Free lesson · Prediction strategies

Quoting revenue and adverse selection

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A market maker can earn the spread yet lose money when informed traders choose when to trade against stale quotes.

Separate round-trip spread capture from inventory revaluation. The completion of a buy and a sell at favorable prices can generate revenue, while an unfinished inventory position remains exposed to event information.

A simple expected-spread worksheet subtracts expected adverse movement and fees. It omits queue priority, cancellations and partial fills; these belong in the next execution model. Inventory limits should apply to actual holdings and live orders.

Apply it in a strategy

• Evaluate whether quoting compensation covers information risk and costs rather than counting the displayed spread.
• Record the input timestamp, executable quantity, currency and horizon. Reconcile the result with a cash-flow or state table.
• Stress this failure condition: Completed-pair selection can omit the worst stranded inventory; contemporaneous mark choice can hide adverse selection.

Research deliverable

Build and explain a quoting revenue and adverse selection worksheet. Evaluate whether quoting compensation covers information risk and costs rather than counting the displayed spread.

Evidence boundary: Synthetic arithmetic and scenarios illustrate mechanics. They are not historical returns, a paper replication, or evidence of an executable edge. Research sources and their access limitations are recorded at the end of this module.

# Python 3.10+; standard library unless NumPy is imported below.
# Inputs and outputs use the units defined in this lesson. Synthetic teaching example.
def maker_expectancy(pairs,spread,adverse,fees):
    if min(pairs,adverse,fees)<0: raise ValueError("Invalid cost inputs")
    return pairs*(spread-adverse-fees)

print(maker_expectancy(100,.04,.025,.005))