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Importance sampling for portfolio cr...

Li, Jingyi.

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Importance sampling for portfolio credit risk.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Importance sampling for portfolio credit risk./
作者:	Li, Jingyi.
面頁冊數:	78 p.
附註:	Source: Dissertation Abstracts International, Volume: 66-05, Section: B, page: 2803.
Contained By:	Dissertation Abstracts International66-05B.
標題:	Operations Research. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3174837
ISBN:	9780542131523

Importance sampling for portfolio credit risk.
Li, Jingyi.

Importance sampling for portfolio credit risk. - 78 p.

Source: Dissertation Abstracts International, Volume: 66-05, Section: B, page: 2803.

Thesis (Ph.D.)--Columbia University, 2005.

The main challenge in modern credit risk management is to construct the loss distribution at the portfolio level. Monte Carlo simulation is a widely used computational tool to get this distribution. It can be rather slow since estimating the loss distribution is basically a rare-event problem. This motivates research to accelerate simulation by variance reduction techniques.

ISBN: 9780542131523Subjects--Topical Terms:

626629
Operations Research.

Importance sampling for portfolio credit risk.
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100 1 $a Li, Jingyi. $3 1672761
245 1 0 $a Importance sampling for portfolio credit risk.
300 $a 78 p.
500 $a Source: Dissertation Abstracts International, Volume: 66-05, Section: B, page: 2803.
500 $a Adviser: Paul Glasserman.
502 $a Thesis (Ph.D.)--Columbia University, 2005.
520 $a The main challenge in modern credit risk management is to construct the loss distribution at the portfolio level. Monte Carlo simulation is a widely used computational tool to get this distribution. It can be rather slow since estimating the loss distribution is basically a rare-event problem. This motivates research to accelerate simulation by variance reduction techniques.
520 $a Importance sampling (IS) is a potentially attractive variance reduction technique in estimating the loss distribution since it is especially effective in the rare-event situation. Yet the application of IS is complicated by the mechanism to model dependence between obligors, and capturing this dependence is essential to a portfolio view of credit risk which is an important feature of modern credit risk management.
520 $a This dissertation studies the dependence structures in two portfolio credit risk models. The first one is the widely used normal copula model and the second one is the mixed Poisson model. We propose an IS procedure to construct the portfolio loss distribution for both models. The procedure has two parts: one applies IS conditional on a set of common factors affecting multiple obligors, the other applies IS to the factors themselves. The relative importance of the two parts of the procedure is determined by the strength of the dependence between obligors. We provide both theoretical and numerical support for the method.
590 $a School code: 0054.
650 4 $a Operations Research. $3 626629
690 $a 0796
710 2 $a Columbia University. $3 571054
773 0 $t Dissertation Abstracts International $g 66-05B.
790 1 0 $a Glasserman, Paul, $e advisor
790 $a 0054
791 $a Ph.D.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3174837