Quantitative Risk Management: Concepts, Techniques, and Tools

By C. Anderson‐Cook. 2006

880 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/29200b465b8c124bdcd20ca1998b15d1a2be2ab6

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Citations in the corpus

Absolutely Continuous Copulas with Given Diagonal Sections (2008, background): “Relevant applications of this fact are provided in finance and insurance: see, for example, Cherubini et al. (2004), McNeil et al. (2005), Received June 22, 2007; Accepted March 12, 2008 Address correspondence to Fabrizio Durante, Department of Knowledge-Based Mathematical Systems, Johannes Kepler…”
Aggregating risk capital, with an application to operational risk (2006, neutral): “Moscadelli (2004) contains an analysis of the Basel II data on Operational Risk coming out of the second Quantitative Impact Study (QIS); see also Chapter 10 in McNeil et al. (2005) for a discussion and further references. As an illustration of our results, we choose as marginals the distribution fu”
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).”
Probabilistic assessment of flood risks using trivariate copulas (2012, methodology): “In that case, a procedure based on eigenvalue decomposition is used to transform correlation matrix into positive definite (McNeil et al. 2005).”
Multivariate peaks over thresholds models (2016, neutral): “Since then, numerous papers have used one-dimensional PoT models (though often not under this name), in areas ranging from earth and atmosphere science to finance, see e.g. Kysel´y et al. (2010), Katz et al. (2002), and McNeil et al. (2015).”
A mixture of generalized hyperbolic distributions (2013, methodology): “McNeil et al. (2005) give the density of a random variable X following the generalized hyperbolic distribution, (cid:0) (cid:1) (cid:8) (cid:9) | − − is the squared Mahalanobis distance between x and µ , and ϑ = ( λ, χ, ψ, µ , ∆ , α ) is the vector of parameters. where Herein, we use the notation X…”
Towards estimating extremal serial dependence via the bootstrapped extremogram (2012, neutral): “[11].”
Portfolio optimization for student t and skewed t returns (2010, background): “The skewed t can also be described as a Normal mean-variance mixture distribution, where the mixture variable W is inverse gamma Ig( /2, /2); see McNeil et al. (2005).”
PRICING AND HEDGING OF PORTFOLIO CREDIT DERIVATIVES WITH INTERACTING DEFAULT INTENSITIES (2008, background): “4 of McNeil et al. (2005) for details.”
Modelling the dependence structure of financial assets : A survey of four copulas (2004, positive): “According to McNeil et al. (2005) it is straightforward to derive the density of this copula, at least if a computer algebra system such as Mathematica is used.”
Modelling energy spot prices by volatility modulated Levy-driven Volterra processes (2013, methodology): “The generalised hyperbolic distribution A detailed review of the generalised hyperbolic distribution can be found in, for example, McNeil, Frey and Embrechts [56] and details on the corresponding implementation in R based on the ghyp package is provided in Breymann and Lüthi [32].”
Selecting and estimating regular vine copulae and application to financial returns (2012, background): “e copula, regular vines 1 Introduction In ﬁnance a ﬂexible modeling of dependencies and especially tails is vital to assess common risk measures such as the popular Value-at-Risk (for a deﬁnition see McNeil et al. (2005)). In particular the most common statistical dependence model, the Gaussian copu”
A Primer on Copulas for Count Data (2007, methodology): “For instance, simple formulas are available for Kendall’s tau in Archimedean and meta-elliptical models; for the basic properties of these two classes of distributions, see, e.g., Chapter 4 of Nelsen (1999) and Chapter 5 of McNeil et al. (2005), respectively.”