What Is a Worked Example of Price Discovery?

Direct answer

A worked example of price discovery is a fully specified scenario that shows how a market price can be inferred from the observable parts of trading—mainly buy orders, sell orders, and the way trades occur when someone is willing to transact at a certain price. The key point is not the final number itself, but the transparent chain of assumptions that links inputs (orders) to an outcome (a resulting trade price and an implied “market” level).

Price discovery is the general process where the market continuously updates price based on new information and competing orders. In practice, the “price” you see is often a last trade price, a mid price, or a quote derived from the current order book—each with different meanings.

How it works: mechanics of the example

To keep this example verifiable without real-time data, we use a simplified order book.

Definitions (used in the example)

Bid: highest price someone is currently willing to buy at.
Ask: lowest price someone is currently willing to sell at.
Spread: ask minus bid.
Crossing the spread: when a buyer accepts the ask (or a seller accepts the bid), a trade occurs.

Assumptions for the worked scenario

There are only two participants for each side: market orders and limit orders.
Prices are quoted in discrete ticks (no fractional pricing).
When a trade happens, it prints at the counterparty’s quoted price.
We ignore currency-conversion complications, swaps, financing, and any jurisdictional rules.
Costs like commissions and slippage are discussed later as limitations, not added to this calculation.

Initial state (before new information)

Highest bid: 1.1000
Lowest ask: 1.1002
Spread: 0.0002

Now suppose new information arrives that changes one participant’s valuation: a buyer becomes more willing to pay.

Update (new orders appear)

A buy order is added as a market order that is immediately willing to buy at the lowest available ask.
The lowest ask remains 1.1002 at the moment of execution.

Resulting trade

A trade prints at 1.1002 because the buyer accepts the ask.

Implied price discovery step After the trade, one commonly-used “next reference” is the new best bid/ask that remains. For a simplified illustration:

The ask at 1.1002 is consumed.
The next lowest ask becomes 1.1003.
The highest bid is still 1.1000.
New spread is now 0.0003.

This is price discovery in action: as orders and willingness to trade change, quoted levels and the traded price update.

Worked evidence: a second numeric comparison

To show how assumptions change the “discovered” price, consider an alternative scenario.

Alternative assumptions

The market is thin on the ask side.
The buyer’s market order still crosses the spread.
There is no remaining sell liquidity at 1.1002 after the trade.

Using the same starting bid/ask (1.1000/1.1002):

The buyer crosses and trades at 1.1002.
Because liquidity at 1.1002 disappears, the next ask is 1.1008 (wider gap due to thin depth).
The new ask/bid becomes 1.1008/1.1000.
The spread becomes 0.0008.

What you can verify

Both scenarios produce the same first trade price (1.1002) because in both cases the buyer crosses at the available ask.
The post-trade quote differs materially because it depends on the next available orders.

So, the worked example shows a practical limitation: a single printed trade can be compatible with very different subsequent market conditions.

Relevant limitations and risks

A worked example clarifies mechanics, but several material failure modes can prevent real markets from matching the scenario:

Stale quotes and delayed execution: the bid/ask you observe may change before your order reaches the matching venue, causing trades at different prices than the simplified model assumes. 2. Hidden liquidity and depth effects: thin books can cause large jumps in quoted levels after one trade. Your “next ask” is not guaranteed. 3. Costs and execution frictions: spreads are only one component; real transactions can include commissions, financing effects, and slippage. 4. Information heterogeneity: different participants may react differently to the same information, so the direction and magnitude of price updates are not predictable from the example alone. 5.