Relevant bibliographies by topics / Copula-based dependence

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  2. Dissertations / Theses
  3. Books
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Academic literature on the topic 'Copula-based dependence'

Author: Grafiati
Published: 9 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "Copula-based dependence"

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Nugroho, Bayu Adi. "The Stability of Islamic Cryptocurrencies and Copula-Based Dependence with Alternative Crypto and Fiat Currencies." ISRA International Journal of Islamic Finance 15, no. 2 (2023): 80–97. http://dx.doi.org/10.55188/ijif.v15i2.543.

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Purpose — This study aims to examine Islamic cryptocurrencies and their dependency on foreign exchange markets in vine copula architecture (CD-Vine) and provide a framework for detecting complex dependence structures, risk management implications, and hedging effectiveness.
 Design/Methodology/Approach — This study used gold-backed cryptocurrencies and three fiat currencies. The vine copula approach was preferred because it applies several distributions and estimates complex dependencies. Hedging effectiveness was measured by constructing simulation-based portfolios optimised with DCC-t-C
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Yang, Jingping, Zhijin Chen, Fang Wang, and Ruodu Wang. "COMPOSITE BERNSTEIN COPULAS." ASTIN Bulletin 45, no. 2 (2015): 445–75. http://dx.doi.org/10.1017/asb.2015.1.

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AbstractCopula function has been widely used in insurance and finance for modeling inter-dependency between risks. Inspired by the Bernstein copula put forward by Sancetta and Satchell (2004, Econometric Theory, 20, 535–562), we introduce a new class of multivariate copulas, the composite Bernstein copula, generated from a composition of two copulas. This new class of copula functions is able to capture tail dependence, and it has a reproduction property for the three important dependency structures: comonotonicity, countermonotonicity and independence. We introduce an estimation procedure bas
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Wu, Yongtuo, Yudong Feng, Yuliang Zhao, and Saiyu Yu. "Joint Probability Distribution of Wind–Wave Actions Based on Vine Copula Function." Journal of Marine Science and Engineering 13, no. 3 (2025): 396. https://doi.org/10.3390/jmse13030396.

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During its service life, a deep-sea floating structure is likely to encounter extreme marine disasters. The combined action of wind and wave loads poses a threat to its structural safety. In this study, elliptical copula, Archimedean copula, and vine copula models are employed to depict the intricate dependence structure between wind and waves in a specific sea area of the Shandong Peninsula. Moreover, hourly significant wave height, spectral peak period, and 10 m average wind speed hindcast data from 2004 to 2023 are utilized to explore the joint distribution of multidimensional parameters an
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Chesneau, Christophe. "Proposal of a Modified Clayton Copula: Theory, Properties and Examples." European Journal of Statistics 4 (September 24, 2024): 9. http://dx.doi.org/10.28924/ada/stat.4.9.

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The Clayton copula is a mathematical tool used in copula theory to model dependence between random variables. It is a notable member of the Archimedean copula family and is best known for its ability to capture tail dependence. In this article, we present a new modified variant of the Clayton copula that aims to improve its flexibility. The proposed modification scheme perturbs its Archimedean nature by integrating a bivariate product of logarithmic functions and an additional tuning parameter. The elaborated copula benefits from a more nuanced representation of the copula density, and negativ
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Lee, Eun-Joo, Noah Klumpe, Jonathan Vlk, and Seung-Hwan Lee. "Modeling Conditional Dependence of Stock Returns Using a Copula-based GARCH Model." International Journal of Statistics and Probability 6, no. 2 (2017): 32. http://dx.doi.org/10.5539/ijsp.v6n2p32.

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Investigating dependence structures of stocks that are related to one another should be an important consideration in managing a stock portfolio, among other investment strategies. To capture various dependence features, we employ copula to overcome the limitations of traditional linear correlations. Financial time series data is typically characterized by volatility clustering of returns that influences an estimate of a stock’s future price. To deal with the volatility and dependence of stock returns, this paper provides procedures of combining a copula with a GARCH model which leads to the c
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Zhou, Jin Yu, Kui Zhou Sun, and Xiu Lian Li. "Reliability Modeling for Symmetric Structure Systems Based on Copulas." Advanced Materials Research 118-120 (June 2010): 319–26. http://dx.doi.org/10.4028/www.scientific.net/amr.118-120.319.

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As a new tool of statistical analysis, Copula is introduced to build reliability model for structural system consisting of identical components, by which the complex feature of failure dependence can be depicted. Aiming at symmetric structure systems, typical failure-dependence mechanism of components is discussed firstly. Considering the failure-dependence mechanism, modeling steps based on Gauss Copula and Archimedean Copulas are put forward, in which the twin stress, components strength are chosen as the basic variables and the safety margins are chosen as the analytic variables. Compared w
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Vaz de Melo Mendes, Beatriz, and Cecília Aíube. "Copula based models for serial dependence." International Journal of Managerial Finance 7, no. 1 (2011): 68–82. http://dx.doi.org/10.1108/17439131111109008.

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Song, Shuai, Jing Liu, Yongjiu Qian, Fang Zhang, and Gang Wu. "Dependence analysis on the seismic demands of typical components of a concrete continuous girder bridge with the copula technique." Advances in Structural Engineering 21, no. 12 (2018): 1826–39. http://dx.doi.org/10.1177/1369433218757234.

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The seismic reliability of a bridge system is significantly affected by the dependence among typical bridge components. This study demonstrates the process of using a copula technique to describe the nonlinear dependence among component seismic demands isolated from their marginal probability distributions. A suite of 100 bridge-ground motion samples were developed with the Latin hypercube sampling approach and bin approach. Based on the incremental dynamic analysis, the tail dependence among component seismic demands at different intensity levels was analyzed with the best-fitting copula func
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Czado, Claudia, and Thomas Nagler. "Vine Copula Based Modeling." Annual Review of Statistics and Its Application 9, no. 1 (2022): 453–77. http://dx.doi.org/10.1146/annurev-statistics-040220-101153.

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With the availability of massive multivariate data comes a need to develop flexible multivariate distribution classes. The copula approach allows marginal models to be constructed for each variable separately and joined with a dependence structure characterized by a copula. The class of multivariate copulas was limited for a long time to elliptical (including the Gaussian and t-copula) and Archimedean families (such as Clayton and Gumbel copulas). Both classes are rather restrictive with regard to symmetry and tail dependence properties. The class of vine copulas overcomes these limitations by
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El Hannoun, Wafaa, Salah-Eddine El Adlouni, and Abdelhak Zoglat. "Vine-Copula-Based Quantile Regression for Cascade Reservoirs Management." Water 13, no. 7 (2021): 964. http://dx.doi.org/10.3390/w13070964.

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This paper features an application of Regular Vine (R-vine) copulas, a recently developed statistical tool to assess composite risk. Copula-based dependence modelling is a popular tool in conditional risk assessment, but is usually applied to pairs of variables. By contrast, Vine copulas provide greater flexibility and permit the modelling of complex dependency patterns using a wide variety of bivariate copulas which may be arranged and analysed in a tree structure to explore multiple dependencies. This study emphasises the use of R-vine copulas in an analysis of the co-dependencies of five re
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Dissertations / Theses on the topic "Copula-based dependence"

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Pappada', Roberta. "Copula-based measures of tail dependence with applications." Doctoral thesis, Università degli studi di Padova, 2014. http://hdl.handle.net/11577/3424539.

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With the advent of globalization and the recent financial turmoil, the interest for the analysis of dependencies between financial time series has significantly increased. Risk measures such as value-at-risk are heavily affected by the joint extreme comovements of associated risk factors. This thesis suggests some copula-based statistical tools which can be useful in order to have more insights into the nature of the association between random variables in the tail of their distributions. Preliminarily, an overview of important definitions and properties in copula theory is given, and some kn
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Longla, Martial. "Modeling dependence and limit theorems for Copula-based Markov chains." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1367944672.

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Di, Lascio Francesca Marta Lilja <1979&gt. "Analyzing the dependence structure of microarray data: a copula–based approach." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/670/1/Tesi_Di_Lascio_Francesca_Marta_Lilja.pdf.

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The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and
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Di, Lascio Francesca Marta Lilja <1979&gt. "Analyzing the dependence structure of microarray data: a copula–based approach." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/670/.

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The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and
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TKACH, KATERYNA. "Essays on multidimensional poverty measurement and the dependence among well-being dimensions." Doctoral thesis, Università degli studi dell'Insubria, 2019. http://hdl.handle.net/10281/317984.

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Evaluating the welfare of nations is high on the research agenda of the economists, practitioners and policy-makers. The literature contributions of the last decades triggered a multivariate perception of the well-being, which is suggested to go beyond the GDP, and created a need for more complex approaches to evaluate the welfare as well as poverty. The first essay investigates the approaches to multivariate poverty measurement and focuses on the composite index approach and the steps involved in it. An important aspect of the multivariate perspective in well-being is the dependence amon
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Spanhel, Fabian [Verfasser], and Stefan [Akademischer Betreuer] Mittnik. "A copula-based approach to model serial dependence in financial time series / Fabian Spanhel ; Betreuer: Stefan Mittnik." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2015. http://d-nb.info/1131551893/34.

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[Verfasser], Suroso, and András [Akademischer Betreuer] Bárdossy. "Asymmetric dependence based spatial copula models : empirical investigations and consequences on precipitation fields / Suroso ; Betreuer: András Bárdossy." Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2017. http://d-nb.info/1139709720/34.

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Zhang, Fan. "Management of foreign reserves : an approach based on vine-copula, regime-switching dependence and Bayesian opinion pooling." Thesis, Durham University, 2014. http://etheses.dur.ac.uk/10847/.

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This research is constructed to address the issue of structure management for colossal foreign exchange reserves holders, such as China and other emerging economies. Contrary to the discussion of optimal quantity on the reserve level, structure management considers the ideal applications of the national wealth, specifically the compositions in the reserves' financial investments. Two perspectives are considered for the safety and liquidity tranche of the foreign reserves, and another one for the return tranche. The thwo perspectives are further developed into three chapters of this thesis and
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Damaseb, W. B. "Investigation on the efficient frontier based on CVaR under copula dependence structure with applications to South African JSE stocks." Master's thesis, University of Cape Town, 2005. http://hdl.handle.net/11427/4877.

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Includes bibliographical references.<br>We study the feasihility of using a coherent monetary risk measure, Conditional Value at Risk (CVaR) also known as Expected Shortfall (ES), to optimise a portfolio of South African stocks. Value at Risk (VaR) is not a sub-additive risk measure and therefore does not possess one of the four properties that all coherent risk measures must satisfy. Using copula to describe the dependence structure between the instruments in our portfolio, we implement and backtest a CVaR optimization algorithm and compare the backtested results to those obtained using param
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Safari, Katesari Hadi. "BAYESIAN DYNAMIC FACTOR ANALYSIS AND COPULA-BASED MODELS FOR MIXED DATA." OpenSIUC, 2021. https://opensiuc.lib.siu.edu/dissertations/1948.

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Available statistical methodologies focus more on accommodating continuous variables, however recently dealing with count data has received high interest in the statistical literature. In this dissertation, we propose some statistical approaches to investigate linear and nonlinear dependencies between two discrete random variables, or between a discrete and continuous random variables. Copula functions are powerful tools for modeling dependencies between random variables. We derive copula-based population version of Spearman’s rho when at least one of the marginal distribution is discrete. In
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Books on the topic "Copula-based dependence"

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Emura, Takeshi, and Yi-Hau Chen. Analysis of Survival Data with Dependent Censoring: Copula-Based Approaches. Springer, 2018.

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Emura, Takeshi, Shigeyuki Matsui, Virginie Rondeau, and Yi-Hau Chen. Survival Analysis with Dependent Censoring and Correlated Endpoints: Copula-Based Approaches. Springer Singapore Pte. Limited, 2018.

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Book chapters on the topic "Copula-based dependence"

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Di Lascio, F. Marta L., Fabrizio Durante, and Roberta Pappadà. "Copula–based clustering methods." In Copulas and Dependence Models with Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64221-5_4.

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Erdely, Arturo. "Copula-based piecewise regression." In Copulas and Dependence Models with Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64221-5_5.

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Di Lascio, F. Marta L., Fabrizio Durante, and Aurora Gatto. "Copula-Based Hierarchical Clustering for Complete Dependence." In Italian Statistical Society Series on Advances in Statistics. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-64350-7_87.

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Xu, Jia, and Longbing Cao. "Vine Copula-Based Asymmetry and Tail Dependence Modeling." In Advances in Knowledge Discovery and Data Mining. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93034-3_23.

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Erkal Sonmez, Ozlen, and Alp Baray. "On Copula Based Serial Dependence in Statistical Process Control." In Lecture Notes in Management and Industrial Engineering. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03317-0_11.

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Kim, Seongyong, and Daeyoung Kim. "Directional Dependence Analysis Using Skew-Normal Copula-Based Regression." In Statistics and Causality. John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781118947074.ch6.

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De Keyser, Steven, and Irène Gijbels. "Copula-Based Divergence Measures for Dependence Between Random Vectors." In Building Bridges between Soft and Statistical Methodologies for Data Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15509-3_14.

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Puarattanaarunkorn, Ornanong, and Songsak Sriboonchitta. "Copula Based GARCH Dependence Model of Chinese and Korean Tourist Arrivals to Thailand: Implications for Risk Management." In Modeling Dependence in Econometrics. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03395-2_22.

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Kiatmanaroch, Teera, and Songsak Sriboonchitta. "Relationship between Exchange Rates, Palm Oil Prices, and Crude Oil Prices: A Vine Copula Based GARCH Approach." In Modeling Dependence in Econometrics. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03395-2_25.

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Pappadà, Roberta, Fabrizio Durante, and Nicola Torelli. "A Graphical Tool for Copula Selection Based on Tail Dependence." In Studies in Classification, Data Analysis, and Knowledge Organization. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-55708-3_23.

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Conference papers on the topic "Copula-based dependence"

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Johnn, Syu-Ning, Hasan Nikkhah, Meng-Lin Tsai, Styliani Avraamidou, Burcu Beykal, and Vassilis M. Charitopoulos. "Data-Driven Chance-Constrained Mixed Integer Nonlinear Bi-level Optimisation Via Copulas: Application To Integrated Planning And Scheduling Problems." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.169891.

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Planning and scheduling are integral components of process supply chains. The presence of data correlation, particularly multivariate demand data dependency, can pose significant challenges to the decision-making process. This necessitates the consideration of dependency structures inherent in the underlying data to generate good-quality, feasible solutions to optimisation problems such as planning and scheduling. This work proposes a chance-constrained optimisation framework integrated with copulas, a non-parametric data estimation technique to forecast uncertain demand levels in accordance w
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Pitertsev, A. A., R. B. Sinitsyn, and F. J. Yanovsky. "Copula based dependence measure for polarimetric weather radar." In 2015 16th International Radar Symposium (IRS). IEEE, 2015. http://dx.doi.org/10.1109/irs.2015.7226408.

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Xu, Jia, Wei Wei, and Longbing Cao. "Copula-Based High Dimensional Cross-Market Dependence Modeling." In 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2017. http://dx.doi.org/10.1109/dsaa.2017.67.

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Choi, Sora, Hao He, and Pramod K. Varshney. "Copula based dependence modeling for inference in RADAR systems." In 2015 IEEE Radar Conference. IEEE, 2015. http://dx.doi.org/10.1109/radarconf.2015.7411879.

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Zhang, Jun, and Ziping Du. "Clustering of financial time series based on temporal dependence copula." In International conference on Management Innovation and Information Technology. WIT Press, 2014. http://dx.doi.org/10.2495/miit131872.

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Chen, Zhong-Zhe, Yu Liu, Hong-Zhong Huang, Xuehai Wu, and Liping He. "A Reliability Allocation Method Considering Failure Dependence." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12944.

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Traditional reliability allocation methods are based on the assumption that the subsystems of a system are independence in order to simplify the problem. However, this assumption could deviate from the engineering practice. To achieve the reliability requirement of the system, the subsystems must be allocated high reliability based on traditional reliability allocation approaches which neglect the dependence between subsystems. To solve this problem, an improved reliability allocation method is developed in this paper. Firstly, the failure dependence between subsystems of mechanical systems is
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Yundai, Xu, and Yuan Yue. "Analysis of Aggregated Wind Power Dependence Based on Optimal Vine Copula." In 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). IEEE, 2019. http://dx.doi.org/10.1109/isgt-asia.2019.8881069.

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Yi, Wen-de. "Copula-Based Dependence Models of Two Markov Time Series of Order 1." In Eighth International Conference of Chinese Logistics and Transportation Professionals (ICCLTP). American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/40996(330)503.

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Lu, Qiuyu, Wei Hu, Yong Min, Fei Yuan, and Zonghe Gao. "Wind power uncertainty modeling considering spatial dependence based on Pair-copula theory." In 2014 IEEE Power & Energy Society General Meeting. IEEE, 2014. http://dx.doi.org/10.1109/pesgm.2014.6938902.

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Vanem, Erik, Øystein Lande, and Elias Fekhari. "A Simulation Study on the Usefulness of the Bernstein Copula for Statistical Modeling of Metocean Variables." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-121159.

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Abstract Probabilistic modelling of relevant environmental variables are crucial for the safe design and operation of marine structures. Using metocean data, a joint model of several variables can be estimated, including their dependence structure. Often, a conditional model is assumed for this, but recently the non-parametric Bernstein copula has been suggested as an alternative tool to model such dependencies. As a non-parametric technique, it is very flexible and often provides excellent goodness-of-fit to data with different dependencies. However, non-parametric techniques are prone to ove
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Reports on the topic "Copula-based dependence"

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Bouezmarni, Taoufik, Mohamed Doukali, and Abderrahim Taamouti. Copula-based estimation of health concentration curves with an application to COVID-19. CIRANO, 2022. http://dx.doi.org/10.54932/mtkj3339.

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COVID-19 has created an unprecedented global health crisis that caused millions of infections and deaths worldwide. Many, however, argue that pre-existing social inequalities have led to inequalities in infection and death rates across social classes, with the most-deprived classes are worst hit. In this paper, we derive semi/non-parametric estimators of Health Concentration Curve (HC) that can quantify inequalities in COVID-19 infections and deaths and help identify the social classes that are most at risk of infection and dying from the virus. We express HC in terms of copula function that w
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