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

By: Contributor(s): Material type: TextTextSeries: Optimization in insurance and finance setPublication details: London, UK : Elsevier, 2017.Description: xiv, 173 pages : illustrations ; 24 cmISBN:
  • 9781785480843 (hbk.)
Subject(s): DDC classification:
  • 332.60151 23 H649
Contents:
1. Optimization Problems -- 2. Enlargement of Filtration -- 3. Portfolio Optimization with Credit Risk -- 4. Portfolio Optimization with Information Asymmetry.
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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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 332.60151 H649 (Browse shelf(Opens below)) Available 138346
Total holds: 0

Includes bibliographical references and index.

1. Optimization Problems --
2. Enlargement of Filtration --
3. Portfolio Optimization with Credit Risk --
4. Portfolio Optimization with Information Asymmetry.

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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