Overview
- Seamlessly blends mathematical theory and computational techniques in finance
- Implementations are demonstrated in Python
- An instructor’s manual providing exercise solutions and programming guidance is available for course instructors
Part of the book series: Springer Undergraduate Texts in Mathematics and Technology (SUMAT)
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Keywords
- Computational Finance
- Option Pricing
- Python
- Monte Carlo
- Data Analytics for Finance
- Stochastic Differential Equations
- Numerical Analysis
- Simulation for Finance
About this book
This book offers an up-to-date introductory treatment of computational techniques applied to problems in finance, placing issues such as numerical stability, convergence and error analysis in both deterministic and stochastic settings at its core.
The first part provides a welcoming but nonetheless rigorous introduction to the fundamental theory of option pricing, including European, American, and exotic options along with their hedge parameters, and combines a clear treatment of the mathematical framework with practical worked examples in Python. The second part explores the main computational methods for valuing options within the Black-Scholes framework: lattice, Monte Carlo, and finite difference methods. The third and final part covers advanced topics for the simulation of financial processes beyond the standard Black-Scholes setting. Techniques for the analysis and simulation of multidimensional financial data, including copulas, are covered and will be of interest to those studying machine learning for finance. There is also an in-depth treatment of exact and approximate sampling methods for stochastic differential equation models of interest rates and volatilities.
Written for advanced undergraduate and masters-level courses, the book assumes some exposure to core mathematical topics such as linear algebra, ordinary differential equations, multivariate calculus, probability, and statistics at an undergraduate level. While familiarity with Python is not required, readers should be comfortable with basic programming constructs such as variables, loops, and conditional statements.
Authors and Affiliations
About the author
Cónall Kelly is a Senior Lecturer in Financial Mathematics and Director of the MSc Financial and Computational Mathematics at the School of Mathematical Sciences, University College Cork, Ireland. He teaches core modules on derivatives pricing and computational finance to undergraduate and postgraduate students. He is an active researcher in the field of computational stochastics and, since 2018, he has contributed to the graduate programme at the African Institute for Mathematical Sciences in Senegal.
Bibliographic Information
Book Title: Computation and Simulation for Finance
Book Subtitle: An Introduction with Python
Authors: Cónall Kelly
Series Title: Springer Undergraduate Texts in Mathematics and Technology
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Hardcover ISBN: 978-3-031-60574-1Due: 04 August 2024
Softcover ISBN: 978-3-031-60577-2Due: 04 August 2024
eBook ISBN: 978-3-031-60575-8Due: 04 August 2024
Series ISSN: 1867-5506
Series E-ISSN: 1867-5514
Edition Number: 1
Number of Pages: VII, 318
Number of Illustrations: 8 b/w illustrations, 61 illustrations in colour