  This paper uses the development of multi-agent market models to present a
unified approach to the joint questions of how financial market movements may
be simulated, predicted, and hedged against. We examine the effect of different
market clearing mechanisms and show that an out-of-equilibrium clearing process
leads to dynamics that closely resemble real financial movements. We then show
that replacing the `synthetic' price history used by these simulations with
data taken from real financial time-series leads to the remarkable result that
the agents can collectively learn to identify moments in the market where
profit is attainable. We then employ the formalism of Bouchaud and Sornette in
conjunction with agent based models to show that in general risk cannot be
eliminated from trading with these models. We also show that, in the presence
of transaction costs, the risk of option writing is greatly increased. This
risk, and the costs, can however be reduced through the use of a delta-hedging
strategy with modified, time-dependent volatility structure.
