Results 71 to 80 of about 276 (185)
Nonlinear Dependence Structure Between BRICS Stock Markets, Gold, and Cryptocurrencies
The Manchester School, Volume 94, Issue 1, Page 75-89, January 2026.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
Simplified vine copula models: State of science and affairs
Risk SciencesVine copula models have become highly popular practical tools for modeling multivariate dependencies. To maintain tractability, a commonly employed simplifying assumption is that conditional copulas remain unchanged by the conditioning variables.
Thomas Nagler
doaj +1 more source
A class of directed acyclic graphs with mixed data types in mediation analysis
Canadian Journal of Statistics, Volume 53, Issue 4, December 2025.Abstract We propose a unified class of generalized structural equation models (GSEMs) with data of mixed types in mediation analysis, including continuous, categorical, and count variables. Such models extend substantially the classical linear structural equation model to accommodate many data types arising from the application of mediation analysis ...
Wei Hao, Canyi Chen, Peter X.‐K. Song
wiley +1 more source
A Novel Flexible Kernel Density Estimator for Multimodal Probability Density Functions
CAAI Transactions on Intelligence Technology, Volume 10, Issue 6, Page 1759-1782, December 2025.ABSTRACT Estimating probability density functions (PDFs) is critical in data analysis, particularly for complex multimodal distributions. traditional kernel density estimator (KDE) methods often face challenges in accurately capturing multimodal structures due to their uniform weighting scheme, leading to mode loss and degraded estimation accuracy ...
Jia‐Qi Chen +5 more
wiley +1 more source
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2015 The article points out the possibilities of using static D-Vine copula ARMA-GARCH model for estimation of 1 day ahead market Value at Risk. For the illustration we use data of the four companies listed on Prague Stock Exchange in range from 2010 to 2014.
Václav Klepáč, David Hampel
doaj +1 more source
D-vine copula based quantile regression and the simplifying assumption for vine copulas [PDF]
, 2017 In the first part of this thesis we propose a novel semiparametric approach to perform quantile regression using D-vine copulas, a subclass of the flexible class of vine copula models. Various applications and the extension to discrete data are presented.
openaire
Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression
Risks, 2017 Measuring interdependence between probabilities of default (PDs) in different industry sectors of an economy plays a crucial role in financial stress testing. Thereby, regression approaches may be employed to model the impact of stressed industry sectors
Matthias Fischer +3 more
doaj +1 more source
Contributions to Vine-Copula Modeling
, 2022 Regular vine-copula models (R-vines) are a powerful statistical tool for modeling thedependence structure of multivariate distribution functions. In particular, they allow modelingdierent types of dependencies among random variables independently of their marginaldistributions, which is deemed the most valued characteristic of these models.
openaire +1 more source
Learning Vine Copula Models for Synthetic Data Generation
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 A vine copula model is a flexible high-dimensional dependence model which uses only bivariate building blocks. However, the number of possible configurations of a vine copula grows exponentially as the number of variables increases, making model selection a major challenge in development.
Sun, Yi +2 more
openaire +3 more sources
Copula Modeling of COVID-19 Excess Mortality
RisksCOVID-19’s effects on mortality are hard to quantify. Issues with attribution can cause problems with resulting conclusions. Analyzing excess mortality addresses this concern and allows for the analysis of broader effects of the pandemic.
Jonas Asplund, Arkady Shemyakin
doaj +1 more source