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Stochastic Finance - An Introduction in Discrete Time

English · Hardback

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This book is an introduction to financial mathematics. It is intended for graduate students in mathematics and for researchers working in academia and industry.
The focus on stochastic models in discrete time has two immediate benefits. First, the probabilistic machinery is simpler, and one can discuss right away some of the key problems in the theory of pricing and hedging of financial derivatives. Second, the paradigm of a complete financial market, where all derivatives admit a perfect hedge, becomes the exception rather than the rule. Thus, the need to confront the intrinsic risks arising from market incomleteness appears at a very early stage.
The first part of the book contains a study of a simple one-period model, which also serves as a building block for later developments. Topics include the characterization of arbitrage-free markets, preferences on asset profiles, an introduction to equilibrium analysis, and monetary measures of financial risk.
In the second part, the idea of dynamic hedging of contingent claims is developed in a multiperiod framework. Topics include martingale measures, pricing formulas for derivatives, American options, superhedging, and hedging strategies with minimal shortfall risk.
This third revised and extended edition now contains more than one hundred exercises. It also includes new material on risk measures and the related issue of model uncertainty, in particular a new chapter on dynamic risk measures and new sections on robust utility maximization and on efficient hedging with convex risk measures.

About the author










Hans Föllmer, Humboldt-Universität zu Berlin; Alexander Schied, Universität Mannheim.

Product details

Authors Hans Föllmer, Alexander Schied
Publisher De Gruyter
 
Languages English
Product format Hardback
Released 01.02.2011
 
EAN 9783110218046
ISBN 978-3-11-021804-6
No. of pages 544
Weight 938 g
Illustrations 14 b/w ill.
Series De Gruyter Textbook
Gruyter Textbook
Graduate
De Gruyter Textbook
Graduate
Subject Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics

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