Portfolio Optimization with Different Information Flow

__Portfolio Optimization with Different Information Flow__ recalls the stochastic tools and results concerning the stochastic optimization theory and the enlargement filtration theory.The authors apply the theory of the enlargement of filtrations and solve the optimization problem. Two main types of enlargement of filtration are discussed: initial and progressive, using tools from various fields, such as from stochastic calculus and convex analysis, optimal stochastic control and backward stochastic differential equations. This theoretical and numerical analysis is applied in different market settings to provide a good basis for the understanding of portfolio optimization with different information flow.

Portfolio Optimization with Different Information Flow recalls the stochastic tools and results concerning the stochastic optimization theory and the enlargement filtration theory.The authors apply the theory of the enlargement of filtrations and solve the optimization problem. Two main types of enlargement of filtration are discussed: initial and progressive, using tools from various fields, such as from stochastic calculus and convex analysis, optimal stochastic control and backward stochastic differential equations. This theoretical and numerical analysis is applied in different market settings to provide a good basis for the understanding of portfolio optimization with different information flow.

• Presents recent progress of stochastic portfolio optimization with exotic filtrations
• Shows you how to apply the tools of the enlargement of filtrations to resolve the optimization problem
• Uses tools from various fields from enlargement of filtration theory, stochastic calculus, convex analysis, optimal stochastic control, and backward stochastic differential equations

Front Cover -- Portfolio Optimization with Different Information Flow -- Copyright -- Contents -- Introduction -- Acknowledgments -- 1. Optimization Problems -- 1.1. Portfolio optimization problem -- 1.2. Duality approach -- 1.3. Dynamic programming principle -- 1.4. Several explicit examples -- 1.5. Brownian-Poisson filtration with general utility weights -- 2. Enlargement of Filtration -- 2.1. Conditional law and density hypothesis -- 2.2. Initial enlargement of filtration -- 2.3. Progressive enlargement of filtration -- 3. Portfolio Optimization with Credit Risk -- 3.1. Model setup -- 3.2. Direct method with the logarithmic utility -- 3.3. Optimization for standard investor: power utility -- 3.4. Decomposition method with the exponential utility -- 3.5. Optimization with insider's information -- 3.6. Numerical illustrations -- 4. Portfolio Optimization with Information Asymmetry -- 4.1. The market -- 4.2. Optimal strategies in some examples of side-information -- 4.3. Numerical illustrations -- Bibliography -- Index -- Back Cover « Portfolio Optimization with Different Information Flow recalls the stochastic tools and results concerning the stochastic optimization theory and the enlargement filtration theory. The authors apply the theory of the enlargement of filtrations and solve the optimization problem. Two main types of enlargement of filtration are discussed: initial and progressive, using tools from various fields, such as from stochastic calculus and convex analysis, optimal stochastic control and backward stochastic differential equations. This theoretical and numerical analysis is applied in different market settings to provide a good basis for the understanding of portfolio optimization with different information flow. »-- Résumé de l'éditeur Portfolio Optimization with Different Information Flow recalls the stochastic tools and results concerning the stochastic optimization theory and the enlargement filtration theory. The authors apply the theory of the enlargement of filtrations and solve the optimization problem. Two main types of enlargement of filtration are discussed: initial and progressive, using tools from various fields, such as from stochastic calculus and convex analysis, optimal stochastic control and backward stochastic differential equations. This theoretical and numerical analysis is applied in different market settings to provide a good basis for the understanding of portfolio optimization with different information flow.-- Provided by Publisher Content: Front matter,Copyright,IntroductionEntitled to full text1 - Optimization Problems, Pages 1-44 2 - Enlargement of Filtration, Pages 45-70 3 - Portfolio Optimization with Credit Risk, Pages 71-139 4 - Portfolio Optimization with Information Asymmetry, Pages 141-163 Bibliography, Pages 165-173 Index, Page 175