Portfolio Optimization with Different Information Flow - Hillairet, Caroline;Jiao, Ying
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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…mehr

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Produktbeschreibung
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.
Autorenporträt
Caroline Hillairet is a Professor at ENSAE ParisTech, University Paris Saclay, CREST in France, where she is in charge of the actuarial science program. Her research interests include information asymmetry and enlargement of filtrations, portfolio optimization, credit risk, and the financial issues of longevity risk.

Ying Jiao is a Professor at University of Lyon in France. Her research interests include mathematical finance, the general theory of processes and enlargement of filtrations, and Stein's method.