Curriculum/optimal-execution

Optimal Execution

market microstructure·L2 · idiom·stub

Replacesthe belief that 'execute over the day' is enough.

Optimal execution chooses a trading schedule that minimises expected cost (impact) plus a risk premium (variance of execution shortfall). Almgren-Chriss 2000 gives a closed-form schedule under linear impact + mean-variance utility; the dynamic version (Bellman) handles state-dependent urgency. TWAP, VWAP, POV, and IS are special cases.

Prerequisites

Unlocks—

Bridges

avellaneda-stoikov-market-makingshared mechanism
Avellaneda-Stoikov 2008 is the inverse problem: not optimal *execution* but optimal *quoting* under inventory risk. The HJB equation is the same shape — both decisions trade off expected gain against inventory variance.
garch-urgency-couplingshared failure mode
Almgren-Chriss's risk-aversion parameter assumes constant volatility. Coupling Stage 3's GARCH vol estimate into the urgency knob (cross-pillar bridge #1 in ROADMAP) makes execution adaptive — trade faster in calm, slower in stress.

Status

This concept is a node in the curriculum DAG. The full lab — page blocks, done state, references — has not been authored yet. The relations above describe where it sits in the graph.

Author at: content/concepts/optimal-execution/card.ts