Which Copula is the Right One

By Valdo Durrleman, Ashkan Nikeghbali, Thierry Roncalli. 2000

195 citations recorded by the source corpus.

Subfields: Geography, Planning and Development

View Paper: https://www.semanticscholar.org/paper/62349644b767034b42c768092e1b8e53b892b688

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In Geography, Planning and Development

1. Valentyn Panchenko
2. C. Savu
3. Rafael Schmidt
4. Thierry Ané
5. Mark Trede
6. Ulrich Stadtmüller
7. Cécile Kharoubi

Citations in the corpus

• Non‐parametric Estimation of Tail Dependence (2006, methodology): “Theodorescu (2001), Embrechts et al. (2003). Important applications of tail copulae in actuarial sciences and finance concern the modelling of dependencies between extreme insurance claims and large default events in credit portfolios, and Value-at-Risk considerations of asset portfolios. Concerning”
• Copulas: An Open Field for Risk Management (2001, unknown): “• The Economic Capital with an α confidence level is usually defined as EC = F−1 (α) (5)”
• Revisiting the Dependence between Financial Markets with Copulas (2000, result): “Note that the expression (22) is equivalent to verify the following relation (Straetmans [1999])”
• Dependence Structure and Risk Measure (2003, methodology): “In the same way as Durrleman, Nikeghbali, and Roncalli (2000), we use the empirical copula function introduced by Deheuvels (1979, 1981) to avoid this problem.”
• Frailty models and copulas: similarities and differences (2008, unknown): “[5] provide a detailed comparison between the two-stage approach and the (joint) maximization of the likelihood.”
• Structural reliability analysis using a copula-function-based evidence theory model (2014, methodology): “Multiple methods are currently available for the selection and verification of the copula functions [56–60].”
• 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”
• Measuring financial contagion:a copula approach (2007, background): “Forbes and Rigobon (2002) generalized the approach of Boyer et al.”
• Goodness-of-fit test for copulas (2005, methodology): “Durrleman et al. [ 5 ] constructed the Deheuvels or empirical copula and compared it with various parametric copulas on the basis of bivariate data.”
• Goodness-of-fit tests for parametric families of Archimedean copulas (2008, methodology): “We estimate the parameter of the generator function by maximum likelihood without specifying the marginal distributions (the canonical maximum likelihood method, see Durrleman et al. (2000)).”
• Multivariate Survival Modelling: A Unified Approach with Copulas (2001, unknown): “Another examples are the following: • the product copula C⊥ For example, we verify that we have in the bivariate case C̆⊥ (u1, u2) = u1 + u2 − 1 + (1− u1) (1− u2) = u1u2 = C⊥ (u1, u2) (46) • The upper Fréchet copula C+ In the case N = 2, we have C̆+ (u1, u2) = u1 + u2 − 1 + min (1− u1, 1− u2) = u1 +”
• Beyond Correlation: Extreme Co-movements Between Financial Assets (2002, unknown): “τ (X, Y ) = P {( X − X̃ ) · ( Y − Ỹ ) > 0 } − P {( X − X̃ ) · ( Y − Ỹ ) < 0 } , (12)”