Why latency is making colocation a strategic decision

Jeff Mezger, Vice President of Product Management at Waypoint Trading Solutions, a TNS business, explains why trading firms need to look beyond traditional data centre criteria when choosing where and how to deploy.

For many industries, colocation is a hosting decision. For trading firms, it may be something closer to a design choice embedded in the execution stack itself. Where infrastructure physically sits, how it connects to exchanges and how consistently it performs under load may help shape execution quality as much as the trading logic running on top of it.

For data centre decision-makers serving financial markets, the practical questions start with proximity, latency consistency, connectivity and how those factors trade off against cost and operational complexity.

Proximity is about predictability

One of the most obvious drivers of colocation in trading is physical distance to an exchange’s matching engine. Shorter distances and more direct network paths may help reduce the time it takes market data to reach trading systems and orders to reach the exchange. However, raw speed is only part of the story.

For latency-sensitive strategies, variability in latency can matter as much as its absolute value. A consistently fast path is often more valuable than one that is fast on average but unpredictable. This is why trading-oriented colocation facilities are typically judged less on general hosting credentials and more on network path simplicity, cross-connect quality and measurable, repeatable latency performance.

Connectivity determines what firms see and do

Execution decisions depend on market data arriving reliably and with minimal delay. Inside a colocation facility, firms typically establish direct cross-connects to exchanges, liquidity venues and market data vendors, rather than routing that traffic across the public internet or longer private circuits.

Connectivity often ends up being the deciding factor between sites. Two facilities can offer comparable power, space and cooling, yet differ sharply in exchange presence, the density of available market data feeds and how easily new cross-connects can be provisioned. For trading firms, this difference matters more than traditional facility criteria.

As firms add venues and data sources, this connectivity model must scale without introducing new latency variability. Evaluating it means looking beyond raw bandwidth to latency consistency, path predictability and the ability to prioritise critical traffic across the overall connectivity model.

In-house or outsource?

Operating global trading infrastructure independently can be expensive and operationally demanding. Colocation helps firms access established trading environments and shift much of that operational burden to a facility partner, while retaining control over their own trading systems, execution logic and data usage.

That control-versus-cost balance usually decides between deployment models:

The right choice depends on trading volume, latency sensitivity and how much operational capacity a firm wants to build in-house versus outsource.

Site selection is a trading decision

Choosing where to deploy may be the highest-stakes decision in a colocation strategy. Decision-makers typically weigh proximity to the specific exchanges or liquidity pools they trade on, the presence of counterparties and brokers, access to established market data ecosystems and regional regulatory requirements.

This is why colocation footprints tend to cluster around major financial hubs: for example, facilities positioned to serve European markets, or deployments near exchanges such as NYSE for US equities, HKEX, SGX and JPX for Asia-Pacific access, or B3 for Brazilian markets. Getting site selection wrong adds latency and may constrain market access and competitive positioning outright.

Scaling globally without starting over each time

As trading firms expand into new regions, the goal is rarely to replicate a single facility everywhere. Instead, firms often look for infrastructure models that support multi-region exchange connectivity and either centralised or distributed trading architectures, so that expansion into a new venue doesn’t mean rebuilding connectivity and data distribution from scratch.

Put simply, global growth is less about adding locations on a map and more about maintaining consistent, low-variability access to execution venues and market data as the footprint grows.

Risk controls belong close to execution

Colocation is about speed to market, but it may also help support institutional workflows like direct market access, where clients trade through a firm’s exchange membership via colocated infrastructure. In these setups, pre-trade risk checks are typically deployed within the same colocation environment, validating orders before they reach the exchange to help support both internal limits and regulatory compliance.

Combining colocated execution, centrally hosted trading logic and high-fidelity market data across regions is powerful, but it may add real operational complexity. This is often a core reason why institutions choose to lean on shared or managed colocation arrangements, rather than managing every layer independently.

The trade-offs

With a colocation strategy, decision-makers generally need to account for:

A practical rollout typically follows a similar sequence regardless of vendor: define latency and market access requirements, select venues based on trading objectives, match the deployment model (retail or managed) to internal capabilities, integrate connectivity and data feeds, and expand incrementally as trading needs evolve.

Trading strategy

For financial infrastructure decision-makers, colocation requires careful alignment between deployment location, connectivity design and operating model on the one hand, and execution requirements, regulatory footprint and growth plans on the other. Viewed in this way, colocation functions less like a hosting contract and more as an integral component of the trading strategy itself.