Sampling nested Archimedean copulas

By Alexander J. McNeil. 2008

276 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Finance

View Paper: https://www.semanticscholar.org/paper/3e2375246bd806d7a2f3c32835d6e896f07f6a12

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Kjersti Aas
2. Claudia Czado
3. Aleksey Min
4. Daniel Berg
5. Eike C. Brechmann
6. Marius Hofert
7. C. Savu
8. Mark Trede

In Finance

1. Claudia Czado
2. Eike C. Brechmann
3. Kjersti Aas
4. Andrew J. Patton
5. Marius Hofert
6. Daniel Berg
7. Aleksey Min
8. Paul Embrechts

Citations in the corpus

• Models for construction of multivariate dependence (2007, methodology): “Hence, the Laplace transform method does not in general apply to PNAC’s of arbitrary dimensions (McNeil, 2007) or to HNAC’s (Savu and Trede, 2006).”
• Reparameterizing Marshall–Olkin copulas with applications to sampling (2011, background): “For instance, McNeil and Hofert 15 16 present efficient sampling strategies for several hierarchical Archimedean copulas.”
• Entropy–Copula in Hydrology and Climatology (2014, background): “In general, extension of Archimedean copulas for high-dimensional problems is not straightforward, and hence, their use for studies that involve a large number of variables is restricted to certain conditions (Joe 1997; McNeil and Ne (cid:2) slehov á 2009 ; McNeil 2008).”
• Multivariate Archimedean copulas, $d$-monotone functions and $\ell_1$-norm symmetric distributions (2009, background): “This idea can be traced back to [23]; see also [24].”
• Properties of hierarchical Archimedean copulas (2013, background): “The representation of the copula in terms of Laplace transforms is very useful for simulation purposes (see [24], [14], [9], [13]).”
• Goodness-of-Fit Tests for Copulas of Multivariate Time Series (2017, unknown): “Other families considered recently in applications include hierarchical copulas (Savu and Trede, 2006),(McNeil, 2008), and copula vines (Bedford and Cooke, 2002), (Aas et al., 2009).”
• Bayesian inference for multivariate copulas using pair-copula constructions. (2010, methodology): “In last years different approaches for constructing multivariate Archimedean copulas of dimension more than 2 have been developed by Joe (1997), Embrechts et al. (2003), Whelan (2004), McNeil et al. (2006), Savu and Trede (2006) and McNeil (2007).”
• Statistics and Quantitative Risk Management for Banking and Insurance (2014, background): “Extending (8) to allow for hierarchies can be achieved in various ways, see for example McNeil (2008) or Hofert (2012).”
• Hierarchies of Archimedean copulas (2010, methodology): “Simulation methods for simple hierarchical structures have been developed by Whelan (2004), McNeil (2006) and Hofert (2007).”
• Models for construction of multivariate dependence – a comparison study (2009, methodology): “g (McNeil, 2008) and (Hofert, 2008).”
• CDO pricing with nested Archimedean copulas (2011, background): “McNeil and Nešlehová (2009) show that an Archimedean generator defines an exchangeable Archimedean copula, given by”
• A stochastic representation and sampling algorithm for nested Archimedean copulas (2012, methodology): “Further references can also be found in [6].”