Contents:

Summary: 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.
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 Calculus -- 3.2.2 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 Formulae -- Bibliography -- Notation -- Index -- EULA.

Item type | Current library | Call number | Status | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|

Ebrary | Afghanistan | Available | EBKAF-N000155 | |||

Ebrary | Algeria | Available | ||||

Ebrary | Cyprus | Available | ||||

Ebrary | Egypt | Available | ||||

Ebrary | Libya | Available | ||||

Ebrary | Morocco | Available | ||||

Ebrary | Nepal | Available | EBKNP-N000155 | |||

Ebrary |
Sudan
Access a wide range of magazines and books using Pressreader and Ebook central. |
Available | ||||

Ebrary | Tunisia | Available |

Total holds: 0

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 Calculus -- 3.2.2 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 Formulae -- Bibliography -- Notation -- Index -- EULA.

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.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2019. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

There are no comments on this title.