.png){kind=icon}
.png){kind=icon}
Return
Credit risk optimization using factor models
.png){kind=icon}
PRE
AI
DOI：10.1007/s10479-006-0136-2.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We study portfolio credit risk management using factor models, with a focus on optimal portfolio selection based on the tradeoff of expected return and credit risk. We begin with a discussion of factor models and their known analytic properties, paying particular attention to the asymptotic limit of a large, finely grained portfolio. We recall prior results on the convergence of risk measures in this large portfolio approximation which are important for credit risk optimization. We then show how the results on the large portfolio approximation can be used to reduce significantly the computational effort required for credit risk optimization. For example, when determining the fraction of capital to) be assigned to particular ratings classes, it is sufficient to solve the optimization problem for the large portfolio approximation, rather than for the actual portfolio. This dramatically reduces the dimensionality of the problem, and the amount of computation required for its solution. Numerical results illustrating the application of this principle are also presented.
Keywords:
credit risk
portfolio optimization
large portfolio approximation
Journal
IF:
4.5
Papers:
8.0K
Citations:
2.1W
Organization
No organization information available