Tail dependence structure between carbon emission allowances returns based on Copulas

Abstract This paper examines correlation and dependence structures between money and the level of economic activity in the USA in the context of a Markov-switching copula vector error correction model. We use the error correction model to focus on the short-run dynamics between money and output while accounting for their long-run equilibrium relationship. We use the Markov regime-switching model to account for instabilities in the relationship between money and output, and also consider different copula models with different dependence structures to investigate (upper and lower) tail dependence.

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Extremal behavior of Archimedean copulas

Advances in Applied Probability ◽

10.1239/aap/1300198519 ◽

2011 ◽

Vol 43 (1) ◽

pp. 195-216 ◽

Cited By ~ 20

Author(s):

Martin Larsson ◽

Johanna Nešlehová

Keyword(s):

Domain Of Attraction ◽

Tail Dependence ◽

Dependence Structure ◽

Tail Behavior ◽

Archimedean Copulas ◽

Radial Part ◽

Stochastic Representation ◽

Lower Tail ◽

Extremal Behavior ◽

Practical Implications

We show how the extremal behavior of d-variate Archimedean copulas can be deduced from their stochastic representation as the survival dependence structure of an ℓ1-symmetric distribution (see McNeil and Nešlehová (2009)). We show that the extremal behavior of the radial part of the representation is determined by its Williamson d-transform. This leads in turn to simple proofs and extensions of recent results characterizing the domain of attraction of Archimedean copulas, their upper and lower tail-dependence indices, as well as their associated threshold copulas. We outline some of the practical implications of their results for the construction of Archimedean models with specific tail behavior and give counterexamples of Archimedean copulas whose coefficient of lower tail dependence does not exist.

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A Method for Systemic Risk Estimation Based on CDS Indices

Review of Economic and Business Studies ◽

10.1515/rebs-2016-0018 ◽

2015 ◽

Vol 8 (1) ◽

pp. 103-124

Author(s):

Gabriel Gaiduchevici

Keyword(s):

Goodness Of Fit ◽

Risk Estimation ◽

Multivariate Time Series ◽

Tail Dependence ◽

Dependence Structure ◽

Parameter Estimates ◽

Copula Models ◽

Goodness Of Fit Tests ◽

Multi Stage ◽

Stage Estimation

AbstractThe copula-GARCH approach provides a flexible and versatile method for modeling multivariate time series. In this study we focus on describing the credit risk dependence pattern between real and financial sectors as it is described by two representative iTraxx indices. Multi-stage estimation is used for parametric ARMA-GARCH-copula models. We derive critical values for the parameter estimates using asymptotic, bootstrap and copula sampling methods. The results obtained indicate a positive symmetric dependence structure with statistically significant tail dependence coefficients. Goodness-of-Fit tests indicate which model provides the best fit to data.

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Copula-Based Assessment of Co-Movement and Tail Dependence Structure Among Major Trading Foreign Currencies in Ghana

Risks ◽

10.3390/risks8020055 ◽

2020 ◽

Vol 8 (2) ◽

pp. 55

Author(s):

Prince Osei Mensah ◽

Anokye M. Adam

Keyword(s):

Exchange Rates ◽

Foreign Currency ◽

Tail Dependence ◽

Time Range ◽

Dependence Structure ◽

Joint Movement ◽

Positive Dependence ◽

Study Results ◽

Foreign Currencies ◽

Dependence Measures

This paper examines the joint movement and tail dependence structure between the pair of foreign exchange rates (EUR, USD and GBP) against the GHS, using daily exchange rates data expressed in GHS per unit of foreign currencies (EUR, USD and GBP) between the time range of 24 February 2009 and 19 December 2019. We use different sets of both static (time-invariant) and time-varying copulas with different levels of dependence and tail dependence measures, and the study results reveal positive dependence between all exchange rates pairs, though the dependencies for EUR-USD and GBP-USD pairs are not as strong as the EUR-GBP pair. The findings also reveal symmetric tail dependence, and dependence evolves over time. Notwithstanding this, the asymmetric tail dependence copulas provide evidence of upper tail dependence. We compare the copula results to DCC(1,1)-GARCH(1,1) model result and find the copula to be more sensitive to extreme co-movement between the currency pairs. The afore-mentioned findings, therefore, offer forex market players the opportunity to relax in hoarding a particular foreign currency in anticipation of domestic currency depreciation.

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Asymmetric Dependence Analysis of International Crude Oil Spot and Futures Based on the Time Varying Copula-GARCH

The Open Petroleum Engineering Journal ◽

10.2174/1874834101508010463 ◽

2015 ◽

Vol 8 (1) ◽

pp. 463-467

Author(s):

He Xin ◽

Zhang Jun

Keyword(s):

Parameter Estimation ◽

Crude Oil ◽

Significant Influence ◽

Tail Dependence ◽

Sliding Window ◽

Dependence Structure ◽

Dependence Analysis ◽

Time Varying ◽

Daily Return ◽

Asymmetric Dependence

Taking daily return of international crude oil spot and futures as sample, this paper analyzed the time varying and asymmetric dependence structure of them by time varying Copula-GARCH model based on sliding window and semi parameter estimation. This paper analyzed the regular changing between dependence structure of crude oil spot and futures and the return fluctuation, and confirmed that there is significant time varying asymmetric tail dependence. This paper found that the size of the sliding window had no significant influence on the conclusion, and the data of weekly return is more suitable for analysis of the trend of dependence structure of spot.

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Multi-Horizon Dependence between Crude Oil and East Asian Stock Markets and Implications in Risk Management

Energies ◽

10.3390/en13020294 ◽

2020 ◽

Vol 13 (2) ◽

pp. 294 ◽

Cited By ~ 1

Author(s):

Xiaojing Cai ◽

Shigeyuki Hamori ◽

Lu Yang ◽

Shuairu Tian

Keyword(s):

Risk Management ◽

Crude Oil ◽

Stock Markets ◽

East Asian ◽

Tail Dependence ◽

Dependence Structure ◽

Time Varying ◽

Risk Hedging ◽

Long Run ◽

East Asian Stock Markets

This paper examines the dynamic dependence structure of crude oil and East Asian stock markets at multiple frequencies using wavelet and copulas. We also investigate risk management implications and diversification benefits of oil-stock portfolios by calculating and comparing risk and tail risk hedging performance. Our results provide strong evidence of time-varying dependence and asymmetric tail dependence between crude oil and East Asian stock markets at different frequencies. The level and fluctuation of their dependencies increase as time scale increases. Furthermore, we find the time-varying hedging benefits differ at investment horizons and reduced over the long run. Our results suggest that crude oil could be used as a hedge and safe haven against East Asian stock markets, especially in the short- and mid-term.

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Pareto Lévy Measures and Multivariate Regular Variation

Advances in Applied Probability ◽

10.1239/aap/1331216647 ◽

2012 ◽

Vol 44 (1) ◽

pp. 117-138 ◽

Cited By ~ 2

Author(s):

Irmingard Eder ◽

Claudia Klüppelberg

Keyword(s):

Regular Variation ◽

Lévy Process ◽

Tail Dependence ◽

Levy Process ◽

Dependence Structure ◽

Lévy Measure ◽

Multivariate Distributions ◽

One Dimensional ◽

The One ◽

Lévy Measures

We consider regular variation of a Lévy process X := (Xt)t≥0 in with Lévy measure Π, emphasizing the dependence between jumps of its components. By transforming the one-dimensional marginal Lévy measures to those of a standard 1-stable Lévy process, we decouple the marginal Lévy measures from the dependence structure. The dependence between the jumps is modeled by a so-called Pareto Lévy measure, which is a natural standardization in the context of regular variation. We characterize multivariate regularly variation of X by its one-dimensional marginal Lévy measures and the Pareto Lévy measure. Moreover, we define upper and lower tail dependence coefficients for the Lévy measure, which also apply to the multivariate distributions of the process. Finally, we present graphical tools to visualize the dependence structure in terms of the spectral density and the tail integral for homogeneous and nonhomogeneous Pareto Lévy measures.

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

Sustainability ◽

10.3390/su11195487 ◽

2019 ◽

Vol 11 (19) ◽

pp. 5487 ◽

Cited By ~ 4

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.

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