Execution algorithms

Dump a large order at once and impact destroys your price; trade it slowly and you’re exposed to risk. Execution algorithms exist to manage exactly that trade-off.

The schedules a desk actually ships. TWAP spreads evenly over time; VWAP matches the volume curve; POV trades a fixed fraction of volume. Each is both a benchmark and an algorithm you’re measured against.

One instrument, many venues: a router decides where each child order goes to get the best price net of fees, latency and fill probability. The defensive twin of latency arbitrage.

A predictable schedule is a target: if others can guess your VWAP curve, they trade ahead of it. Randomising and adapting the schedule is the counter-game.

The canonical optimal-execution model (2000): liquidating a position is a trade-off between market impact (trade fast) and timing risk (trade slow). Minimising a mean-variance cost yields the optimal trajectory; risk aversion sets where on the frontier you sit.