Given a European derivative security with an arbitrary payoff function and
a corresponding set of underlying securities on which the derivative securi
ty is based. we solve the optimal-replication problem: Find a self-financin
g dynamic portfolio strategy-involving only the underlying securities-that
most closely approximates the payoff function at maturity. By applying stoc
hastic dynamic programming to the minimization of a mean-squared error loss
function under Markov-state dynamics. we derive recursive expressions for
the optimal-replication strategy that are readily implemented in practice.
The approximation error or "epsilon" of the optimal-replication strategy is
also given recursively and may be used to quantify the "degree" of market
incompleteness. To investigate the practical significance of these epsilon
-arbitrage strategies, we consider several numerical examples, including pa
th-dependent options and options on assets with stochastic volatility and j
umps.