Results 31 to 40 of about 292 (177)
Statistical arbitrage with vine copulas [PDF]
Quantitative Finance, 2018 We develop a multivariate statistical arbitrage strategy based on vine copulas—a highly flexible instrument for linear and nonlinear multivariate dependence modeling.
Stübinger, Johannes +2 more
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Extreme risk spillovers between China and major international stock markets
Modern Finance, 2023 We examine the complex dependence structure and risk spillovers between the Chinese stock market and twelve major international markets. To this end, we employ three types of vine copulas and tests for the Granger causality in risk of Hong et al. (2009).
Lingling Qian +2 more
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Nonparametric C- and D-vine-based quantile regression
Dependence Modeling, 2022 Quantile regression is a field with steadily growing importance in statistical modeling. It is a complementary method to linear regression, since computing a range of conditional quantile functions provides more accurate modeling of the stochastic ...
Tepegjozova Marija +3 more
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The relationship between WIG-subindexes: evidence from the Warsaw Stock Exchange
Managerial Economics, 2015 Evidence on links among the major Warsaw Stock Exchange subindexes using daily data from the period of 2011.03.01 to 2014.07.21 is provided in the paper. The empirical study for eleven WIG-sectoral subindexes with 844 observations was conducted by means
Henryk Gurgul, Robert Syrek
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Matrix and graph representations of vine copula structures
CoRR, 2022 23 pages, 27 ...
Daniel Pfeifer, Edith Alice Kovács
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Vine copula based dependence modeling in sustainable finance
Journal of Finance and Data Science, 2022 Climate change and sustainability have become societal focal points in the last decade. Consequently, companies have been increasingly characterized by non-financial information, such as environmental, social, and governance (ESG) scores, based on which ...
Claudia Czado +5 more
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Prediction based on conditional distributions of vine copulas [PDF]
Computational Statistics & Data Analysis, 2019 Vine copulas are a flexible tool for multivariate non-Gaussian distributions. For data from an observational study where the explanatory variables and response variables are measured together, a proposed vine copula regression method uses regular vines and handles mixed continuous and discrete variables.
Bo Chang 0002, Harry Joe
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On the connection between cherry-tree copulas and truncated R-vine copulas [PDF]
Kybernetika, 2017 Vine copulas are a flexible way for modeling dependences using only pair-copulas as building blocks. However if the number of variables grows the problem gets fast intractable. For dealing with this problem Brechmann at al. proposed the truncated R-vine copulas.
Edith Kovács, Tamás Szántai
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Univariate conditioning of vine copulas
Journal of Multivariate Analysis, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Application of a Vine Copula for Multi-Line Insurance Reserving
Risks, 2020 This article introduces a novel use of the vine copula which captures dependence among multi-line claim triangles, especially when an insurance portfolio consists of more than two lines of business. First, we suggest a way to choose an optimal joint loss
Himchan Jeong, Dipak Dey
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