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Portfolio optimization with different information flow / Caroline Hillairet, Ying Jiao.

By: Hillairet, Caroline [author.]Contributor(s): Jiao, Ying [author.]Material type: Text

TextSeries: Optimization in insurance and finance setPublisher: London [England] ; Oxford [England] : ISTE Press Ltd : Elsevier Ltd, 2017Copyright date: �2017Description: 1 online resource (192 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 0081011776; 9780081011775Subject(s): Portfolio management | Investment analysis | Stocks | Investments | BUSINESS & ECONOMICS -- Finance | Stocks | Investments | Investment analysis | Portfolio managementGenre/Form: Electronic books.Additional physical formats: Print version:: Portfolio Optimization With Different Information Flow.DDC classification: 332.60151 LOC classification: HG4529.5Online resources: ScienceDirect

Contents:

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 utility3.3. 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.

Summary: 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.

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Item type	Current library	Call number	Status	Date due	Barcode
Ebooks	Mysore University Main Library		Not for loan		EBKELV773

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.

Includes bibliographical references (pages 165-173) and index.

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