The Art of Quantitative Finance Vol. 3
Risk, Optimal Portfolios, and Case Studies
(Sprache: Englisch)
The textbook discusses risk management in capital markets and presents various techniques of portfolio optimization. Special attention is given to risk measurement and credit risk management. Furthermore, the author discusses optimal investment problems and...
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Klappentext zu „The Art of Quantitative Finance Vol. 3 “
The textbook discusses risk management in capital markets and presents various techniques of portfolio optimization. Special attention is given to risk measurement and credit risk management. Furthermore, the author discusses optimal investment problems and presents various examples. In the last section, the book includes numerous case studies based on the author's own work as a fund manager, court-appointed expert and consultant in the field of quantitative finance. This book is the third volume of the quantitative finance trilogy by the author and builds on the theoretical groundwork introduced in the previous books. The volume presents real-life examples of the successful application of the introduced techniques and methods in financial services and capital markets.
Inhaltsverzeichnis zu „The Art of Quantitative Finance Vol. 3 “
Risk measurement and credit risk management.- Optimal investment problems.- Case studies.Autoren-Porträt von Gerhard Larcher
Prof. Gerhard Larcher is full Professor for Financial Mathematics and Head of the Institute for Financial Mathematics and Applied Number Theory at the Johannes Kepler University Linz in Austria. He is the spokesperson of the project 'Quasi-Monte Carlo Methods: Theory and Applications', a special research program funded by the Austrian government.
Bibliographische Angaben
- Autor: Gerhard Larcher
- 2023, 1st ed. 2023, XIV, 368 Seiten, 207 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3031238664
- ISBN-13: 9783031238666
Sprache:
Englisch
Pressezitat
"All problems are from real life and are presented in a straightforward manner: the motivation for the problem, then precise mathematical statement, and the solution. The way in which the problems are solved can serve as an example for the reader own analyses." (Pawel Klibe, zbMATH 1522.91002, 2023)
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