Modeling duration clusters with dynamic copulas

Ng, Wing Lon

doi:10.1016/j.frl.2008.01.001

Cited by 10 publications

(7 citation statements)

References 12 publications

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“…10). Some of the recent contributions which employ copulas to capture time-varying dependencies are Okimoto (2008), Ng (2008, Guégan and Zhang (2010), Dias andEmbrechts (2010), Silva Filho, Ziegelmann, andDueker (2012), and De Lira Salvatierra and Patton (2015). However, these studies and the majority of research on copulas are conducted on the bivariate level.…”

Section: Introductionmentioning

confidence: 99%

“…), which is a stochastic explanatory variable or a function. In particular, Ng (2008) proposes to model w i,t with the special function being…”

mentioning

confidence: 99%

“…However, this model is also limited to the bivariate setting due to the absolute distance Braun (2011) suggests an extension of Ng (2008)'s concept to higher dimensions by replacing the absolute distance measure with the copula density relative to the sum of all copula densities during the lag period. This results in a special function of the following type:…”

mentioning

confidence: 99%

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Modeling the multivariate dynamic dependence structure of commodity futures portfolios

Aepli

Füss

Henriksen³

et al. 2017

Journal of Commodity Markets

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This paper examines the time-varying dependence structure of commodity futures portfolios based on multivariate dynamic copula models. The importance of accounting for time-variation is emphasized in the context of the Basel traffic light system. We enhance the flexibility of this structure by modeling regimes with multivariate mixture copulas and by applying the dynamic conditional correlation model (DCC) to multivariate elliptical copulas. The most suitable dynamic dependence model in terms of in-sample and out-of sample valuation is the dynamic Student-tClayton mixture copula, followed by the dynamic Student-t copula, and the dynamic Gaussian-Clayton mixture. In comparison to the multivariate normal model, the dynamic Clayton copula also scales down significantly the number of VaR(99%) violations during the 2007/08 financial crisis period. The predictive performance of our multivariate dynamic copula models confirms its superiority over bivariate regime-switching copula models for various states of the economy.

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Section: Introductionmentioning

confidence: 99%

“…), which is a stochastic explanatory variable or a function. In particular, Ng (2008) proposes to model w i,t with the special function being…”

mentioning

confidence: 99%

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Modeling the multivariate dynamic dependence structure of commodity futures portfolios

Aepli

Füss

Henriksen³

et al. 2017

Journal of Commodity Markets

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“…Manner [42], Wu [13], and Ng et al [27] further researched the time-varying copulas. In our case, we follow our predecessors achievements to invent the time-varying Frank copula.…”

Section: Application Of Dynamic Dependence Structurementioning

confidence: 99%

Studying Volatility and Dependency of Chinese Outbound Tourism Demand in Singapore, Malaysia, and Thailand: A Vine Copula Approach

Liu

Sriboonchitta

Nguyen

et al. 2014

Modeling Dependence in Econometrics

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“…Patton (2006b) was among the first to address this issue by allowing copulas to be time-varying and therewith triggered a new and fast-growing line of research. Some of the recent contributions which employ copulas to capture timevarying dependencies are Okimoto (2008), Ng (2008), Guégan and Zhang (2010), Dias andEmbrechts (2010), Silva Filho, Ziegelmann, andDueker (2012) and De Lira Salvatierra and Patton (2013). However, these studies and the majority of research on copulas are conducted on the bivariate level.…”

Section: Introductionmentioning

confidence: 99%