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Journal articles on the topic 'Copula-based dependence'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

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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2

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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3

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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6

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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8

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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9

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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10

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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11

Ramadhan, Muhammad Akhirul, Ahmad Fuad Zainuddin, Udjianna Sekteria Pasaribu, and RR Kurnia Novita Sari. "Joint-Life Insurance Premium Model Using Archimedean Copula: The Study of Mortality in Indonesia." Journal of the Indonesian Mathematical Society 31, no. 1 (2025): 1783. https://doi.org/10.22342/jims.v31i1.1783.

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Joint-life insurance pays a sum insured when the first death occurs. This insurance has a case based on the order of exit from the cohort, namely joint life and last survivor. The former means that one of the insured leaves the cohort, while the latter means the last member of the insured has left his or her cohort. For some reasons of simplicity, the insurance premium is usually calculated with the assumption that the husband and wife are mutually independent. However, this assumption is considered unrealistic. Couples are open to the same risks, hence explaining joint survival model should i

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12

Chesneau, Christophe. "On two new modified tawn copulas." Model Assisted Statistics and Applications 19, no. 1 (2024): 35–48. http://dx.doi.org/10.3233/mas-231451.

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At its core, copula theory focuses on constructing a copula function, which characterizes the structure of dependence between random variables. In particular, the creation of extreme value copulas is crucial because they allow accurate modeling of extreme dependence that traditional copulas can ignore. In this article, we propose theoretical developments on this subject by proposing two new extreme value copulas. They aim to extend the functionalities of the so-called Tawn copula. This is of interest because the Tawn copula is known to be a powerful tool in modeling joint distributions, partic

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Alqawba, Mohammed, Dimuthu Fernando, and Norou Diawara. "A Class of Copula-Based Bivariate Poisson Time Series Models with Applications." Computation 9, no. 10 (2021): 108. http://dx.doi.org/10.3390/computation9100108.

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A class of bivariate integer-valued time series models was constructed via copula theory. Each series follows a Markov chain with the serial dependence captured using copula-based transition probabilities from the Poisson and the zero-inflated Poisson (ZIP) margins. The copula theory was also used again to capture the dependence between the two series using either the bivariate Gaussian or “t-copula” functions. Such a method provides a flexible dependence structure that allows for positive and negative correlation, as well. In addition, the use of a copula permits applying different margins wi

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Fernando, Dimuthu, Mohammed Alqawba, Manar Samad, and Norou Diawara. "Review of Copula for Bivariate Distributions of Zero-Inflated Count Time Series Data." International Journal of Statistics and Probability 11, no. 6 (2022): 52. http://dx.doi.org/10.5539/ijsp.v11n6p52.

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The class of bivariate integer-valued time series models, described via copula theory, is gaining popularity in the literature because of applications in health sciences, engineering, financial management and more. Each time series follows a Markov chain with the serial dependence captured using copula-based distribution functions from the Poisson and the zero-inflated Poisson margins. The copula theory is again used to capture the dependence between the two series.  However, the efficiency and adaptability of the copula are being challenged because of the discrete nature of data a

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Fernando, Dimuthu, Mohammed Alqawba, Manar Samad, and Norou Diawara. "Review of Copula for Bivariate Distributions of Zero-Inflated Count Time Series Data." International Journal of Statistics and Probability 11, no. 6 (2022): 28. http://dx.doi.org/10.5539/ijsp.v11n6p28.

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The class of bivariate integer-valued time series models, described via copula theory, is gaining popularity in the literature because of applications in health sciences, engineering, financial management and more. Each time series follows a Markov chain with the serial dependence captured using copula-based distribution functions from the Poisson and the zero-inflated Poisson margins. The copula theory is again used to capture the dependence between the two series.  However, the efficiency and adaptability of the copula are being challenged because of the discrete nature of data a

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16

Saali, Tariq, Mhamed Mesfioui, and Ani Shabri. "Multivariate Extension of Raftery Copula." Mathematics 11, no. 2 (2023): 414. http://dx.doi.org/10.3390/math11020414.

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This paper introduces a multivariate extension of Raftery copula. The proposed copula is exchangeable and expressed in terms of order statistics. Several properties of this copula are established. In particular, the multivariate Kendall’s tau and Spearman’s rho, as well as the density function, of the suggested copula are derived. The lower and upper tail dependence of the proposed copula are also established. The dependence parameter estimator of this new copula is examined based on the maximum likelihood procedure. A simulation study shows a satisfactory performance of the presented estimato

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El Ktaibi, Farid El, Rachid Bentoumi, Nicola Sottocornola, and Mhamed Mesfioui. "Bivariate Copulas Based on Counter-Monotonic Shock Method." Risks 10, no. 11 (2022): 202. http://dx.doi.org/10.3390/risks10110202.

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This paper explores the properties of a family of bivariate copulas based on a new approach using the counter-monotonic shock method. The resulting copula covers the full range of negative dependence induced by one parameter. Expressions for the copula and density are derived and many theoretical properties are examined thoroughly, including explicit expressions for prominent measures of dependence, namely Spearman’s rho, Kendall’s tau and Blomqvist’s beta. The convexity properties of this copula are presented, together with explicit expressions of the mixed moments. Estimation of the dependen

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Lu, Lu, and Sujit Ghosh. "Nonparametric Estimation of Multivariate Copula Using Empirical Bayes Methods." Mathematics 11, no. 20 (2023): 4383. http://dx.doi.org/10.3390/math11204383.

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In the fields of finance, insurance, system reliability, etc., it is often of interest to measure the dependence among variables by modeling a multivariate distribution using a copula. The copula models with parametric assumptions are easy to estimate but can be highly biased when such assumptions are false, while the empirical copulas are nonsmooth and often not genuine copulas, making the inference about dependence challenging in practice. As a compromise, the empirical Bernstein copula provides a smooth estimator, but the estimation of tuning parameters remains elusive. The proposed empiric

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19

Klüppelberg, Claudia, Stephan Haug, and Gabriel Kuhn. "Copula structure analysis based on extreme dependence." Statistics and Its Interface 8, no. 1 (2015): 93–107. http://dx.doi.org/10.4310/sii.2015.v8.n1.a9.

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20

Ozdemir, Onur, Thomas G. Allen, Sora Choi, Thakshila Wimalajeewa, and Pramod K. Varshney. "Copula Based Classifier Fusion Under Statistical Dependence." IEEE Transactions on Pattern Analysis and Machine Intelligence 40, no. 11 (2018): 2740–48. http://dx.doi.org/10.1109/tpami.2017.2774300.

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21

Liebscher, Eckhard. "Copula-Based Dependence Measures For Piecewise Monotonicity." Dependence Modeling 5, no. 1 (2017): 198–220. http://dx.doi.org/10.1515/demo-2017-0012.

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Abstract The aim of the present paper is to develop and examine association coefficients which can be helpfully applied in the framework of regression analysis. The construction of the coeffiecients is connected with the well-known Spearman coeffiecient and extensions of it (see Liebscher [5]). The proposed coeffiecient measures the discrepancy between the data points and a function which is strictly increasing on one interval and strictly decreasing in the remaining domain.We prove statements about the asymptotic behaviour of the estimated coeffiecient (convergence rate, asymptotic normality)

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22

Liu, D., D. Wang, L. Wang, Y. Chen, X. Chen, and S. Gu. "POME-copula for hydrological dependence analysis." Proceedings of the International Association of Hydrological Sciences 368 (May 6, 2015): 251–56. http://dx.doi.org/10.5194/piahs-368-251-2015.

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Abstract. Hydrological multivariate analysis has been widely studied using copula-based modelling, in which marginal distribution inference is one of the key issues. The main object of this study is to discuss the applicability of the principle of maximum entropy (POME) in marginal distribution inference, thus to develop a POME-copula framework to analyse the dependence of hydrological variables. Marginal distributions are derived with the POME approach before bivariate copulas constructed with corresponding parameters estimated by the dependence of the derived margins. The proposed POME-copul

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23

Lu, Lu, and Sujit Ghosh. "Nonparametric Estimation of Conditional Copula Using Smoothed Checkerboard Bernstein Sieves." Mathematics 12, no. 8 (2024): 1135. http://dx.doi.org/10.3390/math12081135.

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Conditional copulas are useful tools for modeling the dependence between multiple response variables that may vary with a given set of predictor variables. Conditional dependence measures such as conditional Kendall’s tau and Spearman’s rho that can be expressed as functionals of the conditional copula are often used to evaluate the strength of dependence conditioning on the covariates. In general, semiparametric estimation methods of conditional copulas rely on an assumed parametric copula family where the copula parameter is assumed to be a function of the covariates. The functional relation

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Shih, Jia-Han, Yoshihiko Konno, Yuan-Tsung Chang, and Takeshi Emura. "Copula-Based Estimation Methods for a Common Mean Vector for Bivariate Meta-Analyses." Symmetry 14, no. 2 (2022): 186. http://dx.doi.org/10.3390/sym14020186.

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Traditional bivariate meta-analyses adopt the bivariate normal model. As the bivariate normal distribution produces symmetric dependence, it is not flexible enough to describe the true dependence structure of real meta-analyses. As an alternative to the bivariate normal model, recent papers have adopted “copula” models for bivariate meta-analyses. Copulas consist of both symmetric copulas (e.g., the normal copula) and asymmetric copulas (e.g., the Clayton copula). While copula models are promising, there are only a few studies on copula-based bivariate meta-analysis. Therefore, the goal of thi

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Zhuang, De Dong. "Tail Dependence Structure between Carbon Emission Allowances Returns Based on Copulas." Applied Mechanics and Materials 397-400 (September 2013): 726–30. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.726.

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This paper has focus on analyzing tail dependence structure between EUA spots returns and futures returns based on copula approach, which EUA spots negotiated on BlueNext and futures negotiated on European Climate Exchange within the European Union Emission Trading Scheme (EU ETS) during the Phase II. According to the generalized Pareto distribution (GPD) and different Copula functions, the research shows that Gumbel Copula based on the GPD marginal distribution can indicate the tail dependence structure of EUA spots returns and futures returns accurately, i.e. the dependence between upper-tai

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Trimech, Anyssa. "Time-varying dependence measures: a comparative analysis through wavelet approach." International Journal of Energy Sector Management 11, no. 2 (2017): 350–64. http://dx.doi.org/10.1108/ijesm-01-2016-0001.

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Purpose This paper aims to investigate the pattern of dependence between crude oil price and energy consumption of the most important economic sectors in the USA, over different time periods, using monthly data set from January 1986 to July 2014 and a comparative study between linear correlation versus copula correlation as a measure of dependence over the single scale and the multiscale analysis. Design/methodology/approach The proposed method is based on the multiresolution analysis which gives more extensive and detailed description of the dependence price-consumption pattern over different

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Zhang, Xiaoqin, Hongbin Zhu, Bo Li, Ruihan Wu, and Jun Jiang. "Power Transformer Diagnosis Based on Dissolved Gases Analysis and Copula Function." Energies 15, no. 12 (2022): 4192. http://dx.doi.org/10.3390/en15124192.

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The traditional DGA (Dissolved Gas Analysis) diagnosis method does not consider the dependence between fault characteristic gases and uses the relationship between gas ratio coding and fault type to make the decision. As a tool of the dependence mechanism between variables, a copula function can effectively analyze the correlation between variables when it cannot determine whether the linear correlation coefficient can correctly measure the correlation between variable relationships. In this paper, the edge variable of a copula function is selected from the fault characteristic gas of a transf

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önalan, ömer. "The modeling of extreme stochastic dependence using copulas and extreme value theory: case study from energy prices." Global Journal of Mathematical Analysis 5, no. 2 (2017): 29. http://dx.doi.org/10.14419/gjma.v5i2.7256.

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In this paper, we investigate the properties of tail dependence with an approach which is based on the copula models and extreme value theory to obtain a joint distribution function of extreme events and to quantify the dependence between random variables. To achieve this objective, we quantify the large co-movements between the random variables returns which are based on the data set daily quotes of exceeds the threshold value of random variables. In this study, stochastic dependence was modeled by the copulas which it provides a good approach for constructing multivariate probability distrib

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Saminger-Platz, Susanne, Anna Kolesárová, Adam Šeliga, Radko Mesiar, and Erich Peter Klement. "New results on perturbation-based copulas." Dependence Modeling 9, no. 1 (2021): 347–73. http://dx.doi.org/10.1515/demo-2021-0116.

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Abstract A prominent example of a perturbation of the bivariate product copula (which characterizes stochastic independence) is the parametric family of Eyraud-Farlie-Gumbel-Morgenstern copulas which allows small dependencies to be modeled. We introduce and discuss several perturbations, some of them perturbing the product copula, while others perturb general copulas. A particularly interesting case is the perturbation of the product based on two functions in one variable where we highlight several special phenomena, e.g., extremal perturbed copulas. The constructions of the perturbations in t

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Liang, Zhicheng, Junwei Wang, and Kin Keung Lai. "Dependence Structure Analysis and VaR Estimation Based on China’s and International Gold Price: A Copula Approach." International Journal of Information Technology & Decision Making 19, no. 01 (2020): 169–93. http://dx.doi.org/10.1142/s0219622019500445.

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Since 2013, China has become the world’s largest gold producer and consumer. To gain the corresponding global pricing power in gold, many actions have been taken by China in recent years, including the International Board at Shanghai Gold Exchange, Shanghai-Hong Kong Gold Connect and Shanghai Gold Fix. Our work studies the dependence structure between China’s and international gold price and examines whether these moves are changing the dependence structure. We use GARCH-copula models to detect the dynamic dependence and tail dependence. The research period is set to contain the Financial Cris

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Kummaraka, Unyamanee, and Patchanok Srisuradetchai. "Interval Estimation of the Dependence Parameter in Bivariate Clayton Copulas." Emerging Science Journal 7, no. 5 (2023): 1478–90. http://dx.doi.org/10.28991/esj-2023-07-05-02.

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In various disciplines, discerning dependencies between variables remains a crucial undertaking. While correlation measures like Pearson, Spearman, and Kendall provide insight into the degree of two-variable relationships, they fall short of revealing the intricate structure of dependencies between these variables. The Clayton copula, known for its flexible attributes, becomes instrumental in unveiling this dependency structure. This paper aims to advance knowledge by providing an explicit formula for creating Wald confidence intervals (CIs) for the dependence parameter in a bivariate Clayton

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Girard, Stéphane. "Transformation of a copula using the associated co-copula." Dependence Modeling 6, no. 1 (2018): 298–308. http://dx.doi.org/10.1515/demo-2018-0017.

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AbstractWe investigate the properties of a new transformation of copulas based on the co-copula and an univariate function. It is shown that several families in the copula literature can be interpreted as particular outputs of this transformation. Symmetry, association, ordering and dependence properties of the resulting copula are established.

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Ibragimov, Rustam. "COPULA-BASED CHARACTERIZATIONS FOR HIGHER ORDER MARKOV PROCESSES." Econometric Theory 25, no. 3 (2009): 819–46. http://dx.doi.org/10.1017/s0266466609090720.

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In this paper, we obtain characterizations of higher order Markov processes in terms of copulas corresponding to their finite-dimensional distributions. The results are applied to establish necessary and sufficient conditions for Markov processes of a given order to exhibitm-dependence,r-independence, or conditional symmetry. The paper also presents a study of applicability and limitations of different copula families in constructing higher order Markov processes with the preceding dependence properties. We further introduce new classes of copulas that allow one to combine Markovness withm-dep

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Liu, Guannan, Wei Long, Xinyu Zhang, and Qi Li. "DETECTING FINANCIAL DATA DEPENDENCE STRUCTURE BY AVERAGING MIXTURE COPULAS." Econometric Theory 35, no. 4 (2018): 777–815. http://dx.doi.org/10.1017/s0266466618000270.

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A mixture copula is a linear combination of several individual copulas that can be used to generate dependence structures not belonging to existing copula families. Because different pairs of markets may exhibit quite different dependence structures in empirical studies, mixture copulas are useful in modeling the dependence in financial data. Therefore, rather than selecting a single copula based on certain criteria, we propose using a model averaging approach to estimate financial data dependence structures in a mixture copula framework. We select weights (for averaging) by a J-fold Cross-Val

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Lai, Yujie, and Yibo Hu. "A Study on Systematic Risks of U.S. and China Stock Markets Based on Markov Copula." Advances in Education, Humanities and Social Science Research 1, no. 1 (2022): 154. http://dx.doi.org/10.56028/aehssr.1.1.154.

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In this paper, Markov SJC copula model is constructed based on the daily data of standard &amp; Poor's index and Shanghai Shenzhen 300 index, and the systematic risk of American and Chinese stock market is empirically analyzed. The results show that SJC copula can well depict the systematic risk of American and Chinese stock market, the risk dependence has obvious tail asymmetry characteristics, and the probability of low risk dependence is higher than that of high risk dependence.

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Rachid, Rachid, Farid El Ktaibi, and Christophe Chesneau. "Counterpart of Marshall-Olkin bivariate copula with negative dependence and its neutrosophic application in meteorology." International Journal of Neutrosophic Science 25, no. 1 (2025): 258–78. http://dx.doi.org/10.54216/ijns.250124.

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Variables that have revived new interest through computational developments and extensive data analysis. This article contributes to the subject by generalizing the bivariate copula introduced recently in8 and based on the concept of the counter-monotonic shock method. The proposed copula has the feature of covering the full range of negative dependence induced by two dependence parameters, which is not so common in the specialized literature. We examine the main characteristics of this copula. In particular, the absolutely continuous and singular copula components are derived. Analytical expr

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Wu, Xinyu, Meng Zhang, Mengqi Wu, and Hao Cui. "Economic Policy Uncertainty and Conditional Dependence between China and U.S. Stock Markets." Complexity 2022 (January 7, 2022): 1–9. http://dx.doi.org/10.1155/2022/8137932.

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In this paper, we investigate the impact of economic policy uncertainty (EPU) on the conditional dependence between China and U.S. stock markets by employing the Copula-mixed-data sampling (Copula-MIDAS) framework. In the case of EPU, we consider the global EPU (GEPU), the American EPU (AEPU), and the China EPU (CEPU). The empirical analysis based on the Shanghai Stock Exchange Composite (SSEC) index in China and the S&P 500 index in the U.S. shows that the tail dependence between China and U.S. stock markets is symmetrical, and the t Copula outperforms alternative Copulas in terms of in-s

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Ramadhani, Adhitya Ryan, and Waskito Pranowo. "Introducing Copula Functions to Estimate the Reliability of Dependent Mechanical Systems." Jurnal Rekayasa Sistem Industri 13, no. 2 (2024): 103–12. http://dx.doi.org/10.26593/jrsi.v13i2.7219.103-112.

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This paper addresses the challenge of assessing the reliability of complex mechanical systems where components are inherently correlated in their failure modes. Traditionally, the assumption of independence among these components has been employed, but it often fails to capture the real-world complexities. To overcome this limitation, copula functions are introduced as a robust methodology for modeling the dependent relationships between correlated variables within mechanical systems. This paper aims to demonstrate the utility of copulas in estimating system reliability while accounting for th

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Syuhada, Khreshna, and Arief Hakim. "Modeling risk dependence and portfolio VaR forecast through vine copula for cryptocurrencies." PLOS ONE 15, no. 12 (2020): e0242102. http://dx.doi.org/10.1371/journal.pone.0242102.

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Risk in finance may come from (negative) asset returns whilst payment loss is a typical risk in insurance. It is often that we encounter several risks, in practice, instead of single risk. In this paper, we construct a dependence modeling for financial risks and form a portfolio risk of cryptocurrencies. The marginal risk model is assumed to follow a heteroscedastic process of GARCH(1,1) model. The dependence structure is presented through vine copula. We carry out numerical analysis of cryptocurrencies returns and compute Value-at-Risk (VaR) forecast along with its accuracy assessed through d

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Latif, Shahid, and Slobodan P. Simonovic. "Trivariate Joint Distribution Modelling of Compound Events Using the Nonparametric D-Vine Copula Developed Based on a Bernstein and Beta Kernel Copula Density Framework." Hydrology 9, no. 12 (2022): 221. http://dx.doi.org/10.3390/hydrology9120221.

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Low-lying coastal communities are often threatened by compound flooding (CF), which can be determined through the joint occurrence of storm surges, rainfall and river discharge, either successively or in close succession. The trivariate distribution can demonstrate the risk of the compound phenomenon more realistically, rather than considering each contributing factor independently or in pairwise dependency relations. Recently, the vine copula has been recognized as a highly flexible approach to constructing a higher-dimensional joint density framework. In these, the parametric class copula wi

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Pouliasis, George, Gina Alexandra Torres-Alves, and Oswaldo Morales-Napoles. "Stochastic Modeling of Hydroclimatic Processes Using Vine Copulas." Water 13, no. 16 (2021): 2156. http://dx.doi.org/10.3390/w13162156.

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The generation of synthetic time series is important in contemporary water sciences for their wide applicability and ability to model environmental uncertainty. Hydroclimatic variables often exhibit highly skewed distributions, intermittency (that is, alternating dry and wet intervals), and spatial and temporal dependencies that pose a particular challenge to their study. Vine copula models offer an appealing approach to generate synthetic time series because of their ability to preserve any marginal distribution while modeling a variety of probabilistic dependence structures. In this work, we

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Bildirici, Melike, and Özgür Ömer Ersin. "Regime-Switching Fractionally Integrated Asymmetric Power Neural Network Modeling of Nonlinear Contagion for Chaotic Oil and Precious Metal Volatilities." Fractal and Fractional 6, no. 12 (2022): 703. http://dx.doi.org/10.3390/fractalfract6120703.

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This paper aims at analyzing nonlinear dependence between fractionally integrated, chaotic precious metal and oil prices and volatilities. With this respect, the Markov regime-switching fractionally integrated asymmetric power versions of generalized autoregressive conditional volatility copula (MS-FIAPGARCH-copula) method are further extended to multi-layer perceptron (MLP)-based neural networks copula (MS-FIAPGARCH-MLP-copula). The models are utilized for modeling dependence between daily oil, copper, gold, platinum and silver prices, covering a period from 1 January 1990–25 March 2022. Kolm

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Longla, Martial. "On dependence structure of copula-based Markov chains." ESAIM: Probability and Statistics 18 (2014): 570–83. http://dx.doi.org/10.1051/ps/2013052.

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Liu, Shisong, and Shaojun Li. "Multi-model D-vine copula regression model with vine copula-based dependence description." Computers & Chemical Engineering 161 (May 2022): 107788. http://dx.doi.org/10.1016/j.compchemeng.2022.107788.

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Xie, Yuan-tao, Juan Yang, Chong-guang Jiang, Zi-yu Cai, and Joshua Adagblenya. "Incidence, Dependence Structure of Disease, and Rate Making for Health Insurance." Mathematical Problems in Engineering 2018 (August 12, 2018): 1–13. http://dx.doi.org/10.1155/2018/4265801.

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In order to analyze the two goals under the national strategy of “Healthy China”, this paper attempts to solve the problem of coverage rate and guarantee level of health insurance, as well as the rational allocation of full life cycle health insurance resources. This paper uses pair copula to model the dependence of different disease incidence and proposes an actuarial model for rate making in health insurance based on the dependence captured by pair copula. These are far more accurate than any other model and more proper for covering a basket of several different diseases. The data for the pa

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Martey, Emmanuel Nii, and Nii Attoh-Okine. "Modeling tamping recovery of track geometry using the copula-based approach." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 232, no. 8 (2018): 2079–96. http://dx.doi.org/10.1177/0954409718757556.

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Assessing and maintaining track geometry within acceptable limits are key components of railroad infrastructure maintenance operations. Track geometry conditions have a significant influence on rider comfort and safety. To maintain the ride quality and safety of the track, maintenance activities pertaining to track geometry, such as tamping, are performed. Tamping enhances the track geometry quality but fails to return the track geometry to an as-good-as-new condition. Majority of studies have evaluated tamping recovery using deterministic techniques, which assume that tamping recovery is depe

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Aminuddin Jafry, Nurul Hanis, Ruzanna Ab Razak, and Noriszura Ismail. "Authors: Nurul Hanis Aminuddin Jafry ; Ruzanna Ab Razak ; Noriszura Ismail." Journal of Social Sciences Research, SPI6 (December 26, 2018): 646–52. http://dx.doi.org/10.32861/jssr.spi6.646.652.

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Studies on dependence between stock markets are important because of their implications on the process of decision-making in investment. Many previous studies measure the dependence between markets using static copula. However, in recent years, time-varying copula has been used as an alternative for measuring dependence due to its capability of capturing time-varying dependence between markets. This study uses both static and time-varying copulas to measure the dependence structure between Malaysia and major stock markets (US, UK and Japan) based on the sample data from year 2007 Q1 until year

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Rusyda, Hasna Afifah, Achmad Zabar Soleh, Lienda Noviyanti, Anna Chadidjah, and Fajar Indrayatna. "Utilization Copula in Determination of Shallot Insurance Premium Based on Regional Harvest Results." EKSAKTA: Journal of Sciences and Data Analysis 20, no. 2 (2020): 160–66. http://dx.doi.org/10.20885/eksakta.vol1.iss2.art11.

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Abstract: Shallot is one of the highest-yielding horticultural crops in Indonesia and has the tendency to increase the profits of farmers in Indonesia. But until now in Indonesia there is no insurance for horticultural crops other than corn, whereas the shallot farmers face various sources of risk such as weather changes, pest attacks, or other technical factors that ultimately lead to uncertainty of agricultural yields (revenue risk). To overcome this loss, insurance companies can make products based on shallot yields and shallot market prices. Therefore it is essential to grasp the distribut

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Ma, Huizi, Lin Lin, Han Sun, and Yue Qu. "Research on the Dependence Structure and Risk Spillover of Internet Money Funds Based on C-Vine Copula and Time-Varying t-Copula." Complexity 2021 (August 24, 2021): 1–11. http://dx.doi.org/10.1155/2021/3941648.

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Internet money funds (IMFs) are the most widely involved products in the Internet financial products market. This research utilized the C-vine copula model to study the risk dependence structure of IMFs and then introduces the time-varying t-copula model to analyze the risk spillover of diverse IMFs. The results show the following: (1) The risks of Internet-based IMFs, bank-based IMFs, and fund-based IMFs have obvious dependence structure, and the degree of risk dependence among different categories of IMFs is significantly different. (2) There are risk spillover effects among diverse IMFs, an

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Katata, Kabir. "Modelling the Naira Exchange Rate Dependence Using Static and Time-Varying Copula." Central Bank of Nigeria Journal of Applied Statistics 14, no. 2 (2023): 41–72. http://dx.doi.org/10.33429/cjas.14223.3/5.

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This paper examines the dependence structure of different currencies versus the Nigerian Naira using constant and time-varying copula. Daily Naira/USD, Naira/Yuan, Naira/Pound, and Naira/Euro exchange rates from 23 December 2011 to 12 May 2020 were utilised. We fitted eight constant and time-varying copula families using the exchange rate standardised residuals. The study finds that the Naira exchange rate may be estimated with student t-copula, Symmetrized Joe-Clayton (SJC), or Rotated Gumbel copula models and Autoregressive (AR)– Glosten Jagannathan Runkle Generalized Autoregressive Conditio

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