Results 61 to 70 of about 493 (183)

Hybrid Clayton-Frank Convolution-Based Bivariate Archimedean Copula

Journal of Probability and Statistics, 2018
This study exploits the closure property of the converse convolution operator to come up with a hybrid Clayton-Frank Archimedean copula for two random variables.
Maxwell Akwasi Boateng, Akoto Yaw Omari-Sasu, Richard Kodzo Avuglah, Nana Kena Frempong   +3 more
doaj   +1 more source

Tail Risk Hedging: The Superiority of the Naïve Hedging Strategy

Journal of Futures Markets, Volume 45, Issue 8, Page 977-1005, August 2025.
ABSTRACT Mitigating extreme tail risk is essential for institutions and corporations to prevent financial losses from severe asset price fluctuations across many asset classes. This study shows that a simple futures hedging strategy, the naïve hedge, is remarkably effective at managing tail risk—so much so that few other methods can beat it.
Min Cao, Thomas Conlon
wiley   +1 more source

Exact simulation of reciprocal Archimedean copulas [PDF]

Statistics & Probability Letters, 2018
The decreasing enumeration of the points of a Poisson random measure whose mean measure has finite survival function on the positive half-axis can be represented as a non-increasing function of the jump times of a standard Poisson process. This observation allows to generalize the essential idea from a well-known exact simulation algorithm for ...
openaire   +2 more sources

A Tale of Two Unprecedented Droughts in Southeast Asia: Physical Drivers and Impending Future Risks

Earth's Future, Volume 13, Issue 8, August 2025.
Abstract Conventional wisdom suggests that tropical droughts in Southeast Asia are closely linked to natural climate variability like El Niño. However, the extreme 2014 drought occurred independently of El Niño, suggesting other dynamic forcings at play.
Shuping Ma, Xiao Peng, Xinyue Liu, Zhongwang Wei, Zhixiao Niu, Wenpeng Zhao, Ming Pan, Xiaogang He   +7 more
wiley   +1 more source

Modeling car‐following behaviors using a driving style–based Bayesian model averaging Copula framework in mixed traffic flow

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 21, Page 3316-3332, 29 August 2025.
Abstract As a fundamental driving behavior, the accurate modeling of car‐following (CF) dynamics is essential for improving traffic flow and advancing autonomous driving technologies. Due to the stochastic nature of CF behaviors, the CF model parameters often exhibit heterogeneity (multimodal trends), distribution uncertainty, and parameter ...
Shubo Wu, Yue Zhang, Yajie Zou, Yuanchang Xie, Yangyang Wang   +4 more
wiley   +1 more source

New Families of Bivariate Copulas via Unit Lomax Distortion

Risks, 2020
This article studies a new family of bivariate copulas constructed using the unit-Lomax distortion derived from a transformation of the non-negative Lomax random variable into a variable whose support is the unit interval.
Fadal Abdullah-A Aldhufairi, Ranadeera G.M. Samanthi, Jungsywan H. Sepanski   +2 more
doaj   +1 more source

Simulating Realistic Design Storms: A Joint Return Period Approach

Water Resources Research, Volume 61, Issue 7, July 2025.
Abstract Design storms are key components for planning drainage networks and flood risk management. Due to atmospheric processes, precipitation accumulations across multiple temporal intervals are often correlated and can combine to shape flood intensities. However, current design storm guidance overlook the observed correlations between return periods
Tabea Cache, Emanuele Bevacqua, Jakob Zscheischler, Hannes Müller‐Thomy, Nadav Peleg   +4 more
wiley   +1 more source

Prediction of the Annual Variation of Groundwater Depth and Its Probability Based on MCAR Model and Copula Functions: A Case Study in Beijing, China

Water Resources Research, Volume 61, Issue 6, June 2025.
Abstract Groundwater (GW) is the primary water source of socio‐economic development in water‐deficient regions, and long‐term overexploitation may cause GW depletion and deterioration. In this study, after analyzing the relationship between GW level and related factors, the main influencing factors were identified from the perspective of climate change
Yan Han, Xiaoling Zhang, Aifeng Lv, Wenbin Zhu   +3 more
wiley   +1 more source

On bivariate Archimedean copulas with fractal support

Dependence Modeling
Due to their simple analytic form (bivariate) Archimedean copulas are usually viewed as very smooth and handy objects, which should distribute mass in a fairly regular and certainly not in a pathological way. Building upon recently established results on
Sánchez Juan Fernández, Trutschnig Wolfgang   +1 more
doaj   +1 more source

On certain transformations of Archimedean copulas: Application to the non-parametric estimation of their generators

Dependence Modeling, 2013
We study the impact of certain transformations within the class of Archimedean copulas. We give some admissibility conditions for these transformations, and define some equivalence classes for both transformations and generators of Archimedean copulas ...
Di Bernardino Elena, Rullière Didier
doaj   +1 more source