Extensions to the Gaussian Copula: Random Recovery and Random Factor Loadings

By Leif Andersen, Jakob Sidenius. 2005

337 citations recorded by the source corpus.

Subfields: Finance

View Paper: https://www.semanticscholar.org/paper/3bd4753d19921c6cac1f91200a8b8e8e84eb4184

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

Citations in the corpus

Valuation of a CDO and an n-th to Default CDS Without Monte Carlo Simulation (2004, methodology): “We evaluate the sensitivity of spreads for an n-th to default CDS and a CDO to a variety of different assumptions concerning default probabilities, recovery rates, and the correlation model chosen.”
The Normal Inverse Gaussian Distribution for Synthetic CDO Pricing (2007, methodology): “Andersen and Sidenius [2005] extended the Gaussian factor copula model to random recovery and random factor loadings. Trinh, Thompson, and Devarajan [2005] allowed for idiosyncratic and systematic jumps to default. Many other authors proposed a different approach—to use a copula that exhibits more t”
Two-Dimensional Markovian Model for Dynamics of Aggregate Credit Loss (2008, methodology): “We chose CIR-like dynamics (1) for the intensity only as a starting point.”
Generalized beta regression models for random loss given default (2008, methodology): “On the other hand, the loss distribution under the constant LGD model deviates substantially from the other two models with random LGD.”
Modeling Dependence in High Dimensions With Factor Copulas (2015, background): “Other variations on factor copulas are presented in Andersen and Sidenius (2004) and van der Voort (2005), who considered certain nonlinear factor structures, and in Rogge and Schönbucher (2003) and Laurent and Gregory (2005), who presented factor copulas for modeling times-to-default. See McNeil, F”
Counterparty Risk and Funding: A Tale of Two Puzzles (2014, methodology): “All this allows for exact computation of the probability in (8.41) by a standard recursive convolution procedure (see e.g. Andersen and Sidenius (2004) or Crépey (2013)).”
Semi-Analytical Valuation of Basket Credit Derivatives in Intensity-Based Models (2005, methodology): “For comparison, the tables also report the fit for the three copula models introduced in the previous section: the Gaussian copula, the RFL copula proposed by Andersen and Sidenius [2004-5], and the double-t copula of Hull and White [2004]. Unsurprisingly, the Gaussian copula provides a very poor de”
The Valuation of Correlation-Dependent Credit Derivatives Using a Structural Model (2010, positive): “The survival time copula model has been extended in a number of ways by authors such as Andersen and Sidenius (2004), Giesecke (2003), and Hull and White (2004).”
Dynamic hedging of synthetic CDO tranches with spread risk and default contagion (2010, background): “for functions h : [0;1) S f 0;:::;mg ! (0;1) and :f0;:::;m 1g ! (0; 1]. It is well known that the introduction of an increasing LGD-function improves the t of CDO-pricing models to observed CDO spreads, see for instance Frey & Backhaus (2008) or Andersen & Sidenius (2004) .”
PRICING AND HEDGING OF PORTFOLIO CREDIT DERIVATIVES WITH INTERACTING DEFAULT INTENSITIES (2008, methodology): “[0 ,3 ] T ra n ch e [3 ,6 ] T ra n ch e [6 ,9 ] T ra n ch e [9 ,1 2 ] T ra n ch e [1 2 ,2 2 ] T ra n ch e”