We describe a bottom-up framework, based on the identification of appropriate
order parameters and determination of phase diagrams, for understanding
progressively refined agent-based models and simulations of financial markets.
We illustrate this framework by starting with a deterministic toy model,
whereby $N$ independent traders buy and sell $M$ stocks through an order book
that acts as a clearing house. The price of a stock increases whenever it is
bought and decreases whenever it is sold. Price changes are updated by the
order book before the next transaction takes place.