Quantitative Portfolio Management: with Applications in Python (Springer Texts in Business and Economics) - Softcover

Buch 102 von 170: Springer Texts in Business and Economics

Brugière, Pierre

 
9783030377427: Quantitative Portfolio Management: with Applications in Python (Springer Texts in Business and Economics)
Softcover
ISBN 10: 3030377423 ISBN 13: 9783030377427
Verlag: Springer, 2021

Inhaltsangabe

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.

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Über die Autorin bzw. den Autor

Pierre Brugière is currently Associate Professor at University Paris 9 Dauphine. Previously he spent 19 years working in investment banking in London, in international banks, and 4 years in Paris in an arbitrage bank. During his career in finance he has been responsible for quant groups in fixed income, asset management and equity derivatives. In addition, in his role working for corporate equity derivatives businesses, he has been involved in structuring marketing and executing very large and strategic transactions for large companies and institutions, mainly in Europe, but also in Emerging Markets.

Von der hinteren Coverseite

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.


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Verlag
Springer
Erscheinungsdatum
2021
Sprache
Englisch
ISBN 10 
3030377423
ISBN 13 
9783030377427
Einband
Taschenbuch
Auflage
1
Anzahl der Seiten
220
Kontakt zum Hersteller
Nicht verfügbar
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9783030377397: Quantitative Portfolio Management: with Applications in Python (Springer Texts in Business and Economics)

Vorgestellte Ausgabe

ISBN 10:  3030377393 ISBN 13:  9783030377397
Verlag: Springer, 2020
Hardcover