FX_Algo_News_November_2025-HighRes-PAGES

ISSUE 40 | NOVEMBER 2025 WWW.FXALGONEWS.COM FOLLOW US AT:
HSBC sees significant algo growth in Asia
TOP STORIES
HSBC has said it expects continued
uptake in adoption from Asia
participants next year as algos continue
to gain popularity in the region, with
the bank’s Asia algo volume currently
on track to be up circa 100% for this
year. According to David Ketley, HSBC’s
Head of Product, Execution and Trading,
Global FX Services, precious metals
algos have also been a key driver of
growth in 2025 for Asia. There has
also been a very strong pipeline in the
Americas, particularly in the hedge fund
sector which is expected to continue
into 2026. In addition, he forecasts
increased use of HSBC’s Basket Algo
offering as a way for institutional clients
and sophisticated corporate clients to
reduce costs and mitigate market risk,
particularly as the franchise deploys the
Basket Algo to use on multi-dealer
platforms. “With our global network,
we have also added USDBRL this
year to our list of NDFs supported
by our algo suite of products.” He
adds: “Discussing customisation
with clients has always been a key
feature of HSBC’s algo offering. In
2026, we are planning to launch the
ability for clients to define the nature
of opportunistic algo behaviours via
client-specific customisation.”
David Ketley
QB launches execution algorithms on B3
exchange
Quantitative Brokers (QB), a provider
of advanced execution algorithms for
institutional traders, has announced
the launch of its algorithmic trading
suite on Brazil’s B3 exchange. With this
expansion, institutional participants
can now access QB’s industry-proven
execution strategies, engineered
for the nuances of local market
microstructure to deliver optimal
execution quality, directly on B3’s
futures markets. “This partnership
David Kalita
with B3 and Ideal CTVM allows us to
deliver QB’s cutting-edge execution
strategies on Brazil’s leading exchange,
while further advancing our growth
in Latin America,” said David Kalita,
CEO of Quantitative Brokers. “Latin
America’s markets are dynamic and
liquid, with rapidly growing demand
for advanced tools to control trading
costs and manage market impact.
This launch marks a key milestone
in QB’s mission to deliver innovation
and measurable value to our clients
worldwide. Ideal was created with the
ambition to modernize the Brazilian
trading industry and help drive
its growth. Partnering up with an
international specialist, to bring stateof-the-art
algos for institutional clients
is another important step towards that
vision. It has been a privilege to work
with Quantitative Brokers and key
market participants on this project. We
are thrilled to help a whole new client
base gain access to B3.”, said Nilson
Monteiro, CEO of Ideal CTVM.
IN THIS ISSUE
p1: TOP STORIES
The latest industry stories
p3: NEWS FEATURES
More in depth news analysis
p4: RECENT EVENT
Tradetech FX 2025
p8: INDUSTRY VIEWS
2026 - A watershed year for FX algos?
p14: ASK A PROVIDER
Impact of liquidity on FX algo trading
p16: PRODUCT PROFILE
SIREN FX Algorithm Reference Rate
p17: EDUCATION & TRAINING
The eRisk Explainer series from HSBC
p18: REGULATORY ISSUES
FCA’s review of algo trading controls
p23: INFORMATIOn & RESOURCES
Links and websites of the month

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2 November 2025

FXSpotStream reports 127%
surge in FX algo demand
FX algo average daily volumes on FXSpotStream reached record levels for a second
consecutive month in October, with algos comprising the fastest growing other
products segment outside FX spot on the platform. Jeff Ward, CEO of FXSpotStream,
shares how the record levels of counterparties seeking to access bank algos and the
rise in volumes is the result of ongoing investment to create a true one-stop service for
the FX market.
TOP STORIES
NEWS FEATURES
Jeff Ward
Developing access to FX algos has been
a significant project for FXSpotStream in
recent years, involving notable upfront
effort in coding to every liquidity
provider on the platform. With this
infrastructure and connectivity now
built, the service is able to offer both
existing and new customers with an
efficient, cost-effective way to give algos
a try, says Ward.
The platform now enables customers to
access up to 70 bank algo strategies, he
adds. “That up-front investment is now
beginning to pay off,” Ward says. “We
have been seeing greater adoption, with
a 45 to 50% increase in the number
of counterparties or customers that
are using algos on the service over
the past 12 months. We have seen
significant growth in both algo use from
new customers on the service and we
have seen greater adoption across our
existing customers, with our volume
growth driven by those two factors.”
RISING ADOPTION
Year on year ADV has increase 127%
in algos specifically year-to-date,
making algos the fastest growing
‘other products’ segment after NDFs
on the platform, which has also seen a
notable 75% increase.
Algos recorded back-to-back record
ADV months for September and
October, following the record ADV’s
reported for April. Monthly ADV for
October in other products – swaps,
NDFs and algos – reached nearly USD
43.8 billion. In addition to record
growth in FX spot, the service has also
a 40% rise in demand of FX swaps
year-on-year.
In addition to recent volatility events
and macro shifts in the interest rate
environment, market liquidity has
also been relatively robust this year.
Ward adds: “As a fully disclosed
relationship-based trading platform,
liquidity provision is very bespoke and
customised to the customer by the
LPs, but our volumes and market share
are very much trending in the right
direction.”
ECOSYSTEM EVOLUTION
FXSpotStream’s largest customer
segments continue to be banks,
regional banks, systematic hedge
funds and institutional brokers, as
well as retail aggregator services in
Tokyo in particular. “Our customers
see market access, market impact, low
latency times and information leakage
as highly critical items,” Ward notes.
“The bilateral trading environment
where only you and your LP or LPs are
aware of that trading activity is one
of the key drivers behind the growth
in direct trading in the past five or six
years. Other models have a time and a
place for different customers, such as
ECNs or primary marketplace central
mid order books, but direct trading
has really outgrown all those other
segments.”
In particular, the systematic hedge
fund segment has been a key
focus of growth and strength for
the platform, according to Ward,
especially the multi-manager, large,
global, systematic hedge fund firms.
“They have been a driver of growth
in the FX markets broadly, but
they have also been a key segment
behind our growth in recent years.
As banks begin to move away from
dedicated workstations on their desk
to aggregators via API, this has been
another key driver for us and our core
offering.”
LOW-COST ACCESS
Investing in connectivity to banks
and their full suites of algos has also
allowed hedge funds, systematic
hedge funds as well as regional banks
to very easily, quickly and at low cost
give bank algos a try, Ward adds.
“The ability for them to do that on
FXSpotStream at very low cost, low
time to market, makes it very easy
to try algo execution,” he says. The
addition of new LPs to the service has
also included large algo providers such
as Deutsche Bank, NatWest and Bank
of New York.
November 2025
3

RECENT EVENT
TradeTech FX 2025:
A new age of FX algo use
in the spotlight
Pictures by Richard Hadley
Who should be using FX algos, when and how they can best be deployed as part of
an overall trading strategy were in focus once again at the recent TradeTech FX event
in Barcelona. Conference Chair Allan Guild, Director Hilltop Walk Consulting, reflects
on some of the key takeaways from the event and the new standards which have
emerged in the use of execution algos over the past decade.
This year’s conference featured a panel
dedicated to exploring the use of
algos, both in-house and third party,
with high level discussions about the
rising profile of algo execution and the
significant role they have established
in FX. Moderated by Stephane Malrait,
Chairman, ACI FMA, the panel featured
a mix of leading figures from both the
buy and sell sides, namely: Ralf Donner,
Head of FICC Execution Solutions,
Goldman Sachs; Sana Horrich, Head
of FX Desk, Banque de France; David
Kalita, CEO, Quantitative Brokers and
Baris Halitoglu, Trader at Nordea Asset
Management.
Looking back on the panel and the
event as a whole, Guild notes that the
conversation on FX algos has matured
significantly in recent years. Having
previously featured on an algo panel
at TradeTech in 2019, Guild explains
that the main topic at that time was
how to increase adoption of FX algos,
whereas today there is a “much better
understanding of algos and their use
cases”. “The conversation has moved
on to how buyside clients can better
manage execution risk and how as an
algo provider you can ensure they have
the tools in place to help,” he adds.
“On the panel we heard two interesting
perspectives on how to achieve this.”
According to Guild, the risk premium
on smaller trades means for many
participants, the certainty of execution
available from an RFQ will still outweigh
the pricing benefit they might get from
4 November 2025

executing an algorithm. “But for larger
transactions where there is that ability to
absorb the execution risk and average it
out over a large number of executions,
there is now a good understanding in
market that this is effectively the strong
use case for algos,” he argues.
DEMAND FOR SOPHISTICATED
TOOLSETS
In relation, Chris Churchman, Head
of Marquee at Goldman Sachs, had
unveiled a new visual structuring tool
at the Buy Side Innovation Day before
the start of the conference. On the
algo panel, Donner shared further
insights about the innovation which
aims to provide buyside traders with
a ‘cockpit view’ of what’s going on in
the market and what the predicted
performance of the algo will be. Guild
adds that effectively one of the biggest
determinations for algo performance
is “what everyone else is doing in
the market at the time that the algos
running”. “While this will always be
more expectation than certainty, with
the new tool this will be based on live
information of what the algo is going to
do against effectively the ability to pay
that risk premium in terms of an RFQ,”
he adds.
“So much of the algo conversation
comes back to that truism – that the
performance of the algo is dependent
on what everyone else is doing in the
market at the same time,” Guild says.
“This activity is providing the liquidity
that algos can then access and an
algo is not worth using without the
necessary liquidity.” The juxtaposition
between in-house and third party algos
was also highlighted by the panel,
particularly around liquidity provision.
One of the advantages of using an algo
that is provided by a major liquidity
provider is the access to that provider’s
internal liquidity pool, according to
Guild. For example, Goldman Sachs’
offering is all about the relationship
between the bank and its clients, with
the algo product and liquidity provision
being very much part of that approach,
he notes, whereas with Quantitative
Brokers, the buyside can access algos
that effectively run independently of
any particular liquidity provider. “Clients
are then guaranteed against conflicts
of interest or information leakage that
could be associated with effectively
November 2025
5

RECENT EVENT
using the algos from a from a particular
liquidity provider,” Guild says.
EXPLORING THE ROLE OF AI
“It comes down to a philosophical
question of whether algo provision
is something that is part of liquidity
provision from a particular liquidity
provider, or if it is something that is
a little bit separate to that and best
sits above the market,” adds Guild.
“In terms of what we heard from the
panel, there is not necessarily a right or
wrong answer to that.” Essentially, this
decision depends on the algo user and
whether they want to be closely aligned
to the liquidity provision that is part
of your relationship with the liquidity
provider, or if they prefer to access the
market on a quasi-anonymous basis to
access general market liquidity rather
than a particular liquidity provider’s
liquidity, he explains.
The panellists also shared their
views on whether AI can improve
algo performance, with the general
consensus being that while this is
the case, AI an also add complication
and an element of uncertainty to the
execution. “When the goal is putting
tools in your client’s hands to help them
manage the execution risk, that kind of
uncertainty in terms of outcome and
approach is not necessarily a positive
thing,” Guild explains. “The potential
benefits of AI and use of AI have to
be balanced against the need for
predictability and manageability.”
In the event in general, dialogue around
the recent drivers of change in the FX
markets appear to have also reached
a more sophisticated level, including
automation and the rise in algo usage,
which was also in evidence at the event.
The use of machine learning and Gen AI
continues to be discussed as a potential
disruptor, although according to
Guild this is still an evolution that is in
progress. “There is still some question
as to what role Gen AI can play in in FX
markets and also financial markets in
general. That is not to say there are not
potential uses in terms of optimisation
of post trade processes and various
other sort of functions around the
outside of trading, but probably for
FX execution there is less of a role for
systems that are unpredictable and
probabilistic in nature,” he concludes.
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November 2025
7

INDUSTRY VIEWS
Could 2026 Be a
Watershed Year
for Algorithmic
FX Trading?
8 November 2025

Following a rapid pace of change over the past five years, the past twelve
months have seen the FX algo space move into a new era of adoption, with
competitive differentiation and innovation remaining top of the agenda for
ongoing algo development. Looking ahead to 2026, three of the market’s
leading FX algo providers share their views on the opportunities for further
growth, technological innovation and value-add services that will continue
to fuel the adoption of algo execution among buyside clients. Nicola
Tavendale writes.
liquidity driven algos – as opposed to
prescriptive algos such as a twap, or
opportunistic strategies like a float algo.
Nicola Tavendale
To highlight the new direction that
FX algo adoption is expected to take,
Preston Mesick, Global Head of FX Algos
at Barclays, shares details of recent
developments that have been made to
the core Barclays algo suite, all of which
are product developments fuelled by
customer feedback. He adds that the
customisation concept can be applied
in two ways, either by building a
product just for a specific customer, or
by extending the product to work for
that customer and any other customers
who want it. “We have taken that
second approach,” says Mesick. “We are
listening to our customers, making sure
that we are innovating and pushing our
product offering in the exact places that
our customers need it.”
Focusing on the algo functionality
space, Barclays has recently extended
its flagship implementation shortfall
algo, Gator Adapt, to NDFs. “Given
that NDF markets are still a lot thinner
than our than our developed deliverable
counterparts, we had waited for some
maturity there,” explains Mesick. “We
found it with a combination of market
data and customer demand. Liquidity
driven algos in NDFs is a place where
we can really help to push the market
forward.” Barclays has also extended
the functionality of its Gator Adapt
and Gator Participate algos, which are
Secondly on the NDF front, Barclays
will be introducing the Barx PowerFill
NDF for take profits and stop losses.
Customers can now leave principal
orders in those currency pairs, rather
than just ‘click and dealing’. Barclays
also recently released a new vwap
algo, Mesick shares. “The vwap allows
much more liquidity and proportional
execution than just a pure, consistent
execution through twap,” he adds.
MATURING MARKET WITH
ROOM FOR GROWTH
The narrative of FX algo development
overall is more evolutionary versus
revolutionary, according to Mesick.
Looking at the stages of growth, he
believes that the market is now very
much in the maturity phase of core algo
functionality. While there are venues in
the market that are still looking at new
order types, new matching exercises or
mechanisms, from the algo perspective
Mesick says that the focus for Barclays
is now more on making incremental
changes in liquidity provision. “We’re
looking at new venues as they arise,”
he adds. “We’re also making sure that
we have our quantitative machinery in
place to validate and reshuffle liquidity
as it comes up and be dynamic with
that. The key is making sure that we are
reacting appropriately as those changes
occur, but not as a catalyst where a big
change happens, but as smooth and
incremental changes made over time.”
In addition, there are still clients that are
new to using algos, often because they
do not yet know how to fit algos into
their workflows, says Asif Razaq, Global
Head of FX Automated Client Execution
at BNP Paribas. There are also a number
of clients which are using algos on an ad
November 2025
9

INDUSTRY VIEWS
Asif Razaq
“As the buyside are
consolidating and more
firms operate multiasset
execution desks,
those with equity
experience are now
bringing the concept of
algo wheels into FX.”
hoc basis, he adds, which can easily move
from ad hoc to a more regular and then
becoming more systematic in their usage
over time. “We definitely believe there
is more growth in this market,” Razaq
says. “Much of this growth will be from
the systematic hedge fund community,
who traditionally used to write their own
algos in house but who are now actively
looking at migrating away from their inhouse
algos and using the bank algos as a
mechanism to access the market.”
ASIA IN FOCUS
The corporate community is also
currently one of the smallest community
of algo users, but that corporate client
segment is now is becoming more algo
aware and are now asking questions
around how they can use algos to
execute their order, according to
Razaq. He adds: “Existing clients that
are using algos will also increase their
market share of how they distribute
their flow versus algo paths versus non
algo paths.” Another trend is that while
Asia tends to be the smaller market in
terms of algo usage globally, there is a
new generation of traders entering the
market who are more comfortable using
technology to execute their orders.
Razaq explains that traditionally, the
relationship between the buyside and
the sales side has been based on voice
relationships, yet the newer generation
are far more open to exploring new
technology solutions.
“We are seeing volumes significantly
increase across the Asia region as more
clients look to algos as a mechanism
to trade, especially now as these
algos are becoming especially good
in managing illiquid currencies and
illiquid time zones,” says Razaq. Further
external factors that are encouraging
the buyside to make the move to
algos includes the ability to prove best
execution, which in turn is fuelling
the concept of algo wheels, he notes.
“Algo wheels are a common concept
in the world of equities. As the buyside
are consolidating and more firms
operate multi-asset execution desks,
those with equity experience are now
bringing the concept of algo wheels
into FX,” Razaq explains. “They allow
clients to distribute their flow across
various algos, across various dealers,
and then measure the performance in
a quantitative way. This awards more
flow to the bank algorithms that are
performing well, but in turn, the wheels
have a monitoring framework which is
helping to proving best execution.”
Furthermore, having seen a recent
market high watermark for algo volume
during 2025, David Ketley, HSBC’s
Head of Product, Execution and Trading,
Global FX Services notes that the bank’s
traditional client segments, including
large corporates, asset managers,
pension funds, hedge funds, are
expected to be increasing their use of
algos in 2026. “We see hedge funds
and systematic trading firms increasing
their use of our algos, specifically with
regards to our FX floating principal
order capability, which allows them to
make liquidity with our principal FX desk
algorithmically and on an anonymous
basis,” he adds. “Regional banks are
also directly using our algos or white
labelling them for their own clients.
And, with the electronification of the
metals spot market, particularly in gold
and the resulting increase in e-volumes
that we have seen this year, we believe
the trend for using our precious metals
algo is upward.”
BALANCING MANUAL AND
ALGO EXECUTION
Ketley also believes that institutional
clients and sophisticated corporate
clients will increasingly make use of
HSBC’s Basket Algo offering as a way
to reduce costs and mitigate market
risk, particularly as the bank deploys
the Basket Algo for use on multi-dealer
platforms. “With our global network,
we have also added USDBRL this year to
our list of NDFs supported by our algo
suite of products,” he adds.
FX algo development is more evolutionary versus revolutionary
Overall, Ketley highlights three
significant factors driving demand
for ongoing algo adoption into next
year. Firstly, technology, where he
notes that there is a strong correlation
between innovation and algo usage.
Secondly, liquidity fragmentation, as
algos can offer an efficient solution for
10 November 2025

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November 2025
11

INDUSTRY VIEWS
Preston Mesick
“Now clients are aiming
to get more insights
into how to best run
the algo for their
particular portfolio and
are taking a far more
scientific approach to
figuring out where they
want to show flow.”
a more fragmented market, covering
key trading venues for different types
of FX products or currency pairs and
splitting execution as appropriate. Then
finally market conditions, where during
periods of high volume and wider
spreads, the use of algos can be more
appealing to market participants.
David Ketley
“It is important to
provide clients with
transparency around
the different methods
an algo provider can
pass internal liquidity
to an algo order.”
“This is dependent on market
conditions to some extent,” he adds.
“There is a natural trend for some algo
users to favour trading on a risk price
when markets are volatile, but spreads
are relatively tight.” According to Ketley,
algo products should be viewed as part
of a wider toolset available for clients
to use according to their short-term
and long-term execution objectives.
“We would expect a natural tendency
for algo usage to increase during the
next year, as the algo market continues
to mature. An increasing range of FX
market participants are also adding algo
execution to their toolkit.”
DEVELOPMENT AND
ADOPTION
In particular Ketley predicts to see more
adoption from Asia participants next
year as algos continue to gain popularity
in the region. “Our Asia algo volume is
on track to be up circa 100% this year,”
he says. “Our precious metals algo has
also been a key driver of growth in
2025 for Asia. We’ve also enjoyed a very
strong pipeline in the Americas during
2025, particularly in the hedge fund
sector, and we expect that momentum
to continue into 2026.”
Technological advancement and
innovation are now permanent features
of the algo market, Ketley continues.
As multi-deal platforms develop the
ability to stage multiple client orders
simultaneously, he adds that HSBC
sees this as the right time to expand
the distribution of its Basket Algo, which
is currently available on the bank’s single
dealer platform, HSBC Evolve. “HSBC is
one of a select few providers who offer
a basket-style product,” adds Ketley.
In addition, discussing customisation
with clients has always been a key
feature of HSBC’s algo offering. Ketley
explains: “It is critical to have the right
combination of default features for
those clients who want to ‘plug and
play’. For an increasing number of
clients, however, that is just the start of
the process. As their trade data sample
grows, the rich real-time and posttrade
analytics that we provide will
facilitate discussions around execution
objectives and lead to the appropriate
customisations.” He shares that in
2026, HSBC is also planning to launch
the ability for clients to define the
nature of opportunistic algo behaviours
via client-specific customisation.
QUALITY RISES TO THE TOP
A further opportunity for growth next
year lies in the increasing number of
clients who are now looking at their
algo performance more closely than
they ever have in the past, according
to Mesick. “For a long time, TCA was
a check box exercise,” he adds. “Now
clients are aiming to get more insights
into how to best run the algo for their
particular portfolio and are taking a
far more scientific approach to figuring
out where they want to show flow.”
When looking at some of the more
liquid pairs, algo wheels might make
sense for some clients, yet Mesick
warns that for clients who tend to be
more idiosyncratic in their liquidity
choices, they still prefer to make more
fine-grained decisions. “These clients
are more data driven when looking at
where they want to send their order,
not just who is next up in the wheel,”
he adds. “We are doing the exact
same thing in our innovation around
algos, as well as our investment in
incremental functionality.”
Looking ahead, leading algo providers
such as Barclays will continue investing
to make ensure the performance
of systems is as robust as possible.
Machine learning has also been part
of e-trading since its founding, notes
Mesick, while AI is still more of thought
experiment, particularly in the case
of algos. “It is still early days for AI
and whether it will fundamentally
change the customer experience when
they need to execute algos.” Instead,
Mesick argues that automation is still
a major theme for a lot of customers.
“In many ways, the execution is
almost secondary to the workflow
automation,” he adds. “This is a trend
that is set to continue. We are obviously
working with our customers on that,
both on the execution side, but more
broadly within FX and markets, on
the various automation, workflow
automation products that we offer.”
For Razaq, the true differentiating
factor is now not so much about
which new algorithms a provider
brings to the market, or how well
their algo performs, but much more
focused on the toolsets that they can
12 November 2025

next year is cross asset algo execution
where providers will offer strategies
that can execute across multiple asset
classes..
Clients are also becoming increasingly sophisticated in the way in which they
evaluate algo performance
offer to algo clients. “It is much more
about the complete package of the
algo offering you make available to
a client,” he says. “The qualitative
measure is equally important as
the quantitative measure.” While
the algos still need to perform well,
Razaq argues that at the same time
clients need to assess the qualitative
measures, such as a reliable platform
that does not go down too often.
“Providers need to offer toolsets
where clients can run analysis, with
pre trade or post trade, or even real
time TCA, which is now in demand
from most clients,” he says.
AN INCREASING
RANGE OF FX MARKET
PARTICIPANTS ARE
ALSO ADDING ALGO
EXECUTION TO THEIR
TOOLKIT.
STANDING OUT FROM THE
COMPETITION
“The other big growth area is
engineering new ideas and new
solutions,” Razaq continues. “We have
built solutions where clients can trade
FX, not only in the OTC landscape, but
we also introduced hybrid execution
with EFP trading, where algo clients can
source liquidity from the OTC market,
whilst settling the trade as an FX Future.
Offering that level of innovation, that
rich toolset that can access liquidity
from multiple different paths, is going
to be a key feature of the market.”
Another key feature Razaq highlights for
Clients are also becoming increasingly
sophisticated in the way in which they
evaluate algo performance, in order
to not only demonstrate transparency
and best execution to their own
stakeholders but also to link directly into
routing decisions, according to Ketley.
He adds that venue and internalisation
performance is an example of this, as
is using third-party TCA providers to
measure execution performance. “With
increased transparency around algo
performance measured against the
execution objectives of a client, we
expect to see a more focussed approach
to the selection of strategies,” says
Ketley. “Third-party pre-trade selection
tools have certainly contributed to this
and will continue to drive innovation in
the space.”
Furthermore, Ketley believes the
market will see an increase in the
breadth of currency pairs covered by
third-party TCA providers, in order
for clients to benchmark their orders
consistently. “NDF pairs are a common
gap in this regard. We’d also welcome
initiatives to ensure data accuracy
and comparability, especially with
the advent of pre-trade tools used by
clients to make routing decisions,” he
adds. “It is important to provide clients
with transparency around the different
methods an algo provider can use to
pass internal liquidity to an algo order,
and we are likely to see more industry
competition around the use of different
types of algos executing fills from
internal inventories.”
Looking ahead to next year, Ketley
notes that the ability for clients to
make liquidity with HSBC’s FX principal
desk using its algo suite, and having
more sophisticated options available to
them, such as the Basket Algo, rather
than merely relying on standalone
algo strategies, will prove to be a key
differentiator. “A less conventional FX
algo tool for occasional use, such as
our percentage-of-volume algo, can
also provide added value for clients and
minimise market impact if it concerns
a particularly large client trade,” he
concludes.
November 2025
13

?
ASK A PROVIDER
Quality, speed, and cost of
trade execution:
What impact does liquidity have on FX algo
trading outcomes and why has it become a
key differentiator amongst providers?
With Andy Mosson, Director, HausFX and FX Execution Advisory Sales at Deutsche Bank
Andy Mosson
Why is liquidity such an important
factor to consider in the use of
FX algorithms - even superseding
execution logic at times as the
most important determinant of
performance?
During volatile periods, access to
reliable liquidity is paramount. We put
significant effort into maintaining strong
relationships with a diverse panel of
external liquidity partners to ensure
continuous access, even under stress.
Without reliable liquidity, even the most
sophisticated execution logic would
struggle to achieve optimal outcomes.
Why is offering access to clean
liquidity with depth something that
relatively few providers of FX algo
trading services are currently able to
offer?
Offering access to clean liquidity not
only requires a curated panel of external
partners it also is dependent on a diverse
and deep client franchise which few
banks have the resources to achieve.
Deutsche Bank’s ability to tap into our
franchise flow provides an edge.
How important is it that clients
understand the liquidity their FX
algo orders are interacting with and
what benefits can this transparency
deliver?
Clients are no longer satisfied with
simply using algos; they want to
understand how they work and prove
their effectiveness. This understanding
is crucial for minimizing market impact
and achieving optimal performance. This
knowledge empowers clients to make
informed decisions about algo usage
and settings, ultimately leading to better
outcomes.
In what ways can internalisation
sometimes help to improve FX algo
execution performance and how
much of a differentiator amongst
providers is this capability?
Internalisation can potentially lead to
better pricing by reducing reliance on
external liquidity sources and reduce
signalling risk. The prominence of
internalization stats within our TCA
reporting is testament to how critically
we treat this requirement in our
product set. The ability to customize
liquidity pools, including the level of
internalisation, is a differentiator, as it
caters to clients’ specific preferences
and allows for fine-tuning of execution
strategies.
We also offer a secondary internalisation
model, whereby we leverage liquidity
from other, carefully selected,
internalising LPs to supplement our
offering, which clients find very
valuable.
In what ways are some providers
leveraging their own quantitative
research to make more effective use
of liquidity for FX algo trading?
We leverage our own quantitative
research through proprietary modelling
and short-term forecasting which allows
our Algos to optimise their execution
path and timing of the underlying fills
to the benefit of our clients.
This quantitative research helps to
intelligently navigate and utilize available
liquidity, adapting to market conditions
for more effective execution.
How difficult is it for providers to
effectively manage and benchmark
various liquidity pools and is being
able to take a more data-driven
approach to this process seen as
another differentiator and strength
amongst some of them?
Managing and benchmarking liquidity
pools is challenging as you require
statistically significant samples from
similar market regimes. Our use
of automated A/B testing, which
customises the liquidity sources
and settings based on their usage
demonstrates our data-driven
approach and ultimately allows
for clients to make more informed
14 November 2025

Algo innovation is a bit like a premier league team, if you do not continually reinvest then you will drop down the rankings
decisions. This capability is seen as a
differentiator and strength, particularly
for our extensive quantitative hedge
fund client base.
Some providers are more resilient
in volatile markets than others so
how are they managing liquidity to
maintain better FX algo execution
quality during times of stress?
Our algos automatically adjust
their order placement strategies
to optimize for liquidity in certain
market conditions. The market
conditions are also modelled within
our Quick Pre Trade tool, so clients
have on demand visibility as well
as the real time TCA and execution
advisory support.
Other providers also offer access to
more diverse liquidity pools than
competitors. What benefits does this
bring and how does it facilitate more
adaptive and effective execution
strategies?
Access to more diverse liquidity pools
brings the benefit of continuous pricing,
even under stress. This diversity facilitates
more adaptive and effective execution
strategies by providing a wider range of
options for order placement and fill. For
example, Stark taps into Deutsche Bank’s
broad client franchise flow and select
liquidity sources to execute faster than
average. A broader and more diverse set
of liquidity sources allows algos to find
optimal execution opportunities across
various market conditions and order types.
More customised liquidity pools are
also starting to appear based on client
preferences. In what ways is this
flexibility helping clients to fine-tune
execution to their particular trading
style as well as improve outcomes?
Customized liquidity pools allow clients
to adapt their setup, including the
ability to increase or decrease the level
of internalized fills by currency pair and
by algo type. This flexibility helps clients
fine-tune execution by enabling them to
align the algo’s liquidity interaction with
their specific trading style, risk appetite,
and objectives. For example, some clients
might prefer higher internalization for
certain currency pairs, while others might
prioritize external liquidity for speed.
There continues to be tremendous
innovation in the algorithmic FX
trading space. As part of these
endeavours how are some providers
taking liquidity management to the
next level and looking to move ahead
of the pack in order to help achieve
even better execution performance and
trading outcomes for their clients?
The flexibility of customized liquidity pools helps clients fine-tune execution
Algo innovation is a bit like a premier
league team, if you do not continually
reinvest then you will drop down the
rankings. In an increasingly data driven
world, that performance matters more
than ever when looking to create
positive feedback loops. Innovation for
innovation’s sake however is a red herring,
it has to be led by client feedback and
help improve their user experience.
Our innovation is pretty broad, across
quantitative research, A/B testing, real
time analytics but our core driver is always
client-led enhancements.
November 2025
15

PRODUCT PROFILE
SIREN FX unveils new
approach to measuring
algo performance
Despite the increasing demand from the buyside for robust measures of algo
performance, the market continues to fall short of having a truly independent
way to ensure a fair and reliable comparison. Dr Jamie Walton, co-founder of
SIREN FX, explains the unreliability of using TWAP algos as a benchmark and how
the SIREN FX Algorithm Reference Rate (SARR) was developed as an innovative
and robust alternative.
TWAPs persist as the FX market’s
preferred choice of execution algo,
despite often being the worst choice
of algo strategy for buyside clients,
according to Walton. One reason for
the popularity of TWAPs in the market
is that they are measurable, he adds,
providing not only algo execution
but also a way to benchmark algo
performance to what the TWAP price
would have been. “Measuring FX
algorithms can be tricky. If the goal is to
hit the TWAP price, that entails trading
linearly and periodically at the same
time, which is the worst way to execute
in terms of market impact,” Walton says.
If a bank measures its own algos, there will
always be the question of whether they’re
marking their own homework
In addition, he warns that because
most passive TWAP algos are no longer
vanilla, they can easily move off their
trajectory of accumulated positions.
“Normally a trajectory of accumulated
positions is linear, but a passive TWAP
is allowed to deviate from that,”
says Walton. “If clients are then still
measuring performance with a TWAP
algo assuming that linear performance,
that measure of algo performance will
be inconsistent.”
RECOGNISING LIMITATIONS
This inconsistency is also evident in
other benchmarks used in FX, most
notably the WMR 4pm Fix, which is
essentially a five minute TWAP itself.
“Yet we know that while a TWAP is
the easiest to detect and measure, it
is also means the wider market can
detect and trade against that activity,”
Walton explains. “The limitations of
executing around the Fix have been
recognised for over a decade. It creates
this recognisable V-shape in flow, which
stems from the market being able to
read those TWAP executions that take
place during that window,” he adds.
The SIREN FX benchmark was
established following a 2018 meeting
Walton had with the Bank of England
about improving outcomes around
the Fix. This led to the development
of the benchmark as an alternative
to TWAPs, achieved by using a
different algo strategy – essentially an
implementation shortfall algo which
Dr Jamie Walton
is used in reverse, Walton explains.
“TWAP is not a great strategy to use if
you care about price,” he adds. While
not so well know in FX, in equities there
is a market-on-close (MOC) algo, which
aims to get close to the Fix but also to
reduce market impact.
The SIREN FX benchmark is based
on the same principles of calculating
the rate while also providing optimal
execution for the buyside, trading
less, reducing market impact but
still increasing as it gets close to the
Fix, according to Walton. He adds:
“It is more sophisticated than a
TWAP, which is only for executing
and has no way to target the price.”
Following FCA authorisation in 2019
many leading FX providers now allow
for execution against the SIREN FX
16 November 2025

benchmark, including Goldman Sachs
and NatWest.
OPTIMAL EXECUTION
PERFORMANCE
More recently, SIREN FX developed the
SIREN FX Algorithm Reference Rate
(SARR) using the same measurement
for the Siren benchmark to calculate
the performance of any benchmark
execution using an FX algo. This new
reference rate extends the curve to
the length of the algo window and
then calculates, using the SIREN FX
benchmark methodology, what would
be the optimal execution rate for that
algo. “The reference rate is essentially
a more advanced form of TCA
analysis for algos,” says Walton. “It
provides a new, entirely independent
way for banks and the buyside to
measure optimal execution for any
algo. This provides the market with
a more accurate and standardised
representation of algo execution
performance than can be achieved
using a TWAP.”
Standard TCA metrics will compare
the price of the child orders using
TWAP, while the new measure
compares the performance against
optimised execution, based on
optimal execution frameworks,
including the original Almgren–
Chriss model, long considered
the foundation of market impact
modelling in equities.
“If a bank measures its own algos,
there will always be the question of
whether they’re marking their own
homework. As a third party, we can
apply an established, academically
recognised model independently,”
Walton adds. “Too many buyside
firms have been missing out on the
advances in the development of
execution algos due to a reliance on
ineffective TCA. Out reference rate
provides a new innovation to the
space which can provide the market
with a far more effective measure of
algo performance.”
About the SIREN FX
Algorithm Reference Rate
SIREN FX offers a unique
approach to assess the
performance of an FX
algorithm, the SIREN FX
Algorithm Reference Rate
(SARR):
• Quant developed, the algo
reference rate leverages
the SIREN FX optimal
execution methodology and
independent market data.
• Available to clients via SIREN
FX’s API.
• Measures the
implementation shortfall -
the price difference between
the outcome of using a
proprietary algorithm and
that of the SARR.
• Independent third-party
provision, promotes greater
transparency in FX.
eFX Explainers: Algo execution
The eRisk Explainers series produced by HSBC’s Global
Markets eRisk Quant Trading desk gives deeper insights
on how the electronic FX market operates, including the
role of different venues in electronic trading, liquidity
provider selection and the use of execution algorithms in
FX markets.
Part one of the algorithmic execution explainer series
offers an introduction to algos, why they are used and
how they are parametrised, accessed and executed.
Part two of the series offers insights into the design and
construction of execution algorithms, including their
development, technical structure and access to liquidity.
EDUCATION & TRAINING
Part three of the series delves into the evalutation of algo
performance and recent developments in the algo space.
The full 3 part series can be downloaded from this page:
https://www.business.hsbc.com/en-gb/insights/marketand-regulatory-insights/efx-explainers
Disclaimer: The eRisk Explainers series is based on
information obtained from sources HSBC believes to be
reliable but which have not been independently verified.
November 2025
17

REGULATORY ISSUES
Multi-firm review of
algorithmic trading controls:
high-level observations
The FCA reviewed a sample of principal
trading firms to assess their compliance
with MiFID Regulatory Technical
Standards (RTS) 6 and identify any areas
of weakness in firms’ algorithmic control
frameworks. They also sought to identify
good practices among algorithmic
trading firms.
Algorithmic trading firms are a major
source of liquidity across a wide range
of the most actively traded markets and
asset classes. Due to their large trading
footprint and trading strategies, and by
linking fragmented markets together,
they can have a significant impact on
price formation and liquidity provision.
They are often at the forefront of
changes in market structure and the use
of technology.
However, there are inherent risks in
algorithmic trading. It is essential
that firms’ controls and key oversight
functions, including compliance and
risk management, keep pace with the
ever-increasing complexity and speed
of financial markets and technological
advancements. It is also critical that
firms consider the market conduct
implications of their algorithmic trading
activity and its impact on market
integrity.
In the FCA’s Dear CEO letter outlining
their supervisory strategy for principal
trading firms, they said that algorithmic
trading controls is a key area of
focus for this sector and that they
would undertake this review. Their
latest publication creates no new
requirements for algorithmic trading
firms and is intended to help them
comply with existing requirements.
Where the FCA uses language like
‘firms must...’ or ‘firms should...’, this is
a reference to existing requirements or
their existing supervisory expectations.
The good practices in this review are
not exhaustive. They present some
(but not all) ways in which firms might
comply with the relevant rules and
requirements. Any poor practices the
FCA outlines highlight areas where firms
should carry out further work to achieve
compliance with the requirements.
1. WHO THIS WILL INTEREST
This multi-firm review will interest
all FCA-regulated principal trading
firms engaging in algorithmic trading
activity. It will also interest all firms that
develop and/or use algorithmic trading
strategies.
2. THE FCA APPROACH
In February 2018, the FCA published a
multi-firm review of Algorithmic Trading
in Wholesale Markets. This found firms
were taking steps to reduce the risks
inherent in algorithmic trading, but
further improvement was required
in some areas. For example, the
documentation of development and
testing procedures, consideration of
conduct risks and the identification of
algorithmic trading.
The FCA’s more recent review included
10 PTFs, a combination of large,
medium and small firms, all with varying
approaches to algorithmic trading.
The FCA reviewed each firm’s most
recent RTS 6 self-assessment, validation
report and supporting documentation
to consider:
• Whether firms had addressed each
aspect of RTS 6.
• The quality of the self-assessments.
• The evidence supporting the firm’s
conclusions.
The FCA also carried out a data request
and reviewed specific areas identified
in the first stage of the work in more
detail, including through meetings with
the firms.
3. THE FCA FINDINGS
3.1. Governance
3.1.1 Self-assessment and validation
There are inherent risks in algorithmic trading
The quality of self-assessment
documents and the overall self-
18 November 2025

It is critical that firms consider the market conduct implications of their algorithmic trading activity and its impact on market integrity
assessment process have improved
since their 2018 review. Most firms
had a better understanding of
the requirements and governance
frameworks have matured. The level
of information and detail in the selfassessments
varied widely across firms.
Generally, larger firms had the most
comprehensive approach to the selfassessment,
while medium-sized and
small firms applied proportionality in
their approach.
Good practice
Some firms had their self-assessments
reviewed by external auditors. This
often resulted in recommendations and
tracked actions for firms to complete, to
further strengthen their compliance.
Room for improvement
At some firms, the FCA found more
detail was required in certain areas
of the self-assessment and identified
deficiencies needed to be addressed
more efficiently. This included out of
date policies and unclear processes
and documentation which indicated
a lack of formal governance and
accountability. In addition, key policy
documentation was not linked or
referenced in some self-assessments.
In some cases, firms did not address
certain elements of RTS 6 at all in their
self-assessments, such as IT outsourcing
and Compliance training. It is important
that firms fully assess their compliance
with the requirements of RTS 6.
3.1.2 Role of the compliance function
Firms are required to make sure that
compliance staff have at least a general
understanding of how the firm’s
algorithms operate.
Overall, technical knowledge of
algorithmic trading among compliance
staff and the level of oversight and
challenge provided by compliance
varied from firm to firm. Some firms
relied more on their risk function
to drive the RTS 6 self-assessment
process and oversight/control. In most
cases, governance structures were
proportionate to the nature, scale and
complexity of firms’ business models.
Good practice
In some firms, compliance staff had
very strong technical knowledge and
provided strong challenge to algorithmic
trading processes. Some firms had a
systematic and formalised compliance
monitoring plan that directly addressed
compliance with RTS 6.
Room for improvement
The compliance functions of some
firms did not have as strong technical
knowledge of algorithmic trading. This
meant the ability of compliance staff
to challenge trading behaviours was
limited. The compliance function in
some firms was also less involved in key
algorithmic trading processes.
3.1.3 Algorithmic inventories
Firms should maintain a comprehensive
inventory of algorithmic trading strategies
and systems. The FCA found that most
firms maintained complete algorithmic
inventories that captured the key details
of each trading algorithm.In many firms,
algorithms were created, developed
November 2025
19

REGULATORY ISSUES
In some firms, compliance staff had very strong technical knowledge and provided strong challenge to algorithmic trading processes
and deployed globally but were subject
to local (UK) control requirements and
approval processes.
Good practice
Many firms maintained a very detailed
inventory which included a qualitative
description of each algorithm’s objective,
ie its intended behaviour. There was
a clear indication of who owned and
who was approved to operate each
algorithm and the markets on which
each algorithm was used. In some cases,
the inventory also included specific risk
parameters that were applied to each
algorithm. All this information formed
part of a comprehensive algorithmic
inventory, which provided useful
management information.
Room for improvement
In some cases, the algorithmic inventory
did not specify the individuals who were
approved to operate the algorithm.
3.1.4 Deployment of algorithms
(including material changes)
It is important that firms have clear,
formalised procedures for deploying
trading algorithms and the management
of material changes to those algorithms.
The FCA found that most firms had
formalised, documented deployment
procedures, which set out clear
accountability for the development,
testing and deployment of algorithms.
They also found that most firms had a
clear and consistent definition of what
constitutes a material change.
Good practice
Some firms had robust governance
procedures for deploying algorithms.
In many cases, algorithms required
approval from a wide range of business
areas before being deployed. In cases
where an algorithm was being deployed
to a new market for the first time,
many firms carried out a much deeper
review, with elevated scrutiny applied to
the algorithm. In addition, some firms
had strong communication procedures
around algorithm deployment, making
sure that all material releases are
communicated in a timely manner to all
relevant parties.
In some firms, dialogue takes place
between the compliance function and
developers of an algorithm during
the deployment process. Significant
challenge was often provided by
the compliance function on the
functionality of the algorithm and how
it would behave on the market.
Most firms had clearly documented
the definition of a material change
to an algorithm and had formal
processes to identify those changes
consistently across the business. Many
firms provided continuous training
for relevant staff on the material
changes policy. Some firms required all
changes to algorithms, regardless of
materiality, to be approved by a Senior
Management Function (SMF). Some
firms also have processes to identify if
changes were not identified as material
changes when they should have been
(false negatives).
Room for improvement
Some firms had out of date policies,
or unclear procedures for testing and
deploying algorithms. In some cases,
firms had not clearly documented the
definition of a material change, nor
was any Management Information
(MI) provided to the board regarding
deployments.
20 November 2025

In some cases, firms that used third
party algorithms did not have a good
technical understanding of how those
algorithms were developed.
3.2. Development and testing
3.2.1 Conformance testing
Conformance testing is an important
element of algorithmic development
and approval. Firms are required to test
the conformance of their algorithms
with the system of the trading venue
or direct market access provider, as per
Article 6 of RTS 6.
The FCA found that most firms were
compliant with Article 6 of RTS 6 and
carried out the required conformance
testing. Some firms noted that
conformance testing procedures differed
significantly from venue to venue.
Good practice
Policies and procedures of some firms
clearly defined the scenarios in which
conformance testing was required.
Some firms proactively identified
upcoming algorithmic changes and
events that required conformance
testing.Some firms had robust
conformance testing procedures, in
some cases carrying out many more
tests than required by the venue.
Room for improvement
Some firms, however, had poorly
defined conformance testing
procedures. This sometimes resulted in
poor record keeping practices.
3.2.2 Simulation testing
Firms must maintain testing processes
to identify potential issues before
deployment and make sure the
algorithm behaves as intended, does
not contribute to disorderly trading
and behaves effectively under stressed
market conditions.
Many firms take a holistic approach to
preventing disorderly trading behaviour
of their algorithms. A key element is
testing algorithms in a simulated testing
environment. Along with risk controls
and continuous monitoring, it is often
an important way firms make sure
Most firms the FCA reviewed had a good understanding of their obligations under RTS 6
their algorithms do not contribute to
disorderly trading conditions.
The approaches firms took to simulation
testing varied, in particular in how
they subjected algorithms to stress.
Some firms simulated theoretical
trading scenarios, others used
historical periods of market stress,
while others used a combination of
both theoretical and observed stress
periods. Most firms, however, deployed
proprietary algorithms and carried out
simulation testing in proprietary testing
environments. However, firms who
used third-party-provided algorithms
relied on the simulation testing of their
vendor.
Good practice
It was clear that simulation testing of
algorithms was a critical element of
certain firms’ operations. Some firms
dedicated significant resources and
expertise to making sure that simulation
testing was as robust as possible
and included a wide variety of stress
scenarios. For some firms, the use of
simulation testing was not limited to
the deployment of new algorithms or
material changes. Rather, simulation
testing was a frequent procedure in
some firms.
When selecting historical market data
against which to test an algorithm,
some firms proactively selected periods
of data that contained higher levels
of stress. This helped to reduce the
risk of the algorithm behaving in an
unintended manner in a stressed
market. As new stressed market events
occurred, some firms proactively and
swiftly updated their simulated testing
data to make sure that algorithms
were tested using the most up-to-date
example of a stressed market.
Room for improvement
Simulation testing carried out by some
firms lacked sophistication or did not
appear to consider a wide range of
market scenarios. Similarly, some firms
lacked formally documented testing
policies and procedures, even though
testing was taking place. Many firms
had strong pre-trade and post-trade
controls in place on their algorithms.
However, it is important that firms
ensure that algorithms are tested
appropriately before deployment, to
make sure they do not contribute
to disorderly trading conditions and
continue to work effectively in stressed
market conditions.
In some firms, there was a focus on
operational effectiveness, and conduct
risks were more thoroughly considered
during post-trade surveillance, rather
than during testing. All firms should
continue to review their testing
techniques and ensure that conduct
risks are considered throughout the
development and testing process. It
is also essential that firms’ testing
capabilities keep pace with the everincreasing
speed and complexity of
their own algorithms, financial markets
and technological advancements
including cross-asset testing, where
relevant.
November 2025
21

REGULATORY ISSUES
3.2.3 Controlled deployment of
algorithms
Firms must have adequate processes to
make sure algorithms are deployed in an
appropriate and controlled manner.
The FCA found that firms took a
conservative approach to deploying
algorithms. Algorithms were deployed to
the live environment in a slow, phased
manner with significant scrutiny.
Good practice
Firms submitted small pilot trades to the
live environment to test the functionality
of the algorithm. These pilot trades were
heavily scrutinised to make sure the
algorithm behaved as expected.
Many firms deployed their existing
algorithms to new markets. In such
instances, even when algorithms had
been well-established and used for many
years in other markets, these algorithms
were subjected to the same level of
review and approval as newly developed
algorithms. Some firms had very robust
governance procedures surrounding
algorithmic deployment, with each stage
of deployment documented and with clear
evidence of approval by senior individuals.
Room for improvement
Some firms lacked formal documented
procedures for the deployment of
algorithms. This was often accompanied
by unclear ownership of key elements of
the algorithmic deployment process.
3.3. Risk controls
3.3.1 Pre/post-trade controls
Firms must have adequate and
robust pre/post trade controls, set
at appropriate levels, to identify and
reduce trading risks and control trading
activity. The FCA found that all firms had
adequate pre-trade controls in place.
Many firms relied on a strong suite of
pre-trade controls, in combination with
robust testing of algorithms, as part
of a holistic approach to preventing
algorithms from contributing to
disorderly trading.
Good practice
Firms had a clearly defined suite of
pre-trade controls applied to their
algorithmic trading. In most cases, these
controls were calibrated according to
the type of algorithm being used and
the asset class being traded. Many
firms carry out pre-trade controls at an
internal server level. This meant that
orders could not leave the firm’s internal
gateway if a pre-trade control was
breached.
Room for improvement
In certain cases, ownership of pre-trade
and post-trade controls was poorly
defined and not documented. Firms’
policies and procedures must clearly
define the individuals with responsibility
for managing pre-trade and post-trade
controls. In some cases, compliance
staff had a lack of oversight of pre-trade
and post-trade controls. This resulted in
certain compliance staff having a weak
understanding of the controls and how
they functioned.
It is important that all firms continuously
review their pre-trade and post-trade
controls, as well as the governance
procedures and documentation.
3.4. Market abuse surveillance
3.4.1 Surveillance systems and
governance and oversight
Firms must consider the potential
impact of their algorithmic trading on
market integrity, monitor for potential
conduct issues, and reduce market
abuse risks.
The FCA found that many firms used their
own, in-house developed surveillance
systems to identify and monitor market
abuse risks. In many cases, in-house
systems provided some additional
efficiencies for firms, as they were easier
to link to downstream systems. Firms
used their Market Abuse Risk Assessments
(MARAs) to define the scope of their
surveillance systems. All firms conducted
regular reviews of the MARA.
Good practice
Many firms had customised their
surveillance systems to the type of
trading they carried out. Some scoped
their surveillance systems to monitor
activity across different asset classes and
trading venues. Many firms had a good
awareness of the specific market abuse
risks that applied to their activities.
Market abuse alert logic calibration was
an important consideration for all firms
and was discussed regularly by relevant
internal committees.
Firms had efficient and effective
procedures for dealing with market
abuse alerts. Most firms had clear
escalation policies and formalised
governance procedures to make sure
alerts were investigated thoroughly and
the correct action taken. In some cases,
firms randomly sampled closed alerts for
additional review and challenge.
Room for improvement
In certain cases, firms had not done
enough to update or invest in their
market surveillance systems. This meant
their surveillance was not developing
commensurately with the nature,
scale and complexity of their trading
activities.Some firms did not have
formalised procedures or governance
structures around market abuse alert
investigation. This often resulted in
alerts taking longer to be investigated
and closed. In some cases, the FCA
also found that market abuse alert
investigation and closure generated
significant resourcing pressure, with a
small number of staff being responsible
for a significant volume of alerts.
4. NEXT STEPS
Most firms the FCA reviewed had
a good understanding of their
obligations under RTS 6. There was,
however, significant variation in the
sophistication of firms and their level
of compliance, even taking account
of the nature, scale and complexity
of their trading activities. The FCA
gave all reviewed firms individual
feedback. Where appropriate, it used
attestations to make sure that progress
is made to meet the requirements.
The FCA encourages PTFs engaged in
algorithmic trading to consider which
elements of its findings might help
them improve their algorithmic control
frameworks.
The FCA will continue to assess firms
algorithmic trading controls as part of
their ongoing supervisory work.
22 November 2025

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