Data Quality, Latency, and Reliability — Why It Matters market data latency
Latency in market data refers to the time between an event occurring on an exchange — a trade executing, a price changing — and that event appearing in a trading system. It accumulates across every step in the chain: data capture at the exchange, transmission to the vendor, processing, and delivery to the end user. Each step adds delay, and the total determines how current the data actually is by the time a decision is based on it.
How latency is measured and why the numbers vary
Latency is measured in milliseconds (ms) for most trading applications and in microseconds (µs) for high-frequency systems where sub-millisecond differences matter. The figure cited by a data provider typically refers to the time between data leaving the exchange and arriving at the vendor's distribution point — not the time it takes to reach your system. Network distance, processing load, and delivery method all add to that number on the receiving end.
The main variables are delivery method and physical distance. Push-based feeds — where data is sent to subscribers as events occur — have lower latency than pull-based APIs, where the client must request an update and wait for a response. Co-location, placing trading infrastructure in the same data centre as the exchange servers, eliminates most network transmission time and is used by firms where microseconds are commercially significant.
For the majority of active traders, the relevant latency range is tens to hundreds of milliseconds. At this scale, the difference between a 20 ms and a 150 ms feed matters for intraday decisions but not for swing trading or longer-horizon strategies. Understanding which range your strategy operates in determines how much latency should influence your feed selection.
Data quality issues in real-time feeds
Low latency and high data quality are separate properties. A feed can be fast and inaccurate. The most common quality problems in real-time market data are the following.
Data anomalies are price spikes or volume figures that do not reflect actual market activity. They occur when erroneous prints reach the feed before being corrected by the exchange. Trading algorithms that consume raw, unfiltered data without anomaly detection can act on these figures before the correction arrives.
Incomplete data means gaps in the tick stream — missing trades, missing quote updates, or sessions where the feed was interrupted. A backtest built on data with gaps produces results that do not match what would have happened in live trading. For tick data used in order flow analysis, completeness is especially important: a missing trade changes the bid/ask volume balance and therefore the signal.
Inconsistent timestamps occur when data from multiple sources or exchange segments carries timestamps in different time zones or with different precision. Strategies that correlate data across markets rely on timestamps being comparable; if they are not, the correlations are noise.
Reliability: redundancy and consistency
A reliable data feed delivers data when the market is open, including during high-volatility periods when data volumes spike and systems are under greatest load. Reliability has two components.
Redundancy means that if one delivery path or server fails, another takes over without interruption. Professional data providers maintain multiple distribution points in separate locations. A provider that routes data through a single point of presence has a single point of failure.
Consistency means that all connected systems receive the same data at the same time. Where latency differences between recipients exist — which they always do to some degree — the provider should document them. Undocumented latency differences between users of the same feed create conditions where some participants are systematically acting on fresher data than others.
High-frequency trading: a different latency requirement
High-frequency trading firms operate in a latency regime where most market participants do not compete. Strategies that hold positions for seconds or less, arbitrage price differences across venues, or provide liquidity through market-making require sub-millisecond data delivery. These firms invest in co-location, FPGA-based data processing, and direct exchange connections precisely because their profitability depends on receiving data before other participants do.
For traders not operating in this category — intraday, swing, or algorithmic traders whose strategies do not depend on microsecond timing — the HFT infrastructure discussion is largely irrelevant. The latency requirements for a futures trader running a trend-following strategy on 1-minute bars are satisfied by a standard professional feed without co-location.
Regulators in multiple jurisdictions have addressed HFT practices including order-to-trade ratios, market access rules, and co-location fee transparency. MiFID II in Europe is the most comprehensive framework currently in place.
Reducing latency for standard trading applications
For most traders, meaningful latency reduction comes from three areas.
Delivery method: switching from a REST polling API to a WebSocket or push-based feed eliminates the round-trip time of each request. This is the largest single improvement available to most users without changing infrastructure.
Network routing: connecting to a data provider with servers close to your location reduces physical transmission time. If your trading infrastructure is in Frankfurt, a European data centre provides lower latency than one in New York for European exchange data.
Software processing: inefficiencies in how data is parsed and acted on after delivery can add as much latency as the network itself. This is a code and infrastructure problem, not a data feed problem — but it contributes to the total time between market event and trading decision.
TAI-PAN data feeds
TAI-PAN, provided by Lenz + Partner — part of the Infront Group — delivers market data via push technology, covering equities, futures, forex, indices, and commodities. The feed is suitable for active intraday trading, order flow analysis, and algorithmic strategies that do not require sub-millisecond HFT infrastructure. A 30-day trial is available for €1.
