A data feed in forex is the continuous stream of market information your trading platform uses to show prices, update charts, and execute orders. Behind the simple bid and ask numbers you see on screen lies a technical plumbing system that collects prices from banks, trading venues and liquidity providers, packages them into ticks and quotes, and delivers them to brokers and platforms. Understanding what a data feed is — and how different feeds can produce different prices — helps traders interpret charts, diagnose fills that look “wrong,” and design strategies that account for the realities of execution.
The basic components of a forex data feed
At its core a forex data feed delivers two types of information: current price updates and context about liquidity. Price updates arrive as ticks, the smallest unit of market movement. Each tick is a single update: a bid or ask change, or a trade that occurred. Over time those ticks build charts, fill order histories, and populate indicators.
Liquidity information is the next layer. Some feeds show only the top-of-book price (the best bid and best ask — often called Level 1). Other feeds supply multiple price levels with the volume available at each level (Level 2 or depth-of-book). Brokers combine these inputs with their own pricing rules to present the feed inside your platform and to decide how to route and execute your orders.
Where the feed comes from and why prices differ
Forex is primarily an over-the-counter market, not a single central exchange. That matters because different institutions see slightly different supplies of orders. Large banks, prime brokers, ECNs and other liquidity providers all publish quotes. A broker chooses one or more of these sources (or aggregates several) to form the feed it supplies to clients. Two practical consequences follow.
First, the same currency pair can show different prices at the same moment on different platforms. Imagine you check gold priced as XAUUSD on two platforms: one shows 1,700.00 and another shows 1,900.00. That discrepancy can stem from different liquidity contributors, instrument definitions, or whether the price is spot, synthetic or a CFD. The numbers are rarely malicious — they simply reflect different data feeds.
Second, smaller retail orders are usually filled from the broker’s available prices and internal matching. Large institutional orders may sweep several price levels from the underlying liquidity, causing slippage that looks like the market “jumped.” For example, an institutional buy of 80 million units might take liquidity at 1.08714 for 4 million, then 1.08715 for 12 million, and so on; the weighted average will be higher than the best displayed price.
Ticks, charts and historical data
Ticks are the raw updates. A tick chart plots every tick as it arrives; a one-minute candlestick is an aggregation of all ticks that fall within that minute. For backtesting and research you need historical tick or minute data. Brokers and data vendors may provide historical feeds with different fidelity: tick-by-tick, per-second, minute, hourly, or daily. Higher‑resolution historical data is more useful for scalpers and high‑frequency strategies but also larger and more expensive to store and process.
A practical example: if you backtest a scalping strategy using minute bars but your broker’s live feed supplies irregular ticks with latency and occasional bundled updates, your live results can differ substantially from the backtest. That mismatch often comes down to differences in tick timing and order execution, not the trading rules themselves.
Order books, depth and execution methods
Order book data shows queued buy and sell orders at various prices. Level 1 shows the best bid and ask; Level 2 shows several levels of bids and asks with volumes. Retail platforms sometimes expose a simplified order book; institutional systems may provide full depth. How execution works depends on the broker model.
Market makers may internalize your order and match it against their own book. ECN/STP brokers pass orders to external liquidity and may fill across several price levels when the requested volume exceeds a single level. Execution models influence spreads, requotes, partial fills and slippage. For most retail traders with small lot sizes, the broker can usually match the order immediately at a single price, but that does not guarantee the same price quoted by another venue for the same instrument.
Latency, high‑speed feeds and practical impact
Latency is the time delay between a market event at the liquidity source and your platform receiving the tick. For many retail traders latency of a few hundred milliseconds is not critical; for algorithmic or high-frequency tactics it is decisive. Providers offering ultra-low latency feeds use direct connections, co-location or microwave links to shave microseconds. Those technologies are expensive and typically relevant only to institutional players.
For everyday traders the practical consequences of latency show up as slippage (your order executed at a different price), stale ticks (a chart that briefly shows an outdated price), or missed scalping opportunities. You can reduce surprises by testing in a demo account with the same broker, or by checking execution speed and the broker’s stated execution policy.
Common execution quirks: slippage, artificial delays and gaps
Slippage occurs when the execution price differs from the quoted price at the moment of order placement. It can be positive or negative. Two common causes are market movement between order submission and execution, and the need to fill volume across multiple price levels. Brokers can also implement small intentional delays or require confirmation ticks to deter very short‑lived scalping strategies. For example, a broker might wait for two or three ticks from its liquidity provider before executing, which effectively shifts the fill to the next available price.
Gaps are abrupt price jumps, often around news releases or session opens. After a gap, brokers may wait for confirming ticks at the new level before executing orders. This practice prevents execution against an isolated or erroneous first tick, but it may result in fills farther from the pre-gap quote than a trader expects.
Choosing and using data feeds as a retail trader
Most retail traders will not subscribe to raw exchange feeds. Instead, they choose brokers or data vendors that offer reliable, timely data and transparent execution. When evaluating a broker or feed, consider practical, testable points: how close are quoted spreads to other reputable venues, how often do you see slippage, and is the historical data quality sufficient for your backtests.
If you build automated strategies, look for API access and a clearly described data format so your system can ingest ticks reliably. For discretionary traders, a stable platform with clear tick printing, realistic tick replay and reasonably consistent fills matters most. Always test a strategy in a demo account that uses the same broker feed and execution environment you intend to trade live.
Practical examples woven into the explanation
Picture a swing trader checking EURUSD on two platforms. One shows 1.1200/1.1202 and another 1.1198/1.1200. The 0.0002 difference may be due to the second platform adding commission into the displayed price, or it may aggregate quotes differently. If the trader places a market buy on the first platform and sees an execution at 1.1204, that could be slippage caused by the market moving between order submission and execution, or because the broker routed the order into a liquidity pool with slightly worse pricing for the requested size.
Imagine a scalper placing many tiny orders that “live” for fractions of a second. The broker may implement a one‑second execution delay or require two confirming ticks to prevent abusive ultra-fast strategies. The trader will notice repeated fills a few ticks away from the displayed price; this is an operational rule, often disclosed in the broker’s terms.
Finally, picture an institutional-sized market order of 80 million units. As described earlier, the order may take liquidity at several price levels: 4 million at level one, 12 million at the next, etc. The resulting weighted average execution can be materially different from the top-of-book price and is an example of legitimate market impact rather than broker misconduct.
Risks and caveats
Trading always involves risk, and data feeds introduce their own operational risks. Differences between feeds can create confusion: prices that look “wrong” may simply reflect a different source. Latency and packet loss can cause delayed or missing ticks, leading to unexpected slippage or fills. Brokers’ execution models — whether they internalize orders, pass them to an ECN, or use aggregated pricing — affect the quality of fills and transparency around how your order was matched. Gaps and major news events can produce rapid price changes that no feed can predict, and exchanges or liquidity providers can occasionally publish erroneous ticks that brokers correct before executing client orders. Always read a broker’s execution policy, test on a demo with the same feed, and recognize that past simulation results do not guarantee future performance. This is general information, not personalized advice, and trading carries the risk of loss.
How to reduce surprises from data‑feed differences
The most practical steps for a retail trader are straightforward. Use a demo account to test execution and measure slippage over time. Compare quotes across a couple of reputable platforms during normal and volatile hours so you learn how your broker’s feed behaves. If you rely on automated trading, choose a provider with documented APIs and stable tick delivery, and include execution tolerances in your code. For backtesting, use historical data that matches the granularity and source you expect to trade against. Finally, keep in mind that no feed removes market risk: good data helps you make decisions, but it does not prevent losses.
Key takeaways
- A forex data feed is the real‑time stream of ticks, bids, asks and liquidity information that powers prices and execution; different feeds can legitimately show different prices.
- Ticks and order‑book depth determine how orders are filled; large orders can sweep multiple price levels and cause slippage, while brokers’ execution models influence retail fills.
- Latency, intentional execution delays, and gaps can change the price you receive versus the price you see; test in a demo and review execution policies to understand your broker’s behavior.
- Trading carries risk; this article provides general information only and is not personalized advice.
References
- https://finansified.com/forex-market-data-feed/
- https://smartbrokersolutions.com/what-is-data-feed-forex/
- https://www.dukascopy.com/swiss/english/marketwatch/historical/
- https://dxfeed.com/market-data/fx/
- https://bookmap.com/blog/the-complete-guide-to-real-time-market-data-feeds-what-traders-need-to-know-in-2025
- https://spiderrock.net/what-is-a-market-data-feed/
- https://lime.co/news/5-things-every-trader-should-know-about-market-data-feeds-143342/
- https://www.investopedia.com/terms/h/high-speed-data-feed.asp
- https://bookmap.com/blog/exploring-market-data-feeds-types-providers-and-benefits