Buch, Englisch, 392 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 719 g
Buch, Englisch, 392 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 719 g
ISBN: 978-1-4051-8369-7
Verlag: Wiley
* Helps to answer the question: which risk measure is best for a given problem?
* Finds new relations between existing classes of risk measures
* Describes applications in finance and extends them where possible
* Presents the theory of probability metrics in a more accessible form which would be appropriate for non-specialists in the field
* Applications include optimal portfolio choice, risk theory, and numerical methods in finance
* Topics requiring more mathematical rigor and detail are included in technical appendices to chapters
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Unternehmensfinanzierung
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Finanzsektor & Finanzdienstleistungen: Allgemeines
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Bankwirtschaft
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Anlagen & Wertpapiere
- Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Börse, Rohstoffe
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensfinanzen Finanzierung, Investition, Leasing
Weitere Infos & Material
Chapter 1 Introduction.
1.1 Probability metrics.
1.2 Applications in finance.
Chapter 2 Probability distances and metrics.
2.1 Introduction.
2.2 Some examples of probability metrics.
2.3 Distance and semidistance spaces.
2.4 Definitions of probability distances and metrics.
2.5 Summary.
2.6 Technical appendix.
Chapter 3 Choice under uncertainty.
3.1 Introduction.
3.2 Expected utility theory.
3.3 Stochastic dominance.
3.4 Probability metrics and stochastic dominance.
3.5 Cumulative Prospect Theory.
3.6 Summary.
3.7 Technical appendix.
Chapter 4 A classification of probability distances.
4.1 Introduction.
4.2 Primary distances and primary metrics.
4.3 Simple distances and metrics.
4.4 Compound distances and moment functions.
4.5 Ideal probability metrics.
4.6 Summary.
4.7 Technical appendix.
Chapter 5 Risk and uncertainty.
5.1 Introduction.
5.2 Measures of dispersion.
5.3 Probability metrics and dispersion measures.
5.4 Measures of risk.
5.5 Risk measures and dispersion measures.
5.6 Risk measures and stochastic orders.
5.7 Summary.
5.8 Technical appendix.
Chapter 6 Average value-at-risk.
6.1 Introduction.
6.2 Average value-at-risk.
6.2.1 AVaR for stable distributions.
6.3 AVaR estimation from a sample.
6.4 Computing portfolio AVaR in practice.
6.5 Back-testing of AVaR.
6.6 Spectral risk measures.
6.7 Risk measures and probability metrics.
6.8 Risk measures based on distortion functionals.
6.9 Summary.
6.10 Technical appendix.
Chapter 7 Computing AVaR through Monte Carlo.
7.1 Introduction.
7.2 An illustration of Monte Carlo variability.
7.3 Asymptotic distribution, classical conditions.
7.4 Rate of convergence to the normal distribution.
7.5 Asymptotic distribution, heavy-tailed returns.
7.6 Rate of convergence, heavy-tailed returns.
7.7 On the choice of a distributional model.
7.8 Summary.
7.9 Technical appendix.
Chapter 8 Stochastic dominance revisited.
8.1 Introduction.
8.2 Metrization of preference relations.
8.3 The Hausdorff metric structure.
8.4 Examples.
8.5 Utility-type representations.
8.6 Almost stochastic orders and degree of violation.
8.7 Summary.
8.8 Technical appendix.