Title :
Importance sampling for risk contributions of credit portfolios
Author_Institution :
Dept. of Manage. Sci., City Univ. of Hong Kong, Kowloon Tong, China
Abstract :
Value-at-Risk is often used as a risk measure of credit portfolios, and it can be decomposed into a sum of risk contributions associated with individual obligors. These risk contributions play an important role in risk management of credit portfolios. They can be used to measure risk-adjusted performances of subportfolios and to allocate risk capital. Mathematically, risk contributions can be represented as conditional expectations, which are conditioned on rare events. In this paper, we develop a restricted importance sampling (IS) method for simulating risk contributions, and devise estimators whose mean square errors converge in a rate of n-1. Furthermore, we combine our method with the IS method in the literature to improve the efficiency of the estimators. Numerical examples show that the proposed method works quite well.
Keywords :
importance sampling; investment; mean square error methods; risk management; credit portfolios; importance sampling method; mean square errors; risk capital allocation; risk contribution; risk management; value-at-risk; Convergence; Equations; Load modeling; Mathematical model; Monte Carlo methods; Portfolios; Random variables;
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2010 Winter
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-9866-6
DOI :
10.1109/WSC.2010.5678972