Nonparametric estimation of simplified vine copula models: comparison of methods

Articles in the same Issue

1. Special Issue: Recent Developments in Quantitative Risk Management
2. On Conditional Value at Risk (CoVaR) for tail-dependent copulas
3. Multivariate extensions of expectiles risk measures
4. Special Issue: Salzburg Workshop on Dependence Models & Copulas
5. Characterizations of bivariate conic, extreme value, and Archimax copulas
6. VaR bounds in models with partial dependence information on subgroups
7. Kendall’s tau and agglomerative clustering for structure determination of hierarchical Archimedean copulas
8. Nonparametric estimation of simplified vine copula models: comparison of methods
9. Inference for copula modeling of discrete data: a cautionary tale and some facts
10. On Truncation Invariant Copulas and their Estimation
11. About tests of the “simplifying” assumption for conditional copulas
12. Interview Article
13. My introduction to copulas
14. The Vine Philosopher
15. Regular articles
16. On capital allocation for stochastic arrangement increasing actuarial risks
17. Copula-Based Dependence Measures For Piecewise Monotonicity
18. Exact distributions of order statistics from l_n,p-symmetric sample distributions
19. New copulas based on general partitions-of-unity and their applications to risk management (part II)
20. A joint regression modeling framework for analyzing bivariate binary data in R
21. A two-component copula with links to insurance
22. CMPH: a multivariate phase-type aggregate loss distribution
23. Measuring herd behavior: properties and pitfalls
24. A simple non-parametric goodness-of-fit test for elliptical copulas
25. Valuation of large variable annuity portfolios: Monte Carlo simulation and synthetic datasets
26. Dependent defaults and losses with factor copula models