enhancements to the existing FX algo

suite?

Our FX distribution strategy is firmly

client-led - we believe that ‘clients

have products’ and not ‘products

have clients’. Among our most recent

enhancements was the launch of auto

rolls on selected channels to simplify

forward execution and greater inflight

flexibility, allowing clients to dynamically

adjust execution parameters during

the trade. Importantly, the auto roll

functionality was developed in direct

collaboration with one of our largest

and most sophisticated algo clients,

reflecting both the strength of our client

Joel Marsden

relationships and our ability to respond

quickly to complex execution needs.

In addition, our FX API now also

supports electronic benchmark orders,

giving clients streamlined access to

the WMR Fix via a secure, automated

execution process.

The service is live and rolling out

across key platforms. These two key

enhancements sit firmly alongside

our broader focus of boosting

internalisation, knowing that clients

increasingly come to us for unique

liquidity access - particularly during

time zones such as the Asia open when

liquidity can be particularly stretched.

Were there any key factors behind

those new additions?

The drivers behind these recent

developments were two-fold. Firstly,

direct client feedback included

requests for even more flexibility

and automation to better manage

execution risk, especially in forwards

and swaps. And secondly from

insights shared by our own trading

desks, where we increasingly see

the importance of internal liquidity,

execution adaptability, and the value

in minimising market footprint,

particularly during thinner liquidity

sessions.

Our collaboration with a major algo client

around developing the new auto rolls

offering further reinforced the message

that our leading clients value more

efficient, scalable forward execution

solutions which integrate seamlessly with

their own execution engines.

What are the unique benefits offered

by Westpac’s franchise and suite of

algos?

We were the first Australian bank

to offer in-house built algorithmic

execution to clients in 2016, combining

innovation with deep local expertise.

Our client-first approach ensures we

offer only the strategies we trust for

our own trading, with proprietary

designs focused on optimising

execution quality and managing

market impact. Supported by our

regional insight and continuous

innovation, we deliver consistently

strong outcomes aligned to our

clients’ evolving needs.

What is behind the continued

increase in the uptake of FX algos?

Several factors are driving the broader

adoption of FX algos, including a

greater focus on execution quality,

transparency, and control across

a broader range of flow sizes.

Furthermore, trust in electronic

execution outcomes has increased

significantly, underpinned by better

liquidity access and the availability of

smarter, next-gen style algos.

Our ability to collaborate closely with

sophisticated clients, such as with the

recent auto roll development, also

gives clients confidence that we are

building tools which directly align with

their evolving execution needs. FX

algo clients increasingly recognise that

partnering with a provider who offers

genuine internal liquidity - particularly

during less liquid times – makes

a meaningful difference, both in

reducing market impact and improving

overall trading performance.

Are you seeing any change in the

sizes of the orders now being

executed using algos? What is

influencing this shift in uptake?

Originally, algos were predominantly

used for very large, sensitive orders;

now we’re seeing broader adoption

across a wider range of ticket sizes.

Clients also increasingly recognise

that market impact matters across

all flows - not just very large tickets

- particularly in thinner liquidity

sessions. Improved inflight flexibility

and smarter liquidity access through

internalisation continue to further

support the uptake of algos for both

strategic and tactical execution.

Notably clients are also far more data

hungry than in the early days of algo

use - they are analysing execution

quality more rigorously through TCA

and, as a result, expect stronger

outcomes across all trade sizes, not

just in flagship transactions. This

data-driven mindset is pushing greater

adoption of algos even for mid-sized

and smaller flows, where consistent

performance still matters.

On the back of this growing

demand for analytics and improved

TCA, how do you support clients

to understand and utilise this data

effectively?

Our clients are becoming increasingly

sophisticated in their use of data

and now expect not just post-trade

summaries but deep, granular insights

that can drive real-time decision making.

We work closely with clients to interpret

their TCA results meaningfully, providing

context around liquidity conditions,

execution style, and market behaviour -

particularly during challenging periods

such as the Asia open.

They also increasingly want to analyse

market impact, slippage, fill quality,

and liquidity characteristics across all

execution sizes, not just the largest

orders. Our goal is to turn analytics

into actionable strategy improvements,

helping clients to continuously refine

their execution approach, rather than

treating TCA as a static compliance

exercise.

To what extent are clients looking

to partner with you on developing

bespoke algos or being able to

change parameters?

Collaboration is very much on the rise.

Clients turn to our algos for the ability

to fine-tune their execution dynamically

- adjusting aggression, slicing style,

and interaction with liquidity without

cancelling and resubmitting.

Our development of the auto roll

feature in collaboration with a very

large and sophisticated client is a great

example - they came to us with a

challenge, and we worked together to

deliver a scalable solution. We believe

close, practical collaboration leads to

better outcomes, both for the client and

for us.

How does Westpac support

clients in being able to overcome

challenging liquidity conditions

while reducing market impact?

Deep internal liquidity access is a

major differentiator via our unique

franchise. Our uniquely strong

internalisation levels help clients

achieve better execution outcomes

with a lower market footprint,

which is especially important during

sessions where liquidity is typically

stretched, such as the Asia open.

Our deep understanding of regional

liquidity dynamics further allows

us to support clients with tailored

execution strategies that recognise

when and where liquidity is genuinely

available. Clients are also then able to

benefit from reduced signalling risk

and more consistent pricing, helping

them manage execution risk more

effectively in challenging conditions.

Have you seen any increase in

interest for liquidity customisation?

We are seeing more clients seeking

different types of liquidity for

different situations. Our offering

is designed to take advantage of a

range of liquidity providers as well as

internal liquidity.

We also continue to ensure there is

a balance between price and market

impact to achieve the best outcomes

for each of our clients.

How will the FX algo market

continue to evolve? What will be

the ongoing focus for Westpac?

The FX algo market will continue

to evolve towards greater real-time

flexibility, smarter liquidity access,

and deeper client customisation.

Clients increasingly expect full

in-flight control, greater liquidity

transparency, and deeper analytics

across all trade sizes.

We expect that demand for data

will also continue to rise, and AI and

machine learning will begin to play

a bigger role in optimising liquidity

selection and execution strategies

in real time. Westpac’s ongoing

focus will be to evolve alongside

these trends while maintaining a

client-centric, transparent approach,

ensuring that innovation always

supports better outcomes for our

clients.

6 May 2025 May 2025

7

INDUSTRY VIEWS

What is currently

influencing FX execution

algo product development?

Now in its ninth year, JP Morgan’s annual e-Trading Edit once again recorded volatile

markets as the leading predicted challenge for institutional traders in the coming year

among some 41% of respondents – and a significant jump from 28% in the previous

2024 survey. On a related note, access to liquidity has also ranked as a leading concern

for the past three annual surveys. For algos clients this played out in the April market

crisis following Trump’s ‘liberation day’, leading to an upturn in volumes, but also an

increased need to review and evaluate whether their current algo selection - and the

related franchise support - is still the best choice to navigate FX liquidity under these

more volatile conditions. Nicola Tavendale investigates.

Image by shutterstock

Nikki Tavendale

The issue of FX algos being able

to source high-quality liquidity in a

fragmented liquidity landscape is a

long-running topic and continues

to be a challenge for many buyside

participants, says Alexis Laming,

FX algo trader at Crédit Agricole

CIB (CACIB). He explains at CACIB,

however, all algos are designed to

be able to cope with these liquidity

issues and to be able to navigate this

landscape. “Our clients are using

algos and are seeing algos as a tool

helping them cope with liquidity

fragmentation,” he adds. “We offer

customised liquidity pools and can

design ad-hoc customisations of those

liquidity pools which overcomes many

liquidity issues, including concerns

about liquidity mirages.” At the same

time, Laming warns that there is not

the case that ‘one-size fits all’ when

looking at algo strategies. When clients

face the trade-off between minimising

market impact, reducing market risk

and maximizing execution certainty

– the overarching algo execution

‘Trilemma’ - algos are useful but should

still be recognised as a tool in the

trading toolbox, rather than a ‘magic

wand’.

The use of algos alone cannot solve

this Trilemma, so the focus needs to

be on the client and their expected

execution outcomes, Laming explains.

“Our focus is always on engaging with

clients and understanding their needs,”

he adds. “And eventually, we can look

at customising the tools by amending

the trading logic, or we can design very

specific liquidity pools for an individual

client, or even add or remove some of

the parameters that are embedded in

the algo. It is similar to Formula One,

where even with the same engine,

individual cars may have very different

outcomes. A small design change

for the car can change a lot in terms

of performance. The same principal

applies with algos. Everything comes

from having these discussions with the

client first, engaging with the client,

understanding their needs and then

working towards meeting those needs

as well as possible.”

As a result, collaborating with clients

is an essential part of how CACIB

operates, Laming continues. “They

are the users of our tools and we are

completely aligned with our clients to

ensure they have the best execution

outcomes possible,” he says. According

to Laming, this is why regular

engagement with clients and listening

to client feedback or providing analytics

data to help work towards achieving

their expected execution outcomes is

key. “At CACIB, we have a very wide

client base, with some corporate clients

who use algos only around once a

year, through to our very sophisticated

clients who are now executing with

algos on a daily basis,” he adds. “It is

not about the size of the order being

executed, but how well we are able to

work with them to understanding their

trading needs and adapting our tools

to help them achieve these goals. Our

algos are set up in a way that allows us

to tailor the algo parameters to suite

the client.”

CHANGING EXECUTION

PRIORITIES

The necessity for data insights and

feedback has also been elevated due

to the uncertain market conditions,

prompting conversations about

whether the parameters and strategies

that worked during more predictable

markets are suitable for these volatile

periods, says Preston Mesick, Global

Head of FX Algos at Barclays. “From

the algo perspective, this has meant

looking at all the data with customers

and with the TCA providers to make

sure we are investing in enhancing the

areas which will prove to be the most

valuable for our customers,” he adds.

Ajay Kataria, Head of Electronic FX

Distribution, Americas at Barclays,

agrees, adding that on the sales side

they have also been actively helping

clients to navigate different volatility and

liquidity regimes, especially when using

the algo suite. “This is not a ‘set it and

forget it’ market. We’re dealing with

headline risk on fly,” he adds. “Being

able to help our clients utilise our tools

effectively, utilising their limit prices

effectively and then choosing an algo

versus risk transfer is pretty important

right now. We are best placed to help

them achieve their execution goals,

because we are the subject matter

experts on our own tools.”

8 May 2025 May 2025

9

INDUSTRY VIEWS

Alexis Laming

“We can design adhoc

customisations

of the liquidity pools

which overcomes

many liquidity issues,

including concerns

about mirages.”

In addition to the liquidity issue,

Mesick adds that customers also need

to find a balance between minimising

market impact, reducing market risk

and certainty of execution - the algo

execution Trilemma outlined by the

BIS. “At one end of the spectrum is

risk transfer, and at the other end,

the client would basically be taking

unlimited market risk,” he adds.

“Customers have become comfortable

with these trade-offs and part of that

has worked into the muscle memory

customers have developed from using

specific algos, from specific providers,

with specific sets of configurations.”

Mesick notes, however, that since

August and the yen move the market

has seen a significant uptick in

volatility and a shift in market dynamics

following the US election and more

recently following Trump’s Liberation

Day. These new market dynamics

are fundamentally what is causing

customers to reflect on what matters

most to them, he adds. “Our algos are

designed to adapt to these changes,

but how well the customer is able to

balance these execution trade-offs is

something that varies depending on

market conditions,” Mesick says. “This

is going to change how customers rank

those three elements of the Trilemma

and that may lead to behavioural

changes.”

LIQUIDITY CURATION

In addition, it is important to ensure

algo performance against the backdrop

of the increasingly complex FX liquidity

landscape, which has resulted in

significant enhancements the BARX

Gator suite over the past two years,

Mesick explains. He adds that part of

this development has been to focus

on increasing the effectiveness of the

sub-components, because those are

shared and put together in different

ways within all of the Gator algos.

“How do we passively place? How do

we access non-visible liquidity? How

do we utilise the franchise? All of these

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10 May 2025 May 2025

11

INDUSTRY VIEWS

Preston Mesick

“The markets aren’t

going to consolidate

tomorrow, there is

always going to be

the these ebbs and

flows. The key thing

is that you have

the quantitative

framework and teams

in place to recalibrate

over time.”

are sub-components, the building

blocks of our algos: Gator adapt, which

is our implementation shortfall algo;

Gator float and our Gator Twap algos,

the core passive algos in the suite,”

Mesick says. “What we’ve seen is that

if you build those well, the algos can

adapt to market conditions. But if the

markets are significantly more volatile

and you’re using a Twap for an hour,

which may have been a perfect setting

just a year ago, in today’s markets that

might no longer be the case. And so

we are continually driven to monitor

and enhance those features within the

algos to ensure our algo suite remains

cutting-edge.”

When clients opt to use a particular

algo strategy or product, they are

also essentially delegating liquidity

management to the algo provider

or algo broker, adds Asif Razaq,

Global Head of FX Algo Execution at

BNP Paribas. He explains that this is

essentially the result of clients typically

having limited access to that market

data, whereas the banks themselves

have a wider data set and a better

understanding of the market data and

liquidity across the different venues. In

addition, algo providers interact with

these venues on a daily basis, which

means they are much better positioned

than a client would be in terms of

determining which venues are better

versus others, Razaq says. “Generally,

the task of managing and dealing

with fragmented liquidity falls upon

the banks and their understanding

of which venues are good and which

venues are bad, as well as how to

best interact with those venues across

different currency pairs at different

times a day,” he adds.

“Liquidity management is an active

part of our day-to-day job as an algo

provider. We are constantly analysing

the different venues that we interact

with - where we currently have access

to more than 15 different execution

venues. But do we proactively trade on

all of them? No, we would probably be

very selective on how we interact with

each of these venues and with what

flavour algorithm we plug into those

venues.”

Razaq continues: “The other aspect of

understanding liquidity is knowing that

when you connect to one venue, that

is not just one liquidity pool. We have

several pools within one venue and we

would have these pools tailored per

algorithm. Depending on the nature of

the algorithm, we can work with those

venues to ensure they curate a liquidity

pool which is going to be suitable for

a particular algo strategy. As a result,

we have different flavours of liquidity

with the same venue. This has been a

significant area of focus for us since

launching our algo service.” The FX

market is also continuously evolving

and so BNP Paribas is constantly

reviewing and tweaking the pools and

the number of venues that it might

actively trade on, he adds.

FINE-TUNING THE FAMILIAR

“This includes reviewing the liquidity

curation for each algo and determining

the right venues to provide good,

low impact execution for our clients,”

adds Razaq. “We then need to decide

- how do we want to interact with a

particular venue? How do we post

our orders onto that venue? And

which order type we utilise on each

of those venues. For some venues, we

may post limit orders which are lit, we

may post some limit orders which are

dark. Dark passive orders are gaining

popularity as the market is becoming

more sensitive to orderbook changes

where we are seeing market impact

on the back of placing lit orders. We

need to be very cautious of where and

how we show interest, and analyse

and monitor market impact on behalf

of our clients. This is because clients

do not have the access to that level

of market data to do the analysis

themselves. That is where we step in.

Our algo clients delegate this analysis

to us, where we tailor-make the

algorithms and the order placement

strategies to ensure that we are

maximising our opportunities and

sources of liquidity.”

In addition, many of the leading algo

providers are now turning their focus

from algo development to ensuring

that existing strategies are instead

tailored to specific market conditions.

James McGuigan, Head of FX Algo

Product at Citi explains that this can

be a result of some clients having

a degree of ‘new algo fatigue’.

This stems from the significant

Ajay Kataria

“We also put our money

where our mouth is.

Our spot desk uses our

algos and our traders

are the biggest active

users of our algos here

at Barclays.”

Asif Razaq

“Liquidity management

is an active part of our

day-to-day job as an

algo provider, we are

constantly analysing

the different venues

that we interact with..”

commitment needed from a client to

understand what the main features

and aims are of any new algo product

when it is introduced, he explains.

“It includes a learning curve around

how best to use the algo and - most

importantly - being confident that

it will perform better than those

they already have available,” adds

McGuigan. “This requires a notable

investment of resource and a nontrivial

element of risk for clients. We

see this most in the liquidity seeking/

opportunistic style strategies as

these inherently provide freedom

for our quants to further exploit in

the search for gains.” He continues:

“The focus on optimising our existing

Arrival and Peg strategies has led to

significant performance improvements

in execution quality, for example. We

have been able to both improve our

slippage metrics whilst also decreasing

the amount of time taken to execute

any given amount. This gives clients

familiar tools that continue to return

incrementally better performance.”

TRANSPARENCY AND

INSIGHTS

Laming also notes a general and

ongoing market trend of algo

volumes increasing across the board

and for all client segments. He adds

that as algo business continues to

grow, it makes sense for the market

to look at the FX Global Code and

ensure the principals are being

applied in the algo community. “At

CACIB, we have always been very

proactive around algo transparency,”

Laming says. “We provide our clients

with a lot of data around their algo

executions and encourage them to

use this data as part of their own

analysis. For instance, we are already

working with several third-party

TCA providers and we are working

on onboarding additional ones. The

data is there on the sell side but

very often the buyside lacks access.

When clients opt to use a particular algo strategy or product, they are also essentially delegating liquidity management to the algo provider

12 May 2025 May 2025

13

INDUSTRY VIEWS

James McGuigan

“The focus on

optimising our existing

Arrival and Peg

strategies has led to

significant performance

improvements in

execution quality.”

We believe that transparency and

sharing these insights with clients is

essential.”

According to Laming, the growth

in third-party TCA is a good feature

for the FX algo market as it adds

an extra level of standardisation,

which is a very good starting point

for discussing algo performance

with clients. “In addition, pre-trade

discussions are always interesting

for buyside clients,” he adds. “At

CACIB, we believe it is important

to strongly segregate those pretrade

discussions with our team

from our trading activity. This allows

our clients to come to ask us for

analysis or insights to help inform

their planned algo executions, which

they know will not be used against

them. We are more than happy to

have this engagement with our

clients, because in helping them

make the best trading decision we

are helping them to achieve the

best outcome possible. We want to

build partnerships with our clients

and so if the outcomes from their

algo execution is good, then we are

happy.”

Laming adds that at CACIB, FX algos

are almost tailor made for clients and

the team is keen to tweak parameters

to match the client expectations and

needs again and again. The discussion

with clients is the important point, as

not every algo strategy will work for

every type of client. “We have some

corporates who could be risk averse,

for instance, or some hedge funds

which might have a lot of appetite for

risk,” he adds.

“So we do not try to offer the same

product across the board, we often

will tweak the parameters and

adapt the curation of liquidity pools

accordingly, but always to match the

client’s expected execution outcomes.

Our approach is that we start with

the client and then we evolve and

adapt the product to meet their

needs. At CACIB, innovation is part of

our DNA. We are always keen to add

new features or products, but if there

is little interest from the client then it

would ultimately be unproductive. So

for us, discussion and collaboration

with clients is the heart of everything

we do and which very often leads to

a win-win situation for both us and

our client. Our approach is clients

first, then we adapt.”

FINDING AN EQUILIBRIUM

Volumes in the algo space are

continuing to increase, which Kataria

says goes hand-in-hand with a higher

level of focus on best execution and

transparency.

“We are on the forefront of our clients

minds because of our ability to meet

those needs,” he says. “Customers

have noticed that we are a top tier

provider for algo execution across a

myriad of metrics. We have fine-tuned

and tailored the sub-components of all

of our algos to create a best-in-class

product. Which means they also come

to use when faced with these liquidity

challenges to help then figure out

how to utilise our tools to find that

balance between cost, efficiency and

execution quality. Third-party analytics

also demonstrate our performance,

for example, our liquidity seeking

algos look really, really good - and our

clients recognise that from their own

data as well.”

Kataria continues: “We also put our

money where our mouth is. Our spot

desk uses our algos and our traders

are the biggest active users of our

algos here at Barclays.” From a sales

perspective, the quant team, the

statistical modelling team is often

included in client calls and meetings,

adds Kataria.

“That is part of the increased

transparency that we offer our clients

as they now are more questions

that are more in depth and more

quantitative focused. Therefore, we

try to bring those resources to them

so we can have those higher level

conversations and go deeper into

answering these questions,” he says.

“Our goal is to bring more certainty

to a very uncertain market and to

increase transparency and to bring

increase efficiency in the spot market.

Our investment in the quant research

over the past year and a half is

testament to this commitment.”

There is also a balance that needs

to be found between internalisation

and the various types of liquidity

available in the market, whether that

is lit pools, dark pegs or mid pools,

Mesick says. “It is pretty clear that at

the extreme ends of the spectrum,

all dark or all lit, is not where this

equilibrium will be found. Instead,

being able to take a hybrid approach

to liquidity and knowing which

venues within those different types

you should be in at any given time is

really based on the amount of quant

research that the business is doing.”

Mesick adds that the quant team has

been involved in a significant amount

of research which the team is able

to harness that within the models to

be more dynamic about where and

ultimately, what that does is it scales.

“The markets aren’t going to

consolidate tomorrow, there is always

going to be the these ebbs and flows.

The key thing is that you have the

quantitative framework and teams

in place to recalibrate over time. And

secondly, that the algos have been

built in a dynamic enough way so

that they are not historically tuned

but can adapt to current conditions,

which is why our algorithms have

performed exceptionally well over the

last two months,” he says.

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14 May 2025 May 2025

15

DQ

DEQUANTIFICATION

Nightjar: flying

under the radars

Patrick Guevel, Head of FX Algo Execution at Societe Generale, tells more about the

Nightjar algorithm which is a very versatile tool indeed.

Patrick Guevel

GENERAL OVERVIEW:

What is the FX algo called?

Nightjar, Societe Generale’ flagship algo

aiming at the highest level of discretion

while mixing passive orders with hit

orders.

What category does it fall into?

Opportunistic and participation-ofvolume,

for efficient cost of execution

and dynamic impact management.

What does it attempt to do?

The Nightjar algorithm places passive,

mid-book and aggressive orders with

the objective to trade at mid-market

in an undetectable fashion. One of

the main objectives, being stealthy like

the eponymous bird, is achieved by

following live market volume curves

to control the noise of the market

participation, while the skew safeness

of the child orders is tested as soon as

practically possible.

STRUCTURE:

What is the algo’s software

architecture?

Societe Generale uses low latency

components written in C++ or C# that

are deployed in the major colocation

centers for the FX markets, to provide

its customers the highest chances

of getting filled. These software

components can operate on a 24/5

mode, providing a full coverage of the

FX markets.

Does it use proprietary modelling?

Yes. Like all the Societe Generale

algos, the Nightjar uses proprietary

modelling for pricing, order

placement, pacing control signals,

etc. Keeping the full control of the

modelling enables the Nightjar to be

very agile.

Does it use technology such as AI or

ML? If so, how?

Yes, with moderation. Machine

Learning is used to help the Nightjar

guess what the market trading activity

is, and is going to be, to control its

market impact.

FUNCTIONAL ASPECTS:

NIGHTJAR

Does the algo adapt automatically

to prevailing market conditions and

if so how?

Yes, it does. The Nightjar has the

capacity to detect slow or high market

activity and adapt its target pacing

accordingly, for any currency pair, at

any time during the day.

The Nightjar uses passive, aggressive and mid-market execution styles

Does it incorporate smart order routing?

Yes! Due to the highly fragmentation of the FX markets, it is

logical to use some smart order routing tools. The Nightjar

is able to skim cost efficient liquidity in all kinds of markets,

by smartly interacting with a large and diversified pool of

execution.

How does it minimise market footprint?

The Nightjar considers two aspects of the market footprint:

the price impact generated by consuming liquidity and the

information leaked by its child orders. FX is not different than

the other asset classes, a large order execution usually results

in a noticeable price movement, and the nightjar looks at

minimizing this footprint by controlling its participation in

the market. The child orders visibility is closely monitored and

controlled to avoid adverse market movements.

What liquidity seeking and access capabilities does it

deploy?

The Nightjar looks for liquidity in the primary and secondary

venues, from Liquidity providers and from mid-market

execution venues. When operating in the so-called lit venues,

the Nightjar deploys some tricks to avoid being detected.

What operational risk management does it include?

The Nightjar, like all SG FX algorithmic orders, has several

controls in place to protect its client electronic order flow from

external negative events, including the following, but not

exclusively:

a. Fat finger limit, pacing control,

b. Per exchange venue circuit breakers,

c. Per child order price and size controls,

d. Per venue aggregated notional value and throughput limits.

PARAMETERS AND CONTROLS:

What client inputs are available in the algo?

Beside product (spot or NDF), direction, size, start and end

times, liquidity pool, our customers can control these Nightjar

specific parameters:

- Speed: slow, normal or aggressive.

- Alpha seeker: an option to speed-up or slow-down when the

asset price over- or under-perform a recent average.

During the execution, our customers can change most of these

parameters, pause and resume the Nightjar, and even switch to

another algo type from SG’ algo suite.

How much real-time feedback does it provide?

The Nightjar reports in real-time its execution status (quantity

and average price, running/paused, etc.), its child trades through

the FIX API and the standard order management platforms. Its

live orders that are also visible through our live TCA, a simple

but efficient tool for visualizing the activity of the Nightjar.

CAPABILITIES AND USE:

What execution styles (e.g. passive/aggressive) does the

algo support?

The Nightjar uses passive, aggressive and mid-market execution

styles. For cost efficiency, it mainly posts passive or mid-book

orders, and sometimes aggressive orders when skewed prices at

mid-market or better are available.

How can it be integrated/called with/by higher-level

workflows?

The Nightjar is available via FIX and FSS, so that it can be

integrated in most systematic or semi-automated execution

workflows.

What is the optimal scenario for its use?

The Nightjar is a stealthy execution strategy, recommended when

discretion is more important than speed. It is a very versatile tool

that is used for large executions over a day or a few hours, at best

orders, and small to medium size orders over a few minutes.

Any other functionality worthy of note?

We like so much its ability to trade at mid-market that we have

embedded the Nightjar in our TWAP+ algo, to improve spread

capture, and it works! Our customers appreciate the capacity to

control the end time of the TWAP+ order while benefitting from

the agility of the Nightjar.

16 May 2025 May 2025

17

BUYSIDE INTERVIEW

What range of instruments are you

generally working with?

We operate across a broad range

of financial instruments, including

equities, developed market credit,

covered bonds, government bonds,

emerging market hard currency bonds,

CDS, swaptions, IRS, FX spot/forwards/

swaps, and listed derivatives.

How would you describe the key

objectives and guiding principles of

your trading desk and the dealing

activities it undertakes?

With Tatu Kallio, Head of Trading

at OP Asset Management

OP Financial Group is Finland’s largest financial services group and has over a

hundred years in managing client assets. OP Asset Management, which is part of

the group, continues this work. Its offering includes the wide array of OP funds,

alternative investments, real estate investments and many additional services.

OP Asset Management emphasises responsible investing (ESG) and risk selection.

Responsibility is always considered in investment decisions and processes, and it’s

a crucial element in its investment operations. In particular, it plays a key role in its

active direct investments. Tatu Kallio runs the cross-asset trading desk at OP Asset

Management and we asked him to tell us a little about his views on algorithmic FX

trading and its place in his day to day dealing operations.

Tatu, please tell us a little about

what your job involves and the key

responsibilities you have.

I lead our multi-asset trading desk,

which consists of five traders including

myself. While I remain actively involved

in trading whenever possible, I also

oversee regulatory compliance, risk

management, process development,

and the seamless integration of our

trading operations within the broader

investment organization.

What types of clients does OP Asset

Management provide services for?

Our largest client segment by far is Finnish

retail investors, primarily through our

mutual funds. In addition, we manage

institutional mandates and wealth

management portfolios. We also oversee

mandates for OP Financial Group’s

insurance and life assurance companies and

manage the liquidity reserve of the bank.

Our mission is straightforward:

to deliver best-in-class execution

outcomes across all asset classes for

our clients. We also aim to generate

alpha by advising portfolio managers

on execution strategies, liquidity

sourcing, market structure, and

instrument selection. In addition,

we play a central role in managing

counterparty relationships and

implementing allocation changes

across fund-of-funds, institutional, and

wealth management portfolios.

Working with multiple assets can be

a complex undertaking. How do you

address the various technology and

workflow challenges involved?

The multi-asset setup requires

both skilled traders and a resilient

infrastructure. We currently use

three core trading platforms by asset

class, which also act as backups—

an often overlooked but critical

aspect of business continuity. While

we’ve explored multi-asset EMS

platforms, the cost-benefit equation

hasn’t yet justified implementation.

Our priority has been workflow

automation: ensuring that traders

receive orders through the correct

systems and formats. This requires

strong integration between the

portfolio management system and our

trading platforms. In FX, we still see

room to improve automation. When

evaluating new workflow tools, our

focus is on automation capabilities and

connectivity to TCA providers, OMS,

and counterparties.

Your team recently started to use

FX algos. What was the motivation

behind that decision?

OP Financial Group is Finland’s largest financial services group

Having used equity algos for years,

expanding into FX algos was a natural

progression. The underlying execution

logic is quite similar, and we saw a

clear opportunity to improve execution

quality. FX algos helped to fill a gap

in our toolbox, particularly for order

types where traditional RFQ or WMR FIX

trading protocols aren’t ideal. Our aim

was to assess whether algos could deliver

better results for certain trade profiles.

What are your main objectives when

undertaking algorithmic FX trading

and what types of orders are usually

a good fit for them?

In notional terms, our largest FX

activity is related to hedging for our

Our priority has been workflow automation

insurance mandates, primarily in

swaps. By ticket volume, however, the

bulk consists of spot and short-dated

forward trades linked to mutual fund

flows. WMR fixing orders still account

for a significant share of our passive

fund flows and are generally not

suitable for algo execution.

This leaves us focusing on larger hedge

adjustments, sizeable spot trades, and

scenarios where FX execution can be

aligned with other asset flows—such

as equity trades executed over the day.

Since our portfolio managers rarely

take active intraday FX views, we can

afford to be patient, accept market risk,

and focus on minimizing market impact

through passive execution. We believe

18 May 2025 May 2025

19

BUYSIDE INTERVIEW

That said, we rarely intervene once

an algo trade is underway. Our order

sizes typically don’t warrant active

management, and more importantly,

hands-off execution allows us to build

a clean and unbiased dataset for

analysis.

Consistency is key when comparing

performance across providers, even

with sophisticated TCA tools. We’re

mindful of the well-known cognitive

bias where people draw conclusions

from isolated outcomes, so we

deliberately avoid overreacting to

individual trade results.

There’s always a trade-off between having broad access to algo providers and maintaining clean, comparable data

this approach yields better long-term

outcomes, even when accounting for

the increased arrival price variance that

passive strategies may cause.

How do you source your FX algos,

and what factors influence your

choices?

algo strategies on paper, we’ve

observed real differences in execution

behavior—particularly in aggressiveness

and liquidity sourcing. Without a

sufficiently large and normalized data

set, these nuances are easy to miss,

which underscores the importance of

strong TCA.

Are you happy to let an algo do its

work without much oversight, or do

you prefer more real-time visibility

during execution?

We’re fortunate to work with providers

that offer strong real-time monitoring

tools which we consider essential.

You’ve been working on a new multiasset

TCA. How is that progressing,

and how is it helping your dealing

activities, including algorithmic FX

trading?

We’ve been working with our multiasset

TCA provider for about two

years. The initial build took roughly

a year, and the system is now

operating smoothly. While there’s

still room to improve data quality

and expand instrument coverage,

centralizing the data has been a major

advantage. It reduces the burden on

our technology and data teams and

enhances transparency, something

our compliance and risk functions

particularly value. That said, relying on

a single provider comes with trade-offs,

as no vendor excels across every asset

class.

FX algos have become a core part of our execution toolkit and open up new opportunities

Crucially, the ability to benchmark

performance against peer groups and

cost estimates adds meaningful insight.

Even aggregate-level EURUSD slippage

figures have limited value on their

own—it’s the context that makes them

actionable.

Do you expect to make more use of

algorithmic trading in the future, and

what will influence that decision?

Absolutely, provided we continue to

receive a sufficient volume of suitable

orders. FX algos have become a core

part of our execution toolkit and open

up new opportunities. One area where

we’d like to see further development

is in ultra-passive strategies. As

mentioned earlier, our preference is

to act more like a market maker—

providing, rather than taking, liquidity.

Even the most passive algos available

today tend to execute too quickly when

mid-market liquidity appears, and often

suffer from some adverse selection

when markets are moving. We’d

welcome tools that allow us to post

interest and truly behave passively. Algo

providers: we hope you’re listening.

As we’re still in the early stages of FX

algo adoption, it made sense to start

by leveraging our existing relationships

with key FX counterparties. We

conducted thorough due diligence to

ensure their offerings matched our

needs—both in functionality and in

terms of connectivity with our trading

platforms and TCA provider.

There’s always a trade-off between

having broad access to algo providers

and maintaining clean, comparable

data. To ensure robust TCA and

meaningful analysis, we’ve limited the

number of algo providers we use. Our

current mix includes global bulgebracket

banks and Nordic niche players

to reflect our regional footprint.

Although most providers offer similar

To ensure robust TCA and meaningful analysis, we’ve limited the number

of algo providers we use

We’re fortunate to work with providers that offer strong real-time monitoring tools which

we consider essential

What advice would you give to

other firms exploring algorithmic FX

trading?

Start with a solid TCA framework so

you understand your baseline execution

costs across different protocols. Only

then can you meaningfully evaluate

whether algos improve outcomes and

confirm that through live testing. Talk

to your counterparties, peers, TCA

providers, and study the algo offerings

carefully. In our experience, passive

algos outperform traditional risk transfer

methods for larger orders and offer

better alignment with asset flows, for

example, using VWAP-style strategies

to match FX with equity execution over

the day. That said, if your orders are very

small or dominated by fixing trades,

algos may offer limited added value.

20 May 2025 May 2025

21

PANEL DISCUSSION

Utilising FX Execution algos:

Gathering practitioner and buyside perspectives

We brought together Farzana Nanji, EMEA Head of eFX Sales at HSBC and Rich Turner,

Senior Trader, Currency Solutions at Insight Investment to ask them some important

questions about algorithmic FX trading.

Farzana Nanji

FN: How would you summarise the

key benefits of using FX execution

algos and what sort of questions

would you expect to be asked by

clients who are just starting out on

their FX algo trading journeys?

FX algos offer a powerful, flexible

execution tool that puts clients in control,

tailored to hit their specific trading

objectives. The key benefits offered by FX

Algos include minimising market impact,

increased transparency and customisable

strategies, resulting in a lower execution

costs for clients. For new clients in

particular, understanding the implication

of these components is essential to their

overall trading journey. Firstly, what is

the quality of the analytical tools from

pre-trade, real-time and post-trade and

will this provide increased transparency

around the quality of the execution?

How can this help develop specific

metrics? What are the various different

strategies available and how can they

minimise transaction costs? What is the

Rich Turner

choice of external trading venue, and

how significant is internalisation? It is

worth noting a child order executed

by the algo internally will benefit from

curated liquidity which will reduce

information leakage. The overall cost

reduction is quantified by comparing

algorithm performance versus risk

transfer price (RTP) - the electronicallystreamed

price at the start of the

execution. It is always important for our

clients to have an in-depth analysis of the

performance of each algo order.

FN: Price and speed are important

factors in FX execution decisions but

why is market impact also of concern

for many buyside firms and how can

algos help to reduce it?

FX algos offer a systematic, data-driven

way to minimise the execution cost

while achieving a client’s objectives

where the price, speed and market

impact are the key risk factors. Market

impact can significantly negatively affect

execution performance and therefore

managing market impact is a critical

success factor in algo value creation,

leveraging on the depth and resilience

of liquidity. Advanced algorithms

mitigate directional flow leakage

through adaptive slicing techniques with

appropriate child order types. These

algorithms leverage high-frequency

microstructure information and

diversified, curated liquidity channels

with minimal interbank exposure.

Quantitative models are employed

to optimise the pace of execution by

analysing observed market impact

signatures, balancing the goals of speed

and cost efficiency.

FN: How do leading providers

go about computing the level of

expected Market Impact that their

algos will be able to deliver?

Leading providers typically engage large

quantitative teams to study market

microstructure, curate liquidity, design

and implement execution algorithms.

These teams continuously refine

their market impact models through

rigorous calibration against historical

algo performance data, which account

for market conditions and chosen

parameters. The effectiveness of these

models is validated using in-house

analytics and third-party services.

Clients receive transparent insights on

expected performance metrics and

associated trading risks.

FN: How are leading FX algo

providers tackling the problem of

differentiating their offerings in this

increasingly competitive market?

For example, by taking a different

approach to liquidity management.

FX algo offerings are highly correlated

to the quality of eFX market making

infrastructure and client franchise

components integrated into algo

strategies and analytics. The flexibility

of a proprietary platform managing the

algo models and smart order router

(SOR), enables banks to curate liquidity

and continuously monitor performance.

The FX market offers many liquidity

styles: primary to secondary, fully

disclosed to anonymous, firm to hybrid,

and a new generation of discrete peerto-peer

liquidity. Providers implement

them differently depending on their

product strategy and IP. Internalisation

is vital in FX algo execution, especially

during periods of high volatility. Each

bank’s approach is shaped by its unique

combination of client profiles, franchise

strength, and operational framework.

This determines capacity to leverage

internal eFX market-making resources,

creating a blend of liquidity options that

set banks apart and benefits algo users.

As the eFX market rapidly evolves,

adapting liquidity curation for efficient

algo execution across new currency

pairs offers a competitive edge. This is

evident in recent developments to adapt

existing algos to the electronification of

NDFs and precious metals. To manage

the market evolution, many banks offer

a full complement of strategies: in

HSBC’s case, it’s a suite of 8 algos that

includes POV (percentage of volume)

and the multi-currency basket, based on

correlation optimisation.

FN: Why has internalisation become

an important consideration for

increasing numbers of FX execution

algo users and what role can it play

in helping to improve execution

performance?

Guidelines and standards in algorithmic FX trading can only be a good thing

Internalisation has become a

fundamental differentiating factor

when executing FX algos, acting as

an additional execution pathway with

minimal information leakage. This

has been particularly noticeable

given the increased market volatility

and complexities of the market

microstructure. Markets have become

increasingly sensitive to directional flow

on public venues, which can impact

market pricing and bid-ask spreads

with the execution of larger orders.

As FX markets remain primarily overthe-counter

(OTC), the advantage of

internalisation can be realised via algo

interaction with a significantly large

OTC liquidity pool, rather than just algo

versus algo.

Major liquidity providers offer significant

levels of internalisation due to the

scale and diversity of their operations.

However, achieving a high degree of

internalisation itself is not the objective.

The goal is to deliver better outcomes

for clients, which principal liquidity

supports through consistently flat

markouts—demonstrating minimal

market impact and low adverse

selection.

RT: Why are pre trade analytical

toolsets becoming increasingly

important for some buyside algo

trading firms?

Pre-trade analysis is becoming

increasingly important as it allows the

trader to bring post trade analytics of

previous executions to the forefront

of decision making. When a trade

arrives on a trader’s blotter, they want

to bring any learning from previous

experiences to the forefront of deciding

how to trade. The information must be

delivered in a transparent, compliant

and auditable way. The decision

to trade may well be also driven by

information pertaining to the underlying

market conditions and any key events

that may be about to be released.

FN: What work is being done by

FX algo providers to enhance their

Transaction Cost Analysis offerings

to help clients make more informed

decisions about algo selection and

execution quality?

Technology, regulatory frameworks and

margin reduction across the industry

have impacted how clients quantify

the quality of their execution. As a

result, the data offered in transaction

cost analysis and post-trade reporting

constantly adapts to these new

requirements. TCA gives clients the

transparency and all the information

required to optimise algo performance

but this process extends beyond a

simple post-trade report.

Recently, the focus has been on

providing data in flexible formats

since clients increasingly request API

integration for independent data

analysis. Third-party analytics providers

have a growing role in the market.

Accurate, resilient integration is vital

for reliable service and performance

22 May 2025 May 2025

23

PANEL DISCUSSION

Recently, the focus has been on providing data in flexible format since clients increasingly

request API integration for independent data analysis

comparisons. In addition, increasing

focus on pre-trade performance stats

underscores the need for accurate data.

FN: The delivery of algo analytics can

be fragmented. What is being done

to improve their usability?

There is considerable development to

align the usability of FX algo analytics

across multi-dealer trading platforms.

Banks’ single dealer platforms, however,

have some of the most comprehensive

analytics tools in the market -- from

analysing the market landscape to

flexibility, transparency and interactivity

throughout their algo executions. In

the case of HSBC, these types of tools

have been designed within the HSBC

AI Markets trading terminal and HSBC

Evolve single dealer framework.

RT: As more asset managers and

corporates start to adopt algo trading

toolsets what would you like to see

done to make disclosures easier to

understand for clients of varying

degrees of sophistication so that they

can match their individual execution

requirements with the most

appropriate execution algo?

The industry has a large divergence

in the understanding of disclosures.

When confronted with a disclosure

for the first time it may seem very

daunting. The journey of improved

execution is iterative in nature and

understanding of things such as

disclosures should also be viewed

this way. When a trader has chosen

a method to execute, he is aligned

to a target outcome and should have

a good understanding of what he is

doing. At that point he should be

thinking of improvements that he could

make to his decision making at the

point of trade and during the execution

of the trade.

FN: How much demand in the future

is there likely to be from buyside

firms for more customised FX algo

trading solutions? For example, to

adapt an existing algo to make it

a perfect match for their particular

needs and requirements.

Buyside demand for customised FX

algo solutions will continue to grow,

fuelled by a need for a differentiated

execution, better control and more

integration with internal analytics and

systems. This process has already been

initiated given each buyside firm has

its own infrastructure and execution

strategy, whether seeking alpha or

simply measuring execution costs.

Almost all algo elements can be

customised -- for example, HSBC offers

a floating principal order algo solution

by aiming to reduce market impact.

Through configuration adjustments,

the algorithm can change its mode

of interaction with HSBC’s central risk

book by placing pegged passive orders

and matching them with incoming

client orders.

RT: In what ways is the growing use

of execution algos in FX likely to

impact on the skillsets required of

traders to manage them?

Over time the skillsets of traders have

evolved. Traders now must be more

skilled in data manipulation to ensure

that output from data sets can be

used in a way that is beneficial to the

trading outcome. Not only must they

ensure that data is clean and relevant,

they must also ensure that the output

is presented in a way that is easily

understood to differing consumers.

Looking forward, the ability to

manipulate this data in an automated

manner will be key. Programming

skills such as Python will be essential.

There is the hope that evolution

in automation will put solutions at

traders’ fingertips, allowing them to

spend more time on market analytics.

We are also on the cusp of great steps

forward in artificial intelligence and

machine learning, which will bring

other opportunities and repercussions

for traders to be mindful of.

RT: We are starting to see the

arrival of guidelines and standards

in algorithmic FX trading. What

benefits do you think these will

deliver particularly in the years

ahead as the level of complexity of

this style of trading continues to

increase?

Guidelines and standards in algorithmic

FX trading can only be a good thing.

In essence, trading desks will have to

ensure there is adequate governance

structure around the algos they use

and how they use them. The level

of complexity is already growing,

and traders need to make sure that

they understand the nuances of the

algos they trade and how they are

constructed.

Transparency and governance

are something that supports the

principals of the FX Global Code.

With that in mind, traders will have

to fully understand how algos work.

Better understanding of urgency,

internalisation, nature of order posting

and differing natures of pools of

liquidity are a few of the parameters

that traders will need to better

understand.

FN: How far are next generation

technologies like AI likely to be

applied in algorithmic FX trading and

what can be done to ensure that

more sophisticated techniques like

Machine Learning can be governed

sufficiently, particularly as some

practitioners believe that ML could

create new market fairness and

stability threats that may require new

distinct governance frameworks?

Algorithmic execution already uses

machine learning techniques, and

appropriate governance on probabilistic

outcomes is in place. Execution

algorithms typically have well-defined

goals and constraints, and the

development process is thoroughly

verified and highly regulated.

We expect to see generative AI being

used in the market in the near future to

enhance and simplify client interactivity

with an algo’s API, as well as to aid

in pre-trade decision-making and

performance interpretation.

FN: How much potential is there for

taking a more multi-asset approach

to FX algo development, particularly

where FX is not sitting alone but is

part of other trades being undertaken

by buyside firms?

Equity and fixed income managers

have been generally less proactive at

managing their FX risk, resulting in

fragmented FX execution behaviours.

Recent market dynamics have, however,

prompted global investors to quantify

the FX returns in their underlying

investments. The HSBC FX Basket

Algo caters to this type of buyside

requirement, and has been designed

to optimise currency basket execution

through FX correlation analysis. This new

algo strategy is suitable for any crossasset

portfolio manager looking for an

efficient FX transaction, as defined by a

reduction in electronic execution costs

and operational workloads.

FN: As buyside firms seek to deepen

their understanding of FX algos, how

far should sellside providers be willing

to go in offering more comprehensive

execution coverage specifically

focused on algorithmic trading?

The algo analytics suite equips clients

with dynamic tools to help them achieve

Artificial intelligence and Machine learning will bring other opportunities and repercussions

for traders to be mindful of

their execution goals. This starts with

customised onboarding, for each client,

product education and continuing

throughout the algo order’s lifecycle.

Comprehensive in-flight coverage is

available via segregated algo teams or

self-serve analytics tools, or a combination

of both depending on each clients’ focus.

The service continues post-trade, with

detailed scrutiny of performance to help

clients assess whether their objectives

were met, whether alternative strategies

should be used, and, in some cases,

whether bespoke configurations should

be incorporated.

RT: As the use of algorithmic trading

in our industry gathers pace what

implications does that have for the

nature of the trading room of the

future?

The trading room of the future will

have more reliance on automation and

data analytics. Manual tasks will be

moved away from traders’ fingertips.

Smaller trades which don’t need a

trader’s attention will be auto traded

with a governance structure to capture

any exceptions for analysis. This will

allow traders to spend more time

on trades that require greater focus,

to generate as good an outcome as

possible.

There will be more reliance on the

delivery of data analytics at point

of trade, to help the trader optimise

their outcome. Evolutions in artificial

intelligence and machine learning are

on their way, so desks are making

preparations to take full advantage.

The trading room of the future will have more reliance on automation and data analytics

24 May 2025 May 2025

25

INDUSTRY REPORT

FX Trading in 2025:

Growth amid fragmentation, AI, and the

shift to direct connectivity

To examine institutional trading

firms’ approach to FX infrastructure

investment, Acuiti recently partnered

with Avelacom to survey or interview

senior executives from 68 proprietary

trading firms, brokers and banks that

trade FX. Survey respondents were

based in Europe, US, APAC, MEA and

LatAM. The results were published in a

whitepaper which examined the state

of play in FX and where firms envisage

the greatest challenges. It also explored

how they are approaching connectivity

and how recent innovation such as

stablecoins and FX ETFs might affect

market dynamics in the future.

KEY FINDINGS FROM THE

SURVEY FOUND THAT:

• 82% of survey respondents expect

spot FX trading volumes to increase

over the next 12 months.

• 51% of survey respondents

anticipate that AI and ML will drive

the market’s greatest technological

advancements over the next three

years. This is a higher level of

enthusiasm than was shown for

other technological opportunities,

such as automation, blockchain

settlement and cloud computing.

However, there is still caution in the

application of AI technology. This was

most often caused by high costs of

implementation and a burst of third

party offerings that it can be difficult

to differentiate between.

• High operational costs and liquidity

concerns are common problems for

market participants.

• While cloud adoption for

infrastructure is relatively low, it

is growing in popularity as firms

invest in connectivity and look to

improve their processing power and

scalability.

• Over a quarter of firms that currently

rely on third party platforms for

liquidity sourcing are planning to

take more control of connectivity

and establish more direct access to

venues, bypassing brokerage-led

execution.

• Most survey respondents set up their

infrastructure three or more years

ago, with 29% having done so more

than five years ago — suggesting

that the market is ready for a new

wave of investment in the area.

NEW TECHNOLOGY

FX is already a highly mature market in

terms of electronification. However, the

need to innovate and adopt efficiencyenhancing

technologies is still high.

Source: FX Trading in 2025: Growth Amid Fragmentation,

AI, and the Shift to Direct Connectivity

When considering which technological

advancements would have the greatest

impact on FX markets in the coming

three years, survey respondents

placed highest importance on artificial

intelligence and machine learning in

non-trading operations. When asked

more specifically about the technology’s

potential for FX trading in the future,

most survey respondents thought

the impact would be significant and

nearly one fifth said it would be game

changing.

EXPECTATIONS FOR

ALGORITHMIC TRADING

Data analytics and visualization tools

have also been increasing in importance

in recent years, particularly in light of

best execution requirements. Buy-side

demand for tools like TCA have

increased rapidly in the wake of new

rules and growing client demand for

transparency. These tools support

granular analysis of the costs of

each trade and enable comparison

of the sellside firms that they have

relationships with. It should also be

noted that expectations of innovation

in algorithmic trading are also high

amongst survey respondents continuing

a trend of heavy investment in this area

in recent years.

AI and machine learning are poised to

significantly change FX trading, with

51% of respondents identifying these

technologies as the most impactful over

the next three years. From enhancing

data analytics to improving algorithmic

trading, these innovations will be key to

maintaining a competitive edge in an

increasingly fragmented and complex

market.

More information about the survey can

be found at:

https://www.acuiti.io/wp content/

uploads/2025/05/FX-Trading-in-2025.

pdf

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References

Richard S. S. Sutton and Andrew G. G. Barto, 2018, Reinforcement Learning: An An Introduction, Second

Edition

Cameron Davidson-Pilon, “Bayesian Methods for for Hackers: Probabilistic Programming and Bayesian

Inference “, “, 2016, Addison-Wesley Data && Analytics

Merton, Robert, 1980, On On estimating the the expected return on on the the market: An An exploratory investigation.

Journal of of Financial Economics, Volume 8, 8, Issue 4, 4, December 1980, Pages 323-361

Junya Honda and Akimichi Takemura, Optimality of of Thompson Sampling for for Gaussian Bandits

Depends on on Priors, Proceedings of of Machine Learning Research, Volume 33: 33: Artificial Intelligence

and Statistics, 22-25 April 2014

Tze Tze Leung Lai Lai and Herbert Robbins. Asymptotically efficient adaptive allocation rules. Advances in

ian

applied in applied mathematics, 6(1):4–22, 1985 1985

Daniel Kahneman, 2011, Thinking, Fast and Slow, Penguin

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148 | november 2018 e-FOREX

EXPERT OPINION

Redefining the boundaries

between buying and building

FX algo trading architectures

By Mike Powell, CEO of Rapid Addition.

Mike Powell

With U.S. trade policy shifts fuelling

intense market volatility, many FX

trading firms are enjoying a surge in

trading volumes. But behind the scenes,

there’s also a fair bit of nail-biting.

Spiking activity and unpredictable price

swings—reminiscent of the COVIDera

chaos—are once again testing the

resilience of trading infrastructure.

In the highly dynamic world of

electronic foreign exchange trading

where geopolitical flare-ups and

economic surprises can spark seismic

price moves, technology isn’t just

an enabler, it’s a critical strategic

asset. However, firms must juggle

performance, resilience, and budget

constraints, all while striving to stand

out in a highly competitive market.

This raises a pivotal question:

should firms build their own trading

infrastructures - which may need to

include algo execution functionality - or

tap into the capabilities of third-party

solutions? Historically, this has been a

debate centred on control, cost, and

competitive edge. But as technology

evolves and managed infrastructure

matures, the lines between what’s

worth building versus buying are being

redrawn.

THE BUILD VS. BUY DEBATE:

REFRAMED

Traditionally, building your own

system offered maximum control

over performance, fine-tuning every

layer, from execution logic to latency

optimisation. This was especially

attractive to large sell-side banks and

HFT firms, hunting every microsecond

of edge.

On the flip side, buying pre-built

solutions offered speed (time-tomarket),

reduced project risk, and access

to external expertise. Smaller firms,

constrained by budget and specific

expertise, often leaned on whitelabelled

platforms or specialist vendors

to stay competitive.

But the landscape has shifted. It’s no

longer just about speed vs. control

because new technologies and

operating models have redefined what’s

possible.

WHAT’S CHANGING? THE

TECH EVOLUTION BEHIND THE

SHIFT

The advent of next-generation

technologies is transforming how

firms approach this decision. Cloud

computing and high-performance

managed colocation in FX hubs like LD4

and NY4 are reducing barriers to entry.

Firms can now scale infrastructure as

needed, without the burden of upfront

capital investment. This “infrastructureas-a-service”

model is levelling the

playing field, enabling firms of all

sizes to tap into low-latency, scalable

environments and execute sophisticated

trading strategies under a flexible opex

model that better aligns costs with

revenues.

API-driven modular platforms are also

changing the game. Firms can now

more easily plug in specialist tools

(such as execution algorithms, pricing

engines, or liquidity modules) taking

a modular, best of breed approach

leveraging in-house and third-party

applications. This approach frees

organisations from committing to a

single monolithic system and frees

internal developer and quant teams to

focus on delivering genuine competitive

advantage, leveraging third parties

for critical but non-differentiating

components.

For regional or mid-sized players, this

approach can be a game-changer. With

smaller budgets and limited quant

expertise, they can still deploy cuttingedge

tools via open APIs, integrating

third-party algos and tools without the

overhead of a full in-house build.

THE ROLE OF AI AND ML:

HYPE OR HELP?

Artificial Intelligence (AI) and Machine

Learning (ML) are becoming increasingly

embedded in FX trading workflows,

from analytic models to execution algos.

But the reality is these technologies

demand deep datasets, serious

computational power, and highly

specialised talent.

For many firms, building AI capabilities

from scratch is a daunting task and

may not be feasible for many. A better

option? Partnering with vendors already

investing heavily in AI, allowing firms

to gain early access to capabilities they

wouldn’t otherwise develop in-house.

This isn’t just about efficiency it’s about

survival. With AI poised to become the

next battleground for execution quality,

those who don’t adopt will likely fall

behind.

REGULATORY PRESSURE ADDS

COMPLEXITY

It’s hard to ignore regulatory trends

in the context of capital markets.

The recently implemented Digital

Operational Resilience Act (DORA) in

the EU has raised the bar on how firms

handle operational risk, cyber resilience,

and third-party oversight.

While building in-house systems

may provide more direct control over

compliance and reporting structures,

vendors are rapidly enhancing their

platforms to meet these demands. In

many cases, third-party providers have

cross-jurisdictional insight and specialist

compliance teams that allow them to

adapt faster than internal development

cycles allow. They also have the

advantage of working with multiple

customers, sitting in the centre of an

industry feedback loop.

So, while regulation might initially

seem like a reason to build, it may

actually strengthen the case for

selectively outsourcing and leveraging

the investment and expertise of third

parties.

MAKING THE CALL: WHAT TO

BUILD AND WHAT TO BUY?

There’s no one-size-fits-all solution. But

here are four key areas firms should

assess when defining their strategy:

1. Differentiation potential

• Build what sets you apart, custom

algos, unique execution logic,

proprietary data models, and other

capabilities that genuinely help you

stand out from your peers.

• Buy common capabilities,

middleware, risk systems, backtesting

and analytics tools or where

vendors may be ahead of the curve

(like in AI).

2. Cost and scalability

• Building can deliver to your exact

needs but can also be expensive

and risky. Upfront investment, talent

acquisition, and long development

cycles can strain even large budgets.

• Buying potentially offers more

predictable opex and scalable

AI and Machine Learning are becoming increasingly embedded in FX trading workflows

infrastructure, especially with SaaS

and cloud models that grow with

your needs.

3. Compliance and resilience

• In-house systems can offer more

control over data and faster

adaptation to regulatory changes,

especially under frameworks like

DORA.

• But vendors bring deep regulatory

know-how from serving multiple

clients, often easing the burden

on internal teams and speeding

compliance delivery.

4. Integration and staff continuity

• Legacy in-house stacks can become

brittle over time, especially if

documentation is lacking or staff

turnover is high.

• Vendor platforms, built with modern,

API-first principles, are easier to

integrate and maintain and vendors

usually have deeper talent pools to

support ongoing operations.

THE RISE OF THE HYBRID

MODEL

As the market evolves, so too does the

approach to architecture. Increasingly,

firms are blending in-house IP with bestof-breed

vendor tools. The hybrid model

allows for innovation where it counts

and efficiency everywhere else.

For example, large institutions may

pair proprietary quant strategies with

vendor UI layers or algo deployment

frameworks to reduce time-to-market

and gain advantage. While a smaller,

regional bank might use hosted

infrastructure and third-party algos to

deliver its trading stack, focusing on

local expertise and client relationships to

create differentiation.

All firms regardless of size face

common constraints: limited resources,

overloaded tech teams, and growing

regulatory demands. While some firms

are committed to building tech, many

are realizing that they can be more

efficient and agile by focusing internal

efforts on what makes them stand

out and relying on trusted partners for

everything else.

LOOKING AHEAD: THE NEXT

EVOLUTION IN FX TRADING

ARCHITECTURE

The FX industry isn’t done evolving,

far from it. The next generation of FX

trading infrastructure will likely be

modular, AI-enhanced, and seamlessly

blend in-house IP with best-in-class third

party technology. Execution decisions

will be data-driven and automated.

Platform architectures will need to

support both human and machine

workflows seamlessly.

In this future, firms that intelligently

navigate the build-vs-buy continuum will

be the ones that thrive. Those who try to

build everything risk falling behind; those

who rely too heavily on third parties may

struggle to differentiate. The winners will

strike a balance by building proprietary

tech where it creates advantage and

embracing vendor innovation where it

accelerates time to value.

In short, building and buying aren’t

opposites anymore. They’re two parts of

a smarter, more strategic whole.

28 May 2025 May 2025

29

ALGOTECH

Delivering the fuel for

FX algo trading:

Navigating the global data challenge

Image by shutterstock

This makes global state awareness not a

luxury, but a requirement.

However, market data doesn’t arrive

equally or simultaneously, making it

difficult to get the complete picture

needed to act with confidence. It’s

not hard to see why, given all the

variables at play. Without deliberate

effort, any company’s FX trading and

risk management efforts can be badly

hindered.

TRADING VENUE POLICIES

HAVE A BIG IMPACT

By Tim Boyle, Chief Strategy Officer, Quincy Data

Policies at trading venues can

exacerbate the problem. One of the

least discussed—but most important—

factors in FX infrastructure is access.

How market data is made available to

customers—when, to whom, and under

what conditions—can have as much

impact on trading outcomes as the data

itself.

Tim Boyle

IN FX MARKETS, DATA IS THE

FUEL—AND INCREASINGLY

THE BOTTLENECK.

FX has long been relatively difficult to

navigate given how globally distributed

and highly fragmented the asset

class is. Unlike equities or futures,

which centralize around relatively few

dominant venues (often central limit

order books, or CLOBs), FX liquidity is

scattered across dozens of ECNs, bank

platforms, bilateral streams, and now

innovative cash pools like CME’s new FX

Spot+. This fragmentation creates not

only opportunity, but also operational

complexity—especially for algorithmic

trading boutiques trying to access,

integrate, and act on price signals with

consistency and speed.

The complications don’t stop there.

Operating in FX means dealing with

an extremely long list of potential

catalysts: signals from equity indices,

commodities, central bank actions,

geopolitical headlines, and much

more. An FX trading system may need

to understand the price of crude in

Singapore, interest rate futures in

Frankfurt, and S&P futures in Chicago—

all within milliseconds of each other.

When trading venues have opaque

or non-uniform access policies, that

makes it hard for firms that lack deep

pockets to do well. When some market

participants get advantaged access

to source data—whether through

preferred network arrangements,

venue-specific speed bumps, or private

order handling protocols—those

preferred customers tend to dominate

trading volume. Market participation

stagnates. While this customer

concentration is beneficial to the bestresourced

participants in the short

term, over the long haul this suppresses

innovation and prevents broad-based

liquidity formation. Markets clearly

suffer under those conditions, becoming

less efficient.

Conversely, equal, transparent access

to market data and execution venues

is an incredible enabler. It gives smaller

firms the confidence to build, deploy,

and scale strategies without needing to

own infrastructure. It creates conditions

where firms can compete on signal

quality and execution precision, not just

physical proximity or exclusive vendor

arrangements. More participants leads

to better liquidity.

This is an unequivocally good thing

for markets. (Full disclosure: Several

companies, including my own—

30 May 2025 May 2025

31

ALGOTECH

Many attempts to reduce the role of speed in trading, such as artificial speed bumps often

degrade markets

Quincy Data—can solve this problem

for customers via fast and resilient data

feeds. Our industry does the hard work

of connecting to venues and collating a

firehose of data from many geographically

disparate sources in a structured way that

any trading firm can use.)

In FX—where the number of venues

is expanding, not shrinking—ensuring

equal access to data isn’t just a policy

virtue, it’s a necessity to keep access

to this vital asset class open and

transparent to more than just the

biggest players in markets.

WHY PREFERRED ACCESS

HARMS FX

Some believe the increased pace of

trading has harmed FX (and other asset

classes). And so there have been various

attempts to slow things down. It’s

counterintuitive, but many attempts to

reduce the role of speed in trading—such

as artificial speed bumps, asymmetric

dissemination, or exclusive infrastructure

agreements—often degrade markets

by making it difficult for anyone but

the largest and best resourced firms to

participate. Here’s why:

1. Opaque rules reward the alreadyconnected

When access policies are unclear—such

as when only certain firms understand

or are technically able to exploit a

venue’s data-dissemination behavior—

it creates informational asymmetries

that disadvantage the broader market.

These advantages tend to accrue to

firms with the deepest infrastructure,

engineering teams, or privileged

exchange relationships, allowing

them to consistently extract value.

Others—lacking such access, clarity,

or the means to fairly compete—are

left operating defensively or exiting

altogether.

2. Deliberate slowdowns favor those

with private alternatives

When a venue introduces a speed bump

or deliberately slows its public feed, the

goal is often to level the playing field by

neutralizing latency advantages. But in

practice, these mechanisms can devalue

public data and increase the relative

value of private or privileged access.

The issue isn’t just private networks—

it’s advantaged private fills, selective

disclosures, and geographic disparities

in infrastructure.

For example, if a firm receives private fill

information ahead of the public print,

and the public data is then delayed by

a speed bump, that firm has a multimillisecond

head start—not because

they were faster, but because they were

first to know. Though well-intended to

try to help less agile market participants

(Banks, dealers) in highly global markets

like FX, where venues are separated

by oceans, milliseconds of divergence

are commonplace, and the effects of a

speed bump can easily be overwhelmed

by private or geographically advantaged

information channels.

Ironically, speed bumps that aim to

neutralize latency arbitrage can entrench

the very dynamics they’re meant to fix.

If not accompanied by transparent and

equitable access policies—particularly

around fill disclosure and data

dissemination—these delays may end

up benefiting firms already operating

ahead of the public signal, rather than

bringing others closer to it.

3. Lack of transport clarity limits

participation

Even if a venue offers its feed to all

participants, if the mechanisms for

delivery (e.g., physical access, routing

complexity, handoff details) are

complex or undocumented, only the

best-resourced firms can reliably access

and integrate the data. This excludes

smaller or newer firms and narrows

the field of viable participants, leading

to concentrated flow and reinforcing

feedback loops around dominant

players.

4. Favoring “anti-HFT” behavior often

favors a few firms with exclusive

deals

Even if a venue offers its feed to all

participants, if the mechanisms for

delivery (e.g., physical access, routing

complexity, handoff details) are

complex or undocumented, only the

best-resourced firms can reliably access

and integrate the data. This excludes

smaller or newer firms and narrows

the field of viable participants, leading

to concentrated flow and reinforcing

feedback loops around dominant

players.

WHAT PREVENTS THIS?

TRANSPARENT, EQUAL

INFRASTRUCTURE

The antidote to customer concentration

isn’t banning speed or regulating

away behavior. It’s ensuring equal,

transparent, and frictionless access to

core infrastructure:

• Clear data dissemination rules

• Equal opportunity to connect and

receive feeds

• No exclusivity, no preferred paths

• Normalized access for firms of all

sizes

By removing ambiguity and minimizing

architectural privilege, markets can

foster diverse, competitive ecosystems,

where new strategies can emerge, and

risk isn’t concentrated among a handful

of entities.

STORAGE AND INTEGRATION:

WHAT MAKES DATA HARD TO

USE

Algorithmic FX trading strategies rely

on accurate, timely, and complete data

across a wide range of sources. This

includes:

• Real-time pricing from multiple FX

venues

• Futures data from exchanges

• On-chain and off-chain crypto data

• Macroeconomic indicators and interasset

correlations

• Internal trade and fill data for alpha

modeling

Each of these has its own quirks:

formats, latencies, update behaviors, and

integration risks. The challenge isn’t just

getting the data; it’s aligning, storing,

and indexing it at high frequency, and

delivering it to inference systems or signal

engines with minimal drift.

Well-designed systems prioritize

deterministic latency, timestamp

consistency, and redundancy in data

flow. For machine learning models,

consistency matters even more than

sheer speed. In many cases, the most

scalable systems trade nanoseconds

of speed for microseconds of

predictability—and that trade-off is

worth it.

TECHNOLOGY TRENDS: FROM

LATENCY TO RESILIENCE

The new frontier in FX data

infrastructure isn’t just latency. It’s

resilience and scalability. The best

systems now combine:

• Geographically diverse wireless transport

• Hollow-core and 40/100/400 Gbps

The new frontier in FX data infrastructure isn’t just latency. It’s resilience and scalability

fibers for high-capacity resilient

transport

• Signal feeds that distill high-value

data into fast formats

• Smart arbitration across redundant

paths

• Precision timing and high capacity

data capture for multi-venue

synchronization

These technologies reduce dependence

on single venues, central data centers,

or exclusive carrier agreements. They

empower firms to run inference at the

edge, execute locally, and coordinate

globally in real time.

The establishment of CME’s FX Spot+

offering in Aurora illustrates this well:

New pools of liquidity demand new

connectivity models. If data transport

doesn’t scale with venue access,

fragmentation will only deepen.

WHAT TO LOOK FOR IN A

DATA PROVIDER

Trading firms looking to partner with

a trusted vendor on data should

evaluate:

• Latency and determinism, not just

one-way speed

• Path diversity and resilience

• Support for normalized formats and

structured metadata

• Transparency in update timing,

sequencing, and access

• Commitment to equal access and

customer neutrality

The goal isn’t just data. You also need

trustworthy market state, delivered at

scale, with the transparency to support

competitive growth.

CONCLUSION: EQUAL ACCESS

AS INFRASTRUCTURE

FX algo trading doesn’t run on code

alone. Data is vital too. And for data

to be useful, it has to be available,

integrated, and trusted. As markets

fragment and correlations deepen

across geographies and asset classes,

the winning data infrastructure will be

the one that delivers clean, resilient,

and equal access to market-moving

information.

Quincy Data and our peers exist

to make that data infrastructure

accessible—not just to the largest

firms, but to any participant with a

good strategy and a need for speedy

access. By combining normalized

data, low-latency global distribution,

deterministic delivery, and equal access,

Quincy and its competitors bring elite

data distribution and insight within

reach of even the smallest desks.

Equal access isn’t just a principle. It’s

a performance advantage. And it’s the

foundation for the next generation of

global FX innovation.

32 May 2025 May 2025

33

EDUCATION & TRAINING

ONE FOR THE NOTEBOOK

Coming Soon

The e-Forex and FXAlgoNews team are partnering

with the ACI Financial Markets Association to

BOOK OF THE MONTH

The Complete Guide to

Quantitative Finance and

Algorithmic Trading

Algorithmic Trading vs

Automated Trading: Are

they different?

BLOG OF THE MONTH

PODCAST OF THE MONTH

How to Become a

Quantitative Trader

Despite how difficult it is to develop a career as a

quantitative trader, the financial security and future

possibilities make the pursuit worth it.

Machine Learning

for Algo Trading

In this episode of the DATAcated podcast, host Kate

Strachnyi talks with Stefan Jansen about machine learning

for algorithmic trading.

corporatefinanceinstitute.com/resources/career/coursesquantitative-trader/

becominghuman.ai/ml-for-algorithmic-trading-with-stefanjansen-7f051fa612d6

publish a unique handbook in November this year:

This will provide market participants with a directory

of products and services from leading e-FX providers

and an overview of important developments including:

Currency market developments

• Regulatory harmonisation and increasing systematic

oversight

• Central Bank Digital Currencies: From concept to realworld

application

• Growing institutional engagement with Tokenisation,

Stablecoins & Crypto’s

• More attention becomes focused on the benefits of

FX Clearing

Execution & trade lifecycle transformation

• The arrival of hybrid models of execution utilising

mixed OTC/Listed venues

• The growing interest in FX-as-a-Service models

• Ongoing post trade FX initiatives and the move

towards T+0 settlement

• The open road ahead for FX algorithmic execution

Emerging fintech solutions

• Big Data applications in FX increasingly make their

presence felt

• DLT and Blockchain-based FX comes of age

• Innovation in cross border payment mechanisms

gathers pace

• Product development of customer, liquidity and

execution analytics

What’s on the horizon

• Gauging the transformative potential of AI in FX

• Mapping the growth of Decentralized Finance (DeFi)

• Programmable finance and its growing relevance in FX

• No code algo builders and bot marketplaces for retail

investors

For more information about the handbook please

contact: charles.jago@e-forex.net

academyflex.com/the-complete-guide-to-quantitative-finance-and-algorithmictrading

Charles Jago

Editor

charles.Jago@fxalgonews.com

+44 1736 740 130

Nicola Tavendale

News editor

nicola@ntavendale.com

+44 1736 740 130

Susan Rennie

Managing Editor

susie.rennie@fxalgonews.com

+44 1208 821 802

QUANT STRATS LONDON

14- 15th October 2025

alphaevents.com/events-quantstratsuk

Charles Harris

Advertising sales

charles.harris@fxalgonews.com

+44 1736 740 130

David Fielder

Subscriptions manager

david.fielder@fxalgonews.com

+44 1736 740 130

Tim Hendy

Digital & Web services

tim@thstudio.co.uk

+ 44 1209 217168

Matt Sanwell

Design & Origination

matt@designunltd.co.uk

+44 7515 355960

Larry Levy

Photographry

larrydlevy@gmail.com

intrinio.com/blog/algorithmic-trading-vs-automated-trading-are-they-different

Michael Best

Events manager

michael.best@fxalgonews.com

+44 1736 740 130

TRADETECH FX BARCELONA

16 - 18th September 2025

tradetechfx.wbresearch.com

SJB Media Ltd

Suite 153, 3 Edgar Buildings

George Street, Bath, BA1 2FJ

United Kingdom

Tel: + 44 (0)1208 82 18 02 (switchboard)

Tel: + 44 (0)1736 74 01 30 (Sales & editorial)

Fax: + 44 (0)1208 82 18 03

Printed by Headland Printers

Published quarterly. ISSN 2056-9750

Although every effort has been made to ensure the accuracy of the information contained in this publication the publishers can accept no liabilities for inaccuracies that may

appear. The views expressed in this publication are not necessarily those of the publisher. Please note, the publishers do not endorse or recommend any specific website featured

in this newsletter. Readers are advised to check carefully that any website offering a specific FX trading product and service complies with all required regulatory conditions and

obligations. The entire contents of FXALGONEWS are protected by copyright and all rights are reserved.

FOR THE DIARY

34 May 2025 May 2025

35

Reimagining the power

of FX Algos

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performance and add resilience to their trading workflow through:

• Sophisticated Smart Order Router

• Comprehensive liquidity access including UBS internalization

• Advanced machine-learning framework

• Robust strategies from liquidity seeking to passive execution

Find out more, search UBS FX Algo

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36 May 2025

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