Results 141 to 150 of about 87,023 (313)
Upper Comonotonicity and Risk Aggregation Under Dependence Uncertainty
Mathematical Finance, EarlyView.ABSTRACT In this paper, we study dependence uncertainty and the resulting effects on tail risk measures, which play a fundamental role in modern risk management. We introduce the notion of a regular dependence measure, defined on multimarginal couplings, as a generalization of well‐known correlation statistics such as the Pearson correlation. The first
Corrado De Vecchi +2 more
wiley +1 more source
Copula "inter mares" in Pirascca sagaris satnius (Dalman) (Lepidoptera, Riodinidae, Riodininae) [PDF]
, 2000 Marcelo Duarte +2 more
openalex +1 more source
Stochastic Frontier Models With Correlated Error Components [PDF]
In the productivity modelling literature, the disturbances U (representing technical inefficiency) and V (representing noise) of the composite error W=V-U of the stochastic frontier model are assumed to be independent random variables.
Murray D Smith
core
Nonlinear Dependence Structure Between BRICS Stock Markets, Gold, and Cryptocurrencies
The Manchester School, EarlyView.ABSTRACT This study aims to conduct an in‐depth analysis of the complex nonlinear dependence relationships between cryptocurrencies and gold within the stocks of BRICS countries. The study employs a GARCH‐EVT‐Vine‐Copula and wavelet coherence models to evaluate the interconnectedness, tail risk and Co‐movement pattern of these assets before and after ...
Jiale Yan
wiley +1 more source
Supervised parameter updating of deformation analyses for rockfill dams using prior knowledge
Computer-Aided Civil and Infrastructure Engineering, EarlyView.Abstract Accurate and reliable numerical simulation is crucial for the safe construction and operation of infrastructure such as rockfill dams. Model parameter updating through inverse analysis based on monitoring data is key to improving analysis accuracy.
Zhitao Ai +6 more
wiley +1 more source
Median and quantile conditional copulas
Dependence ModelingThis article studies the conditional dependency between random variables, conditionally upon a covariate (vector). The conditional copula fully characterizes this conditional dependency.
Gijbels Irène, Matterne Margot
doaj +1 more source
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT For binary outcome models, an endogeneity correction based on nonlinear rank‐based transformations is proposed. Identification without external instruments is achieved under one of two assumptions: Either the endogenous regressor is a nonlinear function of one component of the error term, conditional on the exogenous regressors, or the ...
Alexander Mayer, Dominik Wied
wiley +1 more source
Bayesian Inference for Joint Estimation Models Using Copulas to Handle Endogenous Regressors
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT This study proposes a Bayesian approach for finite‐sample inference of the Gaussian copula endogeneity correction. Extant studies use frequentist inference, build on a priori computed estimates of marginal distributions of explanatory variables, and use bootstrapping to obtain standard errors. The proposed Bayesian approach facilitates precise
Rouven E. Haschka
wiley +1 more source
Efficient estimation of parameters in marginals in semiparametric multivariate models [PDF]
Recent literature on semiparametric copula models focused on the situation when the marginals are specified nonparametrically and the copula function is given a parametric form.
Artem Prokhorov, Valentyn Panchenko
core
GARCH copulas and GARCH-mimicking copulas
The bivariate copulas that describe the dependencies and partial dependencies of lagged variables in strictly stationary, first-order GARCH-type processes are investigated. It is shown that the copulas of symmetric GARCH processes are jointly symmetric but non-exchangeable, while the copulas of processes with symmetric innovation distributions and ...
Dias, Alexandra +2 more
openaire +2 more sources