Direct answer
Spread by pair can behave differently when the underlying currency market is less liquid, more volatile, or structurally more expensive to quote and execute. In practice, this means that the same broker or platform can show wider or more variable costs for some currency pairs than for others, depending on time, market activity, and trading frictions. This explanation is about conditional behaviour, not forecasting.
Mechanism or definition
“Spread by pair” is the typical difference between the quoted buy price and sell price for a specific currency pair. A key point is that this spread is influenced by factors that are partly stable (how the pair tends to trade, how deep the market usually is) and partly variable (how active liquidity is right now, how much risk a market maker must carry).
To reason about conditions, separate three layers:
- Market liquidity: how many orders are available near the current price and how easily they can be matched.
- Market volatility: how quickly prices move and how uncertain the next quote is.
- Trading friction and execution: how costs show up in your actual fills, including commissions or slippage, which can differ from simple “displayed spread.”
When liquidity thins and volatility rises, market makers generally need a wider buffer to manage the risk of quoting. That buffer can show up as a different spread-by-pair profile.
Evidence or example (with clear assumptions)
Assumption for examples: no real-time data is used, and you are comparing generic conditions, not predicting exact numbers.
-
Example 1: Low-liquidity hours vs active hours If one currency pair usually trades with deeper liquidity and another is commonly quoted with thinner liquidity, then during quieter hours the thinner pair can experience a larger proportional increase in spread. The behaviour is conditional: widening is more likely where the market cannot replenish orders quickly.
-
Example 2: Higher volatility during scheduled news windows During periods when macro expectations change rapidly (for example, around major economic announcements), short-term uncertainty increases. Pairs most sensitive to changing expectations can show stronger spread widening because quoting risk rises.
-
Example 3: Stress and one-direction order imbalance If many participants trade in one direction, the order book near the current price may thin on the opposite side. That can make the next executable prices less favourable, which can appear as a spread-by-pair difference even if the displayed quote changes only briefly.
These examples show why the behaviour can differ by pair across conditions, but they do not establish future results.
Limitations and risks
- Published spreads vs realized costs: What you see as “spread” may not equal what you ultimately pay. Execution timing, market movement between quote and fill, and additional fees can alter realized costs.
- Provider methodology differences: Different platforms or data feeds may measure or display spreads differently (for example, averages versus snapshots). Comparisons across sources may not be perfectly aligned.
- Historical patterns are not predictive: Even if a pair typically widens in certain conditions, that relationship can change with liquidity regimes and market structure.
- Failure mode—misattribution: A user might attribute higher costs to the pair alone, while the driver is actually volatility, event timing, or execution quality.
Verification or next question
To independently verify the relevant facts without relying on predictions, collect consistent observations of spread-by-pair across multiple market conditions you can define (for example, active vs quiet trading windows, or pre-event vs event periods). Then check whether differences correlate more strongly with liquidity or volatility proxies than with the pair name alone.
If you want, the next useful question is: what data is needed to assess spread by pair in a way that makes the comparisons fair?