What is a worked example of Liquidity Providers?

Explore What is a worked: mechanics, differences, limitations, and practical checks.

Liquidity providers: definition and what “worked example” means

Liquidity providers are entities that help ensure there is buy-side and sell-side interest in a market. In practice, this support shows up as the presence of quotes and the ability to execute trades when there is an order flow. A “worked example” is a fully transparent scenario where you set numeric inputs (prices, sizes, costs) and compute step by step, stating every assumption.

How the mechanics work in a simple scenario

To keep this self-contained and verifiable, assume a basic spot FX situation with two sides: a market participant who submits an order and counterparties that can transact at available quotes.

Assumptions for the worked example:

  1. There is an indicative mid price of 1.10000.
  2. The quoted bid/ask spread at the moment of execution is 20 “pips” wide, meaning bid = 1.09990 and ask = 1.10010.
  3. A buyer wants to buy 100,000 units of the base currency.
  4. Execution is assumed to fill at the current ask for the full size (no partial fill and no slippage). This is a simplifying assumption.
  5. We also include a flat transaction cost of 2 “pips” worth of cost, representing any combination of fees or additional execution costs. This is an assumption for illustration.

For a buy order, the gross execution price is the ask: 1.10010. The cost in price terms is:

  • Spread cost versus mid: (1.10010 − 1.10000) = 0.00010
  • Flat transaction cost versus mid (modeled as 2 pips): 0.00020

So the effective price impact relative to mid is 0.00010 + 0.00020 = 0.00030. The effective execution price is therefore:

  • Effective price = 1.10000 + 0.00030 = 1.10030

If you want the same scenario stated as a currency amount, assume the quote is USD per 1 unit of the base currency and base is 100,000 units. Then the “paid amount” relative to mid is:

  • 100,000 × 0.00030 = 30 USD

Worked example compared to variable conditions (same inputs, different outcome)

Now keep the same initial numbers (mid 1.10000, indicative spread 20 pips) but change one assumption: allow slippage due to market movement or depth limits.

Assumptions for the second scenario:

  1. The buyer still wants 100,000 units.
  2. Instead of filling at 1.10010, the order fills at a worse ask because liquidity updates while the order waits.
  3. The worse fill ask becomes 1.10020.
  4. The flat 2-pip transaction cost remains 0.00020.

Compute the effective price impact:

  • Spread versus mid becomes (1.10020 − 1.10000) = 0.00020
  • Plus flat cost 0.00020
  • Total impact = 0.00040

Effective execution price becomes 1.10040, and the “paid amount” relative to mid is:

  • 100,000 × 0.00040 = 40 USD

Material difference: even with the same initial spread concept, the effective cost increases because execution quality changed.

Limitations and risks: what a worked example cannot guarantee

  1. Quotes are time-sensitive: the bid/ask you assume may not be the bid/ask you actually execute at.
  2. Liquidity is not uniform: available liquidity can vary by time, size, and instrument, which can create partial fills or slippage.
  3. Costs are model-dependent: the “2 pips” flat fee is an illustration. Real costs may be nonlinear, include different fee components, or depend on execution venue and policy.
  4. Counterparty behavior can differ: liquidity provision may change as risk limits, internal demand, or market volatility shift.

A failure mode for the buyer in the example is delayed execution leading to worse-than-expected price, turning an “assumed spread cost” into a larger effective cost. Another failure mode is assuming full-size fills at one quote level when real execution may occur across multiple updates.

How to verify understanding independently

To independently verify relevant facts, focus on three checks:

  • Definition check: confirm what “liquidity provider” means in your reference material (general role versus specific entity behavior).
  • Math check: repeat the calculations using your own stated assumptions (mid, bid/ask, order size, and modeled costs).
  • Evidence check: compare modeled execution with transaction records (executed price, fees, and timestamps). Historical relationships or typical spreads do not imply future execution quality.
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