Trading execution algorithms manage how an order is submitted and filled. Their task can include dividing an order, choosing when to submit each part and adjusting to available liquidity. They are different from the research that decides whether the trade should exist.
The problem they solve
The price visible when a decision is made is not necessarily the price available for the whole order. Trading immediately may consume liquidity. Waiting may expose the unfinished order to an adverse market move. An execution algorithm manages this trade-off; it cannot make it disappear.
TWAP uses a time-based objective, while VWAP refers to a volume-weighted benchmark. More adaptive designs can incorporate market-state information. These are execution concepts, not proof that any one method always produces the lowest cost.
How should execution be evaluated?
A useful comparison considers the average fill price, fees, completion rate and price movement during execution. Looking only at the most favourable individual fill can hide the cost of the remaining order.
AlphaNet’s architecture treats execution as a separate part of the quantitative stack, connecting an order objective to market conditions.
This separation makes responsibility clearer: a strong execution process can help preserve an edge, but it cannot turn an unsupported trade idea into a reliable strategy.