Problems and Solutions in Mathematical Finance : Commodity and Foreign Exchange Derivatives

Mathematical finance requires the use of advanced mathematical techniques drawn from the theory of probability, stochastic processes and stochastic differential equations. These areas are generally introduced and developed at an abstract level, making it problematic when applying these techniques to practical issues in finance. Problems and Solutions in Mathematical Finance Volume I: Stochastic Calculus is the first of a four-volume set of books focusing on problems and solutions in mathematical finance. This volume introduces the reader to the basic stochastic calculus concepts required for the study of this important subject, providing a large number of worked examples which enable the reader to build the necessary foundation for more practical orientated problems in the later volumes. Through this application and by working through the numerous examples, the reader will properly understand and appreciate the fundamentals that underpin mathematical finance. Written mainly for students, industry practitioners and those involved in teaching in this field of study, Stochastic Calculus provides a valuable reference book to complement one's further understanding of mathematical finance.

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Year of publication:	2014 ; 1st ed.
Authors:	Chin, Eric
Other Persons:	Ólafsson, Sverrir (contributor) ; Nel, Dian (contributor)
Publisher:	New York : John Wiley & Sons, Incorporated
Subject:	Finanzmathematik \| Mathematical finance \| Derivat \| Derivative \| Optionspreistheorie \| Option pricing theory
Description of contents:	Description [zbmath.org]

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Extent:	1 online resource (398 pages)
Series:	Wiley finance series The Wiley Finance Ser
Type of publication:	Book / Working Paper
Language:	English
Notes:	Description based on publisher supplied metadata and other sources. Cover; Title Page; Copyright; Contents; Preface; Prologue; About the Authors; Chapter 1 General Probability Theory; 1.1 Introduction; 1.2 Problems and Solutions; 1.2.1 Probability Spaces; 1.2.2 Discrete and Continuous Random Variables; 1.2.3 Properties of Expectations; Chapter 2 Wiener Process; 2.1 Introduction; 2.2 Problems and Solutions; 2.2.1 Basic Properties; 2.2.2 Markov Property; 2.2.3 Martingale Property; 2.2.4 First Passage Time; 2.2.5 Reflection Principle; 2.2.6 Quadratic Variation; Chapter 3 Stochastic Differential Equations; 3.1 Introduction; 3.2 Problems and Solutions 3.2.1 Itō Calculus3.2.2 One-Dimensional Diffusion Process; 3.2.3 Multi-Dimensional Diffusion Process; Chapter 4 Change of Measure; 4.1 Introduction; 4.2 Problems and Solutions; 4.2.1 Martingale Representation Theorem; 4.2.2 Girsanov's Theorem; 4.2.3 Risk-Neutral Measure; Chapter 5 Poisson Process; 5.1 Introduction; 5.2 Problems and Solutions; 5.2.1 Properties of Poisson Process; 5.2.2 Jump Diffusion Process; 5.2.3 Girsanov's Theorem for Jump Processes; 5.2.4 Risk-Neutral Measure for Jump Processes; Appendix A Mathematics Formulae; Appendix B Probability Theory Formulae Appendix C Differential Equations FormulaeBibliography; Notation; Index; EULA
ISBN:	978-1-119-96607-4 ; 978-1-119-96583-1
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012600767