Technical paper/Credit risk
Hybrid equity-credit modelling
Cutting edge: Hybrid models
Modelling counterparty credit exposure for credit default swaps
Modelling counterparty credit exposure for credit derivatives is more complicated than for non-credit products, since the reference credit and counterparty can exhibit positive default correlation. Here, Christian Hille, John Ring and Hideki Shimamoto…
Modelling counterparty credit exposure for credit default swaps
Modelling counterparty credit exposure for credit derivatives is more complicated than for non-credit products, since the reference credit and counterparty can exhibit positive default correlation. Here, Christian Hille, John Ring and Hideki Shimamoto…
Modelling counterparty credit exposure for credit default swaps
Modelling counterparty credit exposure for credit derivatives is more complicated than for non-credit products, since the reference credit and counterparty can exhibit positive default correlation. Here, Christian Hille, John Ring and Hideki Shimamoto…
A Markovian approach to modelling correlated defaults
Vladyslav Putyatin, David Prieul and Svetlana Maslova unveil a simple dynamic binomial credit model with a Poissonian mixing distribution to satisfy the constraints faced by financial institutions assessing their credit exposure in a consistent manner…
Estimating default correlations using a reduced-form model
Credit risk : Cuttingedge
Maximum likelihood estimate of default correlations
Estimating asset correlations is difficult in practice since there is little available data andmany parameters have to be found. Paul Demey, Jean-Frédéric Jouanin, Céline Roget andThierry Roncalli present a tractable version of the multi-factor Merton…
Mixed default modelling
Structural and reduced-form models are two well-established approaches to modelling afirm’s default risk. Here, Li Chen, Damir Filipovic/ and Vincent Poor develop a new default riskmodelling strategy based on combining these two frameworks in order to…
A credit loss control variable
Viktor Tchistiakov, Jeroen de Smet and Peter-Paul Hoogbruin explain and demonstrate how the efficiency of Monte Carlo simulation in valuing a portfolio of credit risky exposures is improved by the use of the Vasicek distribution as a control variable. An…
Quantifying operational risk
This is the fifth of Charles Smithson's latest series of Class Notes, which will run in alternate issues of Risk through to the end of 2004. Class Notes is an educational series, designed to pull together the threads of recent developments and thinking…
A credit loss control variable
Viktor Tchistiakov, Jeroen de Smet and Peter-Paul Hoogbruin explain and demonstrate how the efficiency of Monte Carlo simulation in valuing a portfolio of credit risky exposures is improved by the use of the Vasicek distribution as a control variable. An…
Correlated defaults: let’s go back to the data
Estimates of asset value correlation are a key element of Merton-style credit portfolio models. Many practitioners have access to asset value data for a large universe of listed firms, so estimation is within reach. Alan Pitts describes a statistical…
Cross-market valuation
This article takes the guesswork out of what credit margin to use when valuing credit-risky derivatives, and also sheds light on how relative value trading and capital structure arbitrage may be analysed quantitatively.
The score for credit
Jorge Sobehart and Sean Keenan discuss the benefits and limitations of model performance measures for default and credit spread prediction, and highlight several common pitfalls in the model comparison found in the literature and vendor documentation. To…
Multi-factor adjustment
The author presents an analytical method for calculating portfolio value-at-risk and expected shortfall in the multi-factor Merton framework. This method is essentially an extension of the granularity adjustment technique to a new dimension.
Bringing credit portfolio modelling to maturity
Michael Barco shows how to perform mark-to-market credit portfolio modelling by extendingthe well-known saddle-point technique, introducing spread and recovery rate volatility. Hethen tests his results on a fictitious portfolio, showing how asset…
Bringing credit portfolio modelling to maturity
Michael Barco shows how to perform mark-to-market credit portfolio modelling by extending the well-known saddle-point technique, introducing spread and recovery rate volatility. He then tests his results on a fictitious portfolio, showing how asset…
Using the grouped t-copula
Student-t copula models are popular, but can be over-simplistic when used to describe credit portfolios where the risk factors are numerous or dissimilar. Here, Stéphane Daul, Enrico De Giorgi, Filip Lindskog and Alexander McNeil construct a new,…
Unexpected recovery risk
For credit portfolio managers, the priority is to properly incorporate recovery rates into existingmodels. Here, Michael Pykhtin improves upon earlier approaches, allowing recovery rates todepend on the idiosyncratic part of a borrower's asset return, in…
Ultimate recoveries
Measuring recovery using the ultimate rate observed at emergence from bankruptcy may be conceptually desirable, but modelling it is difficult.
A false sense of security
Credit portfolio models often assume that recovery rates are independent of default probabilities. Here, Jon Frye presents empirical evidence showing that such assumptions are wrong. Using US historical default data, he shows that not only are recovery…
Ultimate recoveries
Measuring recovery using the ultimate rate observed at emergence from bankruptcy may be conceptually desirable, but modelling it is difficult. Craig Friedman and Sven Sandow tackle the problem by maximising the creditor’s utility function, constructed…
A false sense of security
Credit portfolio models often assume that recovery rates are independent of defaultprobabilities. Here, Jon Frye presents empirical evidence showing that such assumptions arewrong. Using US historical default data, he shows that not only are recovery…
Unexpected recovery risk
For credit portfolio managers, the priority is to properly incorporate recovery rates into existing models. Here, Michael Pykhtin improves upon earlier approaches, allowing recovery rates to depend on the idiosyncratic part of a borrower’s asset return,…