Results 61 to 70 of about 385 (163)

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

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

WORLD FINANCIAL RELATIONS: UNDERSTANDING THE CREDIT DERIVATIVE SWAPS (CDS) DEPENDENCE STRUCTURE

REAd
This study investigates the copula model that best fit to model the dependence structure of Credit Derivative Swaps (CDS) spreads. For the analysis, we consider daily data from the period of January 1, 2009 to December 31, 2014.
Fernanda Maria Müller, Marcelo Brutti Righi, Anderson Luis Walker Amorin   +2 more
doaj   +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

Global Flood Projection and Socioeconomic Implications Under a Deep Learning Framework

Water Resources Research, Volume 61, Issue 5, May 2025.
Abstract As the planet warms, the frequency and severity of weather‐related hazards such as floods are intensifying, posing substantial threats to communities around the globe. Rising flood peaks and volumes claim lives, damage infrastructure, and compromise access to essential services.
Shengyu Kang, Jiabo Yin, Louise Slater, Pan Liu, Fubao Sun, Dedi Liu, Jun Xia   +6 more
wiley   +1 more source

Singularity aspects of Archimedean copulas

Journal of Mathematical Analysis and Applications, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fernández Sánchez, Juan, Trutschnig, Wolfgang   +1 more
openaire   +2 more sources