On the simplified pair-copula construction -- simply useful or too simplistic?

DOI10.1016/j.jmva.2009.12.001zbMath1184.62079OpenAlexW1984931822WikidataQ56865723 ScholiaQ56865723MaRDI QIDQ962223

Ingrid Hobæk Haff, Arnoldo Frigessi, Kjersti Aas

Publication date: 6 April 2010

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10852/34736

zbMATH Keywords

vines multivariate distributions hierarchical structures copulae

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (75)

Modeling dependence structure among European markets and among Asian-Pacific markets: a regime switching regular vine copula approach ⋮ Estimation of high-order moment-independent importance measures for Shapley value analysis ⋮ Nonparametric testing for no covariate effects in conditional copulas ⋮ Copula diagnostics for asymmetries and conditional dependence ⋮ SCOMDY models based on pair-copula constructions with application to exchange rates ⋮ Regime switches in the dependence structure of multidimensional financial data ⋮ Simplified R-vine based forward regression ⋮ Nonparametric estimation of pair-copula constructions with the empirical pair-copula ⋮ Variational inference for high dimensional structured factor copulas ⋮ Specification of informative prior distributions for multinomial models using vine copulas ⋮ Scenario aggregation method for portfolio expectile optimization ⋮ Default probability estimation via pair copula constructions ⋮ Technical and allocative inefficiency in production systems: a vine copula approach ⋮ Estimation of a Copula when a Covariate Affects only Marginal Distributions ⋮ The shifting dependence dynamics between the G7 stock markets ⋮ Smooth nonparametric Bernstein vine copulas ⋮ Structure learning in Bayesian networks using regular vines ⋮ Vine copula based likelihood estimation of dependence patterns in multivariate event time data ⋮ Copula-Based Regression Estimation and Inference ⋮ On kernel-based estimation of conditional Kendall's tau: finite-distance bounds and asymptotic behavior ⋮ Nonparametric C- and D-vine-based quantile regression ⋮ On Kendall's regression ⋮ Simplified pair copula constructions -- limitations and extensions ⋮ Measuring association and dependence between random vectors ⋮ Robust DC optimal power flow with modeling of solar power supply uncertainty via R-vine copulas ⋮ Truncated regular vines in high dimensions with application to financial data ⋮ Pair-copula constructions for non-Gaussian DAG models ⋮ Partial and average copulas and association measures ⋮ Covariance model simulation using regular vines ⋮ About tests of the ``simplifying assumption for conditional copulas ⋮ Modelling credit card exposure at default using vine copula quantile regression ⋮ Model distances for vine copulas in high dimensions ⋮ Estimating non-simplified vine copulas using penalized splines ⋮ Unnamed Item ⋮ Parameter estimation for pair-copula constructions ⋮ Beyond simplified pair-copula constructions ⋮ Comparison of estimators for pair-copula constructions ⋮ Nonparametric Estimation of Copula Regression Models With Discrete Outcomes ⋮ Data-driven polynomial chaos expansion for machine learning regression ⋮ Pair-copula models for analyzing family data ⋮ Sequential truncation of \(R\)-vine copula mixture model for high-dimensional datasets ⋮ Study of partial and average conditional Kendall's tau ⋮ On the weak convergence of the empirical conditional copula under a simplifying assumption ⋮ Estimation of Copula Models With Discrete Margins via Bayesian Data Augmentation ⋮ Selecting and estimating regular vine copulae and application to financial returns ⋮ A partial correlation vine based approach for modeling and forecasting multivariate volatility time-series ⋮ Score tests for covariate effects in conditional copulas ⋮ Vine Copula Specifications for Stationary Multivariate Markov Chains ⋮ Conditional copula simulation for systemic risk stress testing ⋮ Testing the simplifying assumption in high-dimensional vine copulas ⋮ Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas ⋮ pyvine: the Python package for regular vine copula modeling, sampling and testing ⋮ Time series models with infinite-order partial copula dependence ⋮ Testing for equality between conditional copulas given discretized conditioning events ⋮ D-vine copula based quantile regression ⋮ Pair Copula Constructions for Insurance Experience Rating ⋮ A mixture of regular vines for multiple dependencies ⋮ Mixture of D-vine copulas for modeling dependence ⋮ Copula and composite quantile regression-based estimating equations for longitudinal data ⋮ How simplifying and flexible is the simplifying assumption in pair-copula constructions -- analytic answers in dimension three and a glimpse beyond ⋮ Maximum likelihood estimation of mixed C-vines with application to exchange rates ⋮ Bayesian model selection for D-vine pair-copula constructions ⋮ Conditional Quantile Reproducibility of Multivariate Distributions and Simplified Pair Copula Construction ⋮ Generalized Additive Models for Pair-Copula Constructions ⋮ Copula-based Black-Litterman portfolio optimization ⋮ Robust and efficient estimating equations for longitudinal data partial linear models and its applications ⋮ Approximate Bayesian conditional copulas ⋮ Spatial pair-copula model of grade for an anisotropic gold deposit ⋮ A copula‐based risk aggregation model ⋮ Selection of Vine Copulas ⋮ Bayesian ridge estimators based on copula-based joint prior distributions for regression coefficients ⋮ Conditional empirical copula processes and generalized measures of association ⋮ Sampling, conditionalizing, counting, merging, searching regular vines ⋮ Truncation of vine copulas using fit indices ⋮ Efficient information based goodness-of-fit tests for vine copula models with fixed margins: a comprehensive review

Uses Software

QRM

Cites Work

This page was built for publication: On the simplified pair-copula construction -- simply useful or too simplistic?