Stochastic Optimization Models in Finance (Economic theory and mathematical economics)

The Stochastic Optimization Models in Finance book is a comprehensive guide to understanding and applying stochastic optimization models in financial analysis.

With an emphasis on real-world applications, this book covers five key themes: mathematical tools, qualitative economic results, static portfolio selection models, dynamic models that are reducible to static models, and dynamic models.

The author provides a detailed overview of expected utility theory, convexity, and Kuhn-Tucker conditions, followed by an analysis of dynamic programming, stochastic dominance, and measures of risk aversion.

Additionally, the book covers separation theorems, existence and diversification of optimal portfolio policies, effects of taxes on risk taking, two-period consumption models, and portfolio revision.

The author also describes models of optimal capital accumulation and portfolio selection.

This book is an essential resource for mathematicians, economists, and anyone interested in economic theory and mathematical economics.