Copula methods in finance

By Umberto Cherubini, Elisa Luciano, Walter Vecchiato. 2004

1,667 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f5a07d110482abf5bb537b37d414737d114afa09

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Citations in the corpus

Copula‐based drought severity‐duration‐frequency analysis in Iran (2009, background): “Detailed properties and various types of copulas can be founded in Joe (1997), Nelsen (1999), Cherubini et al. (2004) and Salvadori et al.”
A bivariate mixed distribution with a heavy‐tailed component and its application to single‐site daily rainfall simulation (2013, background): “Intuitively, the upper tail dependence can be understood as how likely extreme rainfall events to occur together [Cherubini et al., 2004].”
Selecting and estimating regular vine copulae and application to financial returns (2012, background): “However there is a growing demand for non-Gaussian models especially in ﬁnance (Cherubini et al., 2004) but also in climate research (e.g., Sch¨olzel and Friederichs (2008)), environmental sciences (Salvadori et al. (2007) and Kazianka and Pilz (2011)), medicine (e.g., Beaudoin and Lakhal-Chaieb…”
A multivariate jump-driven financial asset model (2006, unknown): “For a general introduction to copulas, we refer the reader to Nelsen [29], for its applications in finance to Cherubini, Luciano, Vecchiato [10].”
Construction of non-exchangeable bivariate distribution functions (2009, background): “Genest and Mackay 1986), which are largely used in finance, actuarial science and several other fields where one always tries to find the dependence among different random variables (see, for instance, Frees and Valdez 1998; Cherubini et al. 2004; McNeil et al. 2005).”
Hierarchies of Archimedean copulas (2010, methodology): “Recently, copulas have emerged as a powerful tool for creating more flexible and more realistic multivariate distributions in finance (Cherubini et al. 2004).”
Copula-Based Models of Systemic Risk in U.S. Agriculture: Implications for Crop Insurance and Reinsurance Contracts (2015, unknown): “Much of the work on copulas has been motivated by their applicability to the issues in risk management, insurance and financial economics (see, among others, Rodriguez (2003), Cherubini et al. (2004), Hu (2006), Patton (2006), and Jondeau and Rockinger (2006)).”
Uncertainty analysis of bias from satellite rainfall estimates using copula method (2014, background): “(3) Compute the linear correlationmatrix of the transformed data (Cherubini et al., 2004).”
Sampling Student’s T distribution – use of the inverse cumulative distribution function (2006, methodology): “The T copula and its simulation are discussed in Cherubini et al (2004) and Meneguzzo and Vecchiato (2004), and the simulation is as above for the normal case except that (a) between steps 1 and 2 one applies Equation (3) with the same χ2 sample for all the components, and (b) the CDF applied in…”
Modelling stochastic mortality for dependent lives (2008, unknown): “In general, the expectations (6) and ( 7 ) are not known in closed form: however, ar emarkable exception is the case in which the dynamics ofX is given by the SDE: dX(t )= f(X(t))dt + g(X(t))d ˜”
Hierarchical Kendall copulas: Properties and inference (2012, background): “Whether the number of exceedances (“unconditional coverage”) and their occurrences (should be independent; both properties: “conditional coverage”) are appropriate can be evaluated using a range of tests, so-called backtests, that have been proposed in the literature: the proportion of failures test”