Risk Measures

An Introduction to the Mathematical Theory
Erscheinungsjahr 2026
ISBN: 978-1-009-71093-0
Verlag: Cambridge University Press

Buch, Englisch, 211 Seiten, Gewicht: 250 g

Providing comprehensive yet accessible coverage, this is the first graduate-level textbook dedicated to the mathematical theory of risk measures. It explains how economic and financial principles result in a profound mathematical theory that allows us to quantify risk in monetary terms, giving rise to risk measures. Each chapter is designed to match the length of one or two lectures, covering the core theory in a self-contained manner, with exercises included in every chapter. Additional material sections then provide further background and insights for those looking to delve deeper. This two-layer modular design makes the book suitable as the basis for diverse lecture courses of varying length and level, and a valuable resource for researchers.

Autoren/Hrsg.

Molchanov, Ilya

Ziegel, Johanna

Inhaltsverzeichnis

Introduction; 1. Gains, quantiles and Value-at-Risk; 2. Monetary property and acceptance sets; 3. Diversification, convexity and coherence; 4. Average-Value-at-Risk; 5. Dual representation of convex and coherent risk measures; 6. Representation theorems for risk measures on $L_p$-spaces; 7. Constructions of risk measures; 8. Law-determined risk measures; 9. Law-determined risk measures on $L_p$-spaces; 10. Comonotonicity and Choquet integrals; 11. Coherent comonotonic additive risk measures; 12. Multivariate risk measures; List of representations of coherent risk measures; List of important law-determined risk measures; References; Index.

Über Autor(innen)

Ziegel, Johanna
Johanna Ziegel is Professor of Statistics at ETH Zurich, having previously worked at the University of Bern. Her expertise is statistical forecasting theory and applications, mainly in finance and meteorology.

Molchanov, Ilya
Ilya Molchanov is Professor of Probability at the University of Bern, having previously worked at the University of Glasgow. He specialises in stochastic geometry. He authored 'Theory of Random Sets' (2017) and co-authored 'Random Sets in Econometrics' (2018) with Francesca Molinari, discussing the econometric applications of his work at the interface between probability theory and convex geometry.