scholarly journals Vine Copula-Based Asymmetry and Tail Dependence Modeling

2018 ◽  
pp. 285-297 ◽  
Author(s):  
Jia Xu ◽  
Longbing Cao
Keyword(s):  
Tail Dependence ◽  
Dependence Modeling ◽  
Vine Copula

scholarly journals Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula

2021 ◽  
Vol 9 (2) ◽  
pp. 30
Author(s):  
John Weirstrass Muteba Mwamba ◽  
Sutene Mwambetania Mwambi
Keyword(s):  
South Africa ◽  
Crude Oil ◽  
South African ◽  
Asset Allocation ◽  
Markov Switching ◽  
Tail Dependence ◽  
Lower Tail ◽  
Oil Market ◽  
Oil Markets ◽  
Vine Copula

This paper investigates the dynamic tail dependence risk between BRICS economies and the world energy market, in the context of the COVID-19 financial crisis of 2020, in order to determine optimal investment decisions based on risk metrics. For this purpose, we employ a combination of novel statistical techniques, including Vector Autoregressive (VAR), Markov-switching GJR-GARCH, and vine copula methods. Using a data set consisting of daily stock and world crude oil prices, we find evidence of a structure break in the volatility process, consisting of high and low persistence volatility processes, with a high persistence in the probabilities of transition between lower and higher volatility regimes, as well as the presence of leverage effects. Furthermore, our results based on the C-vine copula confirm the existence of two types of tail dependence: symmetric tail dependence between South Africa and China, South Africa and Russia, and South Africa and India, and asymmetric lower tail dependence between South Africa and Brazil, and South Africa and crude oil. For the purpose of diversification in these markets, we formulate an asset allocation problem using raw returns, MS GARCH returns, and C-vine and R-vine copula-based returns, and optimize it using a Particle Swarm optimization algorithm with a rebalancing strategy. The results demonstrate an inverse relationship between the risk contribution and asset allocation of South Africa and the crude oil market, supporting the existence of a lower tail dependence between them. This suggests that, when South African stocks are in distress, investors tend to shift their holdings in the oil market. Similar results are found between Russia and crude oil, as well as Brazil and crude oil. In the symmetric tail, South African asset allocation is found to have a well-diversified relationship with that of China, Russia, and India, suggesting that these three markets might be good investment destinations when things are not good in South Africa, and vice versa.

scholarly journals Application of a Vine Copula for Multi-Line Insurance Reserving

Risks ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 111
Author(s):  
Himchan Jeong ◽  
Dipak Dey
Keyword(s):  
Bayesian Model ◽  
Marginal Distribution ◽  
Development Model ◽  
Model Diagnostics ◽  
Risk Capital ◽  
Dependence Modeling ◽  
Insurance Portfolio ◽  
Out Of Sample ◽  
Vine Copula ◽  
A Company

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 development model for multiple lines of business that considers marginal distribution, vine copula structure, and choice of family for each pair of copulas. The performance of the model is also demonstrated with Bayesian model diagnostics and out-of-sample validation measures. Finally, we provide an implication of the dependence modeling, which allows a company to analyze and establish the risk capital for whole portfolio.

scholarly journals Examining the Interdependence between the Exchange Rates of China and ASEAN Countries: A Canonical Vine Copula Approach

2019 ◽  
Vol 11 (19) ◽  
pp. 5487 ◽  
Author(s):  
Liu ◽  
Wang ◽  
Sriboonchitta
Keyword(s):  
Exchange Rates ◽  
Tail Dependence ◽  
Dependence Structure ◽  
Positive Dependence ◽  
Asymmetric Dependence ◽  
Before And After ◽  
Copula Approach ◽  
Asean Countries ◽  
Vine Copula ◽  
Vine Copulas

Based on the canonical vine (C-vine) copula approach, this paper examines the interdependence between the exchange rates of the Chinese Yuan (CNY) and the currencies of major Association of Southeast Asian Nations (ASEAN) countries. The differences in the dependence structure and degree between currencies before and after the Belt and Road (B&R) Initiative were compared in order to investigate the changing role of the Renminbi (RMB) in the ASEAN foreign exchange markets. The results indicate a positive dependence between the exchange rate returns of CNY and the currencies of ASEAN countries and show the rising power of RMB in the regional currency markets after the B&R Initiative was launched. Besides this, the Malaysian Ringgit proved to be most relevant to the other ASEAN currencies, thus playing an important role in the stability of regional financial markets. Moreover, evidence of tail dependence was found in the returns of three currency pairs after the B&R Initiative, which implies the presence of asymmetric dependence between exchange rates. The results from time-varying C-vine copulas further confirmed the robustness of the results from the static C-vine copulas.

Vine copula selection using mutual information for hydrological dependence modeling

2020 ◽  
Vol 186 ◽  
pp. 109604 ◽  
Author(s):  
Lingling Ni ◽  
Dong Wang ◽  
Jianfeng Wu ◽  
Yuankun Wang ◽  
Yuwei Tao ◽  
...  
Keyword(s):  
Mutual Information ◽  
Dependence Modeling ◽  
Vine Copula

Review of dependence modeling in hydrology and water resources

2016 ◽  
Vol 40 (4) ◽  
pp. 549-578 ◽  
Author(s):  
Zengchao Hao ◽  
Vijay P. Singh
Keyword(s):  
Water Resources ◽  
Nonlinear Dependence ◽  
Future Research ◽  
Dependence Structure ◽  
Structure Modeling ◽  
Dependence Modeling ◽  
The Past ◽  
Extreme Dependence ◽  
Vine Copula ◽  
Hydrology And Water Resources

Various methods have been developed over the past five decades for dependence modeling of multivariate variables in hydrology and water resources, but there has been no overall review of techniques commonly used in the field. This paper, therefore, introduces several methods focusing on dependence structure modeling, including parametric distribution, entropy, copula, and nonparametric. Recent advances in modeling dependences mainly reside in nonlinear dependence modeling (including extreme dependence) with flexible marginal distributions, and in high-dimension dependence modeling via the vine copula construction with flexible dependence structures. Strengths and limitations of different methods and avenues for future research, such as dependence modeling in a changing climate, are discussed to aid water resource planners and managers in the selection and application of suitable techniques.

scholarly journals Aggregation of underwriting risks in insurance industry of Iran using vine copula

2015 ◽  
Vol 5 (4) ◽  
pp. 149-161
Author(s):  
Mohammad Mirbagherijam ◽  
Mohammad Nabi Shahiki Tash ◽  
Gholamreza Zamanian ◽  
Amir Safari
Keyword(s):  
Standard Model ◽  
Risk Measures ◽  
Insurance Industry ◽  
Tail Dependence ◽  
Economic Capital ◽  
Aggregation Process ◽  
Copula Models ◽  
Risk Aggregation ◽  
Copula Method ◽  
Vine Copula

In this paper, the underwriting risks of the insurance industry of Iran were aggregated using various vine copula classes and historical data of loss ratios which corresponds to each business line. The estimated economic capital (EC) for the entire insurance industry considerably varies across different risk measures and vine copula models. In addition, less than the risk-based capital (RBC) charge assessed based on the standard model of RN69 and amounted to 96,943,391 million of Iran Rials. Therefore, it was concluded that using the Vine copula method and allowing symmetry and tail dependence for pairs of business lines’ risks in the risk aggregation process leads to overestimation of the RBC risk charge, as compared to the estimated results of simple and linear aggregation methods of such standard model. Furthermore, the choice of dependency structure and risk measures have a paramount effect on the aggregate economic capital. Highlights: Estimated aggregated economic capital varies across different risk measures and vine copula models; Selecting the appropriate copula model is an important consideration in risk aggregation process; Using the Vine copula method in the risk aggregation leads to overestimation of the RBC risk charge; The estimated economic capital is less than RBC risk charge calculated under standard model of RN69.

scholarly journals Assessing Market Risk in BRICS and Oil Markets: An application of Markov Switching and Vine Copula

2021 ◽  
Author(s):  
John Weirstrass Muteba Mwamba ◽  
Sutene M Mwambi
Keyword(s):  
South Africa ◽  
South African ◽  
Asset Allocation ◽  
Inverse Relationship ◽  
Markov Switching ◽  
Tail Dependence ◽  
Particle Swarm Algorithm ◽  
Lower Tail ◽  
Oil Market ◽  
Vine Copula

This paper investigates the dynamic tail dependence risk between BRICS economies and world energy market in the context of the COVID-19 financial crisis of 2020, to determine optimal investment decisions based on risk metrics. For this purpose, the study employs a combination of novel statistical techniques ranging from Markov Switching, GARCH and Vine copula. Using a dataset consisting of daily stock and world crude oil prices; we find high probability of transition between lower and higher volatility regimes. Furthermore, our results based on the C-Vine copula confirm the existence of two types of tail dependence: - symmetric tail dependence between South Africa and China; South Africa and Russia; and lower tail dependence between South Africa and India; South Africa and Brazil; South Africa and Oil. For the purpose of diversification in these markets, we formulate an asset allocation problem using C-vine copula-based returns and optimize it using Particle Swarm algorithm with a rebalancing strategy. The results show an inverse relationship between the risk contribution and asset allocation of South Africa and oil market supporting the existence of lower tail dependence between them. This suggests that when South African stocks are in distress, investors tend to shift their holdings in oil market. Similar results are found between China and oil. In the upper tail, South African asset allocation is found to have an inverse relationship with that of Brazil, Russia and India suggesting that these three markets might be good investment destinations when things are not good in South Africa and vice-versa.

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