Results 11 to 20 of about 462 (184)

Sequential Truncation of R-Vine Copula Mixture Model for High-Dimensional Datasets

open access: yesInternational Journal of Mathematics and Mathematical Sciences, 2021
Uncovering hidden mixture dependencies among variables has been investigated in the literature using mixture R-vine copula models. They provide considerable flexibility for modeling multivariate data.
Fadhah Amer Alanazi
doaj   +3 more sources

Smooth nonparametric Bernstein vine copulas [PDF]

open access: yesQuantitative Finance, 2012
We propose to use nonparametric Bernstein copulas as bivariate pair-copulas in high-dimensional vine models. The resulting smooth and nonparametric vine copulas completely obviate the error-prone need for choosing the pair-copulas from parametric copula families. By means of a simulation study and an empirical analysis of financial market data, we show
Gregor Wei{\ss}, Marcus Scheffer
openaire   +2 more sources

Vine constructions of Lévy copulas [PDF]

open access: yesJournal of Multivariate Analysis, 2013
Levy copulas are the most general concept to capture jump dependence in multivariate Levy processes. They translate the intuition and many features of the copula concept into a time series setting. A challenge faced by both, distributional and Levy copulas, is to find flexible but still applicable models for higher dimensions. To overcome this problem,
Grothe, Oliver, Nicklas, Stephan
openaire   +3 more sources

A Vine Copula-Based Global Sensitivity Analysis Method for Structures with Multidimensional Dependent Variables

open access: yesMathematics, 2021
For multidimensional dependent cases with incomplete probability information of random variables, global sensitivity analysis (GSA) theory is not yet mature.
Zhiwei Bai   +4 more
doaj   +1 more source

ESTIMASI CVAR PADA PORTOFOLIO SAHAM MENGGUNAKAN METODE GJR-EVT DENGAN PENDEKATAN D-VINE COPULA

open access: yesE-Jurnal Matematika, 2022
Risk measure using Conditional Value at Risk can be calculate if values that exceeds the p-quantile is known in VaR. The models used to accommodate characteristics of the stock portfolio in this research are EVT-GARCH-D-vine copula and EVT-GJR-D-vine ...
DERY MAULANA   +2 more
doaj   +1 more source

MATVines: A vine copula package for MATLAB

open access: yesSoftwareX, 2021
Vine copulas provide a way to model a d-dimensional copula with bivariate building blocks and have been applied to a wide range of research topics. The MATVines package is presented, which implements vine copula functionalities for MATLAB. In particular,
Maximilian Coblenz
doaj   +1 more source

covsim: An R Package for Simulating Non-Normal Data for Structural Equation Models Using Copulas

open access: yesJournal of Statistical Software, 2022
In factor analysis and structural equation modeling non-normal data simulation is traditionally performed by specifying univariate skewness and kurtosis together with the target covariance matrix.
Steffen Grønneberg   +2 more
doaj   +1 more source

Financial dependence analysis: applications of vine copulas [PDF]

open access: yesStatistica Neerlandica, 2013
This paper features the application of a novel and recently developed method of statistical and mathematical analysis to the assessment of financial risk, namely regular vine copulas. Dependence modelling using copulas is a popular tool in financial applications but is usually applied to pairs of securities.
Allen, David E.   +4 more
openaire   +8 more sources

Penerapan Metode GARCH-Vine Copula untuk Estimasi Value at Risk (VaR) pada Portofolio

open access: yesJurnal Fourier, 2018
Salah satu alat ukur yang digunakan untuk menghitung risiko portofolio adalah Value at Risk (VaR). Beberapa metode pengukuran VaR mengasumsikan return berdistribusi normal dan ukuran dependensi antar saham menggunakan korelasi linear.
Herida Okta Pintari, Retno Subekti
doaj   +1 more source

ESTIMASI NILAI CONDITIONAL VALUE AT RISK (CVaR) PORTOFOLIO MENGGUNAKAN METODE EVT-GJR-VINE COPULA

open access: yesE-Jurnal Matematika, 2019
Conditional value at risk (CVaR) is widely used in risk measure that takes into account losses exceeding the value at risk level. The aim of this research is to compare the performance of the EVT-GJR-vine copula method and EVT-GARCH-vine copula method in
NI WAYAN UCHI YUSHI ARI SUDINA   +2 more
doaj   +1 more source

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