Hardcover. Stochastic optimization problems arise in decision-making problems under uncertainty, and find various applications in economics and finance. On the other hand, problems in finance have recently led to new developments in the theory of stochastic control.This volume provides a systematic treatment of stochastic optimization problems applied to finance by presenting the different existing methods: dynamic programming, viscosity solutions, backward stochastic differential equations, and martingale duality methods. The theory is discussed in the context of recent developments in this field, with complete and detailed proofs, and is illustrated by means of concrete examples from the world of finance: portfolio allocation, option hedging, real options, optimal investment, etc.This book is directed towards graduate students and researchers in mathematical finance, and will also benefit applied mathematicians interested in financial applications and practitioners wishing toknow more about the use of stochastic optimization methods in finance. This text provides a systematic treatment of stochastic optimization problems applied to finance by presenting the different existing methods: dynamic programming, viscosity solutions, backward stochastic differential equations and martingale duality methods. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Titolo: Continuous-time Stochastic Control and Optimization with Financial Applications (Hardcover)
Editore: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin
Data di pubblicazione: 2009
Lingua: Inglese
ISBN 10: 3540894993
ISBN 13: 9783540894995
Rilegatura: Hardcover
Condizione: new

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Riassunto

Stochastic optimization problems arise in decision-making problems under uncertainty, and find various applications in economics and finance. On the other hand, problems in finance have recently led to new developments in the theory of stochastic control.

This volume provides a systematic treatment of stochastic optimization problems applied to finance by presenting the different existing methods: dynamic programming, viscosity solutions, backward stochastic differential equations, and martingale duality methods. The theory is discussed in the context of recent developments in this field, with complete and detailed proofs, and is illustrated by means of concrete examples from the world of finance: portfolio allocation, option hedging, real options, optimal investment, etc.

This book is directed towards graduate students and researchers in mathematical finance, and will also benefit applied mathematicians interested in financial applications and practitioners wishing to know more about the use of stochastic optimization methods in finance.

Informazioni sull?autore

1995: PhD in applied mathematics, University Paris Dauphine

1995: Assistant Professor, University Marne-la-Vall�e

1999: Professor, University Paris 7

2006: Member Institut Universitaire de France

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