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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Numerical Probability | An Introduction with Applications to Finance | Gilles Pagès | Taschenbuch | Englisch | Springer | EAN 9783319902746 | Verantwortliche Person für die EU: Springer Heidelberg, Tiergartenstr. 17, 69121 Heidelberg, buchhandel-buch[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer, Berlin, Springer International Publishing, Springer, 2018
ISBN 10: 3319902741 ISBN 13: 9783319902746
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 70,00
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook provides a self-contained introduction to numerical methods in probability with a focus on applications to finance.Topics covered include the Monte Carlo simulation (including simulation of random variables, variance reduction, quasi-Monte Carlo simulation, and more recent developments such as the multilevel paradigm), stochastic optimization and approximation, discretization schemes of stochastic differential equations, as well as optimal quantization methods. The author further presents detailed applications to numerical aspects of pricing and hedging of financial derivatives, risk measures (such as value-at-risk and conditional value-at-risk), implicitation of parameters, and calibration.Aimed at graduate students and advanced undergraduate students, this book contains useful examples and over 150 exercises, making it suitable for self-study.
Lingua: Inglese
Editore: Springer, Berlin, Springer International Publishing, Springer, 2018
ISBN 10: 3319902741 ISBN 13: 9783319902746
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 64,19
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This textbook provides a self-contained introduction to numerical methods in probability with a focus on applications to finance.Topics covered include the Monte Carlo simulation (including simulation of random variables, variance reduction, quasi-Monte Carlo simulation, and more recent developments such as the multilevel paradigm), stochastic optimization and approximation, discretization schemes of stochastic differential equations, as well as optimal quantization methods. The author further presents detailed applications to numerical aspects of pricing and hedging of financial derivatives, risk measures (such as value-at-risk and conditional value-at-risk), implicitation of parameters, and calibration.Aimed at graduate students and advanced undergraduate students, this book contains useful examples and over 150 exercises, making it suitable for self-study. 579 pp. Englisch.