Overview
- Includes exercises based on exam questions
- Illustrates and expresses the main results in plain language understandable by the pure financier
- Details efficient web data extraction techniques
- Enables the reader with a good background in general mathematics to implement most of the results in any chosen market
Part of the book series: Springer Texts in Business and Economics (STBE)
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This self-contained book presents the main techniques of quantitative portfolio management and associated statistical methods in a very didactic and structured way, in a minimum number of pages. The concepts of investment portfolios, self-financing portfolios and absence of arbitrage opportunities are extensively used and enable the translation of all the mathematical concepts in an easily interpretable way.
All the results, tested with Python programs, are demonstrated rigorously, often using geometric approaches for optimization problems and intrinsic approaches for statistical methods, leading to unusually short and elegant proofs. The statistical methods concern both parametric and non-parametric estimators and, to estimate the factors of a model, principal component analysis is explained. The presented Python code and web scraping techniques also make it possible to test the presented concepts on market data.
This book will be useful for teaching Masters students and for professionals in asset management, and will be of interest to academics who want to explore a field in which they are not specialists. The ideal pre-requisites consist of undergraduate probability and statistics and a familiarity with linear algebra and matrix manipulation. Those who want to run the code will have to install Python on their pc, or alternatively can use Google Colab on the cloud. Professionals will need to have a quantitative background, being either portfolio managers or risk managers, or potentially quants wanting to double check their understanding of the subject.
Reviews
“The book contains both rigorously stated theory and practical instructions, up to instructions for programmers, it will be useful for a very wide audience, from students and teachers to experienced professionals in quantitative finance. It is written in clear, simple language and is quite interesting.” (Yuliya S. Mishura, zbMATH 1452.91005, 2021)
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Quantitative Portfolio Management
Book Subtitle: with Applications in Python
Authors: Pierre Brugière
Series Title: Springer Texts in Business and Economics
DOI: https://doi.org/10.1007/978-3-030-37740-3
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-37739-7Published: 29 March 2020
Softcover ISBN: 978-3-030-37742-7Published: 29 March 2021
eBook ISBN: 978-3-030-37740-3Published: 28 March 2020
Series ISSN: 2192-4333
Series E-ISSN: 2192-4341
Edition Number: 1
Number of Pages: XII, 205
Number of Illustrations: 1 b/w illustrations, 22 illustrations in colour
Topics: Quantitative Finance, Statistics for Business, Management, Economics, Finance, Insurance, Computer Applications