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Grouped normal variance mixtures
Hintz, Erik; Hofert, Marius; Lemieux, Christiane - In: Risks : open access journal 8 (2020) 4/103, pp. 1-26
Grouped normal variance mixtures are a class of multivariate distributions that generalize classical normal variance mixtures such as the multivariate t distribution, by allowing different groups to have different (comonotone) mixing distributions. This allows one to better model risk factors...
Persistent link: https://www.econbiz.de/10012373086
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Corporate governance and cost of capital : evidence from emerging market
Khan, Muhammad Yar; Javeed, Anam; Cuong, Ly Kim; Pham Ha - In: Risks : open access journal 8 (2020) 4/104, pp. 1-29
This study used a researcher self-constructed corporate governance index as a proxy to measure the firm-level corporate governance compliance and disclosure with the 2002 Pakistani Code of Corporate Governance, to examine the relationship between corporate governance and cost of capital. We...
Persistent link: https://www.econbiz.de/10012373093
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Neumann series on the recursive moments of copula-dependent aggregate discounted claims
Ramli, Siti Norafidah Mohd; Jang, Jiwook - In: Risks : open access journal 2 (2014) 2, pp. 195-210
We study the recursive moments of aggregate discounted claims, where the dependence between the inter-claim time and the subsequent claim size is considered. Using the general expression for the m-th order moment proposed by Léveillé and Garrido (Scand. Actuar. J. 2001, 2, 98-110), which takes...
Persistent link: https://www.econbiz.de/10010399755
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Determining distribution for the product of random variables by using copulas
Ly, Sel; Pho, Kim-Hung; Ly, Sal; Wong, Wing Keung - In: Risks : open access journal 7 (2019) 1/23, pp. 1-20
and distribution of the product for two or more random variables via copulas to capture the dependence structures among … density and distribution of the product for two log-normal random variables on several different copulas, including Gaussian …, Student-t, Clayton, Gumbel, Frank, and Joe Copulas, and estimate some common measures including Kendall’s coefficient, mean …
Persistent link: https://www.econbiz.de/10012015948
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The investigation of a forward-rate mortality framework
Alai, Daniel H.; Ignatieva, Ekaterina; Sherris, Michael - In: Risks : open access journal 7 (2019) 2/61, pp. 1-22
framework using copulas. We find that dependence increases with age and introduce a suitable covariance structure, one that is …
Persistent link: https://www.econbiz.de/10012018993
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Dependence modelling of lifetimes in Egyptian families
Henshaw, Kira; Hana, Waleed; Constantinescu, Corina; … - In: Risks : open access journal 11 (2023) 1, pp. 1-25
between lifetimes in spousal, parent-child and child-parent relationships, using copulas to capture the strength of …
Persistent link: https://www.econbiz.de/10014233104
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Dependence modelling for heavy-tailed multi-peril insurance losses
Yan, Tianxing; Yi, Lu; Jeong, Himchan - In: Risks : open access journal 12 (2024) 6, pp. 1-17
The Danish fire loss dataset records commercial fire losses under three insurance coverages: building, contents, and profits. Existing research has primarily focused on the heavy-tail behaviour of the losses but ignored the relationship among different insurance coverages. In this paper, we aim...
Persistent link: https://www.econbiz.de/10014636713
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Market-risk optimization among the developed and emerging markets with cvar measure and copula simulation
Trabelsi, Nader; Tiwari, Aviral Kumar - In: Risks : open access journal 7 (2019) 3/78, pp. 1-20
In this paper, the generalized Pareto distribution (GPD) copula approach is utilized to solve the conditional value-at-risk (CVaR) portfolio problem. Particularly, this approach used (i) copula to model the complete linear and non-linear correlation dependence structure, (ii) Pareto tails to...
Persistent link: https://www.econbiz.de/10012127555
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Tail dependence in financial markets : a dynamic copula approach
Cortese, Federico Pasquale - In: Risks : open access journal 7 (2019) 4/116, pp. 1-14
in the computation of Value-at-Risk (VaR). Results show that copulas provide more sophisticated results in terms of the …
Persistent link: https://www.econbiz.de/10012127765
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Robust estimation of value-at-risk through distribution-free and parametric approaches using the joint severity and frequency model : applications in financial, actuarial, and natu...
Guharay, Sabyasachi; Chang, KC; Xu, Jie - In: Risks : open access journal 5 (2017) 3, pp. 1-29
Value-at-Risk (VaR) is a well-accepted risk metric in modern quantitative risk management (QRM). The classical Monte Carlo simulation (MCS) approach, denoted henceforth as the classical approach, assumes the independence of loss severity and loss frequency. In practice, this assumption does not...
Persistent link: https://www.econbiz.de/10011687895