An Introduction to Mathematical Finance with Applications: Understanding and Building Financial Intuition
This textbook aims to fill the gap between those that offer a theoretical treatment without many applications and those that present and apply formulas without appropriately deriving them. The balance achieved will give readers a fundamental understanding of key financial ideas and tools that form the basis for building realistic models, including those that may become proprietary. Numerous carefully chosen examples and exercises reinforce the student’s conceptual understanding and facility with applications. The exercises are divided into conceptual, application-based, and theoretical problems, which probe the material deeper.

The book is aimed toward advanced undergraduates and first-year graduate students who are new to finance or want a more rigorous treatment of the mathematical models used within. While no background in finance is assumed, prerequisite math courses include multivariable calculus, probability, and linear algebra. The authors introduce additional mathematical tools as needed. The entire textbook is appropriate for a single year-long course on introductory mathematical finance. The self-contained design of the text allows for instructor flexibility in topics courses and those focusing on financial derivatives. Moreover, the text is useful for mathematicians, physicists, and engineers who want to learn finance via an approach that builds their financial intuition and is explicit about model building, as well as business school students who want a treatment of finance that is deeper but not overly theoretical.

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An Introduction to Mathematical Finance with Applications: Understanding and Building Financial Intuition
This textbook aims to fill the gap between those that offer a theoretical treatment without many applications and those that present and apply formulas without appropriately deriving them. The balance achieved will give readers a fundamental understanding of key financial ideas and tools that form the basis for building realistic models, including those that may become proprietary. Numerous carefully chosen examples and exercises reinforce the student’s conceptual understanding and facility with applications. The exercises are divided into conceptual, application-based, and theoretical problems, which probe the material deeper.

The book is aimed toward advanced undergraduates and first-year graduate students who are new to finance or want a more rigorous treatment of the mathematical models used within. While no background in finance is assumed, prerequisite math courses include multivariable calculus, probability, and linear algebra. The authors introduce additional mathematical tools as needed. The entire textbook is appropriate for a single year-long course on introductory mathematical finance. The self-contained design of the text allows for instructor flexibility in topics courses and those focusing on financial derivatives. Moreover, the text is useful for mathematicians, physicists, and engineers who want to learn finance via an approach that builds their financial intuition and is explicit about model building, as well as business school students who want a treatment of finance that is deeper but not overly theoretical.

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An Introduction to Mathematical Finance with Applications: Understanding and Building Financial Intuition

An Introduction to Mathematical Finance with Applications: Understanding and Building Financial Intuition

An Introduction to Mathematical Finance with Applications: Understanding and Building Financial Intuition

An Introduction to Mathematical Finance with Applications: Understanding and Building Financial Intuition

Overview

This textbook aims to fill the gap between those that offer a theoretical treatment without many applications and those that present and apply formulas without appropriately deriving them. The balance achieved will give readers a fundamental understanding of key financial ideas and tools that form the basis for building realistic models, including those that may become proprietary. Numerous carefully chosen examples and exercises reinforce the student’s conceptual understanding and facility with applications. The exercises are divided into conceptual, application-based, and theoretical problems, which probe the material deeper.

The book is aimed toward advanced undergraduates and first-year graduate students who are new to finance or want a more rigorous treatment of the mathematical models used within. While no background in finance is assumed, prerequisite math courses include multivariable calculus, probability, and linear algebra. The authors introduce additional mathematical tools as needed. The entire textbook is appropriate for a single year-long course on introductory mathematical finance. The self-contained design of the text allows for instructor flexibility in topics courses and those focusing on financial derivatives. Moreover, the text is useful for mathematicians, physicists, and engineers who want to learn finance via an approach that builds their financial intuition and is explicit about model building, as well as business school students who want a treatment of finance that is deeper but not overly theoretical.

Product Details

ISBN-13: 9781493981373
Publisher: Springer New York
Publication date: 05/31/2018
Series: Springer Undergraduate Texts in Mathematics and Technology
Edition description: Softcover reprint of the original 1st ed. 2016
Pages: 483
Product dimensions: 7.01(w) x 10.00(h) x (d)

About the Author

Arlie Oswald Petters is a Professor of Mathematics, Physics, and Business Administration at Duke University. Petters is also co-author of Birkhauser's Singularity Theory and Gravitational Lensing.

Xiaoying Dong is an Adjunct Assistant Professor of Mathematics at Duke University and has been a professional trader for over 20 years.

Table of Contents

Preface.- 1. Preliminaries and Financial Markets.- 2. The Time Value of Money.- 3. Markowitz Portfolio Theory.- 4. Capital Market Theory and Portfolio Risk Measures.- 5. Binomial Trees and Security Pricing Modeling.- 6. Shastic Calculus and Geometric Brownian Motion Model.- 7. Derivatives: Forwards, Futures, Swaps and Options.- 8. The BSM Model and European Option Pricing.- Index.
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