What is a worked example of low liquidity pairs?
A worked example is a fully numeric scenario where you assume specific liquidity conditions, costs, and execution timing, then calculate what could happen. For low liquidity pairs, the key idea is that there may be fewer active buyers and sellers at any moment, so transactions can be filled at worse prices and with more variability than your quote suggests.
To make this verifiable, we will use only hypothetical numbers (no live prices), and we will state every assumption used in the calculation.
Mechanism and definitions
Low liquidity pairs are currency pairs where trading activity is relatively thin, so the market can have:
- Wider bid–ask spreads: the difference between the buying price (ask) and selling price (bid).
- Less depth at each price level: fewer orders are available before price moves.
- More sensitivity to order flow: a modest-sized trade can move the price more.
Worked example inputs (assumptions)
- You want to buy at a moment when the market shows a bid–ask spread.
- The spread is an observation at the quote moment, but your order may execute slightly later.
- You also incur commissions/fees (modeled as a fixed percentage of notional for this example).
- You experience slippage, modeled as an extra unfavorable price move from the moment you see the quote to the moment your trade fills.
Stable mechanics vs variable conditions:
- Stable mechanics: how bid–ask spreads and slippage affect execution cost.
- Variable conditions: the actual spread at your execution time, the realized fill price, and the order-book dynamics during your order.
Evidence or example (numerical scenario)
Scenario A: “normal liquidity” reference (hypothetical)
Assumptions
- Pair price (mid): 1.2000
- Spread: 0.0001 (1 pip for many FX quotes) → bid 1.19995, ask 1.20005
- Order size: 10,000 units (notional in quote terms not specified; we model per-unit price impact)
- Slippage: 0.0 pip (you fill at the ask you saw)
- Fees: 0.10% of trade notional
- You later sell when the mid has moved to 1.2010 (a +10 pip mid move)
Calculate entry and exit prices (buy then sell)
- Entry buy price: ask = 1.20005
- Exit sell price: bid at mid 1.2010. If spread stays 0.0001, then bid = 1.20095.
Gross price gain per unit
- Gross = exit bid − entry ask = 1.20095 − 1.20005 = 0.00090
Fee estimate
- Trade notional scales the fee. In this example, we treat fees as proportional to notional and assume they reduce net results by 0.10% of notional.
- Because we are not converting notional into account currency, we report the effect conceptually: the net result becomes net ≈ gross price gain minus fees, where fees are an additional drag.
Scenario B: “low liquidity” execution (hypothetical)
Assumptions (changed to represent low liquidity)
- Pair price (mid): 1.2000
- Spread: 0.0005 (5 pips) → bid 1.19975, ask 1.20025
- Order size: same 10,000 units
- Slippage: 2 pips unfavorable from quote to fill. Model this as +0.0002 to the buy price (you effectively pay more than the ask you saw).
- Fees: same 0.10% of notional
- Later mid still moves to 1.2010, but due to thin depth you again sell at a bid consistent with spread 0.0005: bid at mid 1.2010 is 1.20075.
Calculate entry and exit prices
- Entry buy price with slippage: ask + 0.0002 = 1.20025 + 0.0002 = 1.20045
- Exit sell price: bid = 1.20075
Gross price gain per unit
- Gross = 1.20075 − 1.20045 = 0.00030
Compare scenarios
- Scenario A gross: 0.00090
- Scenario B gross: 0.00030
So, even if the mid price ends up the same in both scenarios (+10 pips from 1.2000 to 1.2010), the combination of wider spread and slippage can reduce the realized gross movement by a large fraction. Fees further reduce net results in both cases.
This is the core worked-example point: low liquidity can change the path from “what the quote shows” to “what you actually get filled at,” and that changes realized outcomes.
Limitations and risks (material failure modes)
- Spread may vary at execution time: The spread you observe can be tighter or wider than the spread during your fill.