Authors:
- Discusses all aspects of computation, namely numerical, simulation, and statistical, in a single book
- Explains every procedure with R code and is illustrated with tables and figures
- Includes two chapters on machine learning in finance based on cutting-edge research topics
Part of the book series: Indian Statistical Institute Series (INSIS)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (21 chapters)
-
Front Matter
-
Numerical Methods
-
Front Matter
-
-
Simulation Methods
-
Front Matter
-
-
Statistical Methods
-
Front Matter
-
About this book
This book prepares students to execute the quantitative and computational needs of the finance industry. The quantitative methods are explained in detail with examples from real financial problems like option pricing, risk management, portfolio selection, etc. Codes are provided in R programming language to execute the methods. Tables and figures, often with real data, illustrate the codes. References to related work are intended to aid the reader to pursue areas of specific interest in further detail. The comprehensive background with economic, statistical, mathematical, and computational theory strengthens the understanding. The coverage is broad, and linkages between different sections are explained. The primary audience is graduate students, while it should also be accessible to advanced undergraduates. Practitioners working in the finance industry will also benefit.
Reviews
Authors and Affiliations
-
Applied Statistics Unit, Indian Statistical Institute, Bengaluru, India
Rituparna Sen
-
Department of Mathematics, Chennai Mathematical Institute, Siruseri, India
Sourish Das
About the authors
Rituparna Sen is Associate Professor at the Applied Statistics Division, Indian Statistical Institute, Bangalore Centre, Karnataka, India. Earlier, she was Assistant Professor at the University of California at Davis from 2004–2011. With a Ph.D. in statistics from the University of Chicago, USA, she has been internationally recognized for her outstanding contributions to the applications of statistical theory and methods in finance and for her initiative and leadership in research, teaching, and mentoring in this area. She is on the editorial board of the Applied Stochastic Models in Business and Industry journal and several other journals. Rituparna is an elected member of the International Statistical Institute and a council member of the International Society for Business and Industrial Statistics. She has been awarded the Young Statistical Scientist Award by the International Indian Statistical Association in the Applications category and the Best Student Paper Award by the American Statistical Association section on the Statistical Computing and Women in Mathematical Sciences award by Technical University of Munich, Germany.
Sourish Das is Associate Professor of mathematics at Chennai Mathematical Institute (CMI), Tamil Nadu, India. At CMI, he teaches data science courses, including statistical finance using R and Python. His research interests are in Bayesian methodology, machine learning on big data in statistical finance, and environmental statistics. He did his Ph.D. in statistics from the University of Connecticut and postdoctoral work at Duke University, USA. He was awarded the UK Commonwealth Rutherford Fellowship to visit the University of Southampton, UK. He was awarded the Best Student Research Paper by the American Statistical Association section on Bayesian statistics.
Bibliographic Information
Book Title: Computational Finance with R
Authors: Rituparna Sen, Sourish Das
Series Title: Indian Statistical Institute Series
DOI: https://doi.org/10.1007/978-981-19-2008-0
Publisher: Springer Singapore
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 Singapore Pte Ltd. 2023
Hardcover ISBN: 978-981-19-2007-3Published: 18 May 2023
Softcover ISBN: 978-981-19-2010-3Due: 17 June 2023
eBook ISBN: 978-981-19-2008-0Published: 16 May 2023
Series ISSN: 2523-3114
Series E-ISSN: 2523-3122
Edition Number: 1
Number of Pages: XIII, 353
Number of Illustrations: 34 b/w illustrations, 47 illustrations in colour
Topics: Statistics for Business, Management, Economics, Finance, Insurance, Applications of Mathematics, Probability Theory and Stochastic Processes, Statistics, general, Machine Learning, Statistics and Computing/Statistics Programs