Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/65018


Title: An Importance Sampling Method to Evaluate Value-at-Risk for Assets with Jump Risks
Authors: Wang, R. H.;Lin, Shih-Kuei;Fuh, C. D.
林士貴
Contributors: 金融系
Keywords: Jump Diffusion Models;Value-at-Risk;Quick Simulation;Importance Sampling;Risk Management
Date: 2009.03
Issue Date: 2014-03-31 15:42:52 (UTC+8)
Abstract: Risk management is an important issue when there is a catastrophic event that affects asset price in the market such as a sub-prime financial crisis or other financial crisis. By adding a jump term in the geometric Brownian motion, the jump diffusion model can be used to describe abnormal changes in asset prices when there is a serious event in the market. In this paper, we propose an importance sampling algorithm to compute the Value-at-Risk for linear and nonlinear assets under a multi-variate jump diffusion model. To be more precise, an efficient computational procedure is developed for estimating the portfolio loss probability for linear and nonlinear assets with jump risks. And the titling measure can be separated for the diffusion and the jump part under the assumption of independence. The simulation results show that the efficiency of importance sampling improves over the naive Monte Carlo simulation from 7 times to 285 times under various situations. We also show the robustness of the importance sampling algorithm by comparing it with the EVT-Copula method proposed by Oh and Moon (2006).
Relation: Asia-Pacific Journal of Financial Studies,38(5), 745-772
Data Type: article
DOI 連結: http://dx.doi.org/10.1111/j.2041-6156.2009.tb00029.x
Appears in Collections:[金融學系] 期刊論文

Files in This Item:

File Description SizeFormat
745772.pdf391KbAdobe PDF1071View/Open


All items in 學術集成 are protected by copyright, with all rights reserved.


社群 sharing