An empirical analysis of multivariate copula models

By Matthias Fischer, C. Koeck, Stephan Schlüter, F. Weigert. 2009

161 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/6793b1fe9d7388c8cde1ee326cab45e40e85fc22

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Citations in the corpus

The Joint Distribution of Stock Returns is Not Elliptical (2010, unknown): “But instead of trying to understand the economic or financial mechanisms that lead to some particular dependence between assets and construct copulas that encode these mechanisms, the methodology has been — as is sadly often the case — to brute force calibrate on data copulas straight out from stati”
Pair‐copula constructions for non‐Gaussian DAG models (2012, methodology): “In particular, we may draw from the rich literature on bivariate copula families, see, for example, Joe (1997). Hanea, Kurowicka, & Cooke (2006) rely on elicited expert knowledge to construct multivariate distributions using a PCC approach.”
Copula Theory: An Introduction (2010, background): “Other constructions can be found in [162] (direct compatibility), [95] (nested constructions), and [17, 66, 115, 123].”
Selection of Vine Copulas (2013, background): “Elliptical copulas as well as Archimedean copulas have been shown to be inadequate models to describe the dependence characteristics of real data applications (see for example [1, 24, 23]).”
Pair-Copula Constructions for Financial Applications: A Review (2016, background): “Since then, these constructions have been used for equities [48,53,61–63], interest rates [48,64,65], exchange rates [61,66–69], electricity prices and other commodities [61,70–74] and housing prices [75].”
Pair-Copula Constructions of Multivariate Copulas (2010, methodology): “In subsequent papers (see [13, 19]) these have been added.”
Nonparametric estimation of simplified vine copula models: comparison of methods (2017, background): “Thus, simplified vine copula models give rise to very flexible models which are often found to be superior to other multivariate copula models (Aas et al., 2009, Fischer et al., 2009).”
Risk management with high-dimensional vine copulas: An analysis of the Euro Stoxx 50 (2013, methodology): “…in finance the use of copulas is quite common nowadays (see, e.g., Cherubini et al. (2004)), literature on vine copula modeling so far mainly concentrated on illustrative applications (see Aas et al. (2009), Fischer et al. (2009), Berg and Aas (2009), Min and Czado (2010) and Czado et al. (2012)).”
Selecting and estimating regular vine copulae and application to financial returns (2012, methodology): “While D-vine based models are started to be used in many applications (Fischer et al. (2009), Min and Czado (2010), Chollete et al. (2009), Hofmann and Czado (2010), Mendes et al. (2010), Salinas-Guti´errez et al. (2010), Erdorf et al. (2011), Mercier and Frison (2009), Smith et al. (2010)),…”
Bayesian inference for multivariate copulas using pair-copula constructions. (2010, methodology): “According to recent empirical investigations of Berg and Aas (2007) and Fischer et al. (2007), the vine constructions based on bivariate t−copulas provide a better fit to multivariate financial data than other multivariate copula constructions such as a hierarchical Archimedean construction (Savu…”
Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine (2013, methodology): “In this regard Genest and Favre (2007) propose the use of a simple bivariate independence test based on Kendall’s τ .”