Editors:
- Illustrates the interplay between modern advances in both risk measures and risk attitudes
- Multi-disciplinary coverage appeals to students, researchers and practitioners
- Contains papers presented at the Ludwig-Maximilians University in Munich in December 2010
- Includes supplementary material: sn.pub/extras
Part of the book series: EAA Series (EAAS)
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Table of contents (4 chapters)
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Front Matter
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Risk Attitudes
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Front Matter
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Back Matter
About this book
Risk has been described in the past by a simple measure, such as the variance, and risk attitude is often considered simply a degree of risk aversion. However, this viewpoint is usually not sufficient. Risk Measures and Attitudes collects contributions which illustrate how modern approaches to both risk measures and risk attitudes are inevitably intertwined. The settings under which this is discussed include portfolio choice, mitigating credit risk and comparing risky alternatives.
This book will be a useful study aid for students and researchers of actuarial science or risk management as well as practitioners.
Editors and Affiliations
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Department of Mathematics, University of Munich, Munich, Germany
Francesca Biagini
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Institut for Riskmanagement and Insuranc, University of Munich, Munich, Germany
Andreas Richter
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University of Alabama, Tuscaloosa, USA
Harris Schlesinger
Bibliographic Information
Book Title: Risk Measures and Attitudes
Editors: Francesca Biagini, Andreas Richter, Harris Schlesinger
Series Title: EAA Series
DOI: https://doi.org/10.1007/978-1-4471-4926-2
Publisher: Springer London
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag London 2013
Softcover ISBN: 978-1-4471-4925-5Published: 02 February 2013
eBook ISBN: 978-1-4471-4926-2Published: 01 February 2013
Series ISSN: 1869-6929
Series E-ISSN: 1869-6937
Edition Number: 1
Number of Pages: IX, 91
Number of Illustrations: 4 illustrations in colour
Topics: Actuarial Sciences, Quantitative Finance, Applications of Mathematics, Probability Theory and Stochastic Processes