This book is an introduction to optimal stochastic control for continuous time Markov processes and the theory of viscosity solutions. It covers dynamic programming for deterministic optimal control problems, as well as to the corresponding theory of viscosity solutions. New chapters in this second edition introduce the role of stochastic optimal control in portfolio optimization and in pricing derivatives in incomplete markets and two-controller, zero-sum differential games.

Recent revolutions in the world of finance have created a need for the expertise of research mathematicians in solving problems. The articles in this volume are based on recent research in methods in mathematical finance.

Recent revolutions in the world of finance have created a need for the expertise of research mathematicians in solving problems. The articles in this volume are based on recent research in methods in mathematical finance.

This book is an introduction to optimal stochastic control for continuous time Markov processes and the theory of viscosity solutions. It covers dynamic programming for deterministic optimal control problems, as well as to the corresponding theory of viscosity solutions. New chapters in this second edition introduce the role of stochastic optimal control in portfolio optimization and in pricing derivatives in incomplete markets and two-controller, zero-sum differential games.

This book may be regarded as consisting of two parts. In Chapters I-IV we pre- sent what we regard as essential topics in an introduction to deterministic optimal control theory. This material has been used by the authors for one semester graduate-level courses at Brown University and the University of Kentucky. The simplest problem in calculus of variations is taken as the point of departure, in Chapter I. Chapters II, III, and IV deal with necessary conditions for an opti- mum, existence and regularity theorems for optimal controls, and the method of dynamic programming. The beginning...