Dependence Structure and Risk Measure

By Thierry Ané, Cécile Kharoubi. 2003

170 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/2bcaad0eba9cfb6c228ef6eeb75b90aa6b216c0b

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Citations in the corpus

Estimating the tail-dependence coefficient: Properties and pitfalls (2005, background): “Several empirical surveys such as Ané and Kharoubi (2003) and Malevergne and Sornette (2004) exhibited that the concept of tail dependence is a useful tool to describe the dependence between extremal data in finance.”
Multivariate modeling of droughts using copulas and meta-heuristic methods (2014, methodology): “The expressions for AD and IAD statistics are given as (Ane and Kharoubi 2003): • Anderson–Darling statistic”
Nonlinear Term Structure Dependence: Copula Functions, Empirics, and Risk Implications (2006, unknown): “However, recent empirical studies, e.g. by Ané and Kharoubi (2001) and Malevergne and Sornette (2002), exhibit that the concept of tail dependence is useful in describing dependence structures in financial data.”
Pairs trading: A copula approach (2013, background): “From an economic perspective, it gives analyst the opportunity to use different marginal distributions to account for the diversity in financial risks (or assets) (Ane and Kharoubi, 2003).”
Measurement of Aggregate Risk with Copulas (2005, unknown): “We follow the notation by Ané and Kharubi (2003).”
Canonical vine copulas in the context of modern portfolio management: Are they worth it? (2013, background): “From a modeling viewpoint, the lower the dimensionality of a model, the higher the reliability of the parameters (Ané and Kharoubi, 2003).”
On the construction of copulas and quasi-copulas with given diagonal sections (2008, background): “Tail dependence has been shown to be useful for describing this dependence, in particular in volatile and bear markets (Ané and Kharoubi, 2003; Malevergne and Sornette, 2006), and in contagion and stress testing concepts (Abdous et al.”
Goodness-of-fit tests for copulas: A review and a power study (2006, methodology): “, the analysis of stock index returns by Ané and Kharoubi (2003). The purpose of this paper is to present a critical review of the blanket goodness-of-fit tests proposed to date, to suggest variants or improvements, and to compare the relative power of these procedures through a Monte Carlo study in”
Copula Modeling: An Introduction for Practitioners (2007, background): “These models typically assume that asset prices have a multivariate normal 3 distribution, but Ané and Kharoubi (2003) and Embrechts et al. (2002) argue that this assumption is frequently unsatisfactory because large changes are observed more frequently than predicted under the normality…”
Probabilistic assessment of flood risks using trivariate copulas (2012, methodology): “…¼ 1nþ1 Pn j¼1; 1 Xj Xi ; Vi;n ¼ 1nþ1 Pn j¼1; 1 Yj Yi ; Wi;n ¼ 1nþ1 Pn j¼1; 1 Wj Wi ; i 2 1; . . . ; nf g ð11Þ The expressions for AD and IAD distance measures are given as (Ané and Kharoubi 2003): AD ¼ max 1 i n;1 j n;1 k n bCn in ; jn ; kn Cpθ in ; jn ; kn…”
Copulas: A Review and Recent Developments (2006, methodology): “The issues of measuring financial risk and assessing the effect of copula choice on risk measures were addressed by a number of authors, including Embretchs et al.[40,41], Ané and Kharoubi[2], Mendes and Souza[83], among others.”