An Importance Sampling Method to Evaluate Value-at-Risk for Assets with Jump Risks

NCUIR > School of Management at National Central University > Graduate Institute of Finance > journal & Dissertation > Item 987654321/29540

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/29540

Title:	An Importance Sampling Method to Evaluate Value-at-Risk for Assets with Jump Risks
Authors:	Wang,RH;Lin,SK;Fuh,CD
Contributors:	財務金融所
Keywords:	CONFIDENCE SETS;STOCK RETURNS;DEVIATIONS;BOOTSTRAP;OPTIONS
Date:	2009
Issue Date:	2010-06-29 20:30:23 (UTC+8)
Publisher:	中央大學
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
Appears in Collections:	[Graduate Institute of Finance] journal & Dissertation

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