Optimising connectivity for low latency FX trading is challenging due to the global and fragmented nature of the FX market. Unlike equities and futures markets – which operate primarily within centralised, regulated exchanges – FX trading involves numerous liquidity providers, execution platforms, prime brokers and OTC and exchange-traded execution channels dispersed across multiple geographies.
The speed at which trades are executed can make the difference between trading profit and loss. Every different and disparate point of connection introduces potential latency, requiring FX firms to navigate complex factors such as network topology, geographic distance and data processing requirements for optimised ultra-low latency performance.
Structural challenges
Tim Carmody, chief technology officer of IPC, a global leader in trading communications technology and financial market connectivity outlines a number of factors that make the structure of the FX market particularly challenging for high speed trading firms compared to other markets:
Decentralisation: Unlike centralised markets, FX is largely an over-the-counter or OTC market where trading occurs across numerous liquidity pools and platforms. Lack of centralisation increases the complexity of order and trade routing and efficient access to liquidity.
Geographic dispersion: FX trading spans major financial hubs like New York, London, Tokyo and Singapore. Latency increases with the physical distance between these locations, requiring sophisticated network solutions to mitigate delays.
Diverse data requirements: FX trading relies on a vast array of data sources beyond traditional market data – political, economic and environmental data can influence trading decisions. Processing and integrating diverse datasets in real time adds another layer of complexity.
Another reason why optimising connectivity to achieve low latency FX trading is a complex and difficult process is that without balancing the dynamic flow between network, hardware, software and risk management, it will inevitably fall short.
As Ariel Silahian (who has built and led high performance trading systems and electronic trading solutions for investment banks, hedge funds and asset managers) observes, a fast connection means nothing if order processing lags or risk checks bottleneck the flow.
“The FX market’s decentralised nature makes it uniquely challenging for high speed trading,” he says. “Unlike centralised markets with unified order books, FX operates across many independent venues – banks, brokers, liquidity providers – each with its own pricing and trading rules.”
Systems must handle and aggregate data from multiple order books simultaneously, dealing with differences in latency, pricing and liquidity across venues. This lack of standardisation makes it difficult to create a real-time, accurate market view. The challenge lies in integrating and synchronising fragmented data sources while maintaining precise, responsive execution.
“IaaS platforms provide on-demand access to processing power, storage and bandwidth, allowing FX firms to adapt quickly to changing market conditions.”
Tim Carmody
Latency minimisation
Carmody says there are several effective strategies for minimising latency in FX trading.
“The first is efficient market access,” he says. “Establishing direct connections to liquidity providers and trading venues reduces the number of intermediaries in the end-to-end trade lifecycle, potentially minimising latency. Conversely, establishing multiple direct connections to platforms and exchanges can be time consuming, resource intensive and expensive.”
IPC is focused on removing complexity and cost from global market access. FX firms can leverage its established global trading network and technology infrastructure to connect efficiently to execution venues, liquidity providers and market participants.
“Another important strategy is proximity hosting and co-location,” adds Carmody. “Hosting trading infrastructure close to major liquidity providers or within their data centres significantly reduces physical distance and latency.”
Other recommended approaches include optimised hardware and software (leveraging hardware acceleration – for example, field programmable gate arrays or FPGAs, a type of integrated circuit that can be reprogrammed after manufacturing to meet specific needs) and low latency software stacks to ensure faster data processing and trade execution.
Private performance
“Partnering with specialist ultra-low latency data companies enables firms to process normalised market data more quickly and effectively,” says Carmody. “Using private, low latency networks instead of public internet connections ensures more deterministic performance. For public cloud destinations, IPC’s direct connect certifications with AWS, Azure and Google Cloud offer guaranteed bandwidth and reduced jitter.”
According to Silahian, reducing latency in FX trading requires more than just technical optimisation. “Co-locating servers near major trading venues and fine-tuning network performance are important, but the real edge comes from smarter strategies,” he says. “In my experience, dynamically prioritising trades so the most time-sensitive orders always get the fastest paths can be a game-changer.”
Another overlooked area is normalising and integrating data at its source to eliminate processing delays caused by fragmented systems. “One critical approach I have implemented is dynamic load balancing across all the venues involved,” adds Silahian. “By redistributing system resources in real-time, you can handle bursts of activity without compromising performance. On the risk management side, pre-emptive risk checks built into the execution layer ensure that even under pressure, trades meet compliance and client specific thresholds.”
“In my experience, dynamically prioritising trades so the most time-sensitive orders always get the fastest paths can be a game-changer.”
Ariel Silahian
For FX trading firms looking to optimise their network infrastructure for ultra-low latency, Carmody recommends a combination of hybrid connectivity, a strategic data centre presence, software-defined networking and performance monitoring and diagnostics.
“Combining public cloud elasticity for analytics with private, deterministic connectivity for core trading ensures optimal performance,” he says. “Co-locating infrastructure in data centres near major liquidity hubs minimises physical latency, while software-defined networking allows firms to dynamically optimise traffic flows and improve performance. Finally, continuous monitoring of latency metrics – combined with tools for real-time troubleshooting – ensures peak performance and rapid resolution of issues.
Optimised routing
Co-locating infrastructure in strategic data centres is essential for minimising latency. Firms can further enhance ultra-low latency networks by establishing direct cross-connects between these data centres, significantly reducing hops and latency. Additionally, deploying advanced routing protocols and real-time telemetry enables dynamic adjustments to the fastest pathways as market conditions evolve.
“One of the most effective strategies for achieving the lowest latency is leveraging FPGA-based hardware accelerators, which process packets at line speed, eliminating microseconds at critical junctures,” explains Silahian. “When combined with precise clock synchronisation across locations via GPS or PTP, systems can operate in a tightly coordinated and highly efficient manner.”
Infrastructure as a Service models (IaaS) is an appealing option for keeping costs under control, offering the flexibility to scale resources up or down during peak or quiet periods – a significant advantage in dynamic markets. Added benefits like robust disaster recovery and built-in redundancy further strengthen its appeal.
“FX funds can gain an edge with low latency execution, scalable infrastructure, AI-driven insights, automated operations and real-time risk checks, boosting efficiency, reducing costs and maximising returns,” says Silahian. “That said, it is essential to carefully evaluate providers and closely monitor usage to prevent unexpected costs and ensure the service aligns with business objectives.”
Additional benefits of the infrastructure as a service model include:
Elastic resource scaling – IaaS allows firms to scale computing resources dynamically, aligning capacity with trading volume and market conditions without upfront capital expenditures
Cost efficiency – usage-based, scalable subscription models reduce the need for significant capital investments in hardware and reduce ongoing operational costs
Advanced trading performance/data analysis tools – IaaS platforms often incorporate AI and machine learning tools, enabling firms to improve analytics and gain a competitive edge without significant in-house development
Global reach – IaaS facilitates rapid expansion into new markets, allowing firms to serve clients globally with low latency and minimal setup time
“IaaS platforms provide on-demand access to processing power, storage and bandwidth, allowing FX firms to adapt quickly to changing market conditions,” says Carmody. “This elasticity supports both temporary surges in trading volume and long-term expansion into new asset classes or geographic markets. Firms can also test and deploy new strategies faster, improving their time-to-market for innovations.”
When choosing a cloud provider for ultra-low latency trading, Silahian recommends focusing on proximity to key FX hubs like NY4 or LD4 for reduced latency and robust direct cross-connects while ensuring that the provider offers strong SLAs, redundancy and compliance with financial regulations.
Trading support
It is obviously vital for trading firms that they choose a cloud provider that can support ultra-low latency trading requirements and the firm’s overall business objectives.
Providers offering private, low-latency connections (for example, direct cloud connects) are better suited for latency-sensitive and bandwidth agnostic operations. Service providers with data centres near major liquidity hubs are critical for assuring low latency.
Firms should also evaluate service providers in line with compliance obligations like DORA for assured delivery of the highest levels of operational resilience, security and compliance and these providers must be able to demonstrate robust data encryption, segregation and monitoring to protect proprietary trading strategies.
According to Carmody, it is essential to work with providers that understand the unique demands of FX trading with respect to network connectivity, hardware and software optimisation and assured service delivery.
Migrating FX trading to the cloud brings challenges such as latency, security and cost management but also requires meticulous planning for custom software adaptation and legacy integration.
Silahian suggests that staged migrations in testing environments work best and recommends starting with databases to ensure performance compatibility with existing systems before moving to other components incrementally and finally closely monitoring progress to ensure the transition meets all objectives.
Additional challenges of migrating FX trading infrastructure to the cloud include operational disruption and compliance.
Public cloud solutions may introduce unpredictable latency, which can be addressed by adopting a hybrid model, using public cloud for non-core functions and private connectivity for trade execution.
Private security
Migrating sensitive data to the cloud introduces security risks. Firms should work with providers that meet stringent data protection standards and offer private cloud options.
“Migration can disrupt trading operations,” says Carmody. “A phased approach, with thorough testing and backup systems in place, minimises risks.
Compliance with regulations like DORA and MiFID II requires careful planning. Partnering with compliant providers ensures a smoother transition”.
“Working with providers who have specialist knowledge in networking, hardware and software optimisation is critical for FX trading firms aiming for high speed trading infrastructures,” says Silahian.
Ultra-low latency systems require precise coordination of these elements. Networking expertise ensures optimised routes and minimal hops; hardware specialists leverage cutting-edge solutions like FPGAs for faster processing, and software engineers refine algorithms to maximise efficiency.
“A provider lacking this specialised knowledge risks creating bottlenecks or inefficiencies, which can undermine a firm’s competitive edge,” he adds.
Silahian’s advice to firms who are looking to not only monitor and maintain their trading infrastructures to ensure they work at peak performance but are also looking for ways to improve them further is to maintain and improve trading infrastructure.
“It is essential to combine expertise with advanced monitoring tools,” he says. “A key lesson I have learned is that platforms that provide full operational visibility can quickly identify inefficiencies but having the expertise to act on those insights is just as critical. Regular stress testing, automated maintenance and real-time monitoring are key to ensuring both performance and resilience.”
Carmody agrees that it is crucial for FX firms to collaborate with providers who understand the nuances of high speed trading. “Specialised expertise ensures that infrastructure is optimised for ultra-low latency, deterministic performance and secure data processing,” he says. “Providers such as IPC, with direct connect capabilities and partnerships with data specialists, deliver tailored solutions that meet the rigorous demands of FX trading.”
There are a variety of options for enhancing trading infrastructures, ranging from implementing proactive monitoring, investing in upgrades and leveraging AI and machine learning to collaborating with trusted providers and conducting testing.
Anticipating issues
“We recommend using real-time analytics to continuously monitor latency, bandwidth and overall system performance,” says Carmody. “Tools that provide predictive insights can prevent issues before they occur. We would also advocate regularly evaluating and upgrading network hardware, software and connectivity options to stay competitive and using AI for predictive maintenance, anomaly detection and enhanced data analytics as well as to safeguard proprietary strategies from reverse engineering.”
Working with experienced providers that offer integrated solutions should ensure seamless connectivity, data quality and regulatory compliance.
“Finally, using elastic computing resources in hybrid or public cloud environments presents an opportunity to test new markets, products and trading strategies without jeopardising core systems,” adds Carmody.