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The Journal of Derivatives

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Primary Article

Valuation of a CDO and an n-th to Default CDS Without Monte Carlo Simulation

John C Hull and Alan D White
The Journal of Derivatives Winter 2004, 12 (2) 8-23; DOI: https://doi.org/10.3905/jod.2004.450964
John C Hull
A professor of finance at the Joseph L. Rotman School of Management at the University of Toronto.
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Alan D White
A professor of finance at the Joseph L. Rotman School of Management at the University of Toronto.
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Abstract

Many of the new credit derivative products are based on default experience for a portfolio of financial instruments. These include collateralized debt obligations (CDOs) and similar tranched credit products, and “n-th to default swaps.” Devising good default risk models for single-name credits has been challenging enough, but applying them to credit portfolios introduces much greater complexity, because of the critical importance of correlation. The most common valuation technology is Monte Carlo simulation, but with many bonds, each of which is subject to both correlated and idiosyncratic risk factors, the simulation is time-consuming and limited in scope. In this article, Hull and White offer two straightforward approximation techniques for evaluating default risk within the industry-standard “copula“ model that eliminate simulation of the idiosyncratic risks. Their approach greatly accelerates the solution while still allowing a large degree of flexibility in the choice of factor correlation structure and probability distributions. For example, Student-t distributed shocks that have fatter tails than the normal are easily accommodated.

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Vol. 12, Issue 2
Winter 2004
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Valuation of a CDO and an n-th to Default CDS Without Monte Carlo Simulation
John C Hull, Alan D White
The Journal of Derivatives Nov 2004, 12 (2) 8-23; DOI: 10.3905/jod.2004.450964

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Valuation of a CDO and an n-th to Default CDS Without Monte Carlo Simulation
John C Hull, Alan D White
The Journal of Derivatives Nov 2004, 12 (2) 8-23; DOI: 10.3905/jod.2004.450964
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Cited By...

  • A Robust Decision Support Approach to Portfolio Risk Reduction Based on Credit Default Swap
  • A Simple Model of Correlated Defaults with Application to Repo Portfolios
  • Collateralized Commodity Obligations: * Modeling and Risk Assessment
  • Structural Credit Loss Distributions * under Non-Normality
  • Force-Fitting CDS Spreads to CDS Index Swaps
  • Risk Management Systems During Market Bubbles: The Weakness of Quantitative Models
  • Implied Correlations: Smiles or Smirks?
  • Scopus (236)
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More in this TOC Section

  • The Subprime Credit Crisis of 2007
  • The Determinants of CDS Bid-Ask Spreads
  • Variance Reduction for Multivariate Monte Carlo Simulation
Show more Primary Article

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